Matching Procedure Research Articles

Does taking additional Maths classes in high school affect academic outcomes?

Several studies in the mathematical education literature show the effect of students’ high school skills in maths on their success at higher levels of education and work. In particular, the importance of maths course taking in US high schools is highlighted to be important for college enrollment and completion. The choice of taking additional maths courses or, as in Italy, of choosing a high-school curriculum with more maths, is not random: it depends on several substantial factors such as gender and socio-economic status. This selection bias implies that the differences in the academic outcomes might be traceable not only to mathematics ability and knowledge. In this paper, the aim is to estimate the treatment effect of attending a relatively new high school curriculum in Italy with more maths, with respect to the traditional track of the scientific “liceo”, on two academic outcomes: university enrollment and first-year university performance. After having reduced the selection bias using a caliper multi-level propensity score matching procedure, a multi-state Markov model is used to study the treatment effect on the joint educational outcomes.

Correlation-based passive localization: Linear system modeling and sparsity-aware optimization.

In underwater passive localization, matched field processing has faced mismatch challenges for many years. To overcome the mismatch, data-derived replicas have gained increasing popularity due to their better localization performance than parameter-based ones, among which the cross correlation-based replicas showed enhanced robustness against the spectral differences between the library and target vessels. However, cross correlation-based matching localizations result in high sidelobes and require enough frequency samples to eliminate grating lobes. This issue has been widely reported in the previous literature but has yet to be theoretically analyzed. In this work, we revisit the conventional correlation-based matching procedures and formulate the ambiguity surface as a least-norm solution of an underdetermined linear system. This formulation permits understanding the sidelobes from an optimization perspective. Based on this view, the high sidelobe challenge and requirement of measurements are systematically tackled by recasting the matching problem as a sparsity-aware optimization problem. The superiority of the proposed optimization approach is showcased through simulated data in the waveguide, microphone data in the air, and SWellEx-96 data. The linear system modeling is also extended to a distributed sensor network, profiting from the spatial gain brought by various azimuthal directions with respect to the source.

Corrected evaluation of the breech presentation outcome based on etiology of this presentation in congenitally malformed uterus.

Breech presentation (BP) results from at random filling of the intrauterine cavity, with an equal probability for a BP or cephalic presentation (CP). Each fetus in BP has its "pair" in CP randomly assumed CP. Direct comparison of BP and CP makes bias to less expressed differences between these two groups. It is therefore necessary to subtract the number of fetuses/newborns from the CP set that are identical to the number of fetuses/newborns in the BP set, with identical characteristics, and add this group to the BP set before comparing them to the rest of the CP fetuses/newborns in the matching process. The procedure encompasses nine variables in pregnancies with a congenitally malformed uterus (CMU) identified at the Department of Obstetrics (1985-2014): gestational age, birth mass, birth length, head circumference, shoulders circumference, umbilical length, placental weight, newborn mass/newborn length ratio, and newborn mass/placental mass ratio. Firstly, the probability of BP was determined and its relation to gestational age, physical characteristics, and previous presentations. Then direct comparison as well as case-control matching of the CP and BP were performed. Case-control matching was based on either a single specific variable (M1) or all combined variables (M2). 462 deliveries were identified with CMU. In 81 cases of multiparity, a fetal presentation was found to be an independent event regardless of the previous presentation, gestational age, and newborn physical characteristics. In four types of CMU with 337 deliveries (Bicornuate, Didelphys, Unicornuate, Arcuate), 9 variables with 36 instances of comparison were observed. M1 in 10 instances and M2 in 6 instances showed a statistically significant lower value of breech/random presentation compared with CP. CP have lower value in 2 instances in M1 and 1 in M2. Statistically significant differences were absent without the matching process. The study confirms the maximum probability for the BP is 50%. The case-control matching procedure shows that it is able to detect the difference between the breech/random presentation and CP, while the classic method of direct comparison was unable to detect any differences. The outcome of the breech/random presentation in CMU should be evaluated with the described case-control matching procedure.

