Background independent field quantization with sequences of gravity-coupled approximants. II. Metric fluctuations

ABSTRACTThe slow flow of granular materials is often marked by the existence of narrow shear layers, adjacent to large regions that suffer little or no deformation. This behaviour, in the regime where shear stress is generated primarily by the frictional interactions between grains, has so far eluded theoretical description. In this paper, we present a rigid-plastic frictional Cosserat model that captures thin shear layers by incorporating a microscopic length scale. We treat the granular medium as a Cosserat continuum, which allows the existence of localised couple stresses and, therefore, the possibility of an asymmetric stress tensor. In addition, the local rotation is an independent field variable and is not necessarily equal to the vorticity. The angular momentum balance, which is implicitly satisfied for a classical continuum, must now be solved in conjunction with the linear momentum balances. We extend the critical state model, used in soil plasticity, for a Cosserat continuum and obtain predictions for flow in plane and cylindrical Couette devices. The velocity profile predicted by our model is in qualitative agreement with available experimental data. In addition, our model can predict scaling laws for the shear layer thickness as a function of the Couette gap, which must be verified in future experiments. Most significantly, our model can determine the velocity field in viscometric flows, which classical plasticity-based model cannot.

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More on holographic correlators: twisted and dimensionally reduced structures

Journal of High Energy Physics ◽

10.1007/jhep04(2021)008 ◽

2021 ◽

Vol 2021 (4) ◽

Author(s):

Connor Behan ◽

Pietro Ferrero ◽

Xinan Zhou

Keyword(s):

Field Theory ◽

Theoretical Data ◽

Infinite Family ◽

Tree Level ◽

Chiral Algebra ◽

Perfect Agreement ◽

Four Dimensions ◽

Independent Field ◽

Superconformal Theories ◽

Emergent Structure

Abstract Recently four-point holographic correlators with arbitrary external BPS operators were constructively derived in [1, 2] at tree-level for maximally superconformal theories. In this paper, we capitalize on these theoretical data, and perform a detailed study of their analytic properties. We point out that these maximally supersymmetric holographic correlators exhibit a hidden dimensional reduction structure à la Parisi and Sourlas. This emergent structure allows the correlators to be compactly expressed in terms of only scalar exchange diagrams in a dimensionally reduced spacetime, where formally both the AdS and the sphere factors have four dimensions less. We also demonstrate the superconformal properties of holographic correlators under the chiral algebra and topological twistings. For AdS5× S5 and AdS7× S4, we obtain closed form expressions for the meromorphic twisted correlators from the maximally R-symmetry violating limit of the holographic correlators. The results are compared with independent field theory computations in 4d $$ \mathcal{N} $$ N = 4 SYM and the 6d (2, 0) theory, finding perfect agreement. For AdS4× S7, we focus on an infinite family of near-extremal four-point correlators, and extract various protected OPE coefficients from supergravity. These OPE coefficients provide new holographic predictions to be matched by future supersymmetric localization calculations. In deriving these results, we also develop many technical tools which should have broader applicability beyond studying holographic correlators.

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Black hole solutions in modified gravity induced by quantum metric fluctuations

Physics of the Dark Universe ◽

10.1016/j.dark.2020.100756 ◽

2021 ◽

Vol 31 ◽

pp. 100756

Author(s):

Jin-Zhao Yang ◽

Shahab Shahidi ◽

Tiberiu Harko ◽

Shi-Dong Liang

Keyword(s):

Black Hole ◽

Modified Gravity ◽

Black Hole Solutions ◽

Metric Fluctuations

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Novel Application and Validation of a Method to Assess Visual Impacts of Rotating Wind Turbine Blades Within Woodland Areas

PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science ◽

10.1007/s41064-021-00141-4 ◽

2021 ◽

Vol 89 (1) ◽

pp. 1-14

Author(s):

U. Nopp-Mayr ◽

F. Kunz ◽

F. Suppan ◽

E. Schöll ◽

J. Coppes

Keyword(s):

Environmental Impact ◽

Wind Turbine ◽

Wind Turbines ◽

Power Plants ◽

Laser Scanning ◽

Forest Canopy ◽

Turbine Blades ◽

Wind Turbine Blades ◽

Environmental Impact Assessments ◽

Independent Field

AbstractIncreasing numbers of wind power plants (WPP) are constructed across the globe to reduce the anthropogenic contribution to global warming. There are, however, concerns on the effects of WPP on human health as well as related effects on wildlife. To address potential effects of WPP in environmental impact assessments, existing models accounting for shadow flickering and noise are widely applied. However, a standardized, yet simple and widely applicable proxy for the visibility of rotating wind turbines in woodland areas was largely lacking up to date. We combined land cover information of forest canopy extracted from orthophotos and airborne laser scanning (LiDAR) data to represent the visibility of rotating wind turbines in five woodland study sites with a high spatial resolution. Performing an in-situ validation in five study areas across Europe which resulted in a unique sample of 1738 independent field observations, we show that our approach adequately predicts from where rotating wind turbine blades are visible within woodlands or not. We thus provide strong evidence, that our approach yields a valuable proxy of the visibility of moving rotor blades with high resolution which in turn can be applied in environmental impact assessments of WPP within woodlands worldwide.

