Nearby Neighbors Research Articles

Conspecific interactions between corals mediate the effect of submarine groundwater discharge on coral physiology.

Land-based inputs, such as runoff, rivers, and submarine groundwater, can alter biologic processes on coral reefs. While the abiotic factors associated with land-based inputs have strong effects on corals, corals are also affected by biotic interactions, including other neighboring corals. The biologic responses of corals to changing environmental conditions and their neighbors are likely interactive; however, few studies address both biotic and abiotic interactions in concert. In a manipulative field experiment, we tested how the natural environmental gradient created by submarine groundwater discharge (SGD) affected holobiont and symbiont metabolic rates and endosymbiont physiology of Porites rus. We further tested how the effect of SGD on the coral was mediated by intra and interspecific interactions. SGD is a natural land-sea connection that delivers nutrients, inorganic carbon, and other solutes to coastal ecosystems worldwide. Our results show that a natural gradient of nutrient enrichment and pH variability as a result of acute SGD exposure generally benefited P. rus, increasing gross photosynthesis, respiration, endosymbiont densities, and chlorophyll a content. Conspecifics in direct contact with the a neighboring coral, however, altered the relationship between coral physiology and SGD, lowering the photosynthetic and respiration rates from expected values when the coral had no neighbor. We show that the response of corals to environmental change is dependent on the types of nearby neighbor corals and how neighbors alter the chemical or physical environment around the coral. Our study underscores the importance of considering biotic interactions when predicting the physiologic responses of corals to the environment.

TGPO-WRHNN: Two-stage Grad-CAM-guided PMRS Optimization and weighted-residual hypergraph neural network for pneumonia detection

Recent studies based on chest X-ray images have shown that pneumonia can be effectively detected using deep convolutional neural network methods. However, these methods tend to introduce additional noise and extract only local feature information, making it difficult to express the relationship between data objects. This study proposes a Two-stage Grad-CAM-guided pre-trained model and removal scheme (PMRS) Optimization and weighted-residual hypergraph neural network model (TGPO-WRHNN). First, our model extracts high-dimensional features using the TGPO module to capture both global and local information from an image. Second, we propose a new distance-based hypergraph construction method (DBHC) to amplify the difference between distances and better distinguish the relation between nearby and distant neighbors. Finally, we introduce a weighted-residual hypergraph convolution module (WRHC) to ensure the model maintains excellent performance, even at deeper levels. Our model was tested on a dataset of chest X-ray images of pediatric patients aged 1 to 5 years at the Guangzhou Women and Children’s Medical Centre by 10-fold cross-validation. The results showed that the method achieved a maximum accuracy of 98.97%, precision of 98.86%, recall of 98.43%, F1 score of 98.64%, and AUC of 99.78%. Compared to other existing models, our model demonstrated improvements of 0.87%, 0.86%, 0.16%, and 0.38% in terms of accuracy, precision, F1 score, and AUC, respectively.

Systematically Measuring Ultradiffuse Galaxies. VII. The H i Survey Overview

We present the results from the neutral hydrogen (H i) follow-up survey of 378 optically detected ultradiffuse galaxy (UDG) candidates from the Systematically Measuring Ultra-Diffuse Galaxies survey using the Robert C. Byrd Green Bank Telescope. We detect H i in 110 targets and determine 37 to be UDGs and 73 to be low-surface-brightness (LSB) dwarfs based on their effective radii and central surface brightnesses. In line with previous studies, we find that: (i) our H i detections have on average bluer g − r colors and more irregular morphologies than our H i nondetections, (ii) our H i detections populate the tail end of the star-forming main sequence from the ALFALFA catalog with marginally lower specific star formation rates, and (iii) H i detections are mostly in relatively isolated (i.e., field) environments, while most nondetections have at least one nearby neighbor in projection. We find that the H i mass to stellar mass ratios (i.e., gas richnesses) scale with the physical sizes for UDGs and LSB dwarfs alike, suggesting that mechanisms other than bursty star formation feedback may be at play for UDGs. However, we find a stronger trend between gas richnesses and physical sizes if we define UDGs using their effective surface brightness instead of their central surface brightness. We are in the process of using this unprecedented sample of UDG candidates to carry out detailed follow-up studies (i.e., star formation and environmental analysis, comparisons to simulations) and are obtaining resolved H i observations for several of them.

