Compensation Model Research Articles

The impact of remuneration, extrinsic and intrinsic incentives on interprofessional primary care teams: results from a rapid scoping review.

High-performing primary care relies on effective interprofessional teams and provider payment arrangements. This study aims to examine the impact of provider remuneration mechanisms and intrinsic and extrinsic incentives in team-based primary care. This rapid scoping review assessed various provider payment models and incentives in team-based primary care. Statistical tests were not applicable in this review. Fee-for-service models hindered team collaboration, while salaried and quality-based compensation models enhanced collaboration. Extrinsic incentives, such as pay-for-performance programs for physicians, showed mixed impacts on outcomes. Strong organizational cultures and leadership, resources, team meetings, training, clear protocols, and professional development opportunities facilitated teamwork. Intrinsic incentives like autonomy, mastery, and social purpose improved team performance and satisfaction. This study underscores the importance of a holistic approach to designing interprofessional primary care teams. It highlights the need for implementing non-fee-for-service provider payment models and team-based pay-for-performance incentives. Investments in teams should include health human resources and leadership, training, guidelines, and professional development opportunities. Implementing a performance measurement framework for teams and regular public reporting can foster mastery. Continuous research and evaluation are crucial to optimizing teamwork and healthcare delivery in primary care settings.

A hybrid springback compensation method for geometry complexity in stamping

Abstract Springback compensation is a crucial approach to maintaining the accuracy of stamping parts with complex features. It has been challenging to determine the position of a characteristic point at the geometrical features during springback compensation. The currently available numerical approaches are not always sufficiently accurate and reliable, particularly when high-strength steels are increasingly used for lightweight structures. An enhanced hybrid method named springback path–displacement adjustment (SP-DA) method has been developed based on the well-known conventional displacement adjustment (DA) method to resolve the issue. A finite element method (FEM) model of stamping owning geometry complexity was established, and ST14F, BH300 and DP500, representing low, medium and high-strength steels, respectively, were selected for the study. Springback analyses were conducted, and the springback paths were acquired in the FEM simulation, based on which the spatial position of a node on the mesh of the compensation model was obtained using the SP-DA method. Its effectiveness was first verified numerically, and then, experiments were conducted to validate that the new SP-DA method could significantly increase the accuracy of springback compensation. Stamping of high-strength steels can benefit most from the proposed SP-DA method.

A volume compensation model for multi-resolution moving particle method simulating free-surface flow

A volume compensation model for multi-resolution moving particle method simulating free-surface flow

Barriers to Research for Academic Otologists/Neurotologists in the United States.

The physician-scientist workforce is shrinking in the United States. Academic otologists/neurotologists face a diverse set of barriers to successful careers. We aimed to characterize the factors affecting contemporary otology/neurotology surgeon-scientists. An electronic survey was distributed to faculty members of the American Neurotology Society and the American Otological Society in 2021. The survey queried demographics, practice setting, compensation, and barriers to conducting research for respondents in academic practice. One hundred fifty-seven otologists/neurotologists responded to the survey, corresponding to an overall response rate of 25%. Of the respondents, 94 were in academic practice. The median protected research time was 0.5 days/wk, whereas the mode was zero. Across academic rank, salary compensation was lower for academic surgeons with active research funding and for female academic surgeons as compared with their male counterparts. Grant-funded female academic surgeons had significantly worse compensation compared with rank-matched male surgeons with similar protected time. No grant-funded female earned more than the 30th percentile for their rank. Identified barriers to research were pressure to maintain clinical productivity, insufficient protected time, and personal/family demands. Respondents highlighted several areas for improvement: compensation for research activity, administrative support, and improved grant funding mechanisms for clinician-scientists. Otology/neurotology surgeon-scientists face barriers to research, including limited protected time, poor administrative support, increasingly competitive funding environments, and misaligned compensation models. New initiatives by the National Institute on Deafness and other Communication Disorders aim to increase the surgeon-scientist workforce, but their success may depend upon removing identified barriers at the level of academic institutions.

