Similar Objects Research Articles

Discovery of Jupiter Family Comet 2011 UG104 Through AI Enhanced Citizen Science

We report the discovery of cometary activity from minor planet 2011 UG104, which we classify as a Jupiter Family Comet (JFC). This discovery was aided by our Artificial Intelligence (AI) classification system: TailNet. JFC's, short-period comets with eccentric Jupiter-crossing orbits, originate from the Kuiper Belt and thus give us unique insight into the composition and distribution of volatiles in the outer solar system, past and present. Our AI assistant TailNet first classified 2011 UG104 as active, which was affirmed by Citizen Scientists on our NASA Partner Program Active Asteroids. Through further archival image searches our science team found evidence of activity on 2011 UG104 on three separate observations from 2021 February to 2021 April (81.°8 < f < 95.°0).

A multistart and recombination algorithm for finding many unique solutions to spatial aggregation problems

AbstractSpatial aggregation is essential for applications where data at low level spatial units such as census blocks are grouped into larger regions. This type of problem can be formulated as spatial optimization problems where the goal is to minimize the difference between the grouped regions. These problems are difficult to solve because of their computational intensity. In addition, these problems often have multiple, instead of singular, optimal solutions that have the same or similar objective function values but exhibit different spatial configurations. Existing solution methods often aim to find single solutions to these problems. In this paper, we discuss a new heuristic method that can be used to find a set of unique optimal or near-optimal solutions to spatial aggregation problems. The algorithm consists of two phases. A multistart phase first generates a pool of random solutions to a problem. The size of the pool is specified by the user and contains the number of solutions desired to be found. Each random solution is then improved using an efficient algorithm called give-and-take. The second phase uses a recombination algorithm to create new solutions based on solutions randomly selected from the pool. The worst solution in the pool will be replaced by the new solution if the latter is better and does not exist in the pool. We test this multistart and recombination algorithm (MSRA) using a variety of problems with different sizes and the results suggest the effectiveness of the algorithm in finding multiple unique optimal or near-optimal solutions.

Theoretical Aspects of Determining the Place of Energy (Energy Resources) in the System of Civil Rights Objects

The paper is devoted to determining the role of energy in the system of civil rights objects. The author highlights two main theories. Representatives of the first theory recognize energy as a thing and, accordingly consider it possible to apply the property law regime in relation to it. Currently, the number of supporters of this theory has increased due to the fact that the legislator consolidated regulatory norms regarding the energy supply contract in the chapter of the Civil Code of the Russian Federation devoted to purchase-and-sale transactions. The doctrine also attempts to justify the extension of the property right to energy through the category of «disembodied things». The second theory denies the attribution of energy to things. Representatives of this theory try to substantiate the legal nature of energy based on the existing systematization of objects of civil rights. According to the author, energy is an independent object of civil rights, a special object of a physical nature, having no sign of materiality, capable of generation and, under certain conditions, transfer in economic relations of civil turnover participants, and considered as a commodity with property value and high socioeconomic importance. Thus, energy perfectly fits into the category reserved by the law-maker for similar new objects and classified as «other property». Denying the substantive qualification of energy, the author supports the position of researchers who consider energy exclusively as an object of binding rights, since, given its physical nature and the possibility of generation and transmission exclusively through technical infrastructure, energy as an independent object of civil rights can act exclusively as a subject of binding legal relations

The Contrastive and Referential Function of Specific Classifiers in Xiamen Southern Min—Evidence from a Cognitive Experimental Study

Southern Min is generally known for not using classifiers [CL] for expressing definiteness/indefiniteness as it is associated with the bare classifier construction [CL N]. This paper offers evidence from Xiamen Southern Min (XSM) that the use of a specific classifier vs. the general classifier é contributes to referentiality in an alternative way by supporting object identification as it is due to the semantic specificity present in specific classifiers and absent in the general classifier. In a dialogic cognitive experiment adapted from the “Hidden color-chips” task (Enfield and Bohnemeyer 2001), 18 participants had to manipulate their addressees’ attention toward various objects situated in their immediate physical space through language as well as deictic gestures. The objects were associated with different specific classifiers or with the general classifier, and they were arranged according to the factors of (a) distance from speaker, (b) visibility for speaker, and (c) uniqueness (adjacency of similar items). The results show, among other things, that there is a higher tendency to use the specific CL in the [demonstrative CL N] construction if adjacent similar objects [−unique] are too far away from the speaker for clear identification by a demonstrative or a pointing gesture. This is seen as a last-resort strategy for creating contrast. Further corroboration comes from the use of specific classifiers in later mentions after the general CL failed to achieve clear identification. These findings can be situated in the broader context of other languages with classifiers in contrastive function (Thai, Vietnamese, and Ponapean) and they show the relevance of using dialogic texts for modeling classifier selection in contrast to narrative texts. Finally, dialogic contexts may serve as bridging contexts for grammaticalization from numeral classifiers to definiteness markers.