KAN-HyperMP: An Enhanced Fault Diagnosis Model for Rolling Bearings in Noisy Environments

Rolling bearings often produce non-stationary signals that are easily obscured by noise, particularly in high-noise environments, making fault detection a challenging task. To address this challenge, a novel fault diagnosis approach based on the Kolmogorov–Arnold Network-based Hypergraph Message Passing (KAN-HyperMP) model is proposed. The KAN-HyperMP model is composed of three key components: a neighbor feature aggregation block, a feature fusion block, and a KANLinear block. Firstly, the neighbor feature aggregation block leverages hypergraph theory to integrate information from more distant neighbors, aiding in the reduction of noise impact, even when nearby neighbors are severely affected. Subsequently, the feature fusion block combines the features of these higher-order neighbors with the target node’s own features, enabling the model to capture the complete structure of the hypergraph. Finally, the smoothness properties of B-spline functions within the Kolmogorov–Arnold Network (KAN) are employed to extract critical diagnostic features from noisy signals. The proposed model is trained and evaluated on the Southeast University (SEU) and Jiangnan University (JNU) Datasets, achieving accuracy rates of 99.70% and 99.10%, respectively, demonstrating its effectiveness in fault diagnosis under both noise-free and noisy conditions.

Rectifying self-training with neighborhood consistency and proximity for source-free domain adaptation

Source-free domain adaptation (SFDA) seeks to transfer knowledge from the source domain to the target domain by leveraging only unlabeled target data and pre-trained source model, without accessing source data. Existing approaches for SFDA heavily depend on self-training, involving the generation of pseudo-labels on the target domain. However, these generated labels inevitably suffer from incorrect predictions due to distribution discrepancy, making the training process vulnerable to pseudo-label noise. To track this issue, in this paper, we propose neighborhood semantic consistency and neighborhood spatial proximity to distinguish sample importance and incorporate them to rectify self-training. Specifically, we refer to the sample relationship with nearby neighbors to evaluate the pseudo-label reliability of target samples, explicitly serving as regularization for the optimizing objective. The neighborhood consistency is calculated based on the similarity of sample-wise and data-structure predictions, describing local semantic uniformity, while the neighborhood proximity is calculated by considering the feature distances to nearby samples, which measures local spatial affinity. Furthermore, a regularized neighborhood alignment term is introduced, which adaptively integrates self-distillation with neighborhood supervision to boost representation learning. Comprehensive experiments across several different SFDA benchmarks demonstrate the efficacy of our approach. Further analyses substantiate that the proposed approach exhibits superior robustness against pseudo-label noise, which leads to notable enhancements when compared with conventional pseudo-label-based self-training. The codes of our method are available at https://github.com/xingbw/Rectified-Self-Training.

Pickleball sounds: impact induced vibration and radiated sound

The rapid growth in popularity of pickleball and the ever-increasing number of pickleball courts has resulted in growing concerns about the effect of pickleball sounds on nearby neighbors. The vibration of the ball and paddle that is generated at impact, and which is the source of the radiated sound, was measured for different paddles as a function of frequency using an impact hammer instrumented with a force gage. Average vibration velocities over the paddle surface were generated that scale the radiated sound. Animations of paddle vibration were also generated. A paddles vibration level depends on its internal mechanical damping which was also measured. A performance metric is proposed where the paddles' sound levels are compared at the same "power" in terms of the change in momentum (velocity) of the pickleball on impact. Outdoor directivity measurements of the sound for a paddle were "dipole-like" in character with lower levels, by 10 dB or more, in the plane of the paddle compared to levels perpendicular to its face. The orientation of the courts may be important if the sound levels during play are quieter in the general direction along the nets.

