Fuzzy Multi-Objective Linear Programming and Simulation Approach to the Development of Valid and Realistic Master Production Schedule

Master production schedule (MPS) plays an important role in an integrated production planning system. It converts the strategic planning defined in a production plan into the tactical operation execution. The MPS is also known as a tool for top management to control over manufacture resources and becomes input of the downstream planning levels such as material requirement planning (MRP) and capacity requirement planning (CRP). Hence, inappropriate decision on the MPS development may lead to infeasible execution, which ultimately causes poor delivery performance. One must ensure that the proposed MPS is valid and realistic for implementation before it is released to real manufacturing system. In practice, where production environment is stochastic in nature, the development of MPS is no longer simple task. The varying processing time, random event such as machine failure is just some of the underlying causes of uncertainty that may be hardly addressed at planning stage so that in the end the valid and realistic MPS is tough to be realized. The MPS creation problem becomes even more sophisticated as decision makers try to consider multi-objectives; minimizing inventory, maximizing customer satisfaction, and maximizing resource utilization. This study attempts to propose a methodology for MPS creation which is able to deal with those obstacles. This approach takes into account uncertainty and makes trade off among conflicting multi-objectives at the same time. It incorporates fuzzy multi-objective linear programming (FMOLP) and discrete event simulation (DES) for MPS development.

Chinese Internet language: A sociolinguistic analysis of adaptations of the Chinese writing system

This paper examines the adaptations of the writing system in Internet language in mainland China from a sociolinguistic perspective. A comparison is also made of the adaptations in mainland China with those that Su (2003) found in Taiwan. In Computer-Mediated Communication (CMC), writing systems are often adapted to compensate for their inherent inadequacies (such as difficulty in input). Su (2003) investigates the creative uses of the writing system on the electronic bulletin boards (BBS) of two college student organizations in Taipei, Taiwan, and identifies four popular and creative uses of the Chinese writing system: stylized English, stylized Taiwanese-accented Mandarin, stylized Taiwanese, and the recycling of a transliteration alphabet used in elementary education. According to Coupland (2001; cited in Su 2003), stylization is “the knowing deployment of culturally familiar styles and identities that are marked as deviating from those predictably associated with the current speaking context”. Within this framework and drawing on the data in previous publications on Internet language and online sources, this study identifies five types of adaptations in mainland China’s Internet language: stylized Mandarin (e.g., 漂漂 piāopiāo for 漂亮 ‘beautiful’), stylized dialect-accented Mandarin (e.g., 灰常 huīcháng for 非常 ‘very much’), stylized English (e.g., 伊妹儿 yīmèier for ‘email’), stylized initials (e.g., bt 变态 biàntài for ‘abnormal’; pk, short form for ‘player kill’), and stylized numbers (e.g., 9494 jiùshi jiùshi 就是就是 ‘that is it’). The Internet community is composed of highly mobile individuals and thus forms a weak-tie social network. According to Milroy and Milroy (1992), a social network with weak ties is often where language innovation takes place. Adaptations of the Chinese writing system in Internet language provide interesting evidence for the innovations within a weak-tie social network. Our comparison of adaptations in mainland China and Taiwan shows that, in maximizing the effectiveness and functionality of their communication, participants of Internet communication are confronted with different language resources and situations, including differences in Romanization systems, English proficiency level, and attitudes towards English usage. As argued by Milroy and Milroy (1992), a weak-tie social network model can bridge the social class and social network. In the Internet community, the degree of diversity of the stylized linguistic varieties indexes the virtual and/or social status of its participants: the more diversified one’s Internet language is, the higher is his/her virtual and/or social status.

Human intervertebral disc stiffness correlates better with the Otsu threshold computed from axial T2 map of its posterior annulus fibrosus than with clinical classifications

Degeneration of the intervertebral disc, sometimes associated with low back pain and abnormal spinal motions, represents a major health issue with high costs. A non-invasive degeneration assessment via qualitative or quantitative MRI (magnetic resonance imaging) is possible, yet, no relation between mechanical properties and T2 maps of the intervertebral disc (IVD) has been considered, albeit T2 relaxation time values quantify the degree of degeneration. Therefore, MRI scans and mechanical tests were performed on 14 human lumbar intervertebral segments freed from posterior elements and all soft tissues excluding the IVD. Degeneration was evaluated in each specimen using morphological criteria, qualitative T2 weighted images and quantitative axial T2 map data and stiffness was calculated from the load-deflection curves of in vitro compression, torsion, lateral bending and flexion/extension tests. In addition to mean T2, the OTSU threshold of T2 (TOTSU), a robust and automatic histogram-based method that computes the optimal threshold maximizing the distinction of two classes of values, was calculated for anterior, posterior, left and right regions of each annulus fibrosus (AF). While mean T2 and degeneration schemes were not related to the IVDs' mechanical properties, TOTSU computed in the posterior AF correlated significantly with those classifications as well as with all stiffness values. TOTSU should therefore be included in future degeneration grading schemes.