Transport of dust across the Solar System: Constraints on the spatial origin of individual micrometeorites from cosmic-ray exposure.

The origin of micrometeorites (MMs) from asteroids and comets is well-established, but the relative contribution from these two classes remains poorly resolved. Likewise, determining the precise origin of individual MMs is an open challenge. Here, cosmic-ray exposure ages are used to resolve the spatial origins of 12 MMs collected from urban areas and Antarctica. Their 26Al and 10Be concentration, produced during cosmic-ray irradiation in space, were measured by accelerator mass spectrometry. These data are compared to results from a model simulating the transport and irradiation of the MM precursors in space. This model, for the first time, considers a variety of orbits, precursor particle sizes, compositions and densities and incorporates non-isotropic solar and galactic cosmic-ray flux profiles, depth-dependent production rates, as well as spherical evaporation during atmospheric entry. While the origin for six MMs remains ambiguous, two MMs show a preferential tendency towards an origin in the Inner Solar System (Near Earth Objects to the Asteroid Belt) and four towards an origin in the Outer Solar System (Jupiter Family Comets to the Kuiper Belt). These findings challenge the notion that dust originating from the Outer Solar System is unlikely to survive long-term transport and delivery to the terrestrial planets. This article is part of the theme issue 'Dust in the Solar System and beyond'.

Exploration of an Open Vocabulary Model on Semantic Segmentation for Street Scene Imagery

This study investigates the efficacy of an open vocabulary, multi-modal, foundation model for the semantic segmentation of images from complex urban street scenes. Unlike traditional models reliant on predefined category sets, Grounded SAM uses arbitrary textual inputs for category definition, offering enhanced flexibility and adaptability. The model’s performance was evaluated across single and multiple category tasks using the benchmark datasets Cityscapes, BDD100K, GTA5, and KITTI. The study focused on the impact of textual input refinement and the challenges of classifying visually similar categories. Results indicate strong performance in single-category segmentation but highlighted difficulties in multi-category scenarios, particularly with categories bearing close textual or visual resemblances. Adjustments in textual prompts significantly improved detection accuracy, though challenges persisted in distinguishing between visually similar objects such as buses and trains. Comparative analysis with state-of-the-art models revealed Grounded SAM’s competitive performance, particularly notable given its direct inference capability without extensive dataset-specific training. This feature is advantageous for resource-limited applications. The study concludes that while open vocabulary models such as Grounded SAM mark a significant advancement in semantic segmentation, further improvements in integrating image and text processing are essential for better performance in complex scenarios.

Accelerating material property prediction using generically complete isometry invariants

Periodic material or crystal property prediction using machine learning has grown popular in recent years as it provides a computationally efficient replacement for classical simulation methods. A crucial first step for any of these algorithms is the representation used for a periodic crystal. While similar objects like molecules and proteins have a finite number of atoms and their representation can be built based upon a finite point cloud interpretation, periodic crystals are unbounded in size, making their representation more challenging. In the present work, we adapt the Pointwise Distance Distribution (PDD), a continuous and generically complete isometry invariant for periodic point sets, as a representation for our learning algorithm. The PDD distinguished all (more than 660 thousand) periodic crystals in the Cambridge Structural Database as purely periodic sets of points without atomic types. We develop a transformer model with a modified self-attention mechanism that combines PDD with compositional information via a spatial encoding method. This model is tested on the crystals of the Materials Project and Jarvis-DFT databases and shown to produce accuracy on par with state-of-the-art methods while being several times faster in both training and prediction time.