Low complexity neural network equalizer for nonlinearity mitigation in digital subcarrier multiplexing systems.

This article conducts a comparative study of the complexity reduction of neural network (NN) models for nonlinearity compensation used in digital subcarrier multiplexing (DSCM)-based optical communication systems. We employ the NN model based on bi-directional long short-term memory (biLSTM) and 1D-convolutional NN (1D-CNN) layers. To reduce the computation complexity of the proposed solution, weight clustering is applied to the NN. We specifically compare the performance of our proposed NN-based equalizer with traditional methods such as chromatic dispersion compensation (CDC), digital back-propagation (DBP) and alternative NN, based on triplet coefficients in perturbation analysis, proposed in previous literature, evaluating both Q-factor performance and computational complexity. Our findings show that the NN-based equalizer offers competitive Q-factor improvements while significantly reducing computational complexity, particularly when weight clustering is used. We show that the complexity of the NN can be reduced by up to 91.1% compared to the NN based on the perturbation analysis proposed in previous literature and by 31.5% compared to the DBP with 1 step per span. The results underscore the potential of NN-based approaches to deliver high-performance nonlinear compensation with lower computational demands, positioning them as a promising solution for future optical nonlinear equalizers.

The Enhancement of the Horizontal Ecological Protection Compensation Mechanism in the Yu-Lu Section of the Yellow River Basin

Horizontal ecological compensation represents a significant institutional innovation aimed at advancing ecological civilization and serves as a key functional strategy within China’s current management framework. This paper employs the horizontal ecological protection compensation agreement of the Yu-Lu section of the Yellow River Basin as a case study. Using a game theory model and theoretical analysis, the paper explores the underlying connotations, theoretical foundations, and legal characteristics of the basin’s horizontal ecological protection compensation mechanism. This analysis reveals several challenges within the existing horizontal ecological protection compensation system in the Yellow River Basin, including the predominance of a single compensation entity, unclear compensation standards, a compensation model limited to monetary transfers, and the absence of an effective dispute resolution mechanism. This paper further examines potential improvements to the horizontal ecological protection compensation framework in the Yellow River Basin from a legal system perspective, with the aim of addressing these practical challenges and fostering the region’s ecological, environmental, and economic development.

Spatial variation of land use carbon budget and zoning for carbon compensation in the Huai River Eco-economic Belt, China

Carrying out carbon budget assessment and carbon compensation zoning research from inter-regional perspective can actively boost the formulation of green, low-carbon transformation strategies, guiding the flow of compensation credits, promoting regional equity and sustainable development, and realizing China’s “dual-carbon” goal. Huai River Eco-economic Belt is considered to be a typical example of how land use affects carbon budget due to its more drastic land changes. The paper uses the carbon emission coefficient method to analyze the carbon revenue and expenditure of kinds of land-use patterns, and constructs the carbon compensation model with the help of the carbon budget concentration index and the dominant comparative advantage index, and puts forward the carbon compensation zoning program. Results indicate that (1) Carbon emissions in the Huai River Eco-economic Belt are generally showing a downward trend, and carbon absorption rises modestly. (2) Carbon emissions exhibit a spatial distribution of higher in the western, northern and eastern regions and lower in the center zone, with large differences in carbon absorption among cities in the same year. (3) Carbon compensation types in the Huai River Eco-economic belt include 7 payment zones, 5 balanced zones and 14 compensated zones, which can be finally classified into 5 categories of carbon compensation space optimization areas by combining with the Normalized Revealed Comparative Advantage Index and model for zoning of carbon compensation. Our study enriches practical approaches to reducing carbon emissions through land regulation from inter-regional scales.

