Distance Estimation Research Articles

Robot remote control using virtual reality headset: studying sense of agency with subjective distance estimates

Mobile robots have many applications in the modern world. The autonomy of robots is increasing, but critical cases like search and rescue missions must involve the possibility of human intervention for ethical reasons and safety. To achieve effective human–robot interaction, the operator needs to have a sense of agency (SoA) over the activities of the robot. One possible way to increase one's SoA in remote control could be the use of VR technology. The remote control situation has some important features, so indicators of SoA need to be reproduced there independently. In our study, participants controlled a mobile robot using either a monitor or a VR-headset as an output device. In both cases, active control was contrasted with passive observation of the robot's movement. In each trial, participants estimated the distance traveled by the robot—a putative implicit indicator of SoA. A significant difference between subjective distance estimates was found in the active and passive conditions with the monitor, but not in the active and passive conditions with VR. The effect obtained in the monitor conditions suggests that distance estimates can be used as an implicit indicator of SoA in robot remote control. We believe that the lack of difference between the active and passive conditions in VR was caused by motion sickness due to a mismatch of visual and vestibular sensory cues, leading to a weakened SoA.

Effect of Data-Processing Methods on Acceleration Summary Metrics of GNSS Devices in Elite Australian Football.

This study aimed to measure the differences in commonly used summary acceleration metrics during elite Australian football games under three different data processing protocols (raw, custom-processed, manufacturer-processed). Estimates of distance, speed and acceleration were collected with a 10-Hz GNSS tracking technology device from fourteen matches of 38 elite Australian football players from one team. Raw and manufacturer-processed data were exported from respective proprietary software and two common summary acceleration metrics (number of efforts and distance within medium/high-intensity zone) were calculated for the three processing methods. To estimate the effect of the three different data processing methods on the summary metrics, linear mixed models were used. The main findings demonstrated that there were substantial differences between the three processing methods; the manufacturer-processed acceleration data had the lowest reported distance (up to 184 times lower) and efforts (up to 89 times lower), followed by the custom-processed distance (up to 3.3 times lower) and efforts (up to 4.3 times lower), where raw data had the highest reported distance and efforts. The results indicated that different processing methods changed the metric output and in turn alters the quantification of the demands of a sport (volume, intensity and frequency of the metrics). Coaches, practitioners and researchers need to understand that various processing methods alter the summary metrics of acceleration data. By being informed about how these metrics are affected by processing methods, they can better interpret the data available and effectively tailor their training programs to match the demands of competition.

Reimagining Accessibility: Leveraging Deep Learning in Smartphone Applications to Assist Visually Impaired People Indoor Object Distance Estimation

Every other aspect of life is organized around the sight. A person with vision impairment suffers severely from independent mobility and quality of life. The proposed framework combines mobile deep learning with distance estimation algorithms to detect and classify indoor objects with estimated distance in real-time during indoor navigation. The user, wearing the device with a lanyard or holding it in a way that positions the camera forward, identifies in real-time surroundings indoor objects with estimated distance and voice commentary. Moreover, the mobile framework provides an estimated distance to the obstacles and suggests a safe navigational path through voice-guided feedback. By harnessing the power of deep learning in a mobile setting, this framework aims to improve the independence of visually impaired individuals by facilitating them a higher degree of independence in indoor navigation. This study's proposed mobile object detection and distance estimation framework achieved 99.75% accuracy. This research contributes by leveraging mobile deep learning with identifying objects in real-time, classification and distance estimation, a state-of-the-art approach to use the latest technologies to enhance indoor mobility challenges faced by visually impaired people.

Odour source distance is predictable from a time history of odour statistics for large scale outdoor plumes.

Odour plumes in turbulent environments are intermittent and sparse. Laboratory-scaled experiments suggest that information about the source distance may be encoded in odour signal statistics, yet it is unclear whether useful and continuous distance estimates can be made under real-world flow conditions. Here, we analyse odour signals from outdoor experiments with a sensor moving across large spatial scales in desert and forest environments to show that odour signal statistics can yield useful estimates of distance. We show that achieving accurate estimates of distance requires integrating statistics from 5 to 10 s, with a high temporal encoding of the olfactory signal of at least 20 Hz. By combining distance estimates from a linear model with wind-relative motion dynamics, we achieved source distance estimates in a 60 × 60 m2 search area with median errors of 3-8 m, a distance at which point odour sources are often within visual range for animals such as mosquitoes.

