Compensation Model Research Articles

Spectrum of Complex Partial Performance Disorders in Patients with Mental Illnesses

Recent research highlights a high prevalence of minimal cerebral dysfunctions (MCD) in patients with mental disorders. Nonetheless, empirical understanding of minimal cerebral dysfunctions and diffuse neuropsychological impairments in adult patients remains limited. In our study, we examined 399 patients with diverse common mental disorders on minimal cerebral dysfunctions. 329 patients were in psychosomatic rehabilitation, 40 in forensic psychiatry, and 30 in an addiction ward of a psychiatric hospital at the time of the study. Symptom patterns and anamnesis of MCD and sociodemographic characteristics of the patients were recorded using structured questionnaires. Overall, about 29% of all patients reported MCD symptoms. Patients with MCD reported greater problem burden in everyday coping (attention, arithmetic, memory, sensitivity to noise, orientation) and social interaction (outsider, excitability) than patients without partial performance disorders. Patients with mental illness reported a heterogeneous pattern of minimal cerebral dysfunctions. These frequent disorders should be recognized in diagnostics and treatment. Further studies should investigate therapeutic approaches for MCD according to Baltes' Selective Optimization and Compensation model.

Temperature error compensation method of fiber optic gyroscope based on deep learning

This work provides an error compensation strategy based on deep learning to address the temperature error of a fiber optic gyroscope (FOG). The Attention structure was used to improve the Long Short-Term Memory Network (LSTM), and the improved network was utilized to establish the prediction and compensation model of FOG error. From the two perspectives of the learning ability of the neural network and the improvement of FOG performance, this paper selects three indicators: prediction accuracy, mean square error, and FOG bias stability to comprehensively evaluate the performance of the compensation model. Through comparison, the compensation effect is significantly enhanced.

Are Orthopaedic Trauma Surgeons Appropriately Compensated for Treating Acetabular Fractures? An Analysis of Operative Times and Relative Value Units.

To evaluate the work relative value units (RVUs) attributed per minute of operative time (wRVU/min) in fixation of acetabular fractures, evaluate surgical factors that influence wRVU/min, and compare wRVU/min with other procedures. Retrospective. Level 1 academic center. Two hundred fifty-one operative acetabular fractures (62 A, B, C) from 2015 to 2021. Work relative value unit per minute of operative time for each acetabular current procedural terminology (CPT) code. Surgical approach, patient positioning, total room time, and surgeon experience were collected. Comparison wRVU/min were collected from the literature. The mean wRVU per surgical minute for each CPT code was (1) CPT 27226 (isolated wall fracture): 0.091 wRVU/min, (2) CPT 27227 (isolated column or transverse fracture): 0.120 wRVU/min, and (3) CPT 27228 (associated fracture types): 0.120 wRVU/min. Of fractures with single approaches, anterior approaches generated the least wRVU/min (0.091 wRVU/min, P = 0.0001). Average nonsurgical room time was 82.1 minutes. Surgeon experience ranged from 3 to 26 years with operative time decreasing as surgeon experience increased ( P = 0.03). As a comparison, the wRVU/min for primary and revision hip arthroplasty have been reported as 0.26 and 0.249 wRVU/min, respectively. The wRVUs allocated per minute of operative time for acetabular fractures is less than half of other reported hip procedures and lowest for isolated wall fractures. There was a significant amount of nonsurgical room time that should be accounted for in compensation models. This information should be used to ensure that orthopaedic trauma surgeons are being appropriately supported for managing these fractures. Economic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Research on Power Balance Control Method of Electronic Transformer

Aiming at the problem of poor output stability and power gain of the power electronic transformer of the microgrid energy storage system, a power balance control method for the power electronic transformer of the microgrid energy storage system based on parallel modular multi-level commutation control is proposed. The reactive power outer loop parameter fusion method is used to sample the power dynamic load parameters and information fusion processing for the transformers in the system. According to the static limit active power adjustment of the fuzzy parameter factors on the output voltage side of the DC port, the steady-state gain of the power electronic transformer of the microgrid energy storage system is calculated. The static current limiting adjustment method is used to construct the feedback compensation model of the power electronic transformer of the microgrid energy storage system. In the active power control loop, the optimal design of the power electronic transformer power balance control of the microgrid energy storage system is realized through transient stable power adjustment. The test results show that using this method to perform power balance control on the power electronic transformer of the microgrid energy storage system has high output stability and good active power balance, which improves the robustness and adaptability of the transformer balance control.

