Physical Metrics Research Articles

Palatini f(R,Lm,RμνTμν) gravity and its Born-Infeld semblance

We investigate Palatini $f(\mathcal{R},\mathcal{L}_m, \mathcal{R}_{\mu\nu}T^{\mu\nu})$ modified theories of gravity wherein the metric and affine connection are treated as independent dynamical fields and the gravitational Lagrangian is made a function of the Ricci scalar $\mathcal{R}$, the matter Lagrangian density $\mathcal{L}_m,$ and a "matter-curvature scalar" $\mathcal{R}_{\mu\nu}T^{\mu\nu}$. The field equations and the equations of motion for massive test particles are derived, and we show that the independent connection can be expressed as the Levi-Civita connection of an auxiliary, energy-momentum dependent metric, related to the physical metric by a matrix transformation. Similar to metric $f(\mathcal{R}, T, \mathcal{R}_{\mu\nu}T^{\mu\nu})$ gravity, the field equations impose the non-conservation of the energy-momentum tensor, leading to an appearance of an extra force on massive test particles. We obtain the explicit form of the field equations for massive test particles in the case of a perfect fluid, and an expression for the extra force. The nontrivial modifications to scalar fields and both linear and nonlinear electrodynamics are also considered. Finally, we detail the conditions under which the present theory is equivalent to the Eddington-inspired Born-Infeld (EiBI) model.

Physical performance metrics in elite soccer: do power and acceleration metrics provide insight into positional demands and match-related fatigue in the 4-3-3 system?

The aim of this study was to quantify power and acceleration metrics in elite soccer matches to gain an insight into positional demands and match-related fatigue patterns. Elite players (N.=212, observations =522) were analysed during 50 matches of the Italian Serie A using a semi-automatic tracking system (K-Sport, Montelabbate, Pesaro-Urbino, Italy - Stats, Leeds, UK) during the 2015/16 season. A principal component analysis (PCA) was performed to find the latent variables that better explain the huge amount of data collected; an ANOVA was performed to find differences among positional roles and a mixed factorial analysis of mixed data (FAMD) was carried out to investigate the patterns of fatigue over time. Power and acceleration were defined as the latent variables out of the 19 investigated that provided most of the variance (90.39%); significant differences among roles were found (P<0.05; Effect Size (ES) as ω2>0.14) and significant patterns of fatigue (P<0.05) with a moderate to large ES were observed over time in some of the key performance indicators. The data demonstrate that there are implications for developing power and acceleration in training sessions and assessing these components during a game. With the introduction of "live streaming" of GPS data, the movement patterns could be observed in real time, and interchanges could be made before the onset of fatigue and before evident reductions in performance might be observed.

Relationship of Activity Patterns to Acute Mountain Sickness in South Pole Workers.

This study aimed to evaluate the influence of physical activity on incidence of acute mountain sickness (AMS) by continuous activity monitoring in a free-living sample of South Pole workers over the initial 72 h at altitude exposure of 2,840 m (9,318 ft). Body Media activity monitors were worn by 47 healthy participants. AMS was defined by the Lake Louise symptom questionnaire. Venous blood samples were taken at sea level and approximately 48 h after high altitude exposure. AMS incidence was 34% (n=16/47) over the first 48 h and 40% (n=19/47) over 72 h. On day 2 at high altitude, individuals with AMS demonstrated a significantly greater increase in the percent change in physical activity metrics from baseline: total energy expenditure 19±13 vs. 5±7%, total steps 65±51 vs. 10±18%, metabolic equivalent of tasks 21±13 vs. 7±13%, and time spent performing moderate to vigorous physical activity 114±79 vs. 26±27% for individuals with AMS vs. no AMS, respectively, p<0.05. In addition, erythropoietin and vascular endothelial growth factor were 1.69 and 1.75 times higher, respectively, in those with AMS. In conclusion, workers who engaged in increased physical activity and activity intensity during initial exposure to the South Pole were more susceptible to developing AMS.

The selective personalized radioimmunotherapy for locally advanced NSCLC trial (SPRINT).