A Diamond Ring in X-Ray: Investigating the Diffuse Emission of Supernova Remnant G28.8+1.5

Supernova remnants are products of supernova explosions, which are usually observed in the X-ray band. However, the diffuse emission from the galactic supernova remnant G28.8+1.5 has been overlooked following initial searches for pulsars and pulsar wind nebulae. This paper presents background-subtracted imaging and spatial-resolved spectral analyses using archival XMM-Newton data to reveal unprecedented details of the diffuse emission, providing updated estimates of distance and age. For the first time, an iron overabundance is revealed and the progenitor is suggested to be 9–15 M ⊙. These findings refine our understanding of G28.8+1.5 and contribute to a broader comprehension of the Galactic supernova remnant family.

Distance Estimate Method for Asymptotic Giant Branch Stars Using Infrared Spectral Energy Distributions

We present a method to estimate distances to asymptotic giant branch (AGB) stars in the Galaxy, using spectral energy distributions (SEDs) in the near- and mid-infrared. By assuming that a given set of source properties (initial mass, stellar temperature, composition, and evolutionary stage) will provide a typical SED shape and brightness, sources are color matched to a distance-calibrated template and thereafter scaled to extract the distance. The method is tested by comparing the distances obtained to those estimated from very long baseline interferometry or Gaia parallax measurements, yielding a strong correlation in both cases. Additional templates are formed by constructing a source sample likely to be close to the Galactic center, and thus with a common, typical distance for calibration of the templates. These first results provide statistical distance estimates to a set of almost 15,000 Milky Way AGB stars belonging to the Bulge Asymmetries and Dynamical Evolution (BAaDE) survey, with typical distance errors of ±35%. With these statistical distances, a map of the intermediate-age population of stars traced by AGBs is formed, and a clear bar structure can be discerned, consistent with the previously reported inclination angle of 30° to the GC–Sun direction vector. These results motivate deeper studies of the AGB population to tease out the intermediate-age stellar distribution throughout the Galaxy, as well as determining statistical properties of the AGB population luminosity and mass-loss-rate distributions.

HyperGen: Compact and Efficient Genome Sketching using Hyperdimensional Vectors.

Genomic distance estimation is a critical workload since exact computation for whole-genome similarity metrics such as Average Nucleotide Identity (ANI) incurs prohibitive runtime overhead. Genome sketching is a fast and memory-efficient solution to estimate ANI similarity by distilling representative k-mers from the original sequences. In this work, we present HyperGen that improves accuracy, runtime performance, and memory efficiency for large-scale ANI estimation. Unlike existing genome sketching algorithms that convert large genome files into discrete k-mer hashes, HyperGen leverages the emerging hyperdimensional computing (HDC) to encode genomes into quasi-orthogonal vectors (Hypervector, HV) in high-dimensional space. HV is compact and can preserve more information, allowing for accurate ANI estimation while reducing required sketch sizes. In particular, the HV sketch representation in HyperGen allows efficient ANI estimation using vector multiplication, which naturally benefits from highly optimized general matrix multiply (GEMM) routines. As a result, HyperGen enables the efficient sketching and ANI estimation for massive genome collections. We evaluate HyperGen 's sketching and database search performance using several genome datasets at various scales. HyperGen is able to achieve comparable or superior ANI estimation error and linearity compared to other sketch-based counterparts. The measurement results show that HyperGen is one of the fastest tools for both genome sketching and database search. Meanwhile, HyperGen produces memory-efficient sketch files while ensuring high ANI estimation accuracy. A Rust implementation of HyperGen is freely available under the MIT license as an open-source software project at https://github.com/wh-xu/Hyper-Gen. The scripts to reproduce the experimental results can be accessed at https://github.com/wh-xu/experiment-hyper-gen.