Dual-Loop Integral Sliding Mode Control-Based Path Tracking with Reaction Torque for Autonomous Underwater Vehicle

Path tracking control is an important method for a Six-Degree-Of-Freedom Autonomous Underwater Vehicle to perform specific underwater tasks. Therefore, this paper investigates a dual-loop integral sliding mode control (DLISMC)-based tracking controller for an AUV with model uncertainties and external disturbances, and introduces a new reaction torque model for static compensation in order to improve the attitude control capability for AUVs when performing path tracking. In addition, the stability of tracking control law based on DLISMC is demonstrated using the Lyapunov function. Finally, numerical simulations are carried out on MATLAB 2016/Simulink and compared with the Proportion–Integral–Differential (PID) control commonly used in industry as well as the dual-loop Proportion–Integral–Differential (DLPID). Simulation results show that the DLISMC has a smaller tracking error, faster convergence speed, and more robustness against external disturbances and reaction torque.

Effect of LULC Changes on Annual Water Yield in the Urban Section of the Chili River, Arequipa, Using the InVEST Model

Arequipa is a semi-desert city located in southern Peru which depends on the Chili River as its only water source. During recent years, this city has increased its number of inhabitants significantly as a result of internal migratory flows and population growth. Because of this, the city has undergone a rapid urbanization process which has increased the urban areas near the river and caused the destruction of agricultural areas, as well as their native vegetation. This change in land use can be quantified through satellite image analysis across many years, but as noted, there are no studies on its impact on water yield (WY) in the urban section of the river. Now, by using the Integrated Valuation of Ecosystem Services and Compensation (InVEST) model, which allows the WY of the study area to be evaluated in millimeters and cubic meters by introducing a series of variables, such as precipitation, reference evapotranspiration and types of land use classes, among others, it is possible to determine that the WY from the study area was 1,743,414 m3 in 1984 and 1,323,792 m3 in 2022; the urban area is the type of land use with the highest increase with respect to its percentage contribution to the WY, going from 30.43% to 49.62% between 1984 and 2022, respectively. The increase in urban area mitigated the loss of total WY, explained by a higher percentage runoff rate, surface flow and drainage problems in the study area.

Proxy-Based Sliding Mode Force Control for Compliant Grinding via Diagonal Recurrent Neural Network and Prandtl-Ishlinskii Hysteresis Compensation Model

Traditional industrial robots often face challenges in achieving a perfectly polished surface on a workpiece because of their high mechanical rigidity. The active compliance force control device installed at the robotic arm’s end enables high-precision contact force control between the grinding tool and the workpiece. However, the complex hysteresis nonlinearity between cylinder air pressure and output force, as well as various random disturbances during the grinding process, can affect the accuracy of the contact force and potentially impact the grinding effect of the workpiece, even causing irreversible damage to the surface of the workpiece. Given the complex random variation of cylinder output force in the actual grinding process, a rate-dependent hysteresis model based on diagonal recurrent neural network and Pradtl–Ishlinskii models named dRNN-PI is designed to compensate for the complex nonlinear hysteresis of the cylinder and calculate the desired air pressure to maintain a steady contact force on the workpiece. The proxy-based sliding mode control (PSMC) is utilized to quickly track the desired air pressure without overshooting. This paper also proves the controller’s stability using the Lyapunov-based methods. Finally, the accuracy of the proposed hysteresis compensation model and the effectiveness and robustness of the PSMC are verified by experiment results.