TPS8571 Background: Concurrent chemoradiotherapy for locally advanced non-small cell lung cancer (LA-NSCLC) can cause significant toxicities, and disease recurrence after treatment is common. We previously demonstrated that a dose-painted radiotherapy approach provides excellent local disease control and has a favorable toxicity profile. Consolidation immunotherapy was recently shown to improve outcomes after chemoradiotherapy for LA-NSCLC, and pembrolizumab monotherapy is now a standard of care for patients with advanced high PD-L1-positive NSCLC. We hypothesize that dose-painted thoracic radiotherapy and immunotherapy without chemotherapy will be safe and effective for the treatment of biomarker-selected patients with LA-NSCLC. Methods: Patients with a new diagnosis of unresectable stage II or stage III NSCLC and performance status 0-1 will be enrolled on this phase II trial at one of three participating institutions. Twenty-five subjects with PD-L1 Tumor Proportion Score (TPS) of at least 50% will receive three cycles of induction pembrolizumab (200 mg every 3 weeks). Subjects then receive 20 fractions of dose-painted radiotherapy, where lesions with metabolic tumor volume exceeding 20 cc on FDG-PET receive a dose of 55 Gy, while smaller lesions receive a dose of 48 Gy. Subjects then receive 12 additional cycles of pembrolizumab. The primary endpoint is progression-free survival one year following study enrollment, which we hypothesize will be achieved for at least 65% of study subjects. Other endpoints include overall survival, distant metastasis-free survival, freedom from intrathoracic disease progression, adverse events, patient-reported outcomes, and physical activity metrics captured using wearable devices. In addition, we will explore markers of immune activation as prognostic factors. Approximately 38 patients with PD-L1 TPS below 50% will receive standard chemoradiotherapy and adjuvant therapy to serve as a contemporary comparison cohort. SPRINT is an innovative biomarker-driven study that explores a paradigm shift in the local and systemic therapy used to treat LA-NSCLC. This trial opened in August of 2018, and 5 subjects have been enrolled to date. Clinical trial information: NCT03523702.

Characterizing the Connectivity of Railway Networks

How well stations are connected with each other is a critical performance assessment of railway systems. Network analysis is a highly intuitive and interpretable approach to characterizing the physical connectivity of railway systems. However, the physical connectivity is often limited in depicting transportation network dynamics due to the lack of traffic flow information. This paper first comprehensively reviews the physical connectivity metrics and applies these metrics to evaluate the connectivity of China’s high-speed railway system. Then, through integrating the real-world network topology and travel demand data, we conduct the first data-driven research on comparing the physical connectivity with the logical connectivity of railway systems. The experiments demonstrate that the physical connectivity metrics cannot well represent the connectivity of railway systems, due to the neglect of the heterogeneous distribution and temporal patterns of the passenger flows.

A closer look at the relationship among accelerometer-based physical activity metrics: ICAD pooled data

BackgroundAccelerometers are widely used to assess child physical activity (PA) levels. Using the accelerometer data, several PA metrics can be estimated. Knowledge about the relationships between these different metrics can improve our understanding of children’s PA behavioral patterns. It also has significant implications for comparing PA metrics across studies and fitting a statistical model to examine their health effects. The aim of this study was to examine the relationships among the metrics derived from accelerometers in children.MethodsAccelerometer data from 24,316 children aged 5 to 18 years were extracted from the International Children’s Accelerometer Database (ICAD) 2.0. Correlation coefficients between wear time, sedentary behavior (SB), light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate- and vigorous-intensity PA (MVPA), and total activity counts (TAC) were calculated.ResultsTAC was approximately 22X103 counts higher (p < 0.01) with longer wear time (13 to 18 h/day) as compared to shorter wear time (8 to < 13 h/day), while MVPA was similar across the wear time categories. MVPA was very highly correlated with TAC (r = .91; 99% CI = .91 to .91). Wear time-adjusted correlation between SB and LPA was also very high (r = −.96; 99% CI = -.96, − 95). VPA was moderately correlated with MPA (r = .58; 99% CI = .57, .59).ConclusionsTAC is mostly explained by MVPA, while it could be more dependent on wear time, compared to MVPA. MVPA appears to be comparable across different wear durations and studies when wear time is ≥8 h/day. Due to the moderate to high correlation between some PA metrics, potential collinearity should be addressed when including multiple PA metrics together in statistical modeling.