Low-mass Galaxy Interactions Trigger Black Hole Activity

The existence of high-z overmassive supermassive black holes represents a major conundrum in our understanding of black hole evolution. In this Letter, we probe from the observational point of view how early Universe environmental conditions could have acted as an evolutionary mechanism for the accelerated growth of the first black holes. Under the assumption that the early Universe is dominated by dwarf galaxies, we investigate the hypothesis that dwarf–dwarf galaxy interactions trigger black hole accretion. We present the discovery of 82 dwarf–dwarf galaxy pairs and 11 dwarf galaxy groups using the Hubble Space Telescope, doubling existing samples. The dwarf systems span a redshift range of 0.13 < z < 1.5, and a stellar mass range of 7.24 < log(M */M ⊙) < 9.73. We performed an X-ray study of a subset of these dwarf systems with Chandra and detected six new active galactic nuclei (AGN), increasing the number of known dwarf–dwarf-merger-related AGN from one to seven. We then compared the frequency of these AGN in grouped/paired dwarfs to that of isolated dwarfs and found a statistically significant enhancement (4σ–6σ) in the interacting sample. This study, the first of its kind at the lowest mass scales, implies that the presence of a nearby dwarf neighbor is efficient in triggering black hole accretion. These results open new avenues for indirect studies of the emergence of the first supermassive black holes.

Locality, Personal Ties, and Efficiency in a Food Security Network

Food sharing and distribution organization systems provide critical resources for local communities and food-insecure households. In this article, we investigate a newly collected data set of the Thrive Network in southwestern Virginia, which links forty food security organizations through fifty-one connections, using a theoretical framework of organization science within geographic space. We first test whether more central and higher degree organizations are toward the geographic center of the network, near convenient points of interest. We then measure whether organizations are likely to form connections based on nearness and logistical effectiveness of moving goods, and where this occurs. Finally, we find “missed connections,” defined as sets of organizations that are nearby but highly disconnected in the network. We find that important nodes are not necessarily in the center of the network, but are located on the periphery, and that relatively few organizations are connected to their nearby neighbors. We find that important nodes are not necessarily in the center of the network, but are located on the periphery, and that relatively few organizations are connected to their nearby neighbors. As such, this system could be predicated on bottom-up personal relationships rather than a hub-and-spoke supply chain configuration, and new ties might make the system more effective. We use our findings to help the Thrive Network build a more resilient food-sharing system and better serve vulnerable clients.

Childhood neighbourhoods and life‐time fertility in twentieth‐century Southern Sweden: A k‐nearest neighbour approach

AbstractDespite a large literature on the importance of childhood neighbourhoods for life course transitions, there is a lack of fertility studies combining a life‐course perspective with detailed neighbourhood measures. Addressing this gap, we use longitudinal data in which the entire population of a Swedish town is geocoded at the address‐level, 1939–1967, and linked to national registers from 1968 to 2015. We study how social neighbourhoods in childhood influence fertility outcomes by constructing individual neighbourhoods at the address level to measure the social class of nearby childhood neighbours. We analyse the age at first and last birth, children ever born, birth spacing and childlessness. Growing up in higher‐status neighbourhoods is associated with delayed fertility for both men and women, but no association is found for the number of children ever born or for childlessness. Associations are stable over time, and later ages of neighbourhood exposure matter more, especially for men. Contrary to prior literature's focus on the lower classes, our results are driven by higher‐status individuals growing up in distinctly white‐collar neighbourhoods.

Progress in direct measurements of the Hubble constant

One of the most exciting and pressing issues in cosmology today is the discrepancy between some measurements of the local Hubble constant and other values of the expansion rate inferred from the observed temperature and polarization fluctuations in the cosmic microwave background (CMB) radiation. Resolving these differences holds the potential for the discovery of new physics beyond the standard model of cosmology: Lambda Cold Dark Matter (ΛCDM), a successful model that has been in place for more than 20 years. Given both the fundamental significance of this outstanding discrepancy, and the many-decades-long effort to increase the accuracy of the extragalactic distance scale, it is critical to demonstrate that the local measurements are convincingly free from residual systematic errors. We review the progress over the past quarter century in measurements of the local value of the Hubble constant, and discuss remaining challenges. Particularly exciting are new data from the James Webb Space Telescope (JWST), for which we present an overview of our program and first results. We focus in particular on Cepheids and the Tip of the Red Giant Branch (TRGB) stars, as well as a relatively new method, the JAGB (J-Region Asymptotic Giant Branch) method, all methods that currently exhibit the demonstrably smallest statistical and systematic uncertainties. JWST is delivering high-resolution near-infrared imaging data to both test for and to address directly several of the systematic uncertainties that have historically limited the accuracy of extragalactic distance scale measurements (e.g., the dimming effects of interstellar dust, chemical composition differences in the atmospheres of stars, and the crowding and blending of Cepheids contaminated by nearby previously unresolved stars). For the first galaxy in our program, NGC 7250, the high-resolution JWST images demonstrate that many of the Cepheids observed with the Hubble Space Telescope (HST) are significantly crowded by nearby neighbors. Avoiding the more significantly crowded variables, the scatter in the JWST near-infrared (NIR) Cepheid PL relation is decreased by a factor of two compared to those from HST, illustrating the power of JWST for improvements to local measurements of H 0. Ultimately, these data will either confirm the standard model, or provide robust evidence for the inclusion of additional new physics.

