Target Response Research Articles

EXPRESS: Eye on Context: Individual Differences Reveal the Mechanisms of Statistical Learning.

If a searched-for target object is consistently encountered within repeating spatial distractor arrangements, target detection becomes more efficient relative to non-repeated, i.e., random arrangements (contextual-cueing effect). On the other hand, target location changes within otherwise unchanged distractor arrays substantially weaken the cueing effect. Previous studies reported substantial variations in individual participants' abilities to learn and relearn invariant contexts. Therefore, the current study examined how individual differences in attentional control and focus, as indexed by the well-established Stroop and Navon tasks, respectively, relate to contextual cueing (CC) in a learning phase/relocation phase design. During the visual search, we recorded behavioral reaction times (RTs) and fixation locations, the latter permitting us to decompose search RTs into search- and motor-related substages. We could thus evaluate the processes responsible for CC and the lack thereof after target relocation while also testing whether search and motor components of CC are different for individuals depending on their Stroop/ Navon scores. Repeated contexts yielded faster RTs (and reduced fixation numbers), though there was a substantial decrease in cueing from learning to adaptation, consistent with previous studies. Critically, contextual learning, but not relearning, varied across individuals: participants with high-Stroop interference displayed overall larger CC during early target search, while a more local Navon task bias was associated with increased CC during later processes of target response decisions. Our results demonstrate that analyzing individual differences can help validate the processes responsible for CC in search tasks, particularly distinguishing between early search and later response-related mechanisms.

Validity and Reliability of Patient Activation Measure (PAM13-I) Italian Version Among Patient Undergoing Elective Surgery.

The patient activation measure (PAM), a recognized measure of how active patients are in their care, is one of the most extensively used, widely translated, and tested instruments worldwide in measuring patient activation. This study aimed to assess the psychometric properties and construct validity of the Italian version of the 13-item Patient Activation Measure (PAM13-I) among patients undergoing elective laparoscopic cholecystectomy. A multicenter study was conducted across 111 surgical units in Italy. This study involved the preoperative administration of the PAM questionnaire to 4532 patients. The psychometric properties of the PAM were evaluated using Rasch analysis. The PAM13-I demonstrated good internal consistency (Cronbach's α = 0.95) and reliability indices. While fit statistics were acceptable, ceiling effects were observed. No significant differential item functioning was found. However, issues with targeting and local response dependency were identified. The Italian PAM-13 showed promising psychometric properties among surgical patients, indicating its potential utility in assessing patient activation. However, concerns regarding ceiling effects and targeting suggest the need for further refinement and validation in surgical populations.

A new quality assessment method for airborne SAR images using point, edge and polygon targets

ABSTRACT Accurate assessment and analysis of Synthetic Aperture Radar (SAR) image quality is essential for improving image processing and application potential. To address the limitations of traditional assessment methods that rely solely on point target response energy and consider only single-scale polygon targets, we propose an integrated method for SAR image quality assessment that combines point target energy and morphology, multi-scale edge features and integration of land use categories with multi-scale polygon targets. The assessment results indicate that airborne SAR images exhibit high spatial resolution, better than 1.5 m, with a peak signal-to-noise ratio better than −15 dB. Morphological assessments show that SAR images have morphological consistency above 0.75 and angular consistency above 0.9. With increasing wavelength, the percentage of correctly detected edge features rises from 2.55 in the Ka-band to 3.16 in the S-band. The multi-scale polygon target combined with land use categories indicates that for the same land use category, the difference is less than 0.3 dB, further demonstrating the stability and reliability of the SAR imaging system. Land use categories in cross-polarized SAR images are less affected by noise compared to co-polarized modes. The proposed method exploits the geometric compositional structures within SAR images, improving the accuracy of quality assessment..

Transsynaptic labeling and transcriptional control of zebrafish neural circuits.