Von Neumann stability of modified loop quantum cosmologies

von Neumann stability analysis of quantum difference equations in loop quantized spacetimes has often proved useful to understand the viability of quantizations and whether a general relativistic description is recovered at small spacetime curvatures. We use this technique to analyze the infra-red behavior of the quantum Hamiltonian constraint in recently explored modifications of loop quantum cosmology: mLQC-I and mLQC-II, for the spatially flat FLRW model. We investigate the behavior for the scheme, where the minimum area of loops in the quantization procedure does not take physical metric in to account, and the scheme where quantization procedure uses a physical metric. The fate of stability of quantum difference equations is tested for massless scalar field as well as with inclusion of a positive cosmological constant. We show that for mLQC-I and mLQC-II, the difference equation fails to be von Neumann stable for the scheme if a cosmological constant is included signaling problematic behavior at large volumes. Both of the modified loop quantum cosmologies are von Neumann stable for the scheme. In contrast to standard loop quantum cosmology, properties of roots turn out to be richer and intricate. Our results demonstrate the robustness of the scheme (or ‘improved dynamics’) in loop quantization of cosmological spacetimes even when non-trivial quantization ambiguities of the Hamiltonian are considered, and show that the scheme is non-viable in this setting.

An optimized multi‐attribute vertical handoff approach for heterogeneous wireless networks

SummaryWireless networking is becoming an increasingly important and popular way of providing global information access to users on mobility. Considering the accessibility of different advances, it is hard to choose the best system that guarantees client fulfilment. The best network selection in heterogeneous condition is a primary research issue. In Dynamic Network Selection Function (DNSF) method, which employs physical layer metrics as criteria for network selection, computation of functions‐based relative dynamic weight optimization is proposed. This method is implemented through simulation in a typical heterogeneous wireless environment of Universal Mobile Telecommunications Service (UMTS) and Wireless Local Area Network (WLAN). The number of unnecessary handover occasions with the Handoff failure rate of the client between accessible systems is utilized as the execution measurements, and constantly best‐associated system is chosen in view of the cost function. It is inferred that DNSF based approach yields ideal system determination in heterogeneous condition.

Exposure to Potentially Harmful E-Cigarette Emissions via Vape Tricks: Protocol for a Mixed-Methods Study.

BackgroundThe number of adolescents and adults using e-cigarettes, referred to as vaping, has dramatically increased. E-cigarettes can be used to perform vape tricks by inhaling and exhaling the e-cigarette aerosol in patterns to create visual effects or large clouds. To create these effects, the puffing patterns associated with vape tricks may be different than standard ad-lib e-cigarette usage. The prevalence of vape tricks and the harm associated with exposure to e-cigarette emissions when performing vape tricks is currently unknown.ObjectiveOur objectives are to characterize duration, heart rate, respiratory rate, tidal volume, minute volume, and physical activity metrics associated with the performance of vape tricks and to characterize the emission of e-cigarettes when performing vape tricks in a manner suitable to inform novel exposure modeling.MethodsThe study will recruit e-cigarette users with a history of performing vape tricks. Data collection will occur in two different sessions. In the first session, participants will be asked to puff on their e-cigarette as they normally would for 20 minutes. The second session will be a vape tricks session, where users will be asked to perform a series of up to five different vape tricks with their e-cigarette. Data will be collected through screener surveys, in-person interviews, video recordings, a personal exposure monitor, and a biometric garment.ResultsData analysis is pending and scheduled to take place in the fall of 2019.ConclusionsThis study will be used to assess the feasibility of using a biometric garment to complement environmental and observational data. The approach may provide greater insight into the health risks of performing vape tricks compared to typical e-cigarette use.International Registered Report Identifier (IRRID)DERR1-10.2196/12304

Intermittent bolus versus continuous infusion techniques for local anesthetic delivery in peripheral and truncal nerve analgesia: the current state of evidence

Manually delivered intermittent bolus (MIB) and programmable intermittent bolus (PIB), alternatives to continuous infusion (CI), involve administering a set volume of solution at a set interval of time. The benefits...