Multiplex Liquid Chromatography-Tandem Mass Spectrometry Assay for Simultaneous Therapeutic Drug Monitoring of Ribavirin, Boceprevir, and Telaprevir

New directly acting antivirals (DAAs) that inhibit hepatitis C virus (HCV) replication are increasingly used for the treatment of chronic hepatitis C. A marked pharmacokinetic variability and a high potential for drug-drug interactions between DAAs and numerous drug classes have been identified. In addition, ribavirin (RBV), commonly associated with hemolytic anemia, often requires dose adjustment, advocating for therapeutic drug monitoring (TDM) in patients under combined antiviral therapy. However, an assay for the simultaneous analysis of RBV and DAAs constitutes an analytical challenge because of the large differences in polarity among these drugs, ranging from hydrophilic (RBV) to highly lipophilic (telaprevir [TVR]). Moreover, TVR is characterized by erratic behavior on standard octadecyl-based reversed-phase column chromatography and must be separated from VRT-127394, its inactive C-21 epimer metabolite. We have developed a convenient assay employing simple plasma protein precipitation, followed by high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) for the simultaneous determination of levels of RBV, boceprevir, and TVR, as well as its metabolite VRT-127394, in plasma. This new, simple, rapid, and robust HPLC-MS/MS assay offers an efficient method of real-time TDM aimed at maximizing efficacy while minimizing the toxicity of antiviral therapy.

The more the merrier: Multi-species experiments in ecology

A major objective in ecology is to find general patterns, and to establish the rules and underlying mechanisms that generate those patterns. Nevertheless, most of our current insights in ecology are based on case studies of a single or few species, whereas multi-species experimental studies remain rare. We underline the power of the multi-species experimental approach for addressing general ecological questions, e. g. on species environmental responses or on patterns of among-and within-species variation. We present simulations that show that the accuracy of estimates of between-group differences is increased by maximizing the number of species rather than the number of populations or individuals per species. Thus, the more species a multi-species experiment includes, the more powerful it is. In addition, we discuss some inevitable methodological challenges of multi-species experiments. While we acknowledge the value of single-or few-species experiments, we strongly advocate the use of multi-species experiments for addressing ecological questions at a more general level.

Empowering Medical Professionals to Help Victims of Trafficking

Purpose: to provide commentary of two review articles that discuss the role of medical professionals in combating human trafficking: “Health Care Providers' Training Needs Related to Human Trafficking: Maximizing the Opportunity to Effectively Screen and Intervene” by Isaac, Solak, and Giardino, and “Human Trafficking: What is the Role of the Health Care Provider?” by Crane and Moreno. Findings: Both articles provide a good introduction and explanation of the psychosocial and medical issues faced by many trafficking victims; however, they succeed only to varying degrees in describing all the gaps in the medical system and the vital next steps forward. Conclusion: The key next steps in the fight against human trafficking include: multidisciplinary teams need to improve coordination on all forms of human maltreatment; schools for all medical professions and social work need to significantly strengthen their curriculum on diagnosing and treating human maltreatment; and groups that provide training on human trafficking should partner with other agencies and organizations that provide training on child maltreatment and domestic violence.

Influence of high-conductivity buffer composition on field-enhanced sample injection coupled to sweeping in CE

The aim of this work was to clarify the mechanism taking place in field-enhanced sample injection coupled to sweeping and micellar EKC (FESI-Sweep-MEKC), with the utilization of two acidic high-conductivity buffers (HCBs), phosphoric acid or sodium phosphate buffer, in view of maximizing sensitivity enhancements. Using cationic model compounds in acidic media, a chemometric approach and simulations with SIMUL5 were implemented. Experimental design first enabled to identify the significant factors and their potential interactions. Simulation demonstrates the formation of moving boundaries during sample injection, which originate at the initial sample/HCB and HCB/buffer discontinuities and gradually change the compositions of HCB and BGE. With sodium phosphate buffer, the HCB conductivity increased during the injection, leading to a more efficient preconcentration by staking (about 1.6 times) than with phosphoric acid alone, for which conductivity decreased during injection. For the same injection time at constant voltage, however, a lower amount of analytes was injected with sodium phosphate buffer than with phosphoric acid. Consequently sensitivity enhancements were lower for the whole FESI-Sweep-MEKC process. This is why, in order to maximize sensitivity enhancements, it is proposed to work with sodium phosphate buffer as HCB and to use constant current during sample injection.

Dopaminergic stimulation increases selfish behavior in the absence of punishment threat.