1228-P: Comparison between Combination of Low- or Moderate-Intensity Statin with Ezetimibe and High-Intensity Statin Monotherapy for Primary Prevention of Cardiovascular Disease and All-Cause Mortalities in Patients with Type 2 Diabetes—A Propensity-Matched Natio

Background and Aims: Here, we compared the effects of combination therapy of low- or moderate-statin with ezetimibe and high-intensity statin monotherapy in patients with type 2 diabetes without previous cardiovascular disease (CVD) on incident CVD and all cause mortalities in a real-world setting. Methods: Using the Korean National Health Insurance Service datasets, two cohorts comparing high intensity statin monotherapy with low- or moderate-intensity statin and ezetimibe combination therapy were constructed using a 1:1 propensity score matching procedure and were followed up for 3.4 years. The primary outcome was a composite of myocardial infarction (MI), stroke, and all-cause mortality. The secondary outcome was the occurrence of individual events. Results: Compared to high-intensity statin monotherapy, moderate-intensity statin with ezetimibe combination therapy significantly reduced the risk of composite outcomes (hazard ratio [HR] 0.85, 95% confidence interval [CI] 0.74 - 0.98, P=0.029) as well as stroke (HR 0.70, 95% CI 0.52 - 0.93, P=0.014), but not MI or all cause mortalities. However, there was no significant risk reduction in composite outcomes following low-intensity statin therapy with ezetimibe (HR 1.02, 95% CI 0.75 - 1.39, P=0.882) than that after high-intensity statin monotherapy. The statin with ezetimibe combination showed a consistent efficacy regardless of diverse patients’ baseline characteristics. Conclusions: Moderate-intensity statin with ezetimibe combination therapy was superior to high-intensity statin monotherapy for CVD primary prevention, and low-intensity statin with ezetimibe showed a comparable efficacy to high-intensity statin monotherapy in patients with type 2 diabetes. Disclosure Y.Hwang: None. S.Park: None. I.Jeong: None. K.Ahn: None. H.Chung: None.

Evaluating the impact of 4D seismic data artefacts in data assimilation

Time-lapse or 4D seismic data are important constraints in reservoir studies because they enable monitoring of saturation and pressure changes that result from hydrocarbon production. 4D seismic data have been quantitatively added, along with production data, in history matching or data assimilation procedures to reduce uncertainty and improve production forecasts. Before performing quantitative studies, it is important to ensure that the 4D seismic data are reliable, with minimal artefacts such as side-lobe effects that can disturb the identification of anomalies. In this work, we propose different ways of treating 4D seismic data in data assimilation for a real reservoir. Explicitly, we evaluated the impact on data assimilation results when considering different amounts of 4D information and three treatments to the identified artefacts. The treatments were: ignoring them, excluding them from data assimilation or defining no seismic changes at their locations. The results show that well and seismic matches are improved when 4D seismic data are assimilated, also improving the production predictions. Despite being a thin reservoir, assimilating two single-layer maps allowed us to predict relevant observed dynamic behaviour, such as the evolved gas trapped in the lower interval. Furthermore, when a treatment was applied to the artefacts, they produced better models than using a single two-layer map (with lower production errors and visually closer impedances to the observed data). Our recommendation is the assimilation of well and 4D seismic data, with the exclusion of unreliable information, for better life-cycle decisions.

Wave interaction with a rigid porous structure under the combined effect of refraction–diffraction

Water wave scattering, trapping, and generation by a thin porous structure placed on an uneven bottom are studied approximately. The classical eigenfunction expansion method is employed for the uniform bottom, whereas the Galerkin-Eigenfunction expansion method is employed for the uneven bottom. The solution is derived in the form of a system of algebraic equations through matching procedure. Wave reflection, transmission, and wave-induced forces on the porous structure and backwall are investigated under the combined refraction–diffraction effect. In the scattering problem with periodic bottom, Bragg resonance is minimized at the Bragg frequency, whereas the porous structure at other frequencies maximizes wave reflection. Consequently, wave transmission is very low for all wave frequencies in this situation. In the wave trapping problem, forces on the porous structure and the backwall are reduced substantially when the water depth ratio decreases. Feasible locations of the porous structure are shown at which wave reflection and forces on it and backwall are optimized. In the wave generation problem, the comparison of results for flat and uneven bottoms reveals that waves have a smaller amplitude at infinity as uniform bottom levels become farther for relatively small values of the reciprocal of the wave-effect parameter (C).

