Comment on “Optimal Contract to Induce Continued Effort”

2021 ◽  
Author(s):  
Ping Cao ◽  
Feng Tian ◽  
Peng Sun
Keyword(s):  
Decision Analysis ◽  
Numerical Study ◽  
Model Parameters ◽  
Optimal Contract ◽  
Discount Rates ◽  
Optimal Contracts ◽  
Relative Improvement ◽  
Wide Range ◽  
Contract Structure ◽  
Random Termination

In this comment, we first use a counterexample to demonstrate that the optimal contract structure proposed in section 4 of Sun and Tian (2018) can be wrong when the two players’ discount rates are different. We then specify correct optimal contract structures, which involve generalizing the contract space to allow random termination. Numerical study with a wide range of model parameters illustrates that such a random termination only occurs sparingly in optimal contracts. Moreover, the suboptimality gap, measured by the relative improvement of the optimal contract over the best contract without random termination, is extremely small. This paper was accepted by Manel Baucells, decision analysis.

scholarly journals Strain Sensor via Wood Anomalies in 2D Dielectric Array

Nanomaterials ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1022
Author(s):  
Rashid G. Bikbaev ◽  
Ivan V. Timofeev ◽  
Vasiliy F. Shabanov
Keyword(s):  
Higher Plants ◽  
Numerical Study ◽  
Reciprocal Lattice ◽  
Strain Sensing ◽  
Photonic Materials ◽  
Sensing Applications ◽  
Wide Range ◽  
Sensor Structure ◽  
Optical Behavior ◽  
Chlorophyll Absorption

Optical sensing is one of many promising applications for all-dielectric photonic materials. Herein, we present an analytical and numerical study on the strain-responsive spectral properties of a bioinspired sensor. The sensor structure contains a two-dimensional periodic array of dielectric nanodisks to mimic the optical behavior of grana lamellae inside chloroplasts. To accumulate a noticeable response, we exploit the collective optical mode in grana ensemble. In higher plants, such a mode appears as Wood’s anomaly near the chlorophyll absorption line to control the photosynthesis rate. The resonance is shown persistent against moderate biological disorder and deformation. Under the stretching or compression of a symmetric structure, the mode splits into a couple of polarized modes. The frequency difference is accurately detected. It depends on the stretch coefficient almost linearly providing easy calibration of the strain-sensing device. The sensitivity of the considered structure remains at 5 nm/% in a wide range of strain. The influence of the stretching coefficient on the length of the reciprocal lattice vectors, as well as on the angle between them, is taken into account. This adaptive phenomenon is suggested for sensing applications in biomimetic optical nanomaterials.

scholarly journals Inferring Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 457-467 ◽  
Author(s):  
Z W Luo ◽  
S H Tao ◽  
Z-B Zeng
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Random Mating ◽  
Natural Populations ◽  
Polymorphic Marker ◽  
Marker Locus ◽  
Model Parameters ◽  
Phenotypic Variance ◽  
Wide Range ◽  
Trait Locus

Abstract Three approaches are proposed in this study for detecting or estimating linkage disequilibrium between a polymorphic marker locus and a locus affecting quantitative genetic variation using the sample from random mating populations. It is shown that the disequilibrium over a wide range of circumstances may be detected with a power of 80% by using phenotypic records and marker genotypes of a few hundred individuals. Comparison of ANOVA and regression methods in this article to the transmission disequilibrium test (TDT) shows that, given the genetic variance explained by the trait locus, the power of TDT depends on the trait allele frequency, whereas the power of ANOVA and regression analyses is relatively independent from the allelic frequency. The TDT method is more powerful when the trait allele frequency is low, but much less powerful when it is high. The likelihood analysis provides reliable estimation of the model parameters when the QTL variance is at least 10% of the phenotypic variance and the sample size of a few hundred is used. Potential use of these estimates in mapping the trait locus is also discussed.