Abstract PO3-20-02: Olaparib front line therapy with endocrine therapy in locally advanced unresectable or in metastatic breast cancer: OFELIA TRIAL

Abstract INTRODUCTION: Currently, patients with recurrent or metastatic hormone-sensitive breast cancer are treated with endocrine therapy (ET) in combination with cyclin inhibitors, as it has been shown to improve both overall survival and progression-free survival. However, it has been observed that patients with gBRCA1 or gBRCA2 mutations, who receive treatment with endocrine therapy and CDK4/6 inhibitors, have lower OS and lower PFS compared to those without mutations. These findings could be due to the presence of higher cyclin E mRNA levels, which encode the protein that stimulates CDK2 activity provoking a resistance to CDK4/6 inhibitors. Having this said, the use of PARP inhibitors a potential first-line therapeutic option in combination with endocrine therapy could be an option to be re evaluated. JUSTIFICATION: PARP inhibitors (iPARP) are recommended in international guidelines as second-line palliative treatment and also as adjuvant management in the case of Olaparib. The use of iPARP is approved only as a second-line treatment in HER2 hormone-sensitive breast cancer, according to the results of the EMBRACA and OlympiAD clinical trials. However, these two clinical trials were not designed to evaluate its effectiveness as first-line palliative treatment. Given that patients with gBRCA mutations have lower overall survival when administered cyclin inhibitors (iCDK 4/6) + Endocrine therapy (ET) compared to those without mutations, it is necessary to reevaluate the use of iPARP as first-line palliative treatment in conjunction with ET, with the expectation of achieving a similar objective response rate and progression-free survival. OBJECTIVE: To Determine the ORR in patients with recurrent or metastatic hormone-sensitive HER2-negative breast cancer managed with PARP inhibitors + Endocrine therapy. HYPOTHESIS: The use of PARP inhibitors in combination with endocrine therapy will have an objective response rate of 60% or higher in both early stages and advanced disease. METHODOLOGY: Phase 2 open-label, multicenter clinical trial. Study Population: Cohort : All pre- or postmenopausal patients with a diagnosis of recurrent or metastatic hormone-sensitive HER2-negative breast cancer with gBRCA1 and/or gBRCA2 mutation. Sample: The inclusion of patients will be based on meeting the inclusion criteria. We plan to achieve an ORR of at least 60% with an acceptable minimum of 40%. Assuming a one-sided alpha level of 0.05 and statistical power of 80%, a two-stage Simon design was used to calculate the required sample size. In the first stage, a minimum of 23 patients is assumed, of which 14 patients need to achieve the desired response rate to proceed to the second stage. In the second stage, an additional 28 patients will be added to obtain a total sample size of 51 patients. The objective response rate will be evaluated using RECIST v1.1 criteria at 8 weeks after initiating treatment, with continued assessment during the first year, followed by assessments every 12 weeks during the second and third year, and then every 24 weeks until progression or toxicity. EXPECTED RESULTS: PARP inhibitors + Endocrine therapy will have a similar ORR as reported with cyclin inhibitors + Endocrine therapy, as well as a benefit in progression-free survival. Citation Format: Carlos Arturo González Núñez, Paula Cabrera-Galeana, Juan Enrique Bargalló Rocha, Rafael Vazquez-Romo, Sergio Aguilar-Villanueva, Alexandra Garcilazo, Areli Velazquez-Martinez, Andrea Maliachi, Ruben Rodriguez. Olaparib front line therapy with endocrine therapy in locally advanced unresectable or in metastatic breast cancer: OFELIA TRIAL [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-20-02.