#2912 HYDRATION STATUS IN PATIENTS ON STANDARD HEMODIALYSIS OR ONLINE HEMODIAFILTRATION: ITS RELATIONSHIP WITH PARAMETERS MEASURED OR ESTIMATED BY BIVA

Abstract Background and Aims Altered fluid status and inadequate fluid management, independently and concurrently with depletion of lean mass adversely affect patients’ quality of life, outcomes and prognosis of hemodialysis (HD) patients, both standard (HD) and Hemodiafiltration on-line (HDFOL). Method We conducted a population-based on 470 patients, retrospective longitudinal cohort study, to determine the physical characteristics of bioimpedance measurements and indexes obtained by BIVA on maintenance HD and HDFOL patients, and to analyze the hydration status of the extra and intracellular compartments. The Propensity Score Matching (PSM) procedure, matches case records with similar control records. It first runs a logistic regression with the case/control group variable as the dependent variable. Then it selects a match for each case from the control group based on the PSM from the logistic regression. Euhydrated and Overhydrated groups were macheted separately. Results see Table 1, Figure 1 and 2. Conclusion 1) Compared to standard HD, the HDFOL technique maintains a better water balance between the intracellular and extracellular spaces, especially when the patient is euhydrated. In overhydrated patients, although the ECW/ICW ratio is high, it is lower in patients on HDFOL. 2) The stability of cell membranes in HDFOL is better than in HD. 3) For an adequate assessment of any of the parameters measured directly or derived from the BIA, it must be a “sine qua non” condition that the patient is in a state of euhydration. 4) In hemodialysis patients, the phase angle, must first be considered as a marker of hydration status, and then as a marker of nutritional status.

GPU-based similarity metrics computation and machine learning approaches for string similarity evaluation in large datasets

AbstractThe digital era brings up on one hand massive amounts of available data and on the other hand the need of parallel computing architectures for efficient data processing. String similarity evaluation is a processing task applied on large data volumes, commonly performed by various applications such as search engines, biomedical data analysis and even software tools for defending against viruses, spyware, or spam. String similarities are also used in musical industry for matching playlist records with repertory records composed of song titles, performer artists and producers names, aiming to assure copyright protection of mass-media broadcast materials. The present paper proposes a novel GPU-based approach for parallel implementation of the Jaro–Winkler string similarity metric computation, broadly used for matching strings over large datasets. The proposed implementation is applied in musical industry for matching playlist with over 100k records with a given repertory which includes a collection of over 1 million right owner records. The global GPU RAM memory is used to store multiple string lines representing repertory records, whereas single playlist string comparisons with the raw data are performed using the maximum number of available GPU threads and the stride operations. Further on, the accuracy of the Jaro–Winkler approach for the string matching procedure is increased using both an adaptive neural network approach guided by a novelty detection classifier (aNN) and a multiple-features neural network implementation (MF-NN). Thus, the aNN approach yielded an accuracy of 92% while the MF-NN approach achieved an accuracy of 99% at the cost of increased computational complexity. Timing considerations and the computational complexity are detailed for the proposed approaches compared with both the general-purpose processor (CPU) implementation and the state-of-the-art GPU approaches. A speed-up factor of 21.6 was obtained for the GPU-based Jaro–Winkler implementation compared with the CPU one, whereas a factor of 3.72 was obtained compared with the existing GPU implementation of string matching procedure based on Levenstein distance metrics.

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules

An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices.Graphical abstractOFraMP applied to paclitaxel (ATB ID 35922).

Association of chronic statin use, myopenia, myosteatosis and major morbidity in surgical patients with upper gastrointestinal cancer

