Cellular-Automata Based Qualitative Simulation for Nonprofit Group Behavior

A cellular automata based qualitative simulation of group behavior (referred hitherto as \'loyalty to group\') will be presented by integrating QSIM (Qualitative SIMulation) and CA (Cellular Automata) modeling. First, we provide a breakdown of the structure of a group and offer an analysis of how this structure impacts behavior. The characteristics and impact had by anomalies within a group and by environmental factors are also explored. Second, we explore the transition between cause and effect (referred hitherto as the \'transition rule\') and the change in behavior that is the result of this transition (referred hitherto as the \'successor behavior state\'). A filter for weeding out anomalies is then proposed. The simulation engine is then used integrating all relevant data as outlined above. A concept referred to as the \'Loyalty-cost equilibrium\' is presented and factored into the filter. Third, the validity of this method is tested by running the simulation using eight generalized examples. The input-output of each simulation run using these examples is consistent with what can reasonably be accepted to be true, thus demonstrating that the proposed method is valid. At this point we illustrate how the simulation is applied in context. Simulation outputs (effect on group behavior) at each time stage of two alternating changes in policy are compared to determine which policy would be the most advantageous. This demonstrates that this method serves as reliable virtual tool in the decision making difficulties of group management.Cellular Automata; Qualitative Simulation; Group Behavior; Loyalty-Cost Equilibrium; Loyalty Gravitation; Cost Gravitation

Controlling the simultaneous production of laccase and lignin peroxidase from Streptomyces cinnamomensis by medium formulation

Abstract Background Use of crude ligninase of bacterial origin is one of the most promising ways to improve the practical biodegradation of lignocellulosic biomass. However, lignin is composed of diverse monolignols with different abundance levels in different plant biomass and requires different proportions of ligninase to realize efficient degradation. To improve activity and reduce cost, the simultaneous submerged fermentation of laccase and lignin peroxidase (LiP) from a new bacterial strain, Streptomyces cinnamomensis, was studied by adopting formulation design, principal component analysis, regression analysis and unconstrained mathematical programming. Results The activities of laccase and LiP from S. cinnamomensis cultured with the optimal medium formulations were improved to be five to eight folders of their initial activities, and the measured laccase:LiP activity ratios reached 0.1, 0.4 and 1.7 when cultured on medium with formulations designed to produce laccase:LiP complexes with theoretical laccase:LiP activity ratios of 0.05 to 0.1, 0.5 to 1 and 1.1 to 2. Conclusion Both the laccase and LiP activities and also the activity ratio of laccase to LiP could be controlled by the medium formulation as designed. Using a crude laccase-LiP complex with a specially designed laccase:LiP activity ratio has the potential to improve the degradation of various plant lignins composed of diverse monolignols with different abundance levels.</p

A game-theoretic analysis of social responsibility conduct in two-echelon supply chains

This research investigates how two supply chain members, a downstream firm (F) and an upstream supplier (S), interact with each other with respect to corporate social responsibility (CSR) behavior and what impact exogenous parameters may have on this interaction. A game-theoretic analysis is conducted to obtain equilibriums for both simultaneous-move and sequential-move CSR games. Under certain assumptions, it is concluded that (1) there exists a mutual incentive between their CSR behavior, whereby a win–win performance in terms of both CSR and profitability is achieved as long as exogenous parameters exceed certain critical thresholds; (2) a higher consumer marginal social-benefit potential (MSBP) or a lower consumer marginal perception difficulty (MPD) helps to lower the critical thresholds of CSR budgets and CSR operational efficiency by S and F, making it easier to achieve the win–win performance; (3) an increase in one supply chain member\u27s CSR budget or CSR operational efficiency tends to make the supply chain easier to attain a win–win performance scenario; (4) if CSR decisions are made sequentially, a prior commitment to CSR activities from one supply chain member strengthens the mutual incentive and facilitates the realization of the win–win performance. Business implications of these research findings are also discussed

Social responsibility allocation in two-echelon supply chains: Insights from wholesale price contracts

Corporate social responsibility (CSR) is considered in a two-echelon supply chain consisting of an upstream supplier and a downstream firm that are bound by a wholesale price contract. CSR performance (the outcome of CSR conduct) of the whole supply chain is gauged by a global variable and the associated cost of achieving this CSR performance is only incurred by the supplier with an expectation of being shared with the downstream firm via the wholesale price contract. As such, the key issue is to determine who should be allocated as the responsibility holder with the right of offering the contract and how this right should be appropriately restricted. Game-theoretical analyses are carried out on six games, resulting from different interaction schemes between the supplier and the firm, to derive their corresponding equilibriums. Comparative institutional analyses are then conducted to determine the optimal social responsibility allocation based on both economic and CSR performance criteria. Main results are furnished in a series of propositions and their implications to the real-world business practice are discussed. The key findings are threefold: under the current model settings: (1) the optimal allocation scheme is to assign the supplier as the responsibility holder with appropriate restrictions on the corresponding rights to determine the wholesale price; (2) inherent conflict exists between the economic and CSR performance criteria and, hence, the two maxima cannot be achieved simultaneously; and (3) although integrative channel profit is not attainable, the system-wide profit will be improved by implementing optimal social responsibility allocation schemes