Wearable activity trackers, accuracy, adoption, acceptance and health impact: A systematic literature review.

Wearable activity trackers (WAT) are electronic monitoring devices that enable users to track and monitor their health-related physical fitness metrics including steps taken, level of activity, walking distance, heart rate, and sleep patterns. Despite the proliferation of these devices in various contexts of use and rising research interests, there is limited understanding of the broad research landscape. The purpose of this systematic review is therefore to synthesize the existing wealth of research on WAT, and to provide a comprehensive summary based on common themes and approaches. This article includes academic work published between 2013 and 2017 in PubMed, Embase, Scopus, Web of Science, ACM Digital Library, and Google Scholar. A final list of 463 articles was analyzed for this review. Topic modeling methods were used to identify six key themes (topics) of WAT research, namely: (1) Technology Focus, (2) Patient Treatment and Medical Settings, (3) Behavior Change, (4) Acceptance and Adoption (Abandonment), (5) Self-monitoring Data Centered, and (6) Privacy. We take an interdisciplinary approach to wearable activity trackers to propose several new research questions. The most important research gap we identify is to attempt to understand the rich human-information interaction that is enabled by WAT adoption.

Efficient prediction of the electrical conductivity and percolation threshold of nanocomposite containing spherical particles with three-dimensional random representative volume elements by random filler removal

In this work, the effective electrical conductivity (EEC) and percolation threshold (PT) of a nanocomposite containing spherical particle fillers are predicted by computational homogenization schemes (CHS) with three-dimensional random representative volume elements (RVEs) by random filler removal (RFR). For this prediction, we prepare the RVE having the maximum filler volume fraction (Vf) of 52% with random particle fillers, also termed the master model, by the discrete element method (DEM), and the corresponding finite-element (FE) model is created. Then, 100 RVE samples for each Vf are derived by randomly replacing the material properties of several fillers by those of the matrix from the master model with diverse Vf from 5% to 50%. In addition, the interphase layer is employed by replacing some matrix elements with interphase elements according to the neighboring distance of the fillers.To demonstrate the performance of the proposed scheme, its randomness of RVEs is verified by spatial and physical metrics in terms of autocorrelation analysis, near-neighbor analysis, and directional conductivity ratio. The EEC prediction results with diverse Vf values are compared with those of an analytical model and test results. As a result, the PT at which EEC of the nanocomposites suddenly increases is successfully evaluated, and the effect of the void, interphase thickness, and conductivity, as well as the size of fillers on the EEC and PT is investigated through a sensitivity analysis.

Human-in-the-Loop Wireless Communications: Machine Learning and Brain-Aware Resource Management

Human-centric applications such as virtual reality and immersive gaming are central to future wireless networks. Common features of such services include: 1) their dependence on the human user’s behavior and state and 2) their need for more network resources compared to conventional applications. To successfully deploy such applications over wireless networks, the network must be made cognizant of not only the quality-of-service (QoS) needs of the applications, but also of the perceptions of the human users on this QoS. In this paper, by explicitly modeling the limitations of the human brain, a concrete measure for the delay perception of human users is introduced. Then, a learning method, called probability distribution identification, is developed to find a probabilistic model for this delay perception based on the brain features of a human user. Given the learned model for the delay perception of the human brain, a brain-aware resource management algorithm based on Lyapunov optimization is proposed for allocating radio resources to human users while minimizing the transmit power and taking into account the reliability of both machine type devices and human users. Then, a closed-form relationship between the reliability measure and wireless physical layer metrics of the network is derived. Simulation results show that a brain-aware approach can yield savings of up to 78% in power compared to the system that only considers QoS metrics. The results also show that, compared with QoS-aware, brain-unaware systems, the brain-aware approach can save substantially more power in low-latency systems.