Distance correction range-free localization algorithm for WSNs

Accurate location information is essential for the effective deployment of Wireless Sensor Networks (WSNs) applications. Recently, researchers have developed numerous localization algorithms, with multi-hop methods being particularly attractive due to their cost-effectiveness and robustness, but their accuracy is still unsatisfactory. For better localization accuracy, this paper presented a distance correction range-free localization algorithm (DCRA). Firstly, the proposed algorithm estimates the distance between neighboring nodes based on neighbor connectivity to improve the accuracy of single-hop distance estimation. Secondly, during the multi-hop distance estimation phase, path similarity metrics are employed to ascertain the optimal path correction coefficients, thereby minimizing multi-hop distance estimation errors. Finally, based on the estimated distances, the node localization is converted into an optimization problem, which is then solved using an enhanced particle swarm algorithm to obtain the node coordinates. Simulation results show that the distance estimation accuracy of the DCRA algorithm in different node density scenarios is improved by more than 31 % and 12 % compared to the DV-Hop and DV-RND algorithms, respectively; and in terms of localization accuracy the DCRA algorithm is improved by more than 58 % and 35 % compared to the DV-Hop and DV-RND algorithms, respectively.

Curcuma species DNA fingerprinting of wild and cultivated genotypes from different agroclimatic zones

IntroductionCurcuma isolates from different agroclimatic zones in Chhattisgarh have been found to possess a varied spectrum of Curcumin, we set out to learn more about their genetic diversity by molecular fingerprinting in the present study. MethodsUsing SSR primers, the genetic variability of 25 Curcuma genotypes has been analyzed. These included the fingerprints of Curcuma longa, Curcuma aromatica, and Curcuma caesia. 13 inter simple sequence repeat (ISSR) primers amplified 107 unique fragments across all kinds, whereas 11 simple sequence repeat (SSR) primers amplified 51 unique fragments across all varieties, with 97 % and 86 % showing polymorphism, respectively. ResultsA total of 1080 ISSR and 567 SSR loci were amplified across all genotypes; among these, 5 monomorphic and 102 polymorphic alleles were produced in ISSR primers. However, SSR data showed 47 polymorphic and 4 monomorphic alleles. A panel of ISSR and SSR markers calculated DNA fingerprinting, genetic similarity, and distance estimates between Curcuma genotypes. In order to examine the diversity in different Curcuma genotypes, UPGMA data scoring methods were used. DiscussionCurcuma species demonstrate significant genetic variability, which is essential for breeding initiatives focused on creating better cultivars with desirable characteristics such as increased productivity, resistance to diseases, and improved medicinal capabilities.

Large Pool Fires in the Process Industry. A Simple Model for Safety Distances Estimation

In recent years, the global production growth and the complexity of processes operation have increased safety concern, especially during the design project, considering potential accidental events as fires, explosions, and their related domino effects. Pool fire is one of the most frequent accidental events. Some procedures for safety distances estimation from pool fires were reported. However, there is a lack of adequate simple models to directly estimate safety distances covering a wide range of substances and pool diameters, considering a continuous interval of receptor vulnerabilities (from damage to people to domino effect prevention). In this paper, a simple model to estimate safety distances is proposed, suitable to be incorporated into complex models (e.g. safety management systems, layout optimization). A surrogate model is achieved by adopting a reference one. Methodologically, the main variables that play a key role modelling a pool fire were selected and their influence on the safety distance was analyzed to propose simple mathematical expressions. NLP optimization problems were solved to optimize the model parameters. A conservative, accurate and easy-to-use model was achieved with the aim of developing safer plants or for their safe operation by improving the optimal process design, or implementing safe management systems, considering risks.