Deciphering the connectome, the ensemble of synaptic connections that underlie brain function, is a central goal of neuroscience research. Here we report the in vivo mapping of connections between presynaptic and postsynaptic partners in zebrafish, by adapting the trans-Tango genetic approach that was first developed for anterograde transsynaptic tracing in Drosophila. Neural connections were visualized between synaptic partners in larval retina, brain and spinal cord and followed over development. The specificity of labeling was corroborated by functional experiments in which optogenetic activation of presynaptic spinal cord interneurons elicited responses in known motor neuronal postsynaptic targets, as measured by trans-Tango-dependent expression of a genetically encoded calcium indicator or by electrophysiology. Transsynaptic signaling through trans-Tango reveals synaptic connections in the zebrafish nervous system, providing a valuable in vivo tool to monitor and interrogate neural circuits over time.

Introducing the Response to Sponsorship Dataset: Determinants of Responses by Target States to State Sponsors of Rebel Groups

Empirical studies on the sponsorship of rebel groups have focused on understanding why and how supporter states help rebels, whether this engagement benefits the rebels, and the effects of sponsorship on the conflict outcomes. By comparison, the responses of target states to sponsorship behavior have been neglected despite the possibility of interstate crises, disputes, and conflict due to the sponsorship. This study introduces a new dataset, the Response Sponsorship Dataset (RSD), which measures target states’ responses toward state sponsors of rebel groups intending to terminate the sponsorship. The data includes information on the responses of 58 target states to 102 supporter states concerning the support of 150 rebel groups between 1991 and 2010, comprising 3719 observations. The RSD identifies diplomatic, economic, militarized, domestic, covert responses and inaction as target state responses as well as classifying them as coercive or non-coercive based on target states’ foreign policy engagements with sponsors. The RSD provides new opportunities for researchers and policymakers to analyze target responses with regards to conflict management and foreign policy as well as promising future research on support termination.

The Potential of Oncolytic Virotherapy in the Treatment of Head and Neck Cancer: A Comprehensive Review.

Head and neck cancer (HNC) represents a challenging oncological entity with significant morbidity and mortality rates. Despite advances in conventional therapies, including surgery, chemotherapy, and radiation therapy, the overall survival rates for advanced HNC remain suboptimal. In recent years, the emerging field of oncolytic virotherapy has gained attention as a promising therapeutic approach for various malignancies, including HNC. This review provides a comprehensive overview of the current understanding of oncolytic viruses (Ovs) in the context of HNC treatment, including their mechanisms of action, preclinical and clinical studies, challenges, and future directions. Future oncolytic virotherapy focuses on improving delivery and specificity through nanoparticle carriers and genetic modifications to enhance tumor targeting and immune response. Combining different OVs and integrating them with immunotherapies, such as checkpoint inhibitors, could overcome tumor resistance and improve outcomes. Personalized approaches and rigorous clinical trials are key to ensuring the safety and effectiveness of virotherapy in treating HNC.

An information-theoretic Machine Learning for upscaling and downscaling of uncertainty stochastic reservoir

This work brings together theoretical formulation and computational strategies for upscaling random heterogeneous media. In this context, heterogeneous means multiphysics models at different scales and correlated random parameters at different locations in the physical domain, such as Stokes-Brinkman flow and fractures at the microscale and heterogeneous Darcy flows at the macroscale when the target problem is hydrocarbon reservoir simulation, or a matrix with random inclusions on the rich scale and a homogeneous matrix on the poor scale when the target problem is solid mechanics. The approach uses information-theoretic machine learning methods to extract relevant probabilistic information from the rich scale and adaptively control the stochastic distance between the responses of the two scales. A goal-oriented upscaling procedure is defined to ensure equivalence between poor targets and rich scales for specific outcomes and its generalization to a multi-goal-oriented mathematically sound response, where users control distinct accuracies of specific target responses. Preliminary applications for elliptic and transient equations are presented with their respective results comparisons. Applications use a series of realizations of rich-scale parameter distributions, producing a reduced number of equivalent poor-scale realizations as required by the user's desired accuracy. The full formulation requires solving a difficult optimization problem for an extended Lagrangian formulation which is solved with a new Parallel Deterministic Annealing. The mathematical formulation is such that parallelization is done over realizations, so the overall cost of calculating stochastic upscaling is of the same order as deterministic. Furthermore, a regression with Tikhonov regularization in linear Machine Learning was used to interpolate and extrapolate data from Parallel Deterministic Annealing in order to find an optimal rich scale.