Comparing the dynamics of Jupiter-family Comets and comet-like fireballs

Jupiter-family comets (JFCs), which originate from the Kuiper belt and scattered disk, exhibit low-inclination and chaotic trajectories due to close encounters with Jupiter. Despite their typically short incursions into the inner solar system, a notable number of them are on Earth-crossing orbits, with fireball networks detecting many objects on ``JFC-like'' ($2&lt;T_ J &lt;3$) orbits. This investigation aims to examine the orbital dynamics of JFCs and comet-like fireballs over $10^ $\,yr timescales, focusing on the trajectories and stability of these objects in the context of gravitational interactions within the solar system. We employed an extensive fireball dataset from Desert Fireball Network (DFN), European Fireball Network (EFN), Fireball Recovery and InterPlanetary Observation Network (FRIPON), and Meteorite Observation and Recovery Project (MORP), alongside telescopically observed cometary ephemeris from the NASA HORIZONS database. The study integrates 646 fireball orbits with 661 JFC orbits for a comparative analysis of their orbital stability and evolution. The analysis confirms frequent Jupiter encounters among most JFCs, inducing chaotic orbital behavior with limited predictability and short Lyapunov lifetimes (sim 120 years), underscoring Jupiter's significant dynamical influence. In contrast, "JFC-like" meteoroids detected by fireball networks largely exhibit dynamics divergent from genuine JFCs, with 79-92&lt;!PCT!&gt; on ``JFC-like'' orbits shown not to be prone to frequent Jupiter encounters; in particular, only 1-5&lt;!PCT!&gt; of all fireballs detected by the four networks exhibit dynamics similar to that of actual JFCs. In addition, 22&lt;!PCT!&gt; (16 of 72) of near-Earth JFCs are on highly stable orbits, suggesting a potential main belt origin for some of the bodies. This extensive study delineates the stark dynamical contrast between JFCs and JFC-like meteoroids detected by global fireball networks. The majority of centimeter- and meter-scale meteoroids on JFC-like orbits exhibit remarkably stable trajectories, which starkly differ from the chaotic paths of their km-scale counterparts. Our findings suggest that the JFC-like objects observed by fireball networks predominantly originate from the outer main belt, with only a minor fraction being directly attributable to traditional JFCs.

Automatic movement pattern analysis for data-driven system optimisation – an example for fattening livestock farming monitoring system

AbstractThis paper introduces a method for analysing motion patterns that can be utilised to optimise data-driven systems. The aim is to use surveillance cameras and artificial intelligence to track multiple objects in a reliable manner, thereby preserving the authenticity of movement patterns for numerous and similar objects. In a case study, this method is applied to optimize lighting conditions in animal husbandry. Furthermore, this approach can be utilized not only in animal husbandry but also in other domains.

CRTrack: Learning Correlation-Refine network for visual object tracking

Conducting reliable feature interaction plays a critical role in the visual tracking community, especially in recent dominated Siamese-based tracking paradigm. In general, there are two primary approaches for fusing representations from template and search area in the Siamese setting, i.e., cross-correlation and transformer modeling. The former provides a straightforward interaction solution, which may have limitations in handling complex scenarios, such as appearance variations and occlusion. While the latter offers an effective interaction mechanism, albeit with higher computation complexity and model cost. In contrast to traditional Siamese-based trackers which rely on two mentioned feature cross-correlation operators, this paper proposes a novel Correlation-Refine network to address the issue of lacking semantic information caused by local linear matching in correlation, from both spatial and channel perspectives. Correlation-Refine network (named CR) is solely built on top of fully convolutional layers, without employing intricate transformer mechanisms or complex methods to fuse features from multiple scales. Moreover, we present a concise yet effective convolutional tracking framework based on the correlation-refine network. CR network can increase the discriminative ability of semantic information in a coarse-to-fine manner: it gradually learns the semantic features of the target to be tracked and suppresses interference from similar objects by stacking multiple CR layers. Extensive experiments and comparisons with recent competitive trackers in challenging large-scale benchmarks demonstrate that, our tracker outperforms all previous convolutional trackers and has competitive results with transformer-based method. The code will be made available.

Calcium Chemistry in Carbon-rich Circumstellar Environments: The Laboratory and Astronomical Discovery of Calcium Dicarbide, CaC2 * * This work is based on observations done using the 100 m Green Bank Telescope (GBT), the Yebes 40 m telescope (projects 19A010, 20A017, 20B014, and 21A019), and the IRAM 30 m telescope. The 100 m GBT is an instrument of the Green Bank