Factors influencing the occurrence of the House Sparrow Passer domesticus (Linnaeus, 1758) (Aves: Passeriformes: Passeridae) in Bhavnagar, Gujarat, India

The present study aims to understand key factors influencing the House Sparrow population across different habitat scales in Bhavnagar, Gujarat, India. Correspondingly, different variables such as changes in habitat composition, sound levels, and density of mobile phone base stations were considered with reference to the occurrence of the House Sparrows across the study area. During the study period (December 2016 to November 2018), the number of House Sparrows was recorded through point count without distance estimate method. Non-parametric tests were employed to assess variations in different variables and their correlation with the presence of House Sparrows, revealing that changes in local habitat composition significantly influence their occurrence. Shrubby vegetation, cowsheds, and old/traditional structures emerged as crucial predictors positively impacting House Sparrow’s presence, particularly in urban areas where suitable habitat patches are scarce due to urbanization and modern lifestyles. The decline in these habitats has significantly impacted House Sparrow populations. To counter this decline, implementing strategies like providing artificial nest sites is being considered. However, it’s crucial to ensure that there are adequate shelter and food resources available to effectively conserve the species.

Development of a real-world simulated instrument for evaluating visuospatial working memory: a preliminary psychometric study on older adults

BackgroundA prevalent challenge in neuropsychological assessment, particularly when utilizing instruments designed for controlled laboratory environments, is that the outcomes may not correspond to an individual’s real-life status. Accordingly, assessments of visuospatial working memory (VSWM) conducted in such settings might fail to capture certain facets of this function, as it operates in real life. On the other hand, entirely ecological assessments may risk compromising internal validity. This study aimed to develop an intermediate mode of assessment that measures VSWM in older adults by employing a setting, a task, and a response format that aligns closely with both laboratory and ecological assessments. Furthermore, a preliminary investigation was carried out to study the variations in spatial cognition among different demographic groups.MethodsIn a two-session study, 77 healthy older adults, eight patients with mild cognitive impairment (MCI), and seven patients with Alzheimer’s disease (AD) were recruited to complete the wayfinding questionnaire (WQ), the Corsi block-tapping task (CBTT), and the Spatial Memory Table (SMT). The SMT is a novel instrument developed specifically for this study, aiming to provide a more accurate measure of VSWM performance in older adults’ everyday life. Test-retest and split-half reliabilities, as well as the face, content, concurrent, convergent, and known-groups validities, were analyzed to investigate the psychometric properties of the SMT.ResultsThe analyses were mainly centered on studying the psychometric properties of the SMT. Test-retest reliability (r = .753, p < .001) and split-half reliability (ρSC = 0.747) were found to be acceptable. Concurrent validity using CBTT (r = .264, p = .021), convergent validity using WQ subscales (navigation and orientation: r = .282, p = .014; distance estimation: r = .261, p = .024), and known-groups validity using the SMT scores among people with MCI and AD (χ2 = 35.194, df = 2, p < .001) were also indicative of the instrument’s good validity. Data analysis also revealed acceptable levels of face validity (U = 4.50; p = .095) and content validity (CVR ≥ 0.60). As a result of comparing VSWM and wayfinding variables across genders and education levels, a significant difference was observed for navigation and orientation and spatial anxiety between women and men (p < .05). None of the variables were different among education levels.ConclusionThe SMT was found to be a reliable and valid tool for measuring VSWM performance in older adults. Given these findings, the SMT can be regarded as a measure that sufficiently approximates both laboratory and real-life demands for VSWM. Additionally, the instrument demonstrated a preliminary acceptable capacity to differentiate between healthy individuals and those with MCI and AD.

CRT-Based Clock Synchronization for Millimeter-Wave Communication with Asymmetric Propagation Delays

The rapid advancement of millimeter-wave communication technology has presented new challenges for time synchronization, driven by the need for high-speed and low-latency data transmission. Ethernet synchronization technologies, such as Precise Time Protocol (PTP), have emerged to overcome the limitations of point-to-point architecture and enable precise synchronization across multiple devices. A key drawback of conventional PTP is its reliance on symmetric packet exchange delays, which may not hold in real-world scenarios where there is relative mobility between master and slave nodes, leading to asymmetric propagation delays and clock offset errors. To address this issue, a novel clock synchronization protocol that integrates Chinese Remainder Theory (CRT) has been proposed. This protocol enhances conventional PTP by incorporating distance estimation based on CRT using multi-carrier phase measurement. By combining a coarse estimation of one-way propagation delay from conventional PTP with a fine estimation of remainder distance from CRT, the protocol accurately determines the distance between master and slave nodes, reducing motion errors and enhancing clock synchronization accuracy. Simulation results indicate that the Root Mean Square Error (RMSE) of distance estimation remains below 10−5 m, with a corresponding motion time error of approximately 0.01 picosecond.