EXPERIENCES AND SENTIMENTS OF THE 1st GRADE TEACHERS ON THE CONDUCT OF SCHOOL-BASED TRAINING ON THE IMPLEMENTATION OF THE MATATAG CURRICULUM

The main objective of this study was to gathered teachers experiences and sentiments during the conduct of school-based training on the implementation of the Matatag Curriculum of all 1st Grade Teachers in the Division of Leyte – specifically in Tabango, Leyte-Leyte and Calubian Municipalities. A qualitative Research method was employed in the research, utilizing the Descriptive Phenomenology Approach in answering the objectives to ensure target responses from the participants during the interview for a substantial content of the research work conducted. Findings revealed that the experiences, challenges and sentiments encountered of the 1st Grade teachers are the following: Uncomfortable Venue and Disgruntled Foods; Readiness of the resources; time relevance and Weekend conflicts. Based on the result of the study, the selected 1st Grade teachers of the division of Leyte, is highly recommended that accommodation and time must be systematically observed, seminar trainings and sessions must be conducted during weekdays to avoid personal intervention necessities.

(Invited) Diagnosis and Prognosis for Facilitating High-Performance Lithium-Ion Batteries in Electric Vehicles

Recently, diagnosis and prognosis of state of health (SoH) for lithium-ion batteries (LIBs) have been acknowledged as a very critical factor for retaining their initial performances and optimizing them upon cycling in electric vehicle market because fast-charging and dynamic discharging environmental conditions give rise to a rapid decrease of battery performance even its trend is unstructured. Basically, materials used in LIB systems for EVs are a key determinant in determining their specific performances. Therefore, many researchers have tried to developing the various LIB-related materials in reaching high-energy-density and superior cyclic retention using doping in cathode and anodes, coating on their surfaces and grain boundaries, and building composites. Although these efforts led to opening the new era named as EVs, there are still unsolved degradation origins of the battery performance in chemical and physical points of view. To this end, advanced experimental analyses have been employed to provide a clear understanding of why the battery performance degrades during (dis)charging. Likewise, computational science based on density functional theory (DFT) calculations has been utilized to understand the fundamental reaction mechanism and to diagnose the veiled atomistic origins triggering the performance decrease, and coupling it with multiscale and multiphysics methodologies offered a more practical direction for diagnosing. Considering that a mechanism-agnostic data understanding of the battery materials detracts from its predictive speciality for target response values, in this talk, diagnosing and prognosing SoH based on understanding the materials via artificial intelligence technology are introduced with their feasibilities for high-performance of LIBs in EVs.

An inducible RIPK3-driven necroptotic system enhances cancer cell-based immunotherapy and ensures safety.

Recent progress in cancer cell-based therapies has led to effective targeting and robust immune responses against cancer. However, the inherent safety risks of using live cancer cells necessitate the creation of an optimized safety switch without hindering the efficacy of immunotherapy. The existing safety switches typically induce tolerogenic cell death, potentially leading to an immunosuppressive tumor immune microenvironment (TIME), which is counterproductive to the goals of immunotherapy. Here, we developed and characterized an inducible RIPK3-driven necroptotic system that serves as a dual function of safety switch as well as inducing immunogenic cell death which in turn stimulates antitumor immune responses. We showed that activating RIPK3 safety switch triggered immunogenic responses marked by an increased release of adenosine triphosphate (ATP) and damage-associated molecular patterns (DAMPs). Compared to other existing safety switches, incorporating RIPK3 system inhibited tumor growth, improved survival outcomes in tumor-bearing mice, and fostered long-term antitumor immunity. Moreover, RIPK3 system reinvigorated the TIME by promoting dendritic cell (DC) maturation, polarizing the macrophages towards the M1 phenotype, and reducing the exhaustion of CD4+ and CD8+ T lymphocytes. Our study highlights the dual role of RIPK3-driven necroptotic system in improving the safety and efficacy of cancer cell-based therapy, with broader implications for cellular therapies.

Empathic accuracy and interpersonal emotion regulation in close relationships.

