Search Tracking Research Articles

Data processing method of silicon semiconductor vertex chamber based on impact point coordinate

This paper presents a comprehensive study on the reconstruction of vertex positions and particle tracks using heavy ion collision data from the Large Hadron Collider (LHC). Nonlinear particle trajectories, background noise, and scattering effects complicate accurate vertex prediction and trajectory reconstruction in real particle detectors. The solution proposed in this paper is integrating geometric methods with the DBSCAN density clustering algorithm to overcome these issues. This method effectively improves the precision of vertex finding and particle track reconstruction. In the meantime, a geometrical technique and probabilistic quantization are employed to predict the motion radius of the particle more accurately. This framework has been independently confirmed in an analysis of >10,000 collision points, which proves the frameworks robustness. Compared with the benchmark method, the framework only relies on the coordinates of the hit point recorded by the detector, which not only improves the universality of the algorithm application but also reduces the requirements on the equipment and the complexity of implementation and effectively improves the precision of vertex and trajectory reconstruction. The results are for the vertexing accuracy (0.005 cm) and average tracking search precision (95.40%) with a radius determination error of 0.5 cm. The proposed method also stands valid when these results are evaluated.

Patient Feedback Applied in Undergraduate Dental Education for Individual Student Development and Assessment: A Scoping Review.

Active involvement of patients in healthcare professional education is well established, taking a variety of forms. There is a steer towards patient feedback informing the development of dental students and while there is recognition of its potential value to individual students, challenges exist related to collection and use. What is unclear is, within a dental education setting, the extent and use of patient feedback to individual students. A scoping review was conducted to assess and map the volume and characteristics of the research/literature in this area. Systematic searches of bibliographic databases Ovid MEDLINE(R), Scopus, ERIC and Embase were conducted, and wider literature (Google Scholar) was searched. Screening was conducted based on eligibility criteria and a customised data charting form was used. The electronic and citation tracking searches identified 1021 studies. After duplicates were removed, 778 studies were screened by title and abstract, and 718 studies were found to be irrelevant to the current review. Sixty full-text studies were assessed for eligibility, 46 studies were excluded, and 14 studies were included for data charting. This review has identified that patient feedback has been captured through both simulated and real patient encounters. There was a bias towards feedback generated through simulated patient encounters. Feedback was reported to support the development of a range of skills, most frequently communication and patient management. Challenges that were identified by researchers related to staff/student engagement and available resources.

The DECam Ecliptic Exploration Project (DEEP). VI. First Multiyear Observations of Trans-Neptunian Objects

We present the first set of trans-Neptunian objects (TNOs) observed on multiple nights in data taken from the DECam Ecliptic Exploration Project. Of these 110 TNOs, 105 do not coincide with previously known TNOs and appear to be new discoveries. Each individual detection for our objects resulted from a digital tracking search at TNO rates of motion, using two-to-four-hour exposure sets, and the detections were subsequently linked across multiple observing seasons. This procedure allows us to find objects with magnitudes m VR ≈ 26. The object discovery processing also included a comprehensive population of objects injected into the images, with a recovery and linking rate of at least 94%. The final orbits were obtained using a specialized orbit-fitting procedure that accounts for the positional errors derived from the digital tracking procedure. Our results include robust orbits and magnitudes for classical TNOs with absolute magnitudes H ∼ 10, as well as a dynamically detached object found at 76 au (semimajor axis a ≈ 77 au). We find a disagreement between our population of classical TNOs and the CFEPS-L7 three-component model for the Kuiper Belt.

Robust Frontal Vehicle Pose Estimation Based on Structural Parameter Optimization Using Reliable Edge Point Sequences

In order to enhance the stability of vehicle pose estimation within driving videos, a novel methodology for optimizing vehicle structural parameters is introduced. This approach hinges on evaluating the reliability of edge point sequences. Firstly, a multi−task and iterative convolutional neural network (MI−CNN) is constructed, enabling the simultaneous execution of four critical tasks: vehicle detection, yaw angle prediction, edge point location, and visibility assessment. Secondly, an imperative aspect of the methodology involves establishing a local tracking search area. This region is determined by modeling the limitations of vehicle displacement between successive frames. Vehicles are matched using a maximization approach that leverages point similarity. Finally, a reliable edge point sequence plays a pivotal role in resolving structural parameters robustly. The Gaussian mixture distribution of vehicle distance change ratios, derived from two measurement models, is employed to ascertain the reliability of the edge point sequence. The experimental results showed that the mean Average Precision (mAP) achieved by the MI−CNN network stands at 89.9%. A noteworthy observation is that the proportion of estimated parameters whose errors fall below the threshold of 0.8 m consistently surpasses the 85% mark. When the error threshold is set at less than 0.12 m, the proportion of estimated parameters meeting this criterion consistently exceeds 90%. Therefore, the proposed method has better application status and estimation precision.