Calcium dicarbide, CaC2, has been characterized at high resolution in the laboratory, and its main isotopologue, 40CaC2, has been assigned to 14 rotational emission lines between 14 and 115 GHz, including 12 previously unassigned lines, in the expanding molecular envelope of the evolved carbon star IRC+10216. Aided by high-level quantum calculations and measurements of multiple isotopologues, CaC2 is determined to be a T-shaped molecule with a highly ionic bond linking the metal atom to the C2 unit, very similar in structure to isovalent magnesium dicarbide (MgC2). The excitation of CaC2 is characterized by a very low rotational temperature of 5.8 ± 0.6 K and a kinetic temperature of 36 ± 16 K, similar to values derived for MgC2. On the assumption that the emission originates from a 30″ shell in IRC+10216, the column density of CaC2 is (5.6 ± 1.7) × 1011 cm−2. CaC2 is only the second Ca-bearing molecule besides CaNC and only the second metal dicarbide besides MgC2 identified in space. Owing to the similarity between the predicted ion–molecule chemistry of Ca and Mg, a comparison of the CaC2 abundance with that of MgC2 and related species permits empirical inferences about the radiative association–dissociative recombination processes postulated to yield metal-bearing molecules in IRC+10216 and similar objects.

JWST Spectrophotometry of the Small Satellites of Uranus and Neptune

We use 1.4–4.6 μm multiband photometry of the small inner Uranian and Neptunian satellites obtained with the James Webb Space Telescope’s near-infrared imager NIRCam to characterize their surface compositions. We find that the satellites of the ice giants have, to first order, similar compositions to one another, with a 3.0 μm absorption feature possibly associated with an O-H stretch, indicative of water ice or hydrated minerals. Additionally, the spectrophotometry for the small ice-giant satellites matches spectra of some Neptune Trojans and excited Kuiper Belt objects, suggesting shared properties. Future spectroscopy of these small satellites is necessary to identify and better constrain their specific surface compositions.

Accelerating the transition to zero-emissions ferries

This study investigates how the authorities in Norway have managed to reduce greenhouse gas (GHG) emissions from the ferry sector by implementing a strategic tendering process for domestic ferry services. The study was conducted using interviews and document analysis. The authorities used competitive dialogue to implement zero-emissions technology in the procurement process, rendering the tender process and contract period longer than traditional tenders. The authorities’ first competitive environmental bid process was announced in 2011, and all new ferry tenders are now based on hybrid or zero-emissions technology. The authorities employed push and pull strategies to advance a successful green transition in ferry operations. These measures have led to a significant reduction in GHG emissions from this transport sector but an increase in investment costs compared with traditional diesel ferries. How the authorities used the tender system to make ferry transport more environmentally friendly is useful knowledge for others with similar objectives.

Proposing Smart System for Detecting and Monitoring Vehicle Using Multiobject Multicamera Tracking

Nowadays, the strong development of the economy and society has driven the increase in traffic participation, making traffic management increasingly difficult. To effectively address this issue, AI applications are being applied to improve urban traffic management and operations. Therefore, we propose a smart system to detect and monitor vehicles across multiple surveillance cameras. Our system leverages data collected from traffic surveillance cameras and harnesses the power of deep learning technology to detect and track vehicles smoothly. To achieve this, we use the YOLO model for detection in conjunction with the DeepSORT algorithm for precise vehicle tracking on each camera. Furthermore, our system uses a ResNet backbone model for feature extraction of objects within each camera’s frame. It utilizes cosine distance to identify similar objects in other cameras, facilitating multicamera tracking. To ensure optimal performance, our system is implemented using the NVIDIA DeepStream SDK, enabling it to achieve an impressive speed of 21 fps on each camera and an average of precision approximately 85% for three modules. The results of our study affirm the system’s suitability and its potential for practical applications in the field of urban traffic management.

Mapping and Integrating Security and Risk Standards: a Systematic Literature Review

Organizations are under increasing pressure to comply with various rules, standards, and policies in today&amp;rsquo;s regulatory environment. Compliance controls are put in place to avoid legal or regulatory violations, which could lead to severe penalties, loss of reputation, and financial damages. However, these controls may have similar scopes and objectives, resulting in duplicated work and unnecessary costs for the organizations. To address this issue, researchers carry out the mapping and integration of these standards to avoid duplication, streamline compliance efforts, and identify best practices. Our work aims to improve the State-of-the-Art by exploring the main benefits and problems resulting from these processes, as well as identifying methods or artifacts that can be reused in the future. We focus on the fields of Risk, Security, and Business Continuity, as these are critical areas where compliance is crucial for organizations. Through our research, we have found that current methods of generating mapping artifacts are not only cumbersome to execute but also ineffective, as they output a single artifact without the reasoning behind it.