Interpersonal emotion regulation commonly occurs in the context of close relationships. The present study examined whether accurately knowing the emotions that one's romantic partner would feel in a given situation was associated with the effectiveness of interpersonal emotion regulation attempts. One partner from 92 romantic dyads (N = 184) was randomly assigned to the role of the target, and the other was assigned to the role of the regulator. Each participant read four vignettes depicting emotion-inducing scenarios. Targets rated the emotions they would feel in each situation, whereas regulators reported how they thought their partner would feel in each situation. Targets were then asked to describe what their partner could say to help them feel good or better in each situation, using an open-ended response format. The regulators were asked to describe what they would say to their partners to help them feel good or better in each situation. Accuracy was defined as the mean difference in ratings between the regulator's estimates of their partner's emotions and their actual emotion ratings across the scenarios. Effectiveness of regulation was defined as the mean score of similarity between regulator's open-ended responses and target's open-ended responses as rated by independent coders. The results showed that empathic accuracy significantly predicted regulation effectiveness. We also found that individual differences in regulators' emotional clarity scores predicted empathic accuracy. This study sheds light on the importance of accurately perceiving a partner's emotions for effective regulation in close relationships. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

QLTI-20. BRIDGING THE GAP: UNDERSTANDING THE CURRENT TREATMENT RESPONSES TO ENHANCE THE STANDARD OF CARE AND OUTCOMES FOR MALIGNANT PERIPHERAL NERVE SHEATH TUMORS

Abstract Malignant peripheral nerve sheath tumor (MPNST) are a rare and aggressive cancer that make up 5-10% of all sarcomas. There is currently no effective targeted therapy to treat MPNST and surgical resection remains the mainstay of treatment, though often not feasible due to location, size of the tumor, or presence of metastases. Evaluation of MPNST treatment response to palliative chemotherapy regimens could serve as a reference point for target response rates in clinical trials going forward. We performed a retrospective electronic health record analysis of patients with biopsy-proven diagnoses of MPNST at Washington University and Johns Hopkins University. We evaluated tumor characteristics along with treatment response, overall survival (OS), and progression free survival (PFS) rates for different chemotherapeutic regimens. The cohort comprises 140 patients, with ages at diagnosis ranging from 21 to 40 years. Most patients had tumors located in the extremities, with sizes ranging from 5-10 cm at the time of diagnosis. We identified 66 patients who received adjuvant chemotherapy, 44 received neoadjuvant chemotherapy and 28 did not receive any chemotherapy. We will present objective response rate (ORR) and clinical benefit rate (CBR) for neoadjuvant chemotherapy. Among patients with metastatic disease (n=53), 12 chemotherapy regimens were assessed. All regimens other than gemcitabine-docetaxel chemotherapy regimen performed better than the median PFS of 1.77 months which has been observed in clinical trials of targeted agents to date with the most compelling response to vincristine-irinotecan-temozolomide regimen. Despite advancements in our understanding of MPNST pathogenesis, these tumors carry a poor prognosis. Our study has identified several systemic therapies which should be further evaluated prospectively to improve treatment options and outcomes for patients with this aggressive sarcoma. These results can serve as a benchmark for future clinical trials.

Low-velocity penetration behavior of ice by steel projectile

In this study, the penetration of a steel projectile into a semi-infinite ice target is investigated through experiment and numerical simulation. Five tests with initial impact velocity varying from 42.5 to 110 m/s are conducted. The penetrating behavior of the projectile and the dynamic response of the ice target are captured by a high-speed camera. The experimental results show that the impact velocity has great impact on the dynamic behavior and failure mode of the ice target. Under a low-speed impact, the ice target forms a crater at the impact surface. However, a penetration tunnel is formed under a high-speed impact. The crater diameter and penetration depth increase almost linearly with increasing the impact velocity. Furthermore, the numerical simulation for the tests is carried out using the continuum discontinuum element method (CDEM). The simulated penetration depth history of the projectile and the failure characteristics of the ice target agree with the experimental results, validating the numerical simulation model. It indicates that the ice crater angle keeps almost the same during a penetration. In addition, the maximum deceleration of the projectile and the maximum von Mises stress of the ice elements increase with increasing the impact velocity. These results provide the failure behavior and numerical simulation method for ice penetration, improving the understanding of dynamic fracturing mechanism of ice in engineering applications.

Resurgence in a discrete-trial procedure in rats.