Reviewing the prospect of fermion triplets as dark matter and source of baryon asymmetry in non-standard cosmology

Indirect searches of Dark Matter (DM), in conjugation with 'missing track searches' at the collider seem to confine SU(2) L fermion triplet DM (FTDM) mass within a narrow range around 1 TeV. The canonical picture of the pure FTDM is in tension since it is under-abundant for the said mass range. Several preceding studies have reported that an extra species (ϕ), redshifts faster than the radiation (∼ a (4+n) where n > 0), leads to a faster expanding early Universe by dominating in the energy density with an enhanced Hubble parameter. This has the potential to revive the under-abundant FTDM (ℤ2 odd, lightest generation) by causing freeze-out earlier without modifying the interaction strength between DM and thermal bath. On the other hand, although the CP asymmetry produced due to the decay of ℤ2 even heavier generations of the triplet remains unaffected, its evolution is greatly affected by the non-standard cosmology. It has been observed through numerical estimations that the minimum mass of the triplet, required to produce sufficient baryon asymmetry of the Universe (BAU), can be lowered up to two orders (compared to the standard cosmology) in this fast expansion scenario. The non-standard parameters n and Tr (a reference temperature below which radiation dominance prevails), which simultaneously control DM abundance as well as the frozen value of BAU, are tightly constrained from the observed experimental values. We have found that n is strictly bounded within the interval 0.4 ≲ n ≲ 1.8 where the upper bound is imposed by the BAU constraint whereas the lower bound arises to satisfy the correct DM abundance. It has been noticed that the restriction on Tr is not so stringent as it can vary from sub GeV to a few tens of GeV.

Meta-Research Perspectives on Verbal Lie Detection.

Verbal lie detection (VLD) research, conducted mainly in the cognitive sciences, examines content-based indicators that differ between truth-tellers and lie-tellers. Following the meta-research approach (examination of the research itself), the current paper aimed to ascertain the current status of VLD research across three components: the search for VLD indicators, VLD coding, and VLD research tracks. It highlights several issues that challenge VLD research; these are discussed, along with suggestions for how to address them. This scrutiny may contribute to a further advancement of the field of VLD research and, as a result, an improvement of VLD practices.

In Search for the Right Track from Definition to Diagnosis and Treatment for Heart Failure

In Search for the Right Track from Definition to Diagnosis and Treatment for Heart Failure

The last complex WIMPs standing

We continue the study of weakly interacting massive particles (WIMP) started in Bottaro et al. (Eur Phys J C 82:31, 2022), focusing on a single complex electroweak n-plet with non-zero hypercharge added to the Standard Model. The minimal splitting between the Dark Matter and its electroweak neutral partner required to circumvent direct detection constraints allows only multiplets with hypercharge smaller or equal to 1. We compute for the first time all the calculable WIMP masses up to the largest multiplet allowed by perturbative unitarity. For the minimal allowed splitting, most of these multiplets can be fully probed at future large-exposure direct detection experiments, with the notable exception of the doublet with hypercharge 1/2. We show how a future muon collider can fully explore the parameter space of the complex doublet combining missing mass, displaced track and long-lived track searches. In the same spirit, we study how a future muon collider can probe the parameter space of complex WIMPs in regions where the direct detection cross section drops below the neutrino floor. Finally, we comment on how precision observables can provide additional constraints on complex WIMPs.