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Developing a Simulated Online Model That Integrates GNSS, Accelerometer and Weather Data to Detect Parturition Events in Grazing Sheep: A Machine Learning Approach

Animals ◽

10.3390/ani11020303 ◽

2021 ◽

Vol 11 (2) ◽

pp. 303

Author(s):

Eloise S. Fogarty ◽

David L. Swain ◽

Greg M. Cronin ◽

Luis E. Moraes ◽

Derek W. Bailey ◽

...

Keyword(s):

Machine Learning ◽

Field Trials ◽

Satellite System ◽

False Positives ◽

Sensor Data ◽

Weather Data ◽

Integrated Sensor ◽

Detection Model ◽

Independent Field ◽

Grazing Sheep

In the current study, a simulated online parturition detection model is developed and reported. Using a machine learning (ML)-based approach, the model incorporates data from Global Navigation Satellite System (GNSS) tracking collars, accelerometer ear tags and local weather data, with the aim of detecting parturition events in pasture-based sheep. The specific objectives were two-fold: (i) determine which sensor systems and features provide the most useful information for lambing detection; (ii) evaluate how these data might be integrated using ML classification to alert to a parturition event as it occurs. Two independent field trials were conducted during the 2017 and 2018 lambing seasons in New Zealand, with the data from each used for ML training and independent validation, respectively. Based on objective (i), four features were identified as exerting the greatest importance for lambing detection: mean distance to peers (MDP), MDP compared to the flock mean (MDP.Mean), closest peer (CP) and posture change (PC). Using these four features, the final ML was able to detect 27% and 55% of lambing events within ±3 h of birth with no prior false positives. If the model sensitivity was manipulated such that earlier false positives were permissible, this detection increased to 91% and 82% depending on the requirement for a single alert, or two consecutive alerts occurring. To identify the potential causes of model failure, the data of three animals were investigated further. Lambing detection appeared to rely on increased social isolation behaviour in addition to increased PC behaviour. The results of the study support the use of integrated sensor data for ML-based detection of parturition events in grazing sheep. This is the first known application of ML classification for the detection of lambing in pasture-based sheep. Application of this knowledge could have significant impacts on the ability to remotely monitor animals in commercial situations, with a logical extension of the information for remote monitoring of animal welfare.

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Development of multiple representation based mechanics lectures using dependent and independent field (MR-FD & FI)

Journal of Physics Conference Series ◽

10.1088/1742-6596/1731/1/012083 ◽

2021 ◽

Vol 1731 ◽

pp. 012083

Author(s):

T I Hartini ◽

S Liliasari ◽

A Setiawan ◽

T R Ramalis

Keyword(s):

Multiple Representation ◽

Independent Field

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Forest Road Status Assessment Using Airborne Laser Scanning

Forest Science ◽

10.1093/forsci/fxz053 ◽

2019 ◽

Vol 66 (4) ◽

pp. 501-508 ◽

Cited By ~ 1

Author(s):

Katalin Waga ◽

Piotr Tompalski ◽

Nicholas C Coops ◽

Joanne C White ◽

Michael A Wulder ◽

...

Keyword(s):

British Columbia ◽

Laser Scanning ◽

Airborne Laser Scanning ◽

Height Distribution ◽

Forest Roads ◽

The Road ◽

Airborne Laser ◽

Independent Field ◽

The Status ◽

The Impact

Abstract Forest roads allow access for silvicultural operations, harvesting, recreational activities, wildlife management, and fire suppression. In British Columbia, Canada, roads that are no longer required must be deactivated (temporarily, semipermanently, or permanently) in order to minimize the impact on the overall forested ecosystem. However, the remoteness and size of the road network present challenges for monitoring. Our aim was to examine the utility of airborne laser scanning data to assess the status and quality of forest roads across 52,000 hectares of coastal forest in British Columbia. Within the forest estate, roads can be active or deactivated, or have an unknown status. We classified road segments based on the vegetation growth on the road surface, and edges, by classifying the height distribution of airborne laser scanning returns within each road segment into four groups: no vegetation, minor vegetation, dense understory vegetation, and dense overstory vegetation. Validation indicated that 73 percent of roads were classified correctly when compared to independent field observations. The majority were classified as active roads with no vegetation or deactivated with dense vegetation. The approach presented herein can aid forest managers in verifying the status of the roads in their management area, especially in remote areas where field assessments are costly and time-consuming.

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