Production costs, scope economies, and multi-client outsourcing under quantity competition

Two game models are developed based on production costs and scope economies to investigate the widely observed multi-client outsourcing (MCO) phenomenon. Analytical results demonstrate that outsourcers’ high in-house production costs and the advantage of scope economies motivate firms to outsource collectively to an independent vendor. Under certain conditions, if both firms make their outsourcing decisions simultaneously, collective outsourcing is one of the two equilibria; if both firms make decisions sequentially, collective outsourcing becomes the unique equilibrium. Furthermore, the comparative statics of the critical degree of scope economies are examined for the occurrence of MCO with regard to diverse market parameters. Finally, it is proved that market prices decrease as the degree of scope economies increases when MCO occurs. This research helps explain some widely observed phenomena such as malls, supply chain cities, and the China price

Land Acquisition, Labor Allocation, and Income Growth of Farm Households

This article investigates how land acquisition during urbanization affects labor allocation decisions of farm households in China. We develop an agricultural household model by including land acquisition to examine its impacts on nonfarm labor participation and income. Two data sets (self-designed household surveys at Xingwen County in 2012 and the China Household Finance Survey (CHFS) data covering 29 provinces in 2013) are adopted for empirical analysis. The results find that land reduction has significantly positive effects on the probability and the share of family nonfarm labor allocation from both data sets. We also find that land acquisition increases the household income of the land acquisition group in CHFS data

MPI-Flow: Learning Realistic Optical Flow with Multiplane Images

The accuracy of learning-based optical flow estimation models heavily relies on the realism of the training datasets. Current approaches for generating such datasets either employ synthetic data or generate images with limited realism. However, the domain gap of these data with real-world scenes constrains the generalization of the trained model to real-world applications. To address this issue, we investigate generating realistic optical flow datasets from real-world images. Firstly, to generate highly realistic new images, we construct a layered depth representation, known as multiplane images (MPI), from single-view images. This allows us to generate novel view images that are highly realistic. To generate optical flow maps that correspond accurately to the new image, we calculate the optical flows of each plane using the camera matrix and plane depths. We then project these layered optical flows into the output optical flow map with volume rendering. Secondly, to ensure the realism of motion, we present an independent object motion module that can separate the camera and dynamic object motion in MPI. This module addresses the deficiency in MPI-based single-view methods, where optical flow is generated only by camera motion and does not account for any object movement. We additionally devise a depth-aware inpainting module to merge new images with dynamic objects and address unnatural motion occlusions. We show the superior performance of our method through extensive experiments on real-world datasets. Moreover, our approach achieves state-of-the-art performance in both unsupervised and supervised training of learning-based models. The code will be made publicly available at: \url{https://github.com/Sharpiless/MPI-Flow}.Comment: Accepted to ICCV202

Is endovascular treatment with multilayer flow modulator stent insertion a safe alternative to open surgery for high-risk patients with thoracoabdominal aortic aneurysm?

A best evidence topic in cardiothoracic and vascular surgery was written according to a structured protocol. The question addressed was whether endovascular treatment with multilayer flow modulator stents (MFMS) can be considered a safe alternative to open surgery for high-risk patients with thoracoabdominal aortic aneurysm (TAAA). Altogether 27 papers were identified using the reported search, of which 11 represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes, results, and study limitations are tabulated. The outcomes of interest were all-cause survival, aneurysm-related survival, branch vessel patency and major adverse events. Aneurysm-related survival exceeded 78% in almost all studies, with the exception of one where the MFMS was inserted outside the instructions for use. In that study the aneurysm-related survival was 28.9%. The branch vessel patency was higher than 95% in 10 studies and not reported in one. At 12-month follow-up, several studies showed a low incidence of major adverse events, including stroke, paraplegia and aneurysm rupture. We conclude that MFMS represent a suitable and safe treatment for high-risk patients with TAAA maintaining branch vessel patency when used within their instructions for use. However, a number of limitations must be considered when interpreting this evidence, particularly the complete lack of randomised controlled trials (RCTs), short follow-up in all studies, and heterogeneity of the pathologies among the different populations studied. Further innovative developments are needed to improve MFMS safety, expand their instructions for use, and enhance their efficacy