Theoretical and experimental investigations of the CMOS compatible Pirani gauges with a temperature compensation model

In this article, a CMOS-compatible Pirani vacuum gauge was proposed featuring enhanced sensitivity, lower detection limit, and high-temperature stability, achieved through the implementation of a surface micromachining method coupled with a temperature compensation strategy. To improve performance, a T-type device with a 1 µm gap was fabricated resulting in an average sensitivity of 1.10 V/lgPa, which was 2.89 times larger than that (0.38 V/lgPa) of a L-type device with a 100 µm gap. Additionally, FEA simulations were conducted, analyzing the influence of heater temperature on sensitivity and the attenuation of sensitivity across varying ambient temperatures. A semi-empirical theoretical mode was derived for performance prediction, demonstrating strong alignment with experimental results, underscoring its effectiveness in compensating for sensitivity attenuation. Building on the foundation, the device’s performance under different ambient temperatures was characterized and effectively compensated in two distinct operational modes: constant temperature mode and constant temperature difference mode (the whole range temperature compensation error can be controlled within 2.5%). Finally, the short-time stability (variation level is approximately 1 mV), noise floor (Vrms=384 μV) and detection limit (0.07 Pa @1 Hz) of the device were characterized, confirming its suitability for practical implementation.

State Compensation Model in Adaptive Event-Triggered Predictive Control: A Novel Approach to Mitigating Moving Bottlenecks

Moving bottlenecks, characterized by their high frequency and unpredictability, pose significant challenges to timely response and management, often resulting in road congestion and increased risk of traffic accidents. To address these issues, this paper proposes an adaptive event-triggered variable speed limit (AET-VSL) method based on a state compensation model, which emphasizes the concept of symmetry in the optimization of multi-segment speed limits. This symmetry approach facilitates a balanced and efficient control strategy that adjusts speed limits in a way that harmonizes traffic flow across multiple road segments, reducing congestion and improving overall traffic stability. The state compensation model builds on the classical METANET traffic flow model, incorporating coordination between road segments to reduce congestion while minimizing disruptions to traffic flow stability. By dynamically adjusting speed limits using real-time traffic data, the AET-VSL method addresses fluctuations in traffic conditions and ensures adaptive control to manage bottlenecks efficiently. A simulation framework was employed to evaluate the proposed strategy across varying traffic scenarios. Results demonstrate that AET-VSL outperforms traditional methods, providing consistent improvements in traffic performance. For instance, under low-traffic-flow conditions, AET-VSL reduced waiting time (WT) by 41.36%, potential collisions (PCs) by 51.92%, and fuel consumptionfuel consumption (FC) by 34.07%. This study highlights the novelty and effectiveness of AET-VSL, offering a scalable and reliable solution for dynamic traffic management and showcasing its potential to enhance traffic safety and efficiency.

Application Research of Vision-Guided Grinding Robot for Wheel Hub Castings

The combination of vision and robotic grinding technology provides robots with “visual perception” capabilities that enable them to accurately locate the area to be ground and perform the grinding tasks efficiently. Based on the rough grinding requirements for wheel hub burrs proposed by a casting company, this paper investigates the application of a vision-guided grinding robot in treating burrs on wheel hub castings. First, through vision system calibration, the conversion from pixel coordinate system to robot base coordinate system is implemented, thus ensuring that the subsequently extracted burr point coordinates can be correctly mapped to the robot’s operational coordinate system. Next, the images of the burrs on wheel hub castings are collected and processed. All the burr points are extracted by applying image algorithms. In order to improve grinding accuracy, a height error compensation model is established to adjust the coordinates of the 2D-pixel points; the coordinate error after compensation was reduced by 58.33%. Subsequently, the compensated burr point trajectories are optimized by utilizing an intelligent optimization algorithm to generate the shortest grinding path. Through experimental analysis of the relationship between spindle speed and surface roughness, a grinding trajectory simulation model is constructed, and the simulation results are integrated into the robot system. Finally, actual wheel hub burr grinding experiments are performed to validate the effectiveness and practicality of the proposed solution.