RATIONALE People often face decisions that pit self-interested behavior aimed at maximizing personal reward against normative behavior such as acting cooperatively, which benefits others. The threat of social sanctions for defying the fairness norm prevents people from behaving overly selfish. Thus, normative behavior is influenced by both seeking rewards and avoiding punishment. However, the neurochemical processes mediating the impact of these influences remain unknown. Several lines of evidence link the dopaminergic system to reward and punishment processing, respectively, but this evidence stems from studies in non-social contexts. OBJECTIVES The present study investigates dopaminergic drug effects on individuals' reward seeking and punishment avoidance in social interaction. METHODS Two-hundred one healthy male participants were randomly assigned to receive 300 mg of L-3,4-dihydroxyphenylalanine (L-DOPA) or a placebo before playing an economic bargaining game. This game involved two conditions, one in which unfair behavior could be punished and one in which unfair behavior could not be punished. RESULTS In the absence of punishment threats, L-DOPA administration led to more selfish behavior, likely mediated through an increase in reward seeking. In contrast, L-DOPA administration had no significant effect on behavior when faced with punishment threats. CONCLUSIONS The results of this study broaden the role of the dopaminergic system in reward seeking to human social interactions. We could show that even a single dose of a dopaminergic drug may bring selfish behavior to the fore, which in turn may shed new light on potential causal relationships between the dopaminergic system and norm abiding behaviors in certain clinical subpopulations.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Gut Microbiota Orchestrates Energy Homeostasis during Cold.

Microbial functions in the host physiology are a result of the microbiota-host co-evolution. We show that cold exposure leads to marked shift of the microbiota composition, referred to as cold microbiota. Transplantation of the cold microbiota to germ-free mice is sufficient to increase insulin sensitivity of the host and enable tolerance to cold partly by promoting the white fat browning, leading to increased energy expenditure and fat loss. During prolonged cold, however, the body weight loss is attenuated, caused by adaptive mechanisms maximizing caloric uptake and increasing intestinal, villi, and microvilli lengths. This increased absorptive surface is transferable with the cold microbiota, leading to altered intestinal gene expression promoting tissue remodeling and suppression of apoptosis-the effect diminished by co-transplanting the most cold-downregulated strain Akkermansia muciniphila during the cold microbiota transfer. Our results demonstrate the microbiota as a key factor orchestrating the overall energy homeostasis during increased demand.

Capital Accumulation in the Presence of Informal Credit Contracts: Does the Incentive Mechanism Work Better than Credit Rationing Under Asymmetric Information?

Credit markets with asymmetric information often prefer credit rationing as a profit maximizing device. This paper asks whether the presence of informal credit markets reduces the cost of credit rationing, that is, whether it can alleviate the impact of asymmetric information based on the available information. We used a dynamic general equilibrium model with heterogenous agents to assess this. Using Indian credit market data our study shows that the presence of informal credit market can reduce the cost of credit rationing by separating high risk firms from the low risk firms in the informal market. But even after this improvement, the steady state capital accumulation is still much lower as compared to incentive based market clearing rates. Through self revelation of each firm's type, based on the incentive mechanism, banks can diversify their risk by achieving a separating equilibrium in the loan market. The incentive mechanism helps banks to increase capital accumulation in the long run by charging lower rates and lending relatively higher amount to the less risky firms. Another important finding of this study is that self-revelation leads to very significant welfare improvement, as measured by consumptiuon equivalence.

Antidumping as Strategic Trade Policy Under Asymmetric Information

In the last two decades, trade liberalization under GATT/WTO has been partly offset by an increase in antidumping protection. Economists have argued convincingly that this is partly due to the inclusion of sales below cost in the definition of dumping during the GATT Tokyo Round. The introduction of the cost- based dumping definition gives regulating authorities a better opportunity to choose protection according to their liking. This paper investigates the domestic government's antidumping duty choice in an asymmetric information framework where the foreign firm's cost is observed by the domestic firm, but not by the government. To induce truthful revelation, the government can design a tariff schedule, contingent on firms' cost reports, accompanied by a threat to collect additional information for report verification (i.e., auditing) and, in case misreporting is detected, to set penalty duties. We show that depending on the concrete assumptions, the domestic government may not only be able to extract the true cost information, but also succeeds in implementing the full-information, governmental welfare-maximizing duty. In this case, the antidumping framework within GATT/WTO does not only offer the means to pursue strategic trade policy disguised as fair trade policy, but it also helps overcome the informational problems with regard to correctly determining the optimal strategic trade policy.

Shadow Profit Maximization and a Generalized Measure of Inefficiency

Determining the profit maximizing input-output bundle of a firm requires data on prices. This paper shows how endogenously determined shadow prices can be used in place of actual prices to obtain the optimal input-output bundle where the firm.s shadow profit is maximized. This approach amounts to an application of the Weak Axiom of Profit Maximization (WAPM) formulated by Varian (1984) based on shadow prices rather than actual prices. At these prices the shadow profit of a firm is zero. Thus, the maximum profit that could have been attained at some other input-output bundle is a measure of the inefficiency of the firm. Because the benchmark input-output bundle is always an observed bundle from the data, it can be determined without having to solve any elaborate programming problem. An empirical application to U.S. airlines data illustrates the proposed methodology.

Asymmetric Information, Tax Evasion and Alternative Instruments of Government Revenue

Using a pure-exchange overlapping generations model, characterized with tax evasion and information asymmetry between the government (the social planner) and the financial intermediaries, we try and seek for the optimal tax and seigniorage plans, derived from the welfare maximizing objective of the social planner. We show that irrespective of whether the economy is characterized by tax evasion, or asymmetric information, a benevolent social planner, maximizing welfare and simultaneously financing the budget constraint, should optimally rely on explicit rather than implicit taxation.