Dynamic Metrics Research Articles

Self-reported Sensory Hypersensitivity Moderates Association Between Tactile Psychophysical Performance and Autism-Related Traits in Neurotypical Adults.

Atypical responses to tactile stimulation have been linked to core domains of dysfunction in individuals with autism spectrum disorder (ASD) and phenotypic traits associated with ASD in neurotypical individuals. We investigated (a) the extent to which two psychophysically derived measures of tactile sensitivity-detection threshold and dynamic range-relate to traits associated with ASD and (b) whether those relations vary according to the presence of self-reported sensory hypersensitivities in neurotypical individuals. A narrow dynamic range was associated with increased autism-related traits in individuals who reported greater sensory hypersensitivity. In contrast, in individuals less prone to sensory hypersensitivity, a narrow dynamic range was associated with reduced autism-related traits. Findings highlight the potential importance of considering dynamic psychophysical metrics in future studies.

Comprehensive evaluation of window-integrated semi-transparent PV for building daylight performance

Building-integrated semi-transparent photovoltaic windows (PV windows) have been considered as a potential candidate to replace conventional windows to improve building energy efficiency and hence reduce carbon emissions. With the integration of PV windows, the indoor luminous environment may be significantly affected. The presence of solar cells may cause undesirable shading, low illuminance levels and affect colour quality of the transmitted daylight. Therefore, it is important to comprehensively assess daylight performance of PV windows to ensure a comfortable luminous environment. In this study, the daylight performance of Cadmium telluride (CdTe) PV window with four different transparencies (i.e. 20%, 30%, 40% and 50%) applied to a cellular office space has been assessed in terms of daylight quantity and daylight quality. RADIANCE was selected to predict the annual daylight performance through advanced dynamic metrics including Useful Daylight Illuminance (UDI), simplified Daylight Glare Probability (DGPs) and Illuminance Uniformity (Uo). Correlated Colour Temperature (CCT) and Colour Rendering Index (CRI), which are two attributes to characterise the colour quality of transmitted daylight were used to evaluate performance of the selected PV windows. CCT and CRI were calculated under three CIE standard daylight scenarios (CCT of 4000 K, 6500 K and 25000 K respectively). It is found that CdTe PV windows can significantly improve the homogeneity of daylight distribution on a task area located close to the window and reduce the risk of daylight glare when compared with the performance of a conventional double glazing. Moreover, the recommended CCT (i.e. 3000–7500 K) can be achieved with the employment of CdTe PV windows under 4000 K and 6500 K daylight scenarios. All of the CdTe PV windows examined were able to maintain CRI at a comfortable level i.e. above 90 under the three daylight scenarios.

Piezoelectric sensor–based damage progression in concrete through serial/parallel multi-sensing technique

Structural damage detection using unmanned Structural Health Monitoring techniques is becoming the need of the day with the technologies available presently. Sensors made of Lead Zirconate Titanate materials, due to their simplicity and robustness, are increasingly used as an effective monitoring sensor in Structural Health Monitoring. Continuous monitoring of the structures using Lead Zirconate Titanate sensors often results in a laborious data retrieval process due to the large amount of signal generated. To speed up the data retrieval process, a multi-sensing technique in which the Lead Zirconate Titanate patches are connected in series and parallel is proposed for structural damage detection. The proposed method is validated using an experimental investigation carried out on a reinforced concrete beam embedded with smart Lead Zirconate Titanate sensor units. The beam is subjected to damage, and the location of damage is identified using conductance signatures obtained from patches sensed individually and through multiplexing. This article proposes an effective methodology for selection of patches to be connected in series/parallel to maximise the efficiency of damage detection. Damage quantification using conventional statistical metrics such as root mean square deviation, mean absolute percentage deviation and cross correlations are found to be ineffective in identifying the location of damage from the multiplexed signatures. In turn, dynamic metrics such as moving root mean square deviation, moving mean absolute percentage deviation and moving cross correlation with overlapped moving blocks of data are proposed in the present work and their ability to detect the damage location from multiplexed signatures is discussed.

Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes

Functional connectivity analysis techniques have broadly applied to capture phenomenological aspects of the brain, e.g., by identifying characteristic network topologies for healthy and disease-affected populations, by highlighting several areas important for the global efficiency of the brain during some cognitive processing and at rest. However, most of the known methods for quantifying functional coupling between fMRI time series are focused on linear correlation metrics. In this work, we propose a multidimensional framework to extract multiple descriptors of the dynamic interaction among BOLD signals in their phase space. A set of metrics is extracted from the cross recurrence plots of each couple of signals to form a multilayer connectivity matrix in which each layer is related to a specific complex dynamic phenomenon. The proposed framework is used to characterize functional abnormalities during a working memory task in patients with schizophrenia. Some topological descriptors are then extracted from both multilayer connectivity matrices and the most used Pearson-based connectivity networks to perform a binary classification task of normal controls and patients. The results show that the proposed connectivity model outperforms the statistical correlation-based connectivity in accuracy, sensitivity and specificity. Moreover, the statistical analysis of the selected features highlights that several dynamic metrics could better identify disease-related dynamic states in brain activity than the statistical correlation among physiological signals.

EFFECT OF STATIC ANATOMIC ALIGNMENT ON DYNAMIC LIMB VALGUS DURING SIDE-STEP CUTTING IN UNINJURED ADOLESCENT ATHLETES

BACKGROUND Dynamic limb valgus, combining hip adduction and internal rotation with knee abduction posture and moments, has been implicated in ACL injury. However, the contribution of static lower extremity alignment to dynamic limb valgus is unknown. This study assessed the relationships among lower extremity static alignment and dynamic kinematics and kinetics during side-step cutting in uninjured adolescent athletes. METHODS This prospective study included 88 limbs from 44 uninjured athletes aged 8-15 years (mean 12.3, SD 2.3; 19 (44%) female) who were evaluated during an anticipated 45° side-step cut. 3D lower extremity kinematics and kinetics from a custom 6 degree of freedom model were assessed while standing and during the loading phase of the cut from initial contact to peak knee flexion; 2-3 trials per limb were averaged for analysis. Femoral anteversion was measured for each limb with the participant lying prone. Relationships among static and dynamic measures were investigated using correlation and multiple linear regression. RESULTS In terms of static alignment, more static hip internal rotation and more static knee external rotation (tibia external relative to femur) were associated with more internal hip rotation and external knee rotation dynamically during cutting (r=0.34, p=0.001) (Table 1). Static hip adduction was also related to more external hip rotation and less hip flexion dynamically (p=0.24, p=0.02). More static knee abduction, external hip rotation and hip adduction were associated with higher average knee abduction angles during cutting (r=0.25, p=0.02). However, only static external knee rotation was associated with higher dynamic knee abduction moments (r=0.48, p<0.0001) (Figure 1). During cutting, positive associations were observed between hip flexion, knee flexion, and hip internal rotation (r=0.24, p=0.03). Knee adduction angles were related to more hip flexion, internal hip rotation, and knee external rotation (r=0.25, p=0.02). Additionally, lower peak knee flexion was associated with higher peak ground reaction force and more external knee rotation (r=0.24, p=0.02). Both simple correlation and multiple regression analysis indicated that higher knee abduction moments were related dynamically to higher knee abduction angles, greater knee external rotation, higher hip abduction angles, and greater hip internal rotation (R2=0.72, p<0.001). After considering dynamic metrics, no static measure remained significantly related to knee abduction moments. CONCLUSION/SIGNIFICANCE Static knee rotation was the only anatomic alignment measure associated with knee abduction moments during side-step cutting in uninjured adolescent athletes. Knee abduction moments were influenced more by dynamic posture than static alignment. As knee abduction moments have been implicated in ACL injury, this study supports the notion of dynamic limb valgus, specifically increased knee abduction and hip internal rotation, relating to ACL injury. Motion analysis can be used to identify these risky biomechanical patterns, and neuromuscular training can be used to correct them. Since knee abduction moments are primarily determined by dynamic posture, neuromuscular training can be used to reduce these moments and ACL injury risk. [Figure: see text][Table: see text]