Future directions for patient engagement in research: a participatory workshop with Canadian patient partners and academic researchers

BackgroundPatient engagement in research (also commonly referred to as patient or patient and public involvement in research) strives to transform health research wherein patients (including caregivers and the public) are regularly and actively engaged as multidisciplinary research team members (i.e. patient partners) working jointly towards improved health outcomes and an enhanced healthcare system. To support its mindful evolution into a staple of health research, this participatory study aimed to identify future directions for Canadian patient engagement in research and discusses its findings in the context of the international literature.MethodsThe study met its aim through a multi-meeting pan-Canadian virtual workshop. Participants (n = 30) included Strategy for Patient-Oriented Research-funded academic researchers and patient partners identified through a publicly available database, personal and professional networks and social media. All spoke English, could access the workshop virtually, and provided written informed consent. The workshop was composed of four, 1.5–3-h virtual meetings wherein participants discussed the current and preferred future states of Canadian patient engagement in research. Workshop discussions (i.e. data) were video and audio recorded. Themes were generated through an iterative process of inductive thematic analysis that occurred concurrently with the multi-week workshop.ResultsOur participatory and iterative process identified 10 targetable areas of focus for the future of Canadian patient engagement in research. Five were categorized as system-level (systemic integration; academic culture; engagement networks; funding models; compensation models), one as researcher-level (engagement processes), and four crossed both levels (awareness; diversity and recruitment; training, tools and education; evaluation and impact). System level targetable areas called for reshaping the patient engagement ecosystem to create a legitimized and supportive space for patient engagement to be a staple component of a learning health system. Researcher level targetable areas called for academic researchers and patient partners to collaboratively generate evidence and apply knowledge to inform values and behaviours necessary to foster and sustain supportive health research spaces that are accessible to all.ConclusionsFuture directions for Canadian patient engagement in research span 10 interconnected targetable areas that require strong leadership and joint action between patient partners, academic researchers, and health and research institutions if patient engagement is to become a ubiquitous component of a learning health system.

Reference Values for Water-Specific T1 of the Liver at 3 T: T2*-Compensation and the Confounding Effects of Fat.

T1 mapping of the liver is confounded by the presence of fat. Multiparametric T1 mapping combines fat-water separation with T1-weighting to enable imaging of water-specific T1 (T1Water), proton density fat fraction (PDFF), and T2* values. However, normative T1Water values in the liver and its dependence on age/sex is unknown. Determine normative values for T1Water in the liver with comparison to MOLLI and evaluate a T2*-compensation approach to reduce T1 variability. Prospective observational; phantoms. One hundred twenty-four controls (56 male, 18-75 years), 50 patients at-risk for liver disease (18 male, 30-76 years). 2.89 T; Saturation-recovery chemical-shift encoded T1 Mapping (SR-CSE); MOLLI. SR-CSE provided T1Water measurements, PDFF and T2* values in the liver across three slices in 6 seconds. These were compared with MOLLI T1 values. A new T2*-compensation approach to reduce T1 variability was evaluated test/re-test reproducibility. Linear regression, ANCOVA, t-test, Bland and Altman, intraclass correlation coefficient (ICC). P < 0.05 was considered statistically significant. Liver T1 values were significantly higher in healthy females (F) than males (M) for both SR-CSE (F-973 ± 78 msec, M-930 ± 72 msec) and MOLLI (F-802 ± 55 msec, M-759 ± 69 msec). T1 values were negatively correlated with age, with similar sex- and age-dependencies observed in T2*. The T2*-compensation model reduced the variability of T1 values by half and removed sex- and age-differences (SR-CSE: F-946 ± 36 msec, M-941 ± 43 msec; MOLLI: F-775 ± 35 msec, M-770 ± 35 msec). At-risk participants had elevated PDFF and T1 values, which became more distinct from the healthy cohort after T2*-compensation. MOLLI systematically underestimated liver T1 values by ~170 msec with an additional positive T1-bias from fat content (~11 msec/1% in PDFF). Reproducibility ICC values were ≥0.96 for all parameters. Liver T1Water values were lower in males and decreased with age, as observed for SR-CSE and MOLLI acquisitions. MOLLI underestimated liver T1 with an additional large positive fat-modulated T1 bias. T2*-compensation removed sex- and age-dependence in liver T1, reduced the range of healthy values and increased T1 group differences between healthy and at-risk groups. 2 TECHNICAL EFFICACY: Stage 1.