Smart Drill for a Streamlined Estimation of the Drilling Angle and Channel Length in Orthopedic Surgical Procedures.

The estimation of distances and angles is a routine part of an orthopedic surgical procedure. However, despite their prevalence, these steps are most often performed manually, heavily relying on the surgeon's skill and experience. To address these issues, this study presents a sensor-equipped drill system which enables automatic estimation of the drilling angle and channel length. The angular accuracy and precision of the system were tested over a range of inclination angles and proved to be superior to the manual approach, with mean absolute errors ranging from 1.9 to 4.5 degrees for the manual approach, and from 0.6 to 1.3 degrees with the guided approach. When sensors were used for simultaneous estimation of both the inclination and anteversion angles, the obtained mean absolute errors were 0.35 ± 0.25 and 2 ± 1.33 degrees for the inclination and anteversion angles, respectively. Regarding channel length estimation, using measurements obtained with a Vernier caliper as a reference, the mean absolute error was 0.33 mm and the standard deviation of errors was 0.41 mm. The obtained results indicate a high potential of smart drill systems for improvement of accuracy and precision in orthopedic surgical procedures, enabling better patient clinical outcomes.

Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol’s operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space.

Monitoring of a rockfill embankment dam using TLS and sUAS point clouds

Abstract Terrestrial laser scanning (TLS) and camera-equipped small unmanned aircraft systems (sUAS) are two methods that are often used to produce dense point clouds for several monitoring applications. This paper compares the two methods in their ability to provide accurate monitoring information for rockfill embankment dams. We compare the two methods in terms of their uncertainty, data completeness, and field data acquisition/processing challenges. For both datasets, we derive an error budget that considers registration and measurement uncertainty. We also proceed to merge the TLS and sUAS data and leverage the advantages of each method. Furthermore, we conduct an analysis of the multiscale model-to-model cloud comparison (M3C2) input parameters, namely projection scale, normal scale, and sub-sampling of the reference point cloud, to show their effect on the M3C2 distance estimation. The theoretical methodologies and practical considerations of this paper can assist surveyors, who conduct monitoring of rockfill embankment dams using point clouds, in establishing reliable change/deformation estimations.

Revisiting the accretion disc spectra of dwarf novae and nova-like variables: implications for the standard disc model

ABSTRACT Accretion discs are fundamental to much of astronomy. They can occur around stars, both young and old, around compact objects they provide a window into the extremes of physics, and around supermassive black holes in galaxy centres, they generate spectacular luminosities that can outshine the entire galaxy. However, our understanding of the inner workings of accretion discs remains far from complete. Here, we revisit a conundrum in the observations of some of the simplest accreting systems: the cataclysmic variables (CVs). The high-accretion-rate states of (non-magnetic) CVs can be divided into the short-lived outbursts (∼a week), typical of dwarf novae (DNe), and the long-lived (and sometimes perpetual) high states of nova-like (NL) CVs. Since both sorts of high-state occur in approximately steady-state accretion discs with similar properties and accretors, we would expect them to display similar spectral energy distributions. However, previous analyses based on UV spectra from the International Ultraviolet Explorer have shown that their spectral energy distributions are different. We perform a re-analysis of the data using up to date calibrations and distance (and thus dereddening) estimates to test whether this difference persists and whether it is statistically significant over the sample. We find that it does persist, and it is statistically significant. We propose routes to investigating this discrepancy further and discuss the implications this has for other accreting systems, such as X-ray binaries, active galactic nuclei, and protoplanetary discs.