Glazing Sizing in Large Atrium Buildings: A Perspective of Balancing Daylight Quantity and Visual Comfort

Due to the multiple benefits on energy, well-being, comfort, and the economy, the utilization of daylight remains an imperative topic of architectural design. With the remarkable ability of drawing and increasing daylight deep into the core of buildings, atriums with a large proportion of glazing have become one of the most preferred design forms. The concomitant and unexpected visual discomfort in modern buildings, however, has drawn increasing concerns. Therefore, this study investigated the relation between glazing proportion and daylight performance, as well as the impact of building height and atrium types on daylight performance in atrium buildings by using an annual dynamic simulation method and metrics. It was found that extending glazing proportion had prominent effectiveness in the enhancement of daylighting; building height had a negative influence; round and square types of buildings performed much better than rectangular ones. Moreover, to inform a practical design, we analyzed the link between increasing daylight and visual comfort from the perspective of balancing them, and then proposed a design guide for atrium roof-glazing sizing.

Estimating Sit-to-Stand Dynamics Using a Single Depth Camera.

Kinetic and dynamic motion analysis provides quantitative, functional assessments of human ability that are unobtainable through static imaging methods or subjective surveys. While biomechanics facilities are equipped to perform this measurement and analysis, the clinical translation of these methods is limited by the specialized skills and equipment needed. This paper presents and validates a method for estimating dynamic effects such as joint torques and body momenta using a single depth camera. An allometrically scaled, sagittal plane dynamic model is used to estimate the joint torques at the ankles, knees, hips, and low back, as well as the torso momenta, and shear and normal loads at the L5-S1 disk. These dynamic metrics are applied to the sit-to-stand motion and validated against a gold-standard biomechanical system consisting of full-body active motion-capture and force-sensing systems. The metrics obtained from the proposed method were found to have excellent concordance with peak metrics that are consistent with prior biomechanical studies. This suggests the feasibility of using this system for rapid clinical assessment, with applications in diagnostics, longitudinal tracking, and quantifying patient recovery.

Minimum Daylight Autonomy: A New Concept to Link Daylight Dynamic Metrics with Daylight Factors

ABSTRACT Daylight metrics act as a useful tool to quantify the potential of natural light in an architectural space as well as the energy savings promoted by a suitable design of windows, atriums, and skylights. Accordingly, a new indoor lighting metric is proposed, minimum daylight autonomy, defined as the percentage of occupied time when an illuminance threshold can be met by daylight alone under continuous overcast sky conditions. This novel concept can determine an approximation of the maximum use of electric lighting and the quantification of minimum energy savings without the need for advanced calculation tools. Although daylight factor is the most widespread concept, it cannot forecast energy savings as accurately as dynamic metrics. In addition, daylight autonomy is the most usual dynamic definition, because it estimates the energy consumption of on–off electric lighting systems depending on weather conditions. However, there is no link between static and dynamic metrics, because both concepts are based on different variables. This research proposes the calculation procedure for minimum daylight autonomy, as well as the equations that serve to predict dynamic metrics based on static metrics, after confirming the accuracy of the simulation program that calculates the metrics using a test cell under real conditions.