Numerical study of geometric morphing wings of the 1303 UCAV

2021 ◽  
pp. 1-17
Author(s):  
B. Nugroho ◽  
J. Brett ◽  
B.T. Bleckly ◽  
R.C. Chin
Keyword(s):  
Flight Control ◽  
Numerical Study ◽  
Aerodynamic Characteristics ◽  
Morphing Wing ◽  
Rolling Moment ◽  
Wide Range ◽  
Morphing Wings ◽  
Wing Geometry ◽  
Lift And Drag ◽  
Wing Morphing

ABSTRACT Unmanned Combat Aerial Vehicles (UCAVs) are believed by many to be the future of aerial strike/reconnaissance capability. This belief led to the design of the UCAV 1303 by Boeing Phantom Works and the US Airforce Lab in the late 1990s. Because UCAV 1303 is expected to take on a wide range of mission roles that are risky for human pilots, it needs to be highly adaptable. Geometric morphing can provide such adaptability and allow the UCAV 1303 to optimise its physical feature mid-flight to increase the lift-to-drag ratio, manoeuvrability, cruise distance, flight control, etc. This capability is extremely beneficial since it will enable the UCAV to reconcile conflicting mission requirements (e.g. loiter and dash within the same mission). In this study, we conduct several modifications to the wing geometry of UCAV 1303 via Computational Fluid Dynamics (CFD) to analyse its aerodynamic characteristics produced by a range of different wing geometric morphs. Here we look into two specific geometric morphing wings: linear twists on one of the wings and linear twists at both wings (wash-in and washout). A baseline CFD of the UCAV 1303 without any wing morphing is validated against published wind tunnel data, before proceeding to simulate morphing wing configurations. The results show that geometric morphing wing influences the UCAV-1303 aerodynamic characteristics significantly, improving the coefficient of lift and drag, pitching moment and rolling moment.

scholarly journals A Computational Study on the Role of Parameters for Identification of Thyroid Nodules by Infrared Images (and Comparison with Real Data)

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4459
Author(s):  
José R. González ◽  
Charbel Damião ◽  
Maira Moran ◽  
Cristina A. Pantaleão ◽  
Rubens A. Cruz ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thyroid Nodules ◽  
Numerical Study ◽  
Computational Study ◽  
Internal Heat ◽  
Heat Transfer Process ◽  
The Body ◽  
Physical Parameters ◽  
Infrared Sensors ◽  
Wide Range

According to experts and medical literature, healthy thyroids and thyroids containing benign nodules tend to be less inflamed and less active than those with malignant nodules. It seems to be a consensus that malignant nodules have more blood veins and more blood circulation. This may be related to the maintenance of the nodule’s heat at a higher level compared with neighboring tissues. If the internal heat modifies the skin radiation, then it could be detected by infrared sensors. The goal of this work is the investigation of the factors that allow this detection, and the possible relation with any pattern referent to nodule malignancy. We aim to consider a wide range of factors, so a great number of numerical simulations of the heat transfer in the region under analysis, based on the Finite Element method, are performed to study the influence of each nodule and patient characteristics on the infrared sensor acquisition. To do so, the protocol for infrared thyroid examination used in our university’s hospital is simulated in the numerical study. This protocol presents two phases. In the first one, the body under observation is in steady state. In the second one, it is submitted to thermal stress (transient state). Both are simulated in order to verify if it is possible (by infrared sensors) to identify different behavior referent to malignant nodules. Moreover, when the simulation indicates possible important aspects, patients with and without similar characteristics are examined to confirm such influences. The results show that the tissues between skin and thyroid, as well as the nodule size, have an influence on superficial temperatures. Other thermal parameters of thyroid nodules show little influence on surface infrared emissions, for instance, those related to the vascularization of the nodule. All details of the physical parameters used in the simulations, characteristics of the real nodules and thermal examinations are publicly available, allowing these simulations to be compared with other types of heat transfer solutions and infrared examination protocols. Among the main contributions of this work, we highlight the simulation of the possible range of parameters, and definition of the simulation approach for mapping the used infrared protocol, promoting the investigation of a possible relation between the heat transfer process and the data obtained by infrared acquisitions.

scholarly journals Antifungal Activity of Propyl Disulfide from Neem (Azadirachta indica) in Vapor and Agar Diffusion Assays against Anthracnose Pathogens (Colletotrichum gloeosporioides and Colletotrichum acutatum) in Mango Fruit

2021 ◽  
Vol 9 (4) ◽  
pp. 839
Author(s):  
Muhammad Rafiullah Khan ◽  
Vanee Chonhenchob ◽  
Chongxing Huang ◽  
Panitee Suwanamornlert
Keyword(s):  
Antifungal Activity ◽  
Mycelial Growth ◽  
Colletotrichum Gloeosporioides ◽  
Colletotrichum Acutatum ◽  
Model Parameters ◽  
Pathogenicity Test ◽  
Agar Diffusion ◽  
Wide Range ◽  
Significant Difference ◽  
Diffusion Assay