Machine Learned Texture Prior From Full-Dose CT Database via Multi-Modality Feature Selection for Bayesian Reconstruction of Low-Dose CT.

In our earlier study, we proposed a regional Markov random field type tissue-specific texture prior from previous full-dose computed tomography (FdCT) scan for current low-dose CT (LdCT) imaging, which showed clinical benefits through task-based evaluation. Nevertheless, two assumptions were made for early study. One assumption is that the center pixel has a linear relationship with its nearby neighbors and the other is previous FdCT scans of the same subject are available. To eliminate the two assumptions, we proposed a database assisted end-to-end LdCT reconstruction framework which includes a deep learning texture prior model and a multi-modality feature based candidate selection model. A convolutional neural network-based texture prior is proposed to eliminate the linear relationship assumption. And for scenarios in which the concerned subject has no previous FdCT scans, we propose to select one proper prior candidate from the FdCT database using multi-modality features. Features from three modalities are used including the subjects' physiological factors, the CT scan protocol, and a novel feature named Lung Mark which is deliberately proposed to reflect the z-axial property of human anatomy. Moreover, a majority vote strategy is designed to overcome the noise effect from LdCT scans. Experimental results showed the effectiveness of Lung Mark. The selection model has accuracy of 84% testing on 1,470 images from 49 subjects. The learned texture prior from FdCT database provided reconstruction comparable to the subjects having corresponding FdCT. This study demonstrated the feasibility of bringing clinically relevant textures from available FdCT database to perform Bayesian reconstruction of any current LdCT scan.

Calculation of the local environment of a barium monofluoride molecule in a neon matrix

ABSTRACT The local environment of a barium monofluoride (BaF) molecule embedded in a neon matrix is studied theoretically. The energy of the BaF-Ne triatomic system is calculated with a scalar relativistic Hamiltonian, using coupled-cluster theory at the CCSD(T) level for 1625 positions of the Ne atom relative to the BaF molecule. The calculations are repeated with increasing basis sets (from double to quintuple zeta), and are extrapolated to estimate the complete-basis-set limit. Using the potential obtained from these calculations, it is determined that substituting a BaF molecule for ten Ne atoms is favoured compared to substitutions for other numbers of Ne atoms. The equilibrium position and orientation of the BaF molecule and the displacement of its nearby Ne neighbours are determined. The potential barriers that prevent the BaF molecule from migrating and rotating are calculated. These barriers are essential for the EDM 3 collaboration, which is using BaF molecules embedded in a noble-gas solid to perform a precision measurement of the electron electric dipole moment.

Photometric variability of the LAMOST sample of magnetic chemically peculiar stars as seen by TESS