A Double Deep Q-Network framework for a flexible job shop scheduling problem with dynamic job arrivals and urgent job insertions

In the semiconductor manufacturing industry, the Dynamic Flexible Job Shop Scheduling Problem is regarded as one of the most complex and significant scheduling problems. Existing studies consider the dynamic arrival of jobs, however, the insertion of urgent jobs such as testing chips poses a challenge to the production model, and there is an urgent need for new scheduling methods to improve the dynamic response and self-adjustment of the shop floor. In this work, deep reinforcement learning is utilized to address the dynamic flexible job shop scheduling problem and facilitate near-real-time shop floor decision-making. We extracted eight state features, including machine utilization, operation completion rate, etc., to reflect real-time shop floor production data. After examining machine availability time, the machine's earliest available time is redefined and incorporated into the design of compound scheduling rules. Eight compound scheduling rules have been developed for job selection and machine allocation. By using the state features as inputs to the Double Deep Q-Network, it is possible to acquire the state action values (Q-values) of each compound scheduling rule, and the intelligent agent can learn a reasonable optimization strategy through training. Simulation studies show that the proposed Double Deep Q-Network algorithm outperforms other heuristics and well-known scheduling rules by generating excellent solutions quickly. In most scenarios, the Double Deep Q-Network algorithm outperforms the Deep Q-Network, Q-Learning, and State-Action-Reward-State-Action (SARSA) frameworks. Moreover, the intelligent agent has good generalization ability in terms of optimization for similar objectives.

Application of Web 2.0 to Reduce Failure in English

The purpose of the intervention was to reduce the failure rate in English with the help of a website built to support the learning experience. Action research was employed in a mixed-methods approach with an exploratory sequential design. Techniques such as documentary analysis, semistructured interviews, and participant observation were employed with 255 high schoolers. Findings revealed that the website, together with follow-up from the teacher-researchers, helped most students achieve a passing grade, empowered the learning experience, and enhanced communicative competence and linguistic awareness. Additionally, the website’s user-friendly nature and well-suited interface simplified the learning dynamic. Furthermore, according to website data, this digital space was also used in other settings with similar objectives. Even so, apathy remained a problem as some learners chose not to take part in the strategy and did not pass. We believe that the research contributes to the state of the art and generates knowledge, especially given the lack of research addressing failure in language education.

Differences and similarities of the preliminary ruling procedure of the European Court of Justice, and the advisory opinion of the Permanent Tribunal of Revision of the Mercosur.

The purpose of this paper is to present the reader with a comparative analysis of two judicial tools with similar objectives, under two dissimilar regional integration systems. In order to understand the origin of the differences and similarities of the institute under analysis, we will dive into the cultural, historical, economic and political circumstances, that will ultimately make clear the reasons that explain why the integration outcomes in the Southern Common Market differs from the European one. The final aim is to prove the statement that integration outcomes are highly dependent on regional endogenous properties. The concrete institutions under analysis will present the reader with a concrete case, where the different evolution paths, result in judicial tools of different levels of effectiveness in their respective integration processes.

Tidal Disruption of Planetesimals from an Eccentric Debris Disk Following a White Dwarf Natal Kick

The surfaces of many white dwarfs are polluted by metals, implying a recent accretion event. The tidal disruption of planetesimals is a viable source of white dwarf pollution and offers a unique window into the composition of exoplanet systems. The question of how planetary material enters the tidal disruption radius of the white dwarf is currently unresolved. Using a series of N-body simulations, we explore the response of the surrounding planetesimal debris disk as the white dwarf receives a natal kick caused by anisotropic mass loss on the asymptotic giant branch. We find that the kick can form an apse-aligned, eccentric debris disk in the range 30–240 au, which corresponds to the orbits of Neptune, the Kuiper Belt, and the scattered disk in our solar system. In addition, many planetesimals beyond 240 au flip to counterrotating orbits. Assuming an isotropic distribution of kicks, we predict that approximately 80% of white dwarf debris disks should exhibit significant apsidal alignment and a fraction of counterrotating orbits. The eccentric disk is able to efficiently and continuously torque planetesimals onto radial, star-grazing orbits. We show that the kick causes both an initial burst in tidal disruption events as well as an extended period of 100 Myr where tidal disruption rates are consistent with observed mass accretion rates on polluted white dwarfs.