An in silico discovery of potential 3CL protease inhibitors of SARS-CoV-2 based upon inactivation of the cysteine 145-Histidine 41 catalytic dyad

Coronavirus disease 19 (COVID19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, several countries are at risk of the pandemic caused by this virus. In the absence of any vaccine or virus-specific antiviral treatments, the need is to fast track search for potential drug candidates to combat the virus. Though there are known drugs that are being repurposed to fight against the SARS-CoV-2, there is a requirement for the virus-specific drugs at the earliest. One of the main drug targets of SARS-CoV-2 is an essential non-structural protein, 3CL protease, critical for the life cycle of the virus. We have used molecular docking studies to screen a chemically diverse set of small molecules to identify potential drug candidates to target this protein. Of the 22,630 molecules from varied small molecule libraries, based on the binding affinities and physicochemical properties, we finalized 30 molecules to be potential drug candidates. Eight of these molecules bind in a manner allowing for the scope of a nearly orthogonal backside nucleophilic attack on their suitably placed electrophilic carbonyl groups by the thiol group of cysteine residue 145, while remaining inside a 4 Ǻ distance range. It is interesting since carbonyl groups are known to be attacked in a similar fashion by external nucleophiles and can be relevant when considering these molecules as potential mechanism-based irreversible inhibitors of the 3CLPro. Further, ADMET analysis and Molecular dynamics simulations and available bioactive assays led to the identification of three molecules with high potential to be explored as drug candidates/lead molecules to target 3CLPro of SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Long dead winos

We describe a new code and approach using particle-level information to recast the recent CMS disappearing track searches including all Run 2 data. Notably, the simulation relies on knowledge of the detector geometry, and we also include the simulation of pileup events directly rather than as an efficiency function. We validate it against provided acceptances and cutflows, and use it in combination with heavy stable charged particle searches to place limits on winos with any proper decay length above a centimetre. We also provide limits for a simple model of a charged scalar that is only produced in pairs, that decays to electrons plus an invisible fermion.

Symbol Detection Based on Back Tracking Search Algorithm in MIMO-NOMA Systems

One of the most important methods used to cope with multipath fading effects, which cause the symbol to be received incorrectly in wireless communication systems, is the use of multiple transceiver antenna structures. By combining the multi-input multi-output (MIMO) antenna structure with non-orthogonal multiple access (NOMA), which is a new multiplexing method, the fading effects of the channels are not only reduced but also high data rate transmission is ensured. However, when the maximum likelihood (ML) algorithm that has high performance on coherent detection, is used as a symbol detector in MIMO NOMA systems, the computational complexity of the system increases due to higher-order constellations and antenna sizes. As a result, the implementation of this algorithm will be impractical. In this study, the backtracking search algorithm (BSA) is proposed to reduce the computational complexity of the symbol detection and have a good bit error performance for MIMO-NOMA systems. To emphasize the efficiency of the proposed algorithm, simulations have been made for the system with various antenna sizes. As can be seen from the obtained results, a considerable reduction in complexity has occurred using BSA compared to the ML algorithm, also the bit error performance of the system is increased compared to other algorithms.

COMPARATIVE STUDY OF EVOLUTIONARY ALGORITHMS TO GENERATE FLAT-TOP BEAM PATTERN FOR SYNTHESIS OF A LINEAR ANTENNA ARRAY

In the present paper three evolutionary algorithms are compared and discussed for synthesizing a linear array of dipole antenna of half-wavelength oriented horizontally. All the dipoles are mutually coupled and designed to radiate the flat-top beam (FTB) pattern including multiple single null steering with little ripple deviation. The adopted evolutionary algorithms are; flower pollination algorithm (FPA), firefly algorithm (FA) and back tracking search algorithm (BSA), respectively. These algorithms are then combined with an efficient Inverse Fast Fourier Transform (IFFT) for reduction in the computation of evaluating time meaningfully. The required synthesis is attained by generating the current amplitudes at 00 and 1800 using binary phase shifters for the antenna array. The performance analysis of key antenna parameters along with the statistical parameters is achieved with the help of the optimization process and compared. In this paper, the MATLAB tool is used as a validation tool and the obtained simulation results are very satisfying and acceptable.