Estimating separable matching models

SummaryMost recent empirical applications of matching with transferable utility have imposed a natural restriction: that the joint surplus be separable in the sources of unobserved heterogeneity. We propose here two simple methods to estimate models in this class. The first method is a minimum distance estimator that relies on the generalized entropy of matching. The second applies to the more special but popular Choo and Siow model, which reformulates as a generalized linear model with two‐way fixed effects. Neither method requires solving for the stable matching. Both methods are easy to apply and perform very well.

Effect of early versus late onset of partial visual loss on judgments of auditory distance.

It is important to know whether early-onset vision loss and late-onset vision loss are associated with differences in the estimation of distances of sound sources within the environment. People with vision loss rely heavily on auditory cues for path planning, safe navigation, avoiding collisions, and activities of daily living. Loss of vision can lead to substantial changes in auditory abilities. It is unclear whether differences in sound distance estimation exist in people with early-onset partial vision loss, late-onset partial vision loss, and normal vision. We investigated distance estimates for a range of sound sources and auditory environments in groups of participants with early- or late-onset partial visual loss and sighted controls. Fifty-two participants heard static sounds with virtual distances ranging from 1.2 to 13.8 m within a simulated room. The room simulated either anechoic (no echoes) or reverberant environments. Stimuli were speech, music, or noise. Single sounds were presented, and participants reported the estimated distance of the sound source. Each participant took part in 480 trials. Analysis of variance showed significant main effects of visual status (p<0.05) environment (reverberant vs. anechoic, p<0.05) and also of the stimulus (p<0.05). Significant differences (p<0.05) were shown in the estimation of distances of sound sources between early-onset visually impaired participants and sighted controls for closer distances for all conditions except the anechoic speech condition and at middle distances for all conditions except the reverberant speech and music conditions. Late-onset visually impaired participants and sighted controls showed similar performance (p>0.05). The findings suggest that early-onset partial vision loss results in significant changes in judged auditory distance in different environments, especially for close and middle distances. Late-onset partial visual loss has less of an impact on the ability to estimate the distance of sound sources. The findings are consistent with a theoretical framework, the perceptual restructuring hypothesis, which was recently proposed to account for the effects of vision loss on audition.

A gravitational constant transition within cepheids as supernovae calibrators can solve the Hubble tension

Local universe measurements of the Hubble constant H 0 using SNe Ia with Cepheids as calibrators yield a value of H 0 = 73.04 ± 1.04 km s-1 Mpc-1, which is in tension with the value of H 0 inferred from the Cosmic Microwave Background and other higher redshift probes.In ref. [1], the authors proposed a rapid transition in the value of the effective Newtonian gravitational constant G in order to alleviate the Hubble tension. The transition point was chosen so as to only affect distance estimates to Hubble flow SNe. However, in this study, the authors made the assumption that SNe Ia peak luminosity L increases with Chandrasekhar mass Mc . This hypothesis contradicts a previous semi-analytic study of SN light curves in the presence of a G-transition [2] which concluded that there is an inverse relationship between L and Mc . Motivated by the results of ref. [1] and [2], we propose a hypothesis of a sudden recent change in the effective Newtonian gravitational constant G at an epoch which corresponds to a smaller look-back distance between ∼ 7–80 Mpc. A transition in G at these distances would affect both our estimates of the distances to Cepheids in calibrator galaxies, as well as to the Hubble flow supernovae. Upon fitting the observational data to this hypothesis, we find three interesting results: (i) we find mild evidence for a G-transition at 22.4 Mpc (73 million years ago) which is preferred (using certain estimators) by the calibrator type Ia SNe data over no G-transition, (ii) the Hubble constant inferred under this hypothesis is in good agreement with the value obtained from the CMB for a 4% larger value of G at earlier times, thus potentially resolving the Hubble tension, (iii) we obtain a fit to the scaling relationship between SN peak luminosity L and Chandrasekhar mass Mc , as L ∝ Mc -1.68 ± 0.68, which is in good agreement with the prediction of the theoretical study of ref. [2]. We also discuss how other probes could be used to verify this transition in the value of G.