Comparing Hybrid Tool for Static and Dynamic Object-Oriented Metrics

Software metrics are created and used by the distinctive programming associations intended for assessing, guaranteeing program excellence, activity, and software recovery. Software metrics have turned into a basic part of programming growth and are utilized in each period of the product development life cycle. Software metrics essentially measure programming items like plan source code and help us in taking technical and administrative choices. The desire of this examination is to play out the relative investigation of static and dynamic metrics. In any case, software quality characteristics, for example, performance, execution time and dependability rely upon the dynamic exercises of the product artifact. Due to every one of these variables, we favor dynamic metrics instead of customary static metrics. With the assistance of customary static metrics, we are not capable to analyze different actualities of programming. There are various types of this OO static and dynamic equipments. In this paper we have played out a similar investigation of different OO static and dynamic metrics tools and find out the hybrid too is counted as best one extraction of both, static and dynamic characteristics from mobile Android applications. The source code and a Docker compartment is utilized by open source tool in only three phases pre-static, static and dynamic examination.

Assessing Quality by Anti-pattern Detection in Web Services

Design pattern plays an important role in development of a good quality software system. Service oriented architecture forms the basis for designing web services. Web services must be carefully designed taking into consideration the quality of service parameters like delay, throughput, reliability and cost. In order to maintain QOS design patterns should be analyzed to detect antipatterns, which can hinder the quality of software system. An antipattern is something, which initially appears like a good indication but creates negative results .The analysis can be done on the basis of several metrics. The paper takes into consideration the web service description files collected from various reliable sources and analyze the same based on static metric content. The static metrics used in this research paper are standard CKJM metrics. The future scope of the paper will focus on detection of antipattern based on dynamic metrics e.g. response time.

Towards a sound massive cosmology

It is known that de Rham-Gabadadze-Tolley (dRGT) massive gravity does not permit a homogeneous and isotropic universe with flat or spherical spatial metrics. We demonstrate that a singular reference metric solves this problem in an economic and straightforward way. In the dRGT massive gravity with a singular reference metric, there are sound homogeneous and isotropic cosmological solutions. We investigate cosmologies with the static and dynamical singular reference metrics, respectively. The term like dark energy appears naturally and the universe accelerates itself in some late time evolution. The term simulating dark matter also naturally emerges. We make a preliminary constraint on the parameters in the dRGT massive gravity in frame of the present cosmological model by using the data of supernovae, cosmic microwave back ground radiations, and baryonic acoustic oscillations.

Performance Analyses of Differential Evolution Algorithm Based on Dynamic Fitness Landscape

Dynamic fitness landscape analyses contain different metrics to attempt to analyze optimization problems. In this article, some of dynamic fitness landscape metrics are selected to discuss differential evolution (DE) algorithm properties and performance. Based on traditional differential evolution algorithm, benchmark functions and dynamic fitness landscape measures such as fitness distance correlation for calculating the distance to the nearest global optimum, ruggedness based on entropy, dynamic severity for estimating dynamic properties, a fitness cloud for getting a visual rendering of evolvability and a gradient for analyzing micro changes of benchmark functions in differential evolution algorithm, the authors obtain useful results and try to apply effective data, figures and graphs to analyze the performance differential evolution algorithm and make conclusions. Those metrics have great value and more details as DE performance.

Analysis of Signaling Mechanisms Regulating Microglial Process Movement.

Microglia, the brain's innate immune cells, are extremely motile cells, continuously surveying the central nervous system (CNS) to serve homeostatic functions and to respond to pathological events. In the healthy brain, microglia exhibit a small cell body with long, branched, and highly motile processes, which constantly extend and retract, effectively "patrolling" the brain parenchyma. Over the last decade, methodological advances in microscopy and the availability of genetically encoded reporter mice have allowed us to probe microglial physiology in situ. Beyond their classical immunological roles, unexpected functions of microglia have been revealed, both in the developing and the adult brain: microglia regulate the generation of newborn neurons, control the formation and elimination of synapses, and modulate neuronal activity. Many of these newly ascribed functions depend directly on microglial process movement. Thus, elucidating the mechanisms underlying microglial motility is of great importance to understand their role in brain physiology and pathophysiology. Two-photon imaging of fluorescently labeled microglia, either in vivo or ex vivo in acute brain slices, has emerged as an indispensable tool for investigating microglial movements and their functional consequences. This chapter aims to provide a detailed description of the experimental data acquisition and analysis needed to address these questions, with a special focus on key dynamic and morphological metrics such as surveillance, directed motility, and ramification.