Derangements of body composition affect surgical outcomes. Chronic statin use may induce muscle wasting and impair muscle tissue quality. Aim of this study was to evaluate the association of chronic statin use, skeletal muscle area (SMA), myosteatosis and major postoperative morbidity. Between 2011 and 2021, patients undergoing pancreatoduodenectomy or total gastrectomy for cancer, and using statins since at least 1 year, were retrospective studied. SMA and myosteatosis were measured at CT scan. The cut-off for SMA and myosteatosis were determined using ROC curve and considering severe complications as the binary outcome. The presence of myopenia was defined when SMA was lower that the cut-off. A multivariable logistic regression was applied to assess the association between several factors and severe complications. After a matching procedure (1:1) for key baseline risk factors (ASA; age; Charlson comorbidity index; tumor site; intraoperative blood loss), a final sample of 104 patients, of which 52 treated and 52 not treated with statins, was obtained. The median age was 75 years, with an ASA score ≥ 3 in 63% of the cases. SMA (OR 5.119, 95% CI 1.053–24.865) and myosteatosis (OR 4.234, 95% CI 1.511–11.866) below the cut-off values were significantly associated with major morbidity. Statin use was predictive of major complication only in patients with preoperative myopenia (OR 5.449, 95% CI 1.054–28.158). Myopenia and myosteatosis were independently associated with an increased risk of severe complications. Statin use was associated with a higher risk of having major morbidity only in the subgroup of patients with myopenia.

Refining the GENEVA method for Higgs boson production via gluon fusion

We describe a number of improvements to the Geneva method for matching NNLO calculations to parton shower programs. In particular, we detail changes to the resummed calculation used in the matching procedure, including disentangling the cross section dependence on factorisation and beam scales, and an improved treatment of timelike logarithms. We also discuss modifications in the implementation of the splitting functions which serve to make the resummed calculation differential in the higher multiplicity phase space. These changes improve the stability of the numerical cancellation of the nonsingular term at small values of the resolution parameter. As a case study, we consider the gluon-initiated Higgs boson production process gg → H. We validate the NNLO accuracy of our predictions against independent calculations, and compare our showered and hadronised results with recent data taken at the ATLAS and CMS experiments in the diphoton decay channel, finding good agreement.

Insomnia Symptom Trajectory of Spouse Caregivers of Older Adults with Functional Limitations

ABSTRACT Objectives This study examined the long-term impact of spouse caregiving on insomnia symptoms, compared to propensity-score matched non-caregivers. Methods Health and Retirement Study data between 2006 and 2018 were used. Caregivers (n = 403) were respondents (aged 50+) who assisted their heterosexual spouses in performing (instrumental) activities of daily living at baseline. Non-caregivers were matched using a propensity score matching procedure based on baseline characteristics. Insomnia symptoms were measured every 4 years for both groups. Poisson mixed-effect models estimated the association between caregiver status and insomnia symptoms. Results Compared to matched non-caregivers, caregivers had similar severity of insomnia symptoms at baseline ( β caregiver = 0.018, 95% CI = −0.089, 0.124) and reported a similar yearly change rate ( β caregiver × time = −0.008, 95% CI = −0.017, 0.001). No moderation effects of care-recipients’ dementia status and social support were significant. Conclusions In this study sample, there is no evidence that spouse caregivers, specifically those who performed light duties, experience more severe insomnia symptoms than non-caregivers. Clinical implications Spouse caregiving, especially in a light-duty capacity, may not be detrimental to the caregivers’ sleep health. More data are needed regarding insomnia in spouse caregivers with heavy duties of care to fully assess the health impact of the caregiving experience.

An open data set of scholars on Twitter

Abstract The role played by research scholars in the dissemination of scientific knowledge on social media has always been a central topic in social media metrics (altmetrics) research. Different approaches have been implemented to identify and characterize active scholars on social media platforms like Twitter. Some limitations of past approaches were their complexity and, most importantly, their reliance on licensed scientometric and altmetric data. The emergence of new open data sources such as OpenAlex or Crossref Event Data provides opportunities to identify scholars on social media using only open data. This paper presents a novel and simple approach to match authors from OpenAlex with Twitter users identified in Crossref Event Data. The matching procedure is described and validated with ORCID data. The new approach matches nearly 500,000 matched scholars with their Twitter accounts with a level of high precision and moderate recall. The data set of matched scholars is described and made openly available to the scientific community to empower more advanced studies of the interactions of research scholars on Twitter.