Physical demands on elite lead rugby union referees

ABSTRACTThe aim of this study was to determine the physical demands on elite rugby referees by measuring match duration and some key global positioning system (GPS) metrics such as distance covered, heart rate, speed and metabolic power and to assess whether physical demands changed during the course of the match (first half vs. second half). Physical profile data and GPS metrics were collected from 17 elite referees during 205 matches. Mean match duration was 98 min and distance covered was 6 826 m. Referees produced 5% more metabolic power during the first half of a match (mean: 6.2 W/kg) compared to the second half. Referees spent 27% of the time in the “work zone” (speed 4.1 m/s and above). During a match, referees spent 46.8% of the time below 80% HRmax. Mean numbers of high-speed accelerations, decelerations and sprints/surges were approximately 20% lower during the second half. Comparison of between-individual and within-individual variation of referee physical performance suggests that referees generally performed consistently. Factors such as referee experience and increased rates of substitution might contribute to the reduced power measures during the second half. The results from this investigation can contribute to the development of lead rugby referee-specific physical conditioning programmes.

Protocol for the PreventIT feasibility randomised controlled trial of a lifestyle-integrated exercise intervention in young older adults

IntroductionThe European population is rapidly ageing. In order to handle substantial future challenges in the healthcare system, we need to shift focus from treatment towards health promotion. The PreventIT project...

A Method for Sensor Reduction in a Supervised Machine Learning Classification System

Smart devices employing interconnected sensors for feedback and control are being rapidly adopted. Many useful applications for these devices are in markets that demand cost-conscious solutions. Traditional machine-learning-based control systems often rely on multiple measurements from many sensors to achieve performance targets. An alternative method is presented that leverages a time-series output produced by a single sensor. By using domain expert knowledge, the time-series output is discretized into finite intervals that correspond to the physical events occurring in the system. Statistical measures are taken across these intervals to serve as the features to the machine learning system. Additional features that decouple key physical metrics are identified, improving the performance of the system. This novel approach requires a more modest dataset and does not compromise performance. The resulting development effort is significantly more cost-effective than traditional sensor classification systems, not only due to the reduced sensor count, but also due to a significantly simplified and more robust algorithm development and testing step. Results are presented with the case study of a media-type classification system within a printing system, which was deployed to the field as a commercial product.

Impact of Physical Conditioning on Outcomes in Transplant Patients: Retrospective Data Analysis

Background Stem cell transplantation is a potential curative procedure for many patients with hematologic malignancies. These patients because of age, co-morbid medical conditions and prior therapies can present in various physical conditions from good performance status to poor or frail. This may affect transplant outcome in terms of survival and relapse free survival. A component of our transplant program is a pre-transplant evaluation with cancer rehab specialists. Standard measures are obtained including the visual analog scales for pain and fatigue, timed up and go, and distress thermometer. An exercise program is prescribed for the patient prior to admission as well as during hospitalization and discharge. At day 60 after transplant these standard measures are re-assessed. Our study aims to assess the relationship of measurable physical conditioning metrics and outcomes in survival, progression free survival, relapse rate and transplant related mortality. Methods We conducted a retrospective review of 134 patients who have undergone hematopoietic stem cell transplantation with at least 60 days of follow-up. We collected the data from their pre-transplant cancer rehab evaluation and their 60 day post transplant evaluation including their Karnofsky Performance Status (KPS) score, timed up and go, fatigue and distress measurements. Using their KPS score patients were categorized as high performers (KPS >80) and low performers (KPS Results Our data showed there was increased survival of high performers compared to low performers (p=0.0270). Patients experienced significant decreases in pain scores, fatigue, and distress after transplant. There were no significant differences in progression free survival, relapse rate, or transplant related mortality between high performers and low performers. Conclusions Physical conditioning can lead to better outcomes in terms of survival and symptoms; fatigue, pain, and distress. Future studies of rehab interventions are needed to better understand our observed survival and symptom benefit.