Microorganisms causing anthracnose diseases have a medium to a high level of resistance to the existing fungicides. This study aimed to investigate neem plant extract (propyl disulfide, PD) as an alternative to the current fungicides against mango’s anthracnose. Microorganisms were isolated from decayed mango and identified as Colletotrichum gloeosporioides and Colletotrichum acutatum. Next, a pathogenicity test was conducted and after fulfilling Koch’s postulates, fungi were reisolated from these symptomatic fruits and we thus obtained pure cultures. Then, different concentrations of PD were used against these fungi in vapor and agar diffusion assays. Ethanol and distilled water were served as control treatments. PD significantly (p ≤ 0.05) inhibited more of the mycelial growth of these fungi than both controls. The antifungal activity of PD increased with increasing concentrations. The vapor diffusion assay was more effective in inhibiting the mycelial growth of these fungi than the agar diffusion assay. A good fit (R2, 0.950) of the experimental data in the Gompertz growth model and a significant difference in the model parameters, i.e., lag phase (λ), stationary phase (A) and mycelial growth rate, further showed the antifungal efficacy of PD. Therefore, PD could be the best antimicrobial compound against a wide range of microorganisms.

scholarly journals A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Karim El-Laithy ◽  
Martin Bogdan
Keyword(s):  
Reinforcement Learning ◽  
Spike Timing ◽  
Neural Representation ◽  
Model Parameters ◽  
Learning Framework ◽  
Reference Target ◽  
Wide Range ◽  
Spiking Network ◽  
Dynamic Synapses ◽  
Exclusive Or

An integration of both the Hebbian-based and reinforcement learning (RL) rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

Heat transfer characteristics of nanofluids from a sinusoidal corrugated cylinder placed in a square cavity

2021 ◽  
pp. 095440622110272
Author(s):  
Salaika Parvin ◽  
Nepal Chandra Roy ◽  
Litan Kumar Saha ◽  
Sadia Siddiqa
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Rayleigh Number ◽  
Aspect Ratio ◽  
Average Nusselt Number ◽  
Numerical Study ◽  
Heat Transfer Characteristics ◽  
Number Range ◽  
Transfer Characteristics ◽  
Wide Range

A numerical study is performed to investigate nanofluids' flow field and heat transfer characteristics between the domain bounded by a square and a wavy cylinder. The left and right walls of the cavity are at constant low temperature while its other adjacent walls are insulated. The convective phenomena take place due to the higher temperature of the inner corrugated surface. Super elliptic functions are used to transform the governing equations of the classical rectangular enclosure into a system of equations valid for concentric cylinders. The resulting equations are solved iteratively with the implicit finite difference method. Parametric results are presented in terms of streamlines, isotherms, local and average Nusselt numbers for a wide range of scaled parameters such as nanoparticles concentration, Rayleigh number, and aspect ratio. Several correlations have been deduced at the inner and outer surface of the cylinders for the average Nusselt number, which gives a good agreement when compared against the numerical results. The strength of the streamlines increases significantly due to an increase in the aspect ratio of the inner cylinder and the Rayleigh number. As the concentration of nanoparticles increases, the average Nusselt number at the internal and external cylinders becomes stronger. In addition, the average Nusselt number for the entire Rayleigh number range gets enhanced when plotted against the volume fraction of the nanofluid.

The Application of Multicriteria Decision Analysis Methods in Health Care: A Literature Review

2021 ◽  
pp. 0272989X2110190
Author(s):  
Ilyas Khan ◽  
Liliane Pintelon ◽  
Harry Martin
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Decision Analysis ◽  
Medical Devices ◽  
Hybrid Methods ◽  
Multicriteria Decision Analysis ◽  
Multicriteria Decision ◽  
Health Care Decision ◽  
Wide Range ◽  
Care Decision