Impact of participation in community-based sheep breeding practice on the income of household: A case of Adiyo Woreda, Kaffa Zone, SNNPRS, Ethiopia

Community-based sheep breeding practice emerged in 2009 G.C as a possible option to understand the selection practices of the traditional breeders and to create genetic gains that improve sheep productivity and provides an important source of income for the household. This study was conducted in Adiyo woreda, to assess the impact of participation in community-based sheep breeding practice on the income of a household in southern Ethiopia. Adiyo was selected purposively, and simple random sampling techniques were employed to obtain the desired sample. Data were collected through a cross-sectional survey from a sample of 368 respondents, 165 of whom had participants and 203 non-participants. Primary data were collected through focused group discussion, key informant interviews, and questionnaires. Secondary data were collected from a review of related literature. Descriptive statistics and econometric models are used for analyzing quantitative data. A propensity score matching procedure was employed to decide the causal relationship between participant and non-participant households. The result of propensity score matching method analysis shows that participation in community-based breeding practice has increased average annual household income by 4,301.31birr for the participant than non-participants households and the value is significant at 1% level. The sensitivity analysis result showed that impact results estimated by this study were confident to unobserved selection bias. Hence, the community-based breeding practice has a positive and significant impact on the annual income of households. Hence improving the productivity of local sheep by organizing farmers in CBBP can significantly increase the income of smallholder farmers. Therefore, governmental and non-governmental should work on improving the productivity Bonga sheep breed performance.

Differential costs for the non-adult ADHD population in Catalonia

Attention-Deficit/Hyperactivity Disorder (ADHD) is young children’s most common mental health disorder. We aim to provide causal estimates of the differential costs for the non-adult population with ADHD. We used longitudinal administrative data covering the non-adult population over five years and different healthcare providers (general practitioners, hospitalisations and emergency departments, visits to mental healthcare centres—day-care or hospitals) of 1,101,215 individuals in Catalonia (Spain). We also include the consumption of pharmaceuticals and cognitive therapies. We instrumented ADHD diagnosis by the probability of being diagnosed by the most visited healthcare provider based on individual monthly visits to the provider in which this visit was related to ADHD and the density of professionals in the different mental health providers. After using matching procedures to include a proper control group, we estimated two-part and finite mixture models. Our results indicate that ADHD children and adolescents displayed 610€ higher annual health direct costs compared to not diagnosed counterparts. We provide average costs disentangling the sample by age boundaries, gender, and comorbidities to offer values for cost-effective analyses and incremental costs after diagnosis, which is around 400€. A significant differential annual direct health cost for the non-adult population with ADHD is determined, which will be helpful for cost-effectiveness analysis and complete cost-of-illness studies.

EdgeSFG: A matching game mechanism for service function graph deployment in industrial edge computing environment

Network function virtualization-enabled industrial edge computing is a promising service paradigm. In industrial edge computing (IEC), virtual service functions (VSFs) are used to implement basic functionalities and deliver concrete services. To improve the service response speed, VSFs are organized into service function graphs (SFGs) to process service data parallelly. The main challenge is to select proper edge servers for SFG deployment and minimize latency. However, finding an optimal solution to the SFG deployment problem is an NP-hard problem. This paper proposes a matching-game-based algorithm to deploy a large number of concurrent SFGs in an IEC environment. In the proposed algorithm, the deployment of concurrent SFGs is formulated as a college admission problem where SFGs propose to edge servers expecting a low service latency, and then the edge servers decide whether to accept the SFG proposals according to the possible service gain. A distributed matching procedure is introduced to solve the matching game problem between the SFGs and edge servers. The simulations are conducted to verify the SFGs and evaluate the performance of the proposed algorithm in concurrent SFG deployment. Simulation results show that proposed algorithm performs well in reducing average service latency and improving service acceptance rate.

Auditor Assignments and Audit Quality

AbstractGiven the important role of individual auditors in the audit process, appropriate staffing is an essential issue in audit firms. Using unique audit data for both listed and private companies in China, we define the downward mismatch between auditors and clients as an inappropriate assignment of the engagement auditors who are supposed to serve only private companies, but sign the audit reports of public companies. We find that the downward mismatch leads to poor audit quality. The results are robust to various tests, including using alternative proxies, adopting the Propensity Score Matching (PSM) procedure, and controlling for auditor–client fixed effects and audit firm‐level mismatch. Additional analyses reveal that the negative effect of downward mismatch on audit quality is less pronounced for audit firms with more education and training expenditures, with more informatisation expenditures, and with more partners available. Moreover, this negative effect is more pronounced when clients’ business is more complex. Our findings shed light on the importance of staffing assignment decisions within the audit firm.