Covert political campaigning: Mapping the scope, scale, and cost of cross-platform election influence operations

This study investigates gray areas of contemporary political campaigning from a political economy perspective. Using qualitative field and digital methods, computational methods, and economic modeling, it analyzes the scope, scale, and cost of commissioning social media influencers in the 2022 Philippine Elections across Facebook, Twitter, YouTube, and TikTok. The researchers find that there is a high demand for influencers to campaign for candidates, characterized by premium and dynamic incentives under informal and obscure arrangements. We identified 1425 influencer accounts across the four social media platforms that engage in covert political campaigning and categorized them into seven types. The cost of these influencer-led campaigns is estimated to range from USD 27M following a pay-per-post compensation model, to USD 10.9M using a retainer model. This article serves as a model for both election research and election policy by providing a modular framework that addresses knowledge gaps in various country contexts.

A review of error analysis and calibration techniques for spherical coordinate 3D laser scanners: Focus on non-instrumental and non-geometric factors

Both Terrestrial Laser Scanners (TLSs) and Metrological Laser Radars (MLRs) are typical Spherical Coordinate Laser Scanners (SCLSs), which are used for various fields requiring surface 3D scanning. TLSs are popular in historical preservation and archiving, reverse engineering, surveying geographic modeling, and digital cities, etc. MLRs, on the other hand, are primarily applied in large-scale precision measurements in industrial manufacturing due to their high accuracy in scanned 3D points. The 3D point precision of both TLSs and MLRs is affected significantly by geometric errors inside instruments. While the geometric errors of SCLSs have been reviewed in some studies, a systematic review of external non-instrumental errors and internal non-geometric errors for TLSs and MLRs is still lacking. These error sources also affect the measurement accuracy of SCLSs. This paper aims to review the quantitative and qualitative analysis of external non-instrumental errors and internal non-geometric errors in TLSs and MLRs. The external non-instrumental errors are further classified into surface properties, scanning geometry, and working environment in this review. For internal non-geometric errors, current research primarily focuses on laser signal processing but lacks studies on error mechanisms and their impact on accuracy. Most existing studies address Time-of-Flight (ToF)-based TLSs, with limited attention given to MLRs. While external factors such as scan depth and surface reflectance are well-studied, environmental factors like temperature remain underexplored. Additionally, there is insufficient research on error compensation models for external factors. Future research on MLRs may focus on several aspects. These include analyzing external non-instrument error factors qualitatively and quantitatively, developing error compensation models, studying the impact of the working environment, and evaluating uncertainty using large-scale standard objects. This review may be beneficial for understanding the research development about the non-instrumental and non-geometric errors of SCLSs.

Characterising and reassessing people-centred data governance in cities

The increasing deployment of digital infrastructures in cities highlights challenges in how people shape the conditions of data production that shape their cities and lives. As such, the need to centre data governance (DG) models around people is amplified. This paper unpacks and reassesses how people-centredness materialises at the level of DG in cities by conducting a scoping review of the literature on people-centred data governance (PCDG) in cities. Utilising twelve extraction categories framed by the conceptualisation of DG as a socio-technical system, this review synthesises identified themes and outlines six archetypes. PCDG is characterised by people-centred values; the inclusion of people as agents, beneficiaries, or enablers; the employment of mechanisms for engaging people; or the pursuit of people-centred goals. These coalesce into diverse PCDG archetypes including compensation, rights-based, civic deliberation, civic representation, data donations, and community-driven models. The paper proposes a nuanced reassessment of what constitutes PCDG, focusing on whether DG models include people in the emergent benefits of data or merely legitimise their exclusion, the extent to which embedded power dynamics reflect people’s perspectives, the extent to which participation influences decision-making, and the model’s capacity to balance power asymmetries underpinning the landscape in which it is situated.