Objectives The main objectives of this article are 2-fold. First, we explore the application of multicriteria decision analysis (MCDA) methods in different areas of health care, particularly the adoption of various MCDA methods across health care decision making problems. Second, we report on the publication trends on the application of MCDA methods in health care. Method PubMed was searched for literature from 1960 to 2019 in the English language. A wide range of keywords was used to retrieve relevant studies. The literature search was performed in September 2019. Articles were included only if they have reported an MCDA case in health care. Results and Conclusion The search yielded 8,318 abstracts, of which 158 fulfilled the inclusion criteria and were considered for further analysis. Hybrid methods are the most widely used methods in health care decision making problems. When it comes to single methods, analytic hierarchy process (AHP) is the most widely used method followed by TOPSIS (technique for order preference by similarity to ideal solution), multiattribute utility theory, goal programming, EVIDEM (evidence and value: impact on decision making), evidential reasoning, discrete choice experiment, and so on. Interestingly, the usage of hybrid methods has been high in recent years. AHP is most widely applied in screening and diagnosing and followed by treatment, medical devices, resource allocation, and so on. Furthermore, treatment, screening and diagnosing, medical devices, and drug development and assessment got more attention in the MCDA context. It is indicated that the application of MCDA methods to health care decision making problem is determined by the nature and complexity of the health care problem. However, guidelines and tools exist that assist in the selection of an MCDA method.

scholarly journals Modelling the Inflation and Elastic Instabilities of Rubber-Like Spherical and Cylindrical Shells Using a New Generalised Neo-Hookean Strain Energy Function

2021 ◽  
Author(s):  
Afshin Anssari-Benam ◽  
Andrea Bucchi ◽  
Giuseppe Saccomandi
Keyword(s):  
Experimental Data ◽  
Energy Function ◽  
Limit Point ◽  
Strain Energy ◽  
Cylindrical Shells ◽  
Strain Energy Function ◽  
Model Parameters ◽  
Wide Range ◽  
Cylindrical Tubes ◽  
Gent Model

AbstractThe application of a newly proposed generalised neo-Hookean strain energy function to the inflation of incompressible rubber-like spherical and cylindrical shells is demonstrated in this paper. The pressure ($P$ P ) – inflation ($\lambda $ λ or $v$ v ) relationships are derived and presented for four shells: thin- and thick-walled spherical balloons, and thin- and thick-walled cylindrical tubes. Characteristics of the inflation curves predicted by the model for the four considered shells are analysed and the critical values of the model parameters for exhibiting the limit-point instability are established. The application of the model to extant experimental datasets procured from studies across 19th to 21st century will be demonstrated, showing favourable agreement between the model and the experimental data. The capability of the model to capture the two characteristic instability phenomena in the inflation of rubber-like materials, namely the limit-point and inflation-jump instabilities, will be made evident from both the theoretical analysis and curve-fitting approaches presented in this study. A comparison with the predictions of the Gent model for the considered data is also demonstrated and is shown that our presented model provides improved fits. Given the simplicity of the model, its ability to fit a wide range of experimental data and capture both limit-point and inflation-jump instabilities, we propose the application of our model to the inflation of rubber-like materials.

scholarly journals Study on Friction in Automotive Shock Absorbers Part 1: Friction Simulation Using a Dynamic Friction Model in the Contact Zone of an FEM Model

Vehicles ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 212-232
Author(s):  
Ludwig Herzog ◽  
Klaus Augsburg
Keyword(s):  
Ride Comfort ◽  
Viscous Friction ◽  
Simulation Method ◽  
Friction Model ◽  
Model Parameters ◽  
Dynamic Friction ◽  
Friction Modeling ◽  
Shock Absorbers ◽  
Operation Conditions ◽  
Wide Range

The important change in the transition from partial to high automation is that a vehicle can drive autonomously, without active human involvement. This fact increases the current requirements regarding ride comfort and dictates new challenges for automotive shock absorbers. There exist two common types of automotive shock absorber with two friction types: The intended viscous friction dissipates the chassis vibrations, while the unwanted solid body friction is generated by the rubbing of the damper’s seals and guides during actuation. The latter so-called static friction impairs ride comfort and demands appropriate friction modeling for the control of adaptive or active suspension systems. In this article, a simulation approach is introduced to model damper friction based on the most friction-relevant parameters. Since damper friction is highly dependent on geometry, which can vary widely, three-dimensional (3D) structural FEM is used to determine the deformations of the damper parts resulting from mounting and varying operation conditions. In the respective contact zones, a dynamic friction model is applied and parameterized based on the single friction point measurements. Subsequent to the parameterization of the overall friction model with geometry data, operation conditions, material properties and friction model parameters, single friction point simulations are performed, analyzed and validated against single friction point measurements. It is shown that this simulation method allows for friction prediction with high accuracy. Consequently, its application enables a wide range of parameters relevant to damper friction to be investigated with significantly increased development efficiency.

Sign in / Sign up

Export Citation Format

Share Document