RETRACTED ARTICLE: Forecasting algorithm of tourism service trade based on PSO-optimized hybrid RVM model

As a comprehensive form of trade, tourism service trade has had a profound impact on the economies of various countries. This research mainly discusses the tourism service trade forecasting algorithm based on the PSO-optimized hybrid RVM model. This study extracts 8 indicators including gross national product, total fixed asset investment, total import and export, China's import and export tariff rate, the exchange rate of renminbi to the US dollar, and the global economic growth rate. The same as the impact indicators of tourism service trade, but there is a certain degree of redundancy and correlation in these indicators. In order to measure the correlation between the evaluation indicators, the autocorrelation evaluation function in MATLAB is used, and the principal component analysis method is used to extract the principal components that can represent the indicators in a larger percentage. In order to improve the prediction accuracy of the RVM model, based on the adaptive construction model structure and initial model weights, the PSO algorithm is used to optimize the RVM model weights. The optimization process takes the minimum error of the RVM model as the algorithm search target, and each represents the RVM model. The algorithm finds the value and threshold of the optimal RVM model through the particle swarm tracking search algorithm and then uses the original RVM model and the optimized RVM prediction respectively total amount of tourism service trade in City A, and compares the prediction errors of the single RVM method and the PSO-optimized RVM method, and analyzes the degree of model prediction error reduction after the PSO model optimizes the RVM model. According to the forecast result, the relative average error of 2020 is 5.7%, and the forecast result is relatively accurate. This research is helpful to provide scientific reference for my country's tourism service trade.

Epigenetic Response of Yarrowia lipolytica to Stress: Tracking Methylation Level and Search for Methylation Patterns via Whole-Genome Sequencing.

DNA methylation is a common, but not universal, epigenetic modification that plays an important role in multiple cellular processes. While definitely settled for numerous plant, mammalian, and bacterial species, the genome methylation in different fungal species, including widely studied and industrially-relevant yeast species, Yarrowia lipolytica, is still a matter of debate. In this paper, we report a differential DNA methylation level in the genome of Y. lipolytica subjected to sequential subculturing and to heat stress conditions. To this end, we adopted repeated batch bioreactor cultivations of Y. lipolytica subjected to thermal stress in specific time intervals. To analyze the variation in DNA methylation between stressed and control cultures, we (a) quantified the global DNA methylation status using an immuno-assay, and (b) studied DNA methylation patterns through whole-genome sequencing. Primarily, we demonstrated that 5 mC modification can be detected using a commercial immuno-assay, and that the modifications are present in Y. lipolytica’s genome at ~0.5% 5 mC frequency. On the other hand, we did not observe any changes in the epigenetic response of Y. lipolytica to heat shock (HS) treatment. Interestingly, we identified a general phenomenon of decreased 5 mC level in Y. lipolytica’s genome in the stationary phase of growth, when compared to a late-exponential epigenome. While this study provides an insight into the subculturing stress response and adaptation to the stress at epigenetic level by Y. lipolytica, it also leaves an open question of inability to detect any genomic DNA methylation level (either in CpG context or context-less) through whole-genome sequencing. The results of ONT sequencing, suggesting that 5 mC modification is either rare or non-existent in Y. lipolytica genome, are contradicted with the results of the immunoassay.

Improved RRT-Connect Algorithm for Urban low-altitude UAV Route Planning

Path length and computation time in path planning seriously affect the safety and efficiency of urban low-altitude UAV flight. This paper improves RRT-connect Algorithm for path planning, the search step length, parent node selection and branch orientation selection are optimized to reduce the path length and algorithm time. Starting from the shortest parent node of the two trees, track search is carried out in the Middle Direction, the search step length is changed according to the field of view, the search step length is cut down quickly through the open field, and the search step length in narrow space is reduced, at the same time, the growth direction of the main branch of the search tree is controlled by the angle to reduce the probability of the UAV turning sharply. Simulation experiments show that the proposed algorithm has better time and space advantages and convergence than the current popular algorithm, the comparison results show that the optimized Algorithm RRT-connect is superior to the current flow Algorithms RTT-extend and Lazy-RTT in terms of the time consumption of short-time fast search and the length of path generation.

Recommendations for the FAIRification of genomic track metadata

Background: Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, as well as RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information. Description of work: We propose to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable) to produce searchable metadata for genomic tracks. Findability and Accessibility of metadata can then be ensured by a track search service that integrates globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories. Interoperability and Reusability need to be ensured by the specification and implementation of a basic set of recommendations for metadata. We have tested this concept by developing such a specification in a JSON Schema, called FAIRtracks, and have integrated it into a novel track search service, called TrackFind. We demonstrate practical usage by importing datasets through TrackFind into existing examples of relevant analytical tools for genomic tracks: EPICO and the GSuite HyperBrowser. Conclusion: We here provide a first iteration of a draft standard for genomic track metadata, as well as the accompanying software ecosystem. It can easily be adapted or extended to future needs of the research community regarding data, methods and tools, balancing the requirements of both data submitters and analytical end-users.