Moving target detection based on improved Gaussian mixture model in dynamic and complex environments

AbstractRecently, background modeling has garnered significant attention for motion target detection in vision and image applications. However, most methods do not achieve satisfactory results because of the influence of background dynamics and other factors. The Gaussian mixture model (GMM) background modeling method is a popular and powerful motion background modeling technology owing to its ability to balance robustness and real‐time constraints in various practical environments. However, when the background is complex and the target moves slowly, the traditional GMM cannot accurately detect the target and is prone to misjudging the moving background as a moving target. To address the interference from complex backgrounds, this study proposes a target detection method that combines an adaptive GMM with an improved three‐frame difference method, along with an algorithm that combines grayscale statistics with an improved Phong illumination model for illumination compensation and shadow removal. The experimental results demonstrate that the improved method has better robustness, improves target detection accuracy, and reduces noise and background interference.

“Are you feeling safe?”: an investigation of psychosocial safety climate in the relations of job characteristics and employee exhaustion and engagement

Psychosocial safety climate (PSC) is defined as the corporate climate in relation to employees' perceptions of organizational policies, procedures, and practices for the protection of employee psychosocial safety and well-being. The present study was based on the Demand-Induced Strain Compensation (DISC) Model and proposed that the interplay between identical job demands and resources would be conditioned by PSC. Particularly, high levels of PSC would enable employees to optimally perceive and utilize more job resources in dealing with corresponding job demands. A study was conducted among 406 Chinese workers from various occupational sectors. The findings of hierarchical regression analyses suggested that PSC a) mitigates the negative relation between emotional resources and exhaustion, b) enhances the positive relation between emotional resources and work engagement, and c) mitigates the negative relation between emotional demands and work engagement. We also found that PSC is a compensatory factor for low cognitive resources and demands encouraging high work engagement. Although we did not find the proposed three-way interactions, the present findings support the idea that high PSC is a fundamental contextual factor conducive to workers' health and well-being, especially in perceiving and obtaining emotional resources.

Compensation Study of Vascular Surgeons in the United States.

The Society for Vascular Surgery (SVS) partnered with Phairify, Inc, an organization with experience in physician compensation data compilation for several other medical specialties, to survey its membership and assess factors influencing vascular surgeon compensation. The SVS Compensation Study Task Force developed a vascular surgery-specific survey between January 2023 and May 2023 including experience level, academic rank, bonuses, incentives, gender, race, ethnicity, geography, on-call pay, and other factors influencing overall reimbursement. After a soft launch on May 1, 2023, with an initial phase of SVS leadership engagement in completion, the survey was formally introduced to the SVS membership on June 14, 2023. Data were collected from May 1, 2023, to December 21, 2023. The survey was intended to focus on total compensation as well as its components. Mean compensation was analyzed based on respondent demographic characteristics. Of the 3200 active vascular surgery members of the SVS who were invited to participate in the survey, 708 (22%) completed the survey. The respondents were predominantly men (80%, 564) and white (57%, 403) with relatively equal distribution across regions of the United States. Forty-one percent (292) of vascular surgeons had an academic affiliation. Most respondents (85%, 605) work more than 50 hours per week with 13% (92) reporting working more than 80 hours. The vast majority (93%, 660/708) of vascular surgeons took first call for vascular issues at their institutions, of which 64% (422/660) were on call on average 1 in 4 weekday nights and weekends. Most respondents (80%, 545/682) were not paid for primary call separate from their salary. Although there was no difference between white and non-white respondents, the median total compensation for women was less than men ($475,500 vs. $576,000, p < 0.001). Male gender, years in practice, and being in a practice not owned or run by an academic institution were associated with higher compensation based on multivariate linear regression with ranked transfer of data to normalize values. There was no association between compensation and reported number of hours worked per week. This study highlights vascular surgery specialty-specific compensation models in a variety of practice settings and career levels with greater detail beyond those seen in traditional models. These data can be a useful tool for vascular surgeons when assessing compensation plans from potential employers and may help achieve greater pay equity and workforce diversity.