Context.High-quality light curves from space-based missions have opened up a new window on the rotational and pulsational properties of magnetic chemically peculiar (mCP) stars and have fuelled asteroseismic studies. They allow the internal effects of surface magnetic fields to be probed and numerous astrophysical parameters to be derived with great precision.Aims.We present an investigation of the photometric variability of a sample of 1002 mCP stars discovered in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) archival spectra with the aims of measuring their rotational periods and identifying interesting objects for follow-up studies.Methods.Transiting Exoplanet Survey Satellite (TESS) data were available for 782 mCP stars and were analysed using a Fourier two-term frequency fit to determine the stars’ rotational periods. The rotational signal was then subtracted from the light curve to identify additional non-rotational variability signals. A careful pixel-level blending analysis was performed to check whether the variability originates in the target star or a nearby blended neighbour. We investigated correlations between the observed rotational periods, fractional age on the main sequence, mass, and several other observables.Results.We present rotational periods and period estimates for 720 mCP stars. In addition, we have identified four eclipsing binary systems that likely host an mCP star, as well as 25 stars with additional signals consistent with pulsation (12 stars with frequencies above 10 day−1and 13 stars with frequencies below 10 day−1). We find that more evolved stars have longer rotation periods, which is in agreement with the assumption of the conservation of angular momentum during the main-sequence evolution.Conclusions.With our work, we increase the sample size of mCP stars with known rotation periods and identify prime candidates for detailed follow-up studies. This enables two paths towards future investigations: population studies of even larger samples of mCP stars and the detailed characterisation of high-value targets.

Safest Nearby Neighbor Queries in Road Networks

Safety on the roads has become a major concern in recent days. Travellers prefer to avoid road inconveniences that may occur from crime incidents, street harassment, protests or riots during unrest in a country. To facilitate safe travel, we introduce a novel query for road networks called the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> safest nearby neighbor (SNN) query. Given a query location <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$v_l$</tex-math> </inline-formula> , a distance constraint <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d_c$</tex-math> </inline-formula> and a point of interest <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p_i$</tex-math> </inline-formula> , we define the safest path from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$v_l$</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p_i$</tex-math> </inline-formula> as the path with the highest path safety score among all the paths from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$v_l$</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p_i$</tex-math> </inline-formula> with length less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d_c$</tex-math> </inline-formula> . The path safety score is computed considering the road safety of each road segment on the path. Given a query location <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$v_l$</tex-math> </inline-formula> , a distance constraint <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d_c$</tex-math> </inline-formula> and a set of POIs <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P$</tex-math> </inline-formula> , a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> SNN query returns <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> POIs with the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> highest path safety scores in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P$</tex-math> </inline-formula> along with their respective safest paths from the query location. We develop two novel indexing structures called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Ct$</tex-math> </inline-formula> -tree and a safety score based Voronoi diagram (SNVD). We propose two efficient query processing algorithms each exploiting one of the proposed indexes to effectively refine the search space using the properties of the index. Our extensive experimental study on real datasets demonstrates that our solution is on average an order of magnitude faster than the baseline.

ROS-Based Collaborative Driving Framework in Autonomous Vehicular Networks

This paper investigates the optimal data transmission for collaborative driving in autonomous vehicular networks (AVNs). We consider that vehicles communicate with each other based on the definition of Robot Operating System (ROS), which is a pervasively adopted middleware operating system for autonomous vehicles such as Baidu Apollo. ROS defines a publish/subscribe scheme for inter-vehicular communications, in which vehicles subscribe to “topics” published by adjacent vehicles; a “topic” is related to the real-time sensing/computing data that a vehicle intends to share with nearby neighbors, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , radar or camera images captured. By sharing various sensing data using different topics at the real-time, vehicles in the same area therefore can collaboratively drive with cooperative perception and computing. However, multiple data flows for different topics would coexist along overlapping transmission paths during this process. As a result, a fundamental issue raised is how to schedule the contending data flows in the mobile and bandwidth-constrained vehicular networks. In this paper, we model the ROS-based publish/subscribe scheme as an optimization problem which jointly considers the power allocation and conflict avoidance of the communication process in AVNs. By applying the Lyapunov Optimization, we decompose the model to calculate the power and sub-carrier proportion on each node while avoiding link conflicts, and finally obtain the optimal resource allocation strategy. By combining the corresponding link conflict constraints, we are able to encapsulate the optimization model in a stable set to efficiently avoid link conflicts, and thereby reduce the resource waste caused by the link interference and data flow conflicts. Using simulations, we show that our method has good advantages in resource optimization.

Water-assisted electron capture exceeds photorecombination in biological conditions.