Probing dark matter with disappearing tracks at the LHC

Models where dark matter is a part of an electroweak multiplet feature charged particles with macroscopic lifetimes due to the charged-neutral mass split of the order of pion mass. At the Large Hadron Collider, the ATLAS and CMS experiments will identify these charged particles as disappearing tracks, since they decay into a massive invisible dark matter candidate and a very soft charged Standard-Model particle which fails to pass the reconstruction requirements. While ATLAS and CMS have focused on the supersymmetric versions of these scenarios, we have performed here the reinterpretation of the latest ATLAS disappearing track search for a suite of dark matter multiplets with different spins and electroweak quantum numbers. More concretely, we consider the cases of the inert Two Higgs Doublet model (i2HDM), of Minimal Fermion Dark Matter (MFDM) and of Vector Triplet Dark Matter (VTDM). Our procedure is validated by using the same wino and higgsino benchmark models employed by the ATLAS collaboration. We have found that with the disappearing track signature one can probe a vast portion of the parameter space, well beyond the reach of prompt missing energy searches (notably mono-jets). We provide tables with the upper-limits on the cross-section upper limits, and efficiencies in the lifetime - dark matter mass plane for all the models under consideration. Moreover we make the recasting code employed here publicly available, as part of the LLP Recasting Repository.

Recommendations for the FAIRification of genomic track metadata.

Background: Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, as well as RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information. Description of work: We propose to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable) to produce searchable metadata for genomic tracks. Findability and Accessibility of metadata can then be ensured by a track search service that integrates globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories. Interoperability and Reusability need to be ensured by the specification and implementation of a basic set of recommendations for metadata. We have tested this concept by developing such a specification in a JSON Schema, called FAIRtracks, and have integrated it into a novel track search service, called TrackFind. We demonstrate practical usage by importing datasets through TrackFind into existing examples of relevant analytical tools for genomic tracks: EPICO and the GSuite HyperBrowser. Conclusion: We here provide a first iteration of a draft standard for genomic track metadata, as well as the accompanying software ecosystem. It can easily be adapted or extended to future needs of the research community regarding data, methods and tools, balancing the requirements of both data submitters and analytical end-users.

Vector Finder—A Toolkit for Track Finding in the MPD Experiment

A track reconstruction method based on a constrained combinatorial search for track candidates, i.e. combinations of detector hits possibly belonging to a track, is presented. The algorithm has been implemented as a Vector Finder software toolkit containing a track reconstruction procedure and tools to determine hit acceptance windows (a priori constraints) for the track search. Track reconstruction results for high multiplicity simulated events (∼1000 particles in the detector acceptance) are shown demonstrating good performance of the approach proposed.

Coronavirus (Covid-19) pandemic: How may communication strategies influence our behaviours?

A novel Corona virus (SARS-CoV-2), started in Wuhan China, caused an outbreak of viral pneumonia to subsequently spread throughout the world. Italy has been one of the most affected countries in the world and the increasing number of cases and deaths has created strong emotional reactions in people. This study has aimed at evaluating public attention to this emerging disease through the use of Google Trends. Public attention, measured as the volume of internet search activity, was correlated with Health Communication Strategies and official COVID-19 data. At the moment of the study analysis, Italy was by far the first country in terms of search volume for “coronavirus” and the highest peak of searches was reached on February 23, 2020. We have found that there was a correlation between public attention to coronavirus disease and communications from Public Health policies: we observed spikes in search volumes on the days of Presidential Decree publications. Furthermore, this attention was also correlated with Case Fatality Rate (CFR). Even if CFR data are continuously updated and can be affected by patient histories, the correlation found suggests that the increase in mortality has generated growing interest in the disease and its risk perception. This study shows that tracking searches through Google Trends as a public focus indicator is a useful tool for decision-makers in guiding communication strategies and should as well stimulate a more transparent media and policy making reporting.