174 Magnitude and Origins of Gender Differences in Medicare Payments to Neurosurgeons

INTRODUCTION: Gender pay disparities have been described across numerous specialties but have been relatively unexplored in neurosurgery. METHODS: We analyzed public data summarizing services provided to Medicare beneficiaries from 2013-2019. Practice metrics were compared between male and female neurosurgeons via Students’ T-test, Wilcoxon Rank-Sum, multiple linear regression. RESULTS: Women accounted for 8.3% of the 5,846 neurosurgeons serving the Medicare population. Females were reimbursed 41.8% ($59,163.20) less compared to their male colleagues (p < 0.001). Additionally, females billed for fewer services (288 vs. 474, p < 0.001), beneficiaries treated (128 vs. 193, p < 0.01), and unique codes (38.0 vs. 50.0, p < 0.001). However, the disparity persisted even when controlling for differences in years of practice, number of beneficiaries, and total services ($25,444.76, p < 0.001). There was no difference in geographic practice cost indices. The average payment-per-service was $78.15 (95%-CI, $73.14-$83.17, p < 0.001) less than that of males. This was influenced, in part, by women submitting for fewer services within the top quartile of payment (6.26% vs. 11.21%, p < 0.001). However, even when matching procedures by code, females were reimbursed $177.80 (95%-CI, $153.28-$202.31) less than males (p < 0.001). CONCLUSIONS: Female neurosurgeons are reimbursed 18% less when controlling for metrics of practice volume including number of services and beneficiaries treated. Importantly, the disparity exists even for individual procedures, which may represent more limited use of enhancement modifiers. Identifying origins of this disparity will aid in designing interventions that promote more equitable compensation for the work of female neurosurgeons. It is important to note that this database describes a primarily adult patient population and, therefore, discrepancies in reimbursement for pediatric neurosurgery, a field in which women represent a larger proportion, cannot be extrapolated from this study.

Covariance Matching Based Adaptive Attitude Estimation of a Nano- Satellite Using SVD-Aided EKF

Aims: Tuning the system noise covariance Q matrix for the single-frame method aided Kalman filtering algorithm. Background: The covariance matching procedure of the measurement noise covariance, namely the R matrix, was processed in singular value decomposition (SVD), which is one of the single-frame methods. Objective: Develop the R and Q double covariance matching rule for the single-frame method aided Kalman filtering algorithm. Method: The matching procedure of the measurement noise covariance, namely the R matrix, is processed in singular value decomposition (SVD), which is one of the single-frame methods. The second matching rule is defined in the second stage of the proposed EKF design. Result: The matching rules are run simultaneously, which makes the filter capable of being robust against initialization errors, system noise uncertainties, and measurement malfunctions at the same time without an external filter design necessity. Conclusion: A single-frame method aided Kalman filtering algorithm based double covariance matching rule is presented in this paper. First, the measurement noise covariance matching is introduced using the SVD method that processes the R-adaptation inherently for the filtering stage. Second, the system noise covariance matching is described so as to have double covariance matching at the same time during the estimation procedure. The SVD-Aided AEKF becomes R- and Q-adaptive simultaneously by applying the Q-adaptation rule to the intrinsically R-adaptive SVD-aided EKF.

Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking

The point cloud based 3D single object tracking has drawn increasing attention. Although many breakthroughs have been achieved, we also reveal two severe issues. By extensive analysis, we find the prediction manner of current approaches is non-robust, i.e., exposing a misalignment gap between prediction score and actually localization accuracy. Another issue is the sparse point returns will damage the feature matching procedure of the SOT task. Based on these insights, we introduce two novel modules, i.e., Adaptive Refine Prediction (ARP) and Target Knowledge Transfer (TKT), to tackle them, respectively. To this end, we first design a strong pipeline to extract discriminative features and conduct the matching with the attention mechanism. Then, ARP module is proposed to tackle the misalignment issue by aggregating all predicted candidates with valuable clues. Finally, TKT module is designed to effectively overcome incomplete point cloud due to sparse and occlusion issues. We call our overall framework PCET. By conducting extensive experiments on the KITTI and Waymo Open Dataset, our model achieves state-of-the-art performance while maintaining a lower computational cost.