Associations between daily-living physical activity and laboratory-based assessments of motor severity in patients with falls and Parkinson's disease

IntroductionRecent work suggests that wearables can augment conventional measures of Parkinson's disease (PD). We evaluated the relationship between conventional measures of disease and motor severity (e.g., MDS-UPDRS part III), laboratory-based measures of gait and balance, and daily-living physical activity measures in patients with PD. MethodsData from 125 patients (age: 71.7 ± 6.5 years, Hoehn and Yahr: 1–3, 60.5% men) were analyzed. The MDS-UPDRS-part III was used as the gold standard of motor symptom severity. Gait and balance were quantified in the laboratory. Daily-living gait and physical activity metrics were extracted from an accelerometer worn on the lower back for 7 days. ResultsIn multivariate analyses, daily-living physical activity and gait metrics, laboratory-based balance, demographics and subject characteristics together explained 46% of the variance in MDS-UPDRS-part III scores. Daily-living measures accounted for 62% of the explained variance, laboratory measures 30%, and demographics and subject characteristics 7% of the explained variance. Conversely, demographics and subject characteristics, laboratory-based measures of gait symmetry, and motor symptom severity together explained less than 30% of the variance in total daily-living physical activity. MDS-UPDRS-part III scores accounted for 13% of the explained variance, i.e., <4% of all the variance in total daily-living activity. ConclusionsOur findings suggest that conventional measures of motor symptom severity do not strongly reflect daily-living activity and that daily-living measures apparently provide important information that is not captured in a conventional one-time, laboratory assessment of gait, balance or the MDS-UPDRS. To provide a more complete evaluation, wearable devices should be considered.

Regional Patterns of Extreme Precipitation and Urban Signatures in Metropolitan Areas

AbstractObservations show that metropolitan areas throughout China, which are experiencing rapid urbanization, may have enhanced extreme precipitation. However, the underlying urban‐induced mechanism is poorly understood, particularly for entire characteristics of extreme precipitation. Focusing on the Beijing metropolitan area, we investigate regional patterns of extreme precipitation characterized by magnitude, frequency, duration, and timing metrics according to daily observations from 1975 to 2015 at 20 weather stations. Urbanization effects are explored by physical metrics of urbanization, including area, complexity, fragmentation, and dominance deduced from five periods of land use maps. Results show that the magnitudes and frequencies of extreme precipitation have decreased over time, the consecutive precipitation days have been extended, and the Julian date of maximum precipitation has been delayed. Temporal trends at ~40% of weather stations are significant. According to precipitation metrics and geographical features, three representative regions are identified: the central urban region, the windward slope of topographic area, and the mountainous region. Compared with the metrics in mountainous region, the magnitudes of windward slope and central urban region are 24.3–60.6% and 5.9–47.3% greater, respectively; the frequencies are increased by 1.17 and 1.10 days, respectively; and the average date of maximum precipitation values are delayed by 7.0 and 4.0 days, respectively. The magnitudes and frequencies are enhanced by expansion of urban area, complexity, fragmentation, dominance, and heat islands. The durations are positive for urban area and dominance but negative for urban complexity, fragmentation, and heat islands. Furthermore, the effects in central urban region are more significant due to high urbanization rates.

Table Tennis Ball Impacting Racket Polymeric Coatings: Experiments and Modeling of Key Performance Metrics

The performance of a table tennis racket is often associated with subjective or quantitative criteria such as the adhesion, the control and the speed. Overall, the so-called performance aims at characterizing the impact with the ball. Ultimately, the polymeric layers glued onto the wooden blade play a key role, as evidenced in a previous work where the normal linear (no spin) impact of a ball onto polymeric layers was experimentally and numerically investigated. In this work, more realistic loading conditions leading to varying the incident angle and spin of the ball, were explored. While the sole linear restitution coefficient was determined in the anterior normal impact study, new physical metrics were identified to describe fully the trajectory of the reflected ball after impact. A companion 3D finite elements model was developed where the polymeric time-dependent dissipative compliant behavior measured with dynamic mechanical analysis and compression tests was accounted for. The confrontations with the experimental data highlighted the key role of the polymer intrinsic properties along with the friction coefficient between the ball and the polymer external layer.