The impact of yoga on successful aging based on the selection, optimization, and compensation model in elderly women: A quasi-experimental study.

To investigate the impact of yoga on successful aging based on the selection, optimization, and compensation model in elderly women. Quasi-experimental study. Seniors' meeting points and parks and clubs for the old age pensioners of the ministry of education, ministry of healthcare, and the oil corporation in Shiraz, Iran. 68 elderly women within the age range of 60-86 years were divided into a yoga and a control group. The subjects in both groups were asked to complete the selection, optimization, and compensation model questionnaire before and after the intervention. Successful aging was measured using the selection, optimization, and compensation questionnaire. The yoga training program was implemented in 1-h sessions twice a week for eight weeks. After eight weeks of yoga training, the results showed a significant difference between the pretest and posttest successful aging total scores of the yoga group (P=.005). However, the difference between the yoga and control groups' posttest mean total scores was not significant (P=.601). Based on the results, it seems that yoga training can improve successful aging. Thus, yoga is recommended as an inexpensive and entertaining method.

A Mobile Hybrid Robot and Its Accuracy Issue in Machining of Large-Scale Structures

Accurate and efficient manufacturing of large-scale structures is an important and challenging issue. To this end, a mobile hybrid robot named CraftsRobot is designed and developed for in-situ machining the local features of large-scale structures. The mobile hybrid robot comprises a mobile vehicle, a guide rail, a two degree-of-freedom (DoF) mechanical arm, and a five-DoF light-weight parallel module. The interaction mechanism between the parallel module and the mechanical arm is disclosed to build the error prediction model. On this basis, a model predictive compensation method is proposed. In each servo cycle, the command pose of the parallel module is modified and under the effect of the interaction-induced error superimposed on the modified command pose, the parallel module will reach the target pose. The results of simulation and experiment both verify the effectiveness of the compensation model. After compensation, the mobile hybrid robot is applied to machine the features on a typical large-scale structure and the machining errors are within 0.04 mm. The experimental results show that the designed robot can machine local features of large-scale structures in situ and meet the precision requirements. Together, this study provides a novel approach to achieve accurate and efficient manufacturing of large-scale structures.

Waqf –Takaful Compensation Model: The Documentation Framework Index (DFI) towards Good Governance Practices and Sustainability of Takaful Companies in Malaysia

The concept of Waqf in Takaful refers to the distribution of Takaful contributor death compensation benefits to selected religious institutions for Waqf property. In this given context, the Waqf is established upon the contributor's death, and the compensation received by the Waqf beneficiary will be utilized for religious welfare until the culmination of time on the day of judgment. Therefore, this study focused on the level of implementation of the Waqf-Takaful Compensation Model toward good governance practices and sustainability of takaful companies, using a Documentation Framework Index (DFI) which was developed based on the data collected from 106 takaful agents who were involved directly throughout the introduction of Waqf-Takaful Compensation Scheme until 2022. It was found that 88% of Takaful Agency documented the percentage of the death compensation to participants by choice. Followed by 81% of Takaful Agency declared participants have the right to decide the percentage of the Waqf to be contributed to religious institutions and 79% of Takaful Agency restricted participants can only Waqf the percentage of death compensation not to an individual but to religious institutions. However, there are still some weaknesses in several elements of documentation and marketing of Waqf –Takaful Compensation Scheme by Takaful companies that needs some improvement. Therefore, the Waqf-Takaful Compensation Model, facilitated by the Documentation Framework Index, presents a forward-looking approach that aligns with Islamic principles based on waqf and Takaful compensation practices which promotes good governance, fosters sustainability, and contributes to the overall growth and positive impact of the Takaful industry in the country. However, successful implementation of the Waqf-Takaful Compensation Model requires collaborative efforts from various stakeholders, including regulators, Takaful operators, scholars, and the community. Adequate awareness, education, and buy-in are essential for the widespread adoption of this innovative model.