A Dynamic Virtual Datacenter Selection Strategy for Integrated Cloud Service Platform Construction With Multiclouds

The pay-as-you-go model and network virtualization of cloud computing allow micro and small content businesses (MSCBs) who construct their integrated cloud service platforms (ICSPs) with virtual datacenters (VDCs) to serve their end users with low service latency and construction cost. However, designing a flexible VDC selection strategy to meet the demands of MSCBs is a challenging task. To address this problem, a dynamic VDC selection strategy is designed for MSCBs to construct their ICSPs flexibly with the VDCs from different clouds. To this end, three dynamic landmark selection metrics are proposed and applied to construct the network coordinates. Then, a dynamic VDC selection algorithm is presented to determine the locations and service resources of VDCs, which are purchased from different clouds by MSCBs to construct their ICSPs. Based on our VDC selection strategy, a simulator is developed based on our designed experimental framework to evaluate our VDC selection strategy. The experimental results show that compared with previous server placement strategies, our strategy can actively and effectively determine VDCs' locations and allocate service resources for each VDC with less computing consumption and is a practical VDC selection strategy for cloud construction in a multicloud environment.

Dynamic Routing Capsule Networks for Mild Cognitive Impairment Diagnosis.

Alzheimer's disease (AD) is a chronic neurodegenerative disease that could cause severe cognitive damage to the patients. Diagnosis of AD at its preclinical stage, i.e., mild cognitive impairment (MCI), could help to prevent or slow down AD progression. With machine learning, automatic MCI diagnosis could be achieved. Most of the previous studies mainly share a similar framework, i.e., building a classifier based on the features extracted from static or dynamic functional connectivity. Recently, inspired by the great successes achieved by deep learning in other areas of medical image analysis, researchers have introduced neural network models for MCI diagnosis. In this paper, we propose dynamic routing capsule networks for MCI diagnosis. Our proposed methods are based on a novel neural network fashion of capsule net. Two variants of capsule net are designed and discussed, which respectively uses the intra-ROIs and inter-ROIs dynamic routing to obtain functional representation. More importantly, we design a learnable dynamic functional connectivity metric in our inter-ROIs dynamic model, in which the functional connectivity is dynamically learned during network training. To the best of our knowledge, it's the first time to propose dynamic routing capsule networks for MCI diagnosis. Compared with other machine learning methods and deep learning model, our method can achieve superior performance from various aspects of evaluations.

On the geometry of geodesics in discrete optimal transport

We consider the space of probability measures on a discrete set mathcal {X}, endowed with a dynamical optimal transport metric. Given two probability measures supported in a subset mathcal {Y}subseteq mathcal {X}, it is natural to ask whether they can be connected by a constant speed geodesic with support in mathcal {Y} at all times. Our main result answers this question affirmatively, under a suitable geometric condition on mathcal {Y} introduced in this paper. The proof relies on an extension result for subsolutions to discrete Hamilton–Jacobi equations, which is of independent interest.

Tracking the dynamic functional connectivity structure of the human brain across the adult lifespan.

The transition from early adulthood to the elder is marked by functional and structural brain transformations. Many previous studies examined the correlation between the functional connectivity (FC) and aging using resting-state fMRI. Results showed that the changes in FC are linked to aging as well as the cognitive ability changes. However, some researchers proposed that the FC is not static but dynamic changes during the resting-state fMRI scan. In this study, we examined the correlation between the resting-state dynamic functional network connectivity and age using resting scan data of 434 subjects. The results suggested: (a) age is negatively associated with variability of dynamic functional network connectivity state; (b) the dwell time of each age range spends in each state is different; (c) the dynamic graph metrics curve of each age ranges is different and 19-30 age range has the largest average global efficiency and average local efficiency; (d) some dynamic functional network connectivity measures were correlated to the certain cognitive ability. Overall, the results suggested the changes in dynamic functional network connectivity measures may be a characteristic of the aging process and in further investigations may provide a deep understanding of the aging process.