A decade ago, an electron-attachment process called interatomic Coulombic electron capture has been predicted to be possible through energy transfer to a nearby neighbor. It has been estimated to be competitive with environment-independent photorecombination, but its general relevance has yet to be established. Here, we evaluate the capability of alkali and alkaline earth metal cations to capture a free electron by assistance from a nearby water molecule. We introduce a characteristic distance rIC for this energy transfer mechanism in equivalence to the Förster radius. Our results show that water-assisted electron capture dominates over photorecombination beyond the second hydration shell of each cation for electron energies above a threshold. The assisted capture reaches distances equivalent to a fifth to seventh solvation shell for the studied cations. The far reach of the assisted electron capture is of significant general interest to the broad spectrum of research fields dealing with low-energy electrons, in particular radiation-induced damage of biomolecules. The here introduced distance measure will enable quantification of the role of the environment for assisted electron attachment.

Calculation of the local environment of a barium monofluoride molecule in an argon matrix: a step towards using matrix-isolated BaF for determining the electron electric dipole moment

The local environment of a barium monofluoride (BaF) molecule embedded in an argon matrix is calculated. A substitution of a BaF molecule for four Ar atoms is found to be strongly favoured compared to substitutions for other numbers of Ar atoms. The equilibrium positions of the BaF molecule and its nearby Ar neighbours are found by minimising the total energy. The potential barrier that prevents the migration of the BaF molecule within the solid and the barrier that prevents its rotation are calculated. At the cryogenic temperatures used by the EDM collaboration, these barriers are sufficiently large to fix the position and orientation of the molecule. Knowledge of the local environment of matrix-isolated BaF molecules is essential for the EDM collaboration, which is using them in a precision measurement of the electron electric dipole moment.

Jumping Sharks

Jumping Sharks

A novel privacy protection scheme for location-based services using collaborative caching

Protecting privacy in Location-based services (LBSs) has been one of the major concerns over the last few years. Users’ queries can reveal sensitive information to LBSs, thus giving an opportunity for the adversaries to track the querying user. Existing location privacy protection mechanisms either use a trusted third party (TTP) or a location obfuscation-based scheme. TTP-based schemes require users to report their location-related information to the TTP before sending a query to the location-based service provider (LSP). Once the TTP is compromised, users’ privacy can be breached. On the other hand, location obfuscation schemes achieve privacy at the cost of accuracy. We address these problems by proposing a collaborative caching-based privacy-preserving scheme for LBSs. The scheme prevents the users’ location information leakage from untrusted communication channels as well as LSP while maintaining the quality of service. The scheme uses a novel dummy location generation technique and a virtual identity mechanism to improve users’ location and identity privacy. Furthermore, one-time spatial groups are created with the nearby neighbors to access the localized services, thus providing less interaction with the untrusted LSP. The proposed work has the potential to preserve users’ location privacy and reduce the computation and communication costs of the system. The aforementioned claims are verified by the experimental results.

The use of recycling bags: An overview of collection policies and a spatial assessment of bag use

An increasing number of recycling programs worldwide now use single-use high-density polyethylene (HDPE) plastic bags in conjunction with recycling bins for the storage and collection of recyclable waste. Recycling bags may increase recycling yield and lower street litter; however, they also come with potentially large environmental and economic costs, including the increased use of plastics. To assess the scale of recycling bag use, we conducted a review of municipal management policies and by-laws across Ontario, the birthplace of modern blue box programs. Over 40% of the municipalities we investigated, collectively representing more than 7 million residents, allow the collection of recycling in bags. Subsequently, we conducted a follow-up study to estimate the number of recycling bags actually used by residents, an important metric for environmental managers, in a medium-sized Ontario city that collects recyclables in both bags and bins. Across three collection dates, 9.0 ± 1.3% of households used recycling bags, with a mean of 1.65 bags per house (mean households sampled = 1540). We estimate that approximately 160 households could use over 10,000 recycling bags per year (∼380 kg of plastic). Spatial analysis on the distribution of recycling bags showed some evidence of clustering among nearby neighbours (i.e. social influence); however, these results were inconsistent and highly variable across sampling dates. Our study provides a valuable policy overview and critical baseline data for waste managers weighing the benefits (e.g., litter reduction) and drawbacks (e.g., debagging costs and plastic waste) of recycling bags for the collection of recyclable material.