On-machine separation and compensation of target mirror's surface shape errors in multidimensional interferometric measurement system.

In multi-dimensional nanopositioning and nanomeasuring devices, interference measurement is widely used. The three-dimensional (3D) target mirror serves as the spatial reference plane to achieve multidimensional interference measurements. However, the surface shape errors of the target mirror are superimposed on the geometric dimensions of the measured workpiece, which limits the system's overall measurement accuracy. This paper proposes a method for on-machine separation and compensation of the target mirror's surface shape errors based on the micro-nano-coordinate measuring machine (MNCMM) that employs interference measurement. This method provides the model for the separation and compensation of the surface shape errors. The MNCMM employs a home-made resonant probe and a reference flat crystal to achieve the separation experiment. Subsequently, an interpolation algorithm is used to compensate for the surface shape errors at any point in space according to the compensation model. By comparing the flatness measurement results of a standard flat crystal with a flatness of 50nm before and after compensation, the flatness is reduced from 175 to 77nm. It demonstrates the reliability of the method. This method can be widely applied to on-machine compensation for surface shape errors in multidimensional interference measurement systems.

A Critical Exploration of Tipping Practices in the American Hospitality Landscape from a Qualitative Approach

ABSTRACT This study provides a comprehensive analysis of tipping practices within the U.S. restaurant industry, integrating historical context, consumer experiences, and the impact of technological advancements. Utilizing a qualitative dataset via in-depth interviews with restaurant consumers, this study examines the complex nature of tipping, navigating its dual role as a voluntary gesture and a social norm. Thematic analysis via Latent Dirichlet Allocation reveals key themes such as the service-tipping relationship, customer interactions with touchscreen payment systems, cultural and economic factors, and the impact of the COVID-19 pandemic on both employees and customers. Network analysis and sentiment analysis further illuminate the intricacies of consumer behavior and attitudes toward tipping. Our findings underscore the necessity for a balanced approach to technological innovation in the service industry and advocate for a reevaluation of compensation models and labor practices. This research contributes to the academic discourse on tipping, offers actionable insights for the hospitality industry, and fosters dialogue toward a more equitable, transparent, and sustainable tipping culture.

A Compensated Clock: Temperature and Nutritional Compensation Mechanisms Across Circadian Systems.

Circadian rhythms are ∼24-h biological oscillations that enable organisms to anticipate daily environmental cycles, so that they may designate appropriate day/night functions that align with these changes. The molecular clock in animals and fungi consists of a transcription-translation feedback loop, the plant clock is comprised of multiple interlocking feedback-loops, and the cyanobacterial clock is driven by a phosphorylation cycle involving three main proteins. Despite the divergent core clock mechanisms across these systems, all circadian clocks are able to buffer period length against changes in the ambient growth environment, such as temperature and nutrients. This defining capability, termed compensation, is critical to proper timekeeping, yet the underlying mechanism(s) remain elusive. Here we examine the known players in, and the current models for, compensation across five circadian systems. While compensation models across these systems are not yet unified, common themes exist across them, including regulation via temperature-dependent changes in post-translational modifications.

A Motion Compensation Method for Terahertz SAR Imaging with a Large Squint

Terahertz-band squint synthetic aperture radars (SARs) can obtain high-resolution images and have application potential in airborne radar systems. However, airborne radars usually have a large squint, which has led to traditional SAR algorithms no longer being applicable to airborne SARs. Additionally, terahertz radar imaging systems are more susceptible to the error induced by the platform’s motion. This paper proposes a motion compensation method for terahertz SAR imaging with a large squint angle. First, the signal model of motion compensation is derived, and the processing flow of imaging and motion compensation is detailed. Second, some simulations and experiments are conducted, and the results are reported. The results indicate that the proposed method can effectively correct the motion errors, and the signal model and processing flow are verified.