The Ideal Model of Land Procurement and Compensation for Infrastructure Development (Public Interest) Based on Pancasila

Objective: This study aims to examine and encourage the transition of the ideal model of procurement and compensation for losses that have been generalized in the form of money in the context of land acquisition for public interest or infrastructure development. This study examines the role of law in the form of regulations regulating the provision of compensation in land acquisition for infrastructure development not only limited to the form of money but justified in the form of share ownership. To ensure welfare, balance and justice that reflect the values of Pancasila, for landowners, the ideal compensation model is given in the form of share ownership to residents who release their land. While the number of shares granted can be deliberated by the parties. Method: The method used is normative juridical with a conceptual approach and a statutory approach. Results and Conclusions: From the results of the study shows that the land acquisition mechanism is carried out through land rights release institutions to meet the criteria of subjects in acquiring land acquired not through transfer of rights but based on land controlled by the state so that the consequence is to provide compensation, Thus, an ideal land acquisition model through buying and selling or exchange is not possible. The ideal model can be adopted by land banks in carrying out their activities in the future, so that land acquisition for public interest or infrastructure development can run according to government needs. Originality / Value: This research contributes to the ideal model and sustainability of land acquisition for public interest by proposing the concept of compensation using shares in response to changes in the dynamics of national land management and sustainable economic development of communities in accordance with the values of Pancasila. This research underscores the importance of political commitment in encouraging investment models and community compensation, so that the paradigm of society develops. The value of this study lies in offering new perspectives and potential solutions to the mechanism of land acquisition in the public interest.

Research on Prediction of Insurance Compensation Amount after Fire Disaster

Fire is one of the major disasters that seriously threaten public safety and social development, so it is particularly essential to predict the amount of insurance compensation after a fire. This paper predicts the number of fire occurrences from various aspects such as region, housing, and car fires based on the LSTM model. A model for predicting insurance compensation after a fire is established based on the LSTM-Poisson distribution model and factors such as average house prices. Taking the number of fire occurrences in four regions of the UK from 2001 to 2021 as a case, the fire insurance compensation model is used to predict based on the average house prices and car prices in the UK, providing a reference for insurance companies in terms of fire insurance compensation.

A Case Study of Transient and Dynamic Performance of Saturated Core Reactor Static Var Compensator

This paper presents results related to transient, dynamic and steady state response of a Saturated Core Reactor Static VAr Compensator (SCR-SVC) at regulating a real radial 230 kV transmission line supplying a low density and highly distributed load in a developing area of Brazil. The studies are carried out using a time domain computational simulator in which a comprehensive model for a given twin-triple saturated reactor compensator model was implemented to cope with the receiving end load requirements for voltage regulation. Investigations are then performed to highlight the overall system and reactive compensator behavior at the occurrence of the reactor switch on conditions, final load relief and harmonic distortions.

Analyzing the Interplay of Incentive Pay and Governance in the Boeing 737 MAX Incident: Implications for Corporate Structure and Ethics

This study delves into the relationship between incentive-based compensation models and corporate governance, focusing on the Boeing 737 MAX incident as a critical case study. It thoroughly examines data from annual reports of Boeing Company (2007–2014) and the proxy statements issued between 2008 and 2015 (Boeing Company, 2008–2015), highlighting the impact of incentive-driven decisions, particularly by Boeing’s CEO. Post-2011, the CEO’s compensation, heavily linked to a risk reduction strategy, saw a substantial increase. This strategy received backing from a compensation committee, members of which shared the CEO’s General Electric background, raising concerns about potential conflicts of interest. The research emphasizes the urgent need to reassess corporate governance norms, focusing on executive pay structures and the independence of corporate boards. The Boeing 737 MAX incident starkly warns of the dangers and ethical issues associated with misaligned incentive frameworks. The study calls for reforms to ensure corporate decisions are ethically responsible and in harmony with long-term, sustainable business practices.