Validation Study for Daylight Dynamic Metrics by Using Test Cells in Mediterranean Area

Validation Study for Daylight Dynamic Metrics by Using Test Cells in Mediterranean Area

Daylighting Metrics: an Approach to Dynamic Cubic Illuminance

Advances in research work in the field of numerical analysis of daylight performance have generated in-depth knowledge on photometric measurements of daylight quality. Most dynamic metrics are based on illuminance, which is a two-dimensional concept insofar as it is concerned with the density of luminous flux incident at a point on a surface. In order to extend dynamic metrics into the third dimension and consider the distribution of illumination at a point in space, it is important to generate new advances in simulation environments and consider spatial illumination metrics. In this context, the main objective of the present work was to advance in the development of cubic dynamic daylight metrics, as a complement to the two dimensional analysis currently employed, promoting the use of Climate Based Daylight Modelling (CBDM). For this purpose, cylindrical to horizontal illuminance ratio is applied to dynamic simulation paradigm developing the concept of useful modeling indexs (UMIs). The research methodology applied in this work is divided into two main parts: (i) two dimensional concept: spatial daylight autonomy (sDA(300lx,50%) -horizontal-, sDA(175lx,50%) -vertical-) and uniformity, and (ii) three dimensional concept: useful cylindrical to horizontal illuminance ratio (uEcl/Eh(0.3-0.6)). In order to assess this method, two spaces (RR1 and RR2) of the Lavalle Public Library, located in Mendoza-Argentina, were taken as a case study. Results show important differences in horizontal illuminance between RR1 and RR2 (∆sDA(300lx, 50%) > 80%). Similar values of uEcl/Ewp(0.3-0.6) -useful cylindrical to horizontal illuminance ratio- are detected in both rooms (RR1= 69.32 % and RR2= 72.24 %) in nodes near north opening. Yet there are significant differences (< 36%) of uEcl/Ewp(0.3-0.6) between nodes located near the south wall, this is due to the obstruction of a south opening in RR2. Furthermore, it is important to mention that 2D metrics display a more uniform behavior than 3D metrics. This shows itself clearly if we take into account that difference in sDA are much lower than difference in uEcl/Eh(0.3-0.6), if we compare nodes closest to the north windows to does that are far from it, in both rooms (RR1 and RR2). This results from the fact that cubic metrics are more sensitive to the direction of light. This is of crucial importance for daylight studies in clear sky condition, due to the defined direction of direct solar radiation. Finally, a new approach to daylighting performance analysis based on the addition of cubic metrics to dynamic daylight paradigm is proposed: useful modelling indexs (UMIs). UMIs make it possible to quantify annual occurrence of proper light modelling conditions. As an initial approach, cylindrical to horizontal illuminance ratio (Ecl/Ewp(0.3-0.6)) has been considered, due to its current use in international standards.

Assessing the effectiveness of dynamic metrics in predicting daylight availability and visual comfort in classrooms

In this study, daylight performance and visual comfort have been evaluated by a longitudinal subjective survey (842 total responses) and simulation-based metrics in four classrooms in two LEED™ silver certified buildings during a year. Dynamic and static daylight and glare metrics are reviewed and critiqued based upon their ability to explain the perception of human subjective responses in classrooms. Results indicate high correlation between students' perceptions and dynamic daylight metrics; sDA300/50% and UDI300-3000/50%, in defining the daylit area. Moreover, according to results the Vertical illuminance-based metrics (sDGPexceed) is more compatible than horizontal illuminance-based metrics (ASE) at fitting the range of perceived discomfort glare. However, more and larger studies are needed to confirm utilizing the sDGPexceed index for indication of discomfort glare in early stage of building design. According to results, daylight and glare metrics' thresholds should be reconsidered based on global filed surveys, since occupants' ability to adapt to higher or lower levels of light is related to culture and climate location.