Resurgence is a transient recovery of a previously extinguished target response following a worsening of reinforcement conditions for an alternative response. Laboratory studies with nonhuman animals typically assess resurgence in free-operant situations where subjects can freely emit responses. The purpose of the current study was to investigate whether resurgence would be observed in a discrete-trial procedure where only a single response could occur in each trial, using rats as subjects. The experiment consisted of three phases, and each session ended after 200 trials. All trials began with the insertion of target and alternative levers and ended once a response was emitted. In Phase 1, both target and alternative responses were reinforced with a probability of .25. In Phase 2, the target response was extinguished while still reinforcing the alternative response with a probability of .25. Finally, resurgence was tested by placing the alternative response on extinction. All rats showed robust resurgence in this highly constrained discrete-trial situation. We also found that the latencies of resurged target responses differed from those in Phase 1. Overall, the present discrete-trial procedure could produce reliable resurgence as with typical free-operant procedures and has several potential benefits for studying resurgence.

Research on combined damage characteristics of underwater armor-piercing and explosion based on supercavitating projectile

Recent studies of supercavitating projectiles primarily focus on the formation and evolution of the cavity, as well as its underwater ballistic characteristics, while neglecting the terminal damage effects. Little attention has been given to exploring the combined damage effects of armor-piercing-explosion supercavitating projectiles (APESP). Therefore, this study comparatively analyzes the response processes and failure modes of an underwater aluminum alloy cylindrical shell target under the action of three different types of loads: armor piercing, explosion, and combined armor-piercing and explosion. This study investigates the underwater combined damage mechanisms of the APESP, clarifies each damage phase under the combined effect, discusses the advantages of damage resulting from the combined armor-piercing and explosion effect based on the target responses and damage modes, and explores the reasons for dissipation of explosion energy. The results show that: the APESP combines localized point damage characteristics of armor piercing with overall surface damage features of underwater explosion. Depending on load stages and target responses, the target response process under the action of the APESP can be divided into the hydrodynamic ram phase, penetration phase, shock wave phase, stable vibration phase, and bubble pulsation phase. The entire physical system can be abstracted as a low-frequency series spring system (equivalent to bubble pulsation frequency) with high-frequency external energy input, based on the energy relationship of the medium and the structure. The concept of the 'blower effect' is proposed based on target behavior during the stable vibration phase. Following the application of different loads, the plastic deformation of the target in a stable state is ranked as: underwater explosion > combined armor-piercing and explosion > underwater armor piercing. Supercavity, shell casing and penetration hole will cause the dissipation of explosion energy.

A study of the nonlinear behaviour of the irregular Beni Haroun cable-stayed bridge to progressive seismic failure under SVGM

The progressive failure of the nonlinear irregular Cable-Stayed Bridges (CSBs) under Spatial Variability of Ground Motions (SVGM) counting seismic wave propagation, incoherence effect and site-response effect is investigated. A spectral representation method is used in order to develop a computer code. This code is used to simulate SVGM time histories to be compatible with an overall coherency function and a target response spectrum, A three-dimensional Finite Element Model (FEM) of an asymmetric bridge: the Beni Haroun cable-stayed bridge (CSB) (North Eastern Algeria) is developed in order to include the effects of the main components of SVGM on response parameters in terms of variations of absolute maximum vertical displacements and flexural moments along the deck and on height of short and tall pylons of study CSB, in particular, nonlinear bridge response quantities are examined in terms of rotational ductility demands at the ends of the short and tall piers of the bridge under all components of SVGM. The numerical results are comforted with those obtained assuming uniform seismic excitations. The analysis results reveal, among others, that the bridge responses are very sensitive to the SVGM, with site-response effects being more critical for bridge response than those of incoherence components and wave propagation. As a general trend, it is showed that the assumption of uniform excitation results in much lower ductility demands on bridges than incoherence and site SVGM components and that the latter should be considered for the seismic response assessments and progressive seismic failure studies of irregular cable-stayed bridges.