Error analysis and modeling of the racetrack magnetohydrodynamic linear motion sensor

Micro-vibration measurement methods for spacecraft structures mainly include the use of an accelerometer, laser, and magnetohydrodynamic (MHD) measurement methods. The micro-vibration measurement sensor developed based on the MHD measurement method has no mechanical wear between internal components, a fast high-frequency vibration response, and strong anti-interference properties. To reduce the measurement error of the racetrack MHD linear motion sensor developed in the laboratory, this paper investigated the sensor error, analysed the error source, combined the BP neural network optimized by particle swarm optimization (PSO) with variational mode decomposition (VMD), used the VMD-PSO-BP neural network to establish the error compensation model of the racetrack MHD linear motion sensor, and combined the PSO-BP neural network with wavelet threshold de-noising (WTD). The WTD-PSO-BP and RBF neural networks were used to develop the error compensation model of the racetrack MHD linear motion sensor. Comparing the three models, the experimental results show that the VMD-PSO-BP model has the best compensation effect. The mean absolute error of the output signal of the racetrack MHD linear motion sensor compensated by the VMD-PSO-BP neural network model was 1–2 times lower than that before compensation, the signal-to-noise ratio was 10 times higher on average, and the correlation coefficient was more than 0.95.

Starting Ingine

Research methodology The data has been provided by the protagonist in the form of interviews, tables and figures. Case overview/synopsis Abdul and his team, comprising MS Finance graduates from Lahore University of Management Sciences, embarked on a transformative process that led to the inception of their startup, Ingine. Originating from a discarded idea of importing recycling machines, the team pivoted to address a significant gap in the influencer marketing industry. They envisioned a subscription-based software-as-a-service platform that streamlines interactions between influencers and businesses, emphasizing secure payment processing, messaging and feedback features. The narrative underscores the intricate connection between influencer marketing and the return on investment for small businesses, recognizing the challenge of decoding tangible financial gains. Ingine’s mission is to unravel this puzzle, optimizing small businesses’ investments in influencer marketing while navigating the complexities of crafting a competitive influencer compensation model. The team’s background, strategic considerations and commitment to fostering sustainable relationships between influencers and businesses serve as a compelling backdrop to Ingine’s entrepreneurial aspirations. Complexity academic level The case can be used in entrepreneurship and entrepreneurial finance. The case can be used in undergrad, master’s, MBA, executive MBA and short executive programs. The complexity of a case can be increased or decreased depending on the level of class, i.e. start, middle or end of the course, and the time allocation, i.e. 90 min.

Investigating Determinants of Client Psychotherapy Preference: An Analog Study.

Increased emphasis has been placed on elucidating the contribution of client variables, such as treatment preference, to optimize evidence-based practice. This analog study sought to better understand variables associated with treatment preference using a convenience sample of college students (n = 54) who read brief descriptions of three interventions for negative thoughts-defusion, noticing, and restructuring. They rated each on acceptability and practicality and completed measures of cognitive fusion, emotional distress, and experiential avoidance as possible moderating variables. Restructuring was overwhelmingly preferred and rated as more acceptable than the two alternatives by both the overall sample and a distressed subsample. Preference for defusion or noticing was not predicted by ratings of acceptability or practicality but by elevated levels of cognitive fusion and emotional distress consistent with a compensation model. Limitations of the study and its implications for further research on psychotherapy preference and its integration within evidence-based practice are discussed.

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network.

We aimed to improve the detection accuracy of laser methane sensors in expansive temperature application environments. In this paper, a large-scale dataset of the measured concentration of the sensor at different temperatures is established, and a temperature compensation model based on the ISSA-BP neural network is proposed. On the data side, a large-scale dataset of 15,810 sets of laser methane sensors with different temperatures and concentrations was established, and an Improved Isolation Forest algorithm was used to clean the large-scale data and remove the outliers in the dataset. On the modeling framework, a temperature compensation model based on the ISSA-BP neural network is proposed. The quasi-reflective learning, chameleon swarm algorithm, Lévy flight, and artificial rabbits optimization are utilized to improve the initialization of the sparrow population, explorer position, anti-predator position, and position of individual sparrows in each generation, respectively, to improve the global optimization seeking ability of the standard sparrow search algorithm. The ISSA-BP temperature compensation model far outperforms the four models, SVM, RF, BP, and PSO-BP, in model evaluation metrics such as MAE, MAPE, RMSE, and R-square for both the training and test sets. The results show that the algorithm in this paper can significantly improve the detection accuracy of the laser methane sensor under the wide temperature application environment.