An Empirical Line approach for Agrowing Camera Aerial Images of inland waters based on exponential fit and in situ water measurements

Abstract. With the advancement of technology in the area of remote sensing, monitoring the Earth's surface using multispectral cameras attached to unmanned aerial vehicles (UAV) has become promising. However, in many Earth observation applications, it is needed to make compatible the spatial data of images captured by high spatial resolution multispectral sensors with the spectral response of targets on the Earth's surface. This relation is obtained through a radiometric calibration. The empirical line method is commonly used to calibrate the spectral bands of sensors. Thus, applications of this method using linear fit have retrieved negative values in water bodies. So that, attempting different adjustments, as well different reference targets, can solve this issue. In this study, the water quality of small bodies of water was analysed using a Agrowing multispectral camera, which derived negative values when applying linear fit. The aim of this study, therefore, was to fit a radiometric calibration based on empirical line method for Agrowing camera in inland water applications. Besides of standard reference targets, water samples also were attempted because showed a lower radiance response than the darkest (black) calibration target. Two empirical line methods were applied to convert the digital number (DN) from the Agrowing images into remote sensing reflectance (Rrs): linear and exponential. The exponential method showed to be more appropriate, with greater accuracy, unlike the linear method.

A fast-aware multi-target response prediction approach and its application in aeronautical engineering

Response prediction is a fundamental yet challenging task in aeronautical engineering, requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction (FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation, we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods, the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime (3.514 s).

Statistical Analysis of Near-surface Structure and Material Properties on Momentum Transfer in Rubble Pile Targets Impacted by Kinetic Impactors

Rubble pile asteroids consist of reassembled fragments of once larger monolithic asteroid parent bodies. Recent spacecraft missions to asteroids like Itokawa, Ryugu, Bennu, and Dimorphos suggest that rubble pile asteroids are common in the asteroid population, and rubble piles could be a likely structure among potentially hazardous objects. Therefore, it is important to understand the response of rubble pile targets to kinetic impacts for potential future deflection needs. The recent Double Asteroid Redirection Test (DART) mission motivates an investigation of kinetic impacts into rubble pile targets to understand their effects on deflection. Here, we simulate kinetic impacts into Dimorphos-sized asteroid targets to understand the effect of the impact site structure on the deflection efficiency of relevant sizes for planetary defense. We perform 52 two-dimensional simulations where we vary the impact site structure of the impact site, the target porosity, and the material behavior/strength model to understand their relative effects on crater size and the momentum enhancement factor (β). We find that the effects of the impact site on both crater size and β are greatest for impacts into weaker targets, where impact sites rich in matrix material result in statistically larger craters and higher βs compared to impact sites rich in boulder material. Further, impact site structures that promote increased boulder ejection result in larger β values. These results provide important intuition to understand the DART impact and to extrapolate results to future potential missions.

Assessment of Sentinel-6MF low resolution numerical retracker over ocean: Continuity on reference orbit and improvements

On April 7th, 2022, after 16 months of tandem flight with its predecessor, Jason-3, the Copernicus Sentinel-6 Michael Freilich (MF) satellite became the regional reference mission in the sea level climate record. Its on-board altimeter, POSeidon-4, is the first radar altimeter allowing a simultaneous and continuous acquisition in Low Resolution (LR) as well as in High Resolution (HR) mode. In March 2023, a new version of Sentinel-6MF ground segment (processing baseline F08) brought major improvements for the LR mode, with the implementation of a numerical retracker in addition to the historical Maximum Likelihood Estimator-4 (MLE4) retracker. The present work covers the full assessment of this new LR numerical retracker over open ocean, spanning from the retracker’s outputs to their contribution to the Global Mean Sea Level. Improvements with respect to MLE4 appeared mainly in terms of sea-state related effects, leading to a 60 % reduction of the Sentinel-6MF/Jason-3 Sea Surface Height Anomaly bias correlated to Significant Wave Height. Such result improves an already very good continuity between the two missions. The agreement between Jason-3 and Sentinel-6MF over the tandem phase is also precisely assessed. The small remaining discrepancies are attributed to different components of the system, such as the orbit, the radiometer wet troposphere correction, C-band processing or an MLE4-based empirical adjustment. Another important feature of the Sentinel-6MF numerical retracker is the use of the in-flight Point Target Response to mitigate instrumental changes and thus improve long term stability. The Global Mean Sea Level analysis presented in this paper shows no significant trend difference with respect to Jason-3, once the radiometer wet troposphere correction impact is removed.