Net Neutrality and Investment Incentives

This paper analyzes the effects of net neutrality regulation on investment incentives for Internet service providers (ISPs) and content providers (CPs), and their implications for social welfare. We show that the ISP’s decision on the introduction of discrimination across content depends on a potential trade-off between network access fee and the revenue from the trade of the first-priority. Concerning the ISP’s investment incentives, we find that capacity expansion affects the sale price of the priority right under the discriminatory regime. Because the relative merit of the first priority, and thus its value, becomes relatively small for higher capacity levels, the ISP’s incentive to invest on capacity under a discriminatory network can be smaller than that under a neutral regime where such rent extraction effects do not exist. Contrary to ISPs’ claims that net neutrality regulations would have a chilling effect on their incentive to invest, we cannot dismiss the possibility of the opposite.net neutrality, investment (innovation) incentives, queuing theory, hold-up problem, two-sided markets, vertical integration

ABC transporters as multidrug resistance mechanisms and the development of chemosensitizers for their reversal

One of the major problems related with anticancer chemotherapy is resistance against anticancer drugs. The ATP-binding cassette (ABC) transporters are a family of transporter proteins that are responsible for drug resistance and a low bioavailability of drugs by pumping a variety of drugs out cells at the expense of ATP hydrolysis. One strategy for reversal of the resistance of tumor cells expressing ABC transporters is combined use of anticancer drugs with chemosensitizers. In this review, the physiological functions and structures of ABC transporters, and the development of chemosensitizers are described focusing on well-known proteins including P-glycoprotein, multidrug resistance associated protein, and breast cancer resistance protein

Extensions of the classical fighter-bomber duel

In this dissertation, we consider a two-person zero-sum game in which a fighter with a missile wishes to destroy a bomber. The bomber has much small-caliber ammunition for protecting itself from the fighter. And the fighter possesses a missile for attacking the bomber. We develop models for the behavior of the fighter, in terms of missile launch time, and of the bomber, in terms of ammunition firing rate, in several situations. In particular, we examine extensions of the Weiss-Gillman model and the Karlin model

Design of singlet fission chromophores with cyclic (alkyl)(amino) carbene building blocks

We use MRSF-TDDFT and NEVPT2 methods to design singlet fission chromophores with the building blocks of cyclic (alkyl)(amino)carbenes (CAACs). CAAC dimers with C2, C4, and p-phenylene spacers are considered. The substitutions with trifluoromethyls and fluorine atoms at the α C position are investigated. The electronegative substituents enhance the π accepting capability of the α C, while maintaining it as a quaternary C atom. The phenylene-connected dimers with the two substitutions are identified as promising candidates for singlet fission chromophores. The cylindrically symmetric C2 and C4 spacers allow for substantial structural reorganizations in the S0-to-S1 and S0-to-T1 excitations. Although the two substituted dimers with the C4 spacer satisfy (or very close to satisfy) the primary thermodynamics criterion for singlet fission, the significant structural reorganizations result in high barriers so that the fission is kinetically unfavorable

Benefits of Additional Make-to-Stock Channel with Price Control Characteristic to Make-to-Order Channel

In this paper we study the benefits for a manufacturer or supplier of having a secondary sales channel with price control in addition to its primary sales channel. Our definition of the primary sales channel is that a majority of companys total profit is from it, and that the company has make-to-order (MTO) production environment to meet this demand. On the other hand, our definition of the secondary channel is that the company is assumed to be able to create certain demands by reducing the price of standard products for the channel. Therefore, the secondary channel is supplied by make-to-stock (MTS) products as a manufacturer tries to make use of excess capacity after meeting the demand for the primary channel. We assume that the manufacturer can create just enough volume of demand from the secondary channel to match the excess production capacity. We call the primary channel MTO, and the secondary MTS. In other words, a manufacturer or supplier can increase revenues/profits and smooth the MTO productions by using the MTS channel through utilizing the excess capacity. However, developing MTS channel needs investments. In this paper, we try to find out in what operational characteristics a company can justify the investments for the benefits of developing the additional MTS channel to the existing MTO channel. We measure the quantitative benefits of the additional channel over various sets of operational characteristics and interpret the results. With a set of experiments, we investigate the effect of demand variability, capacity utilization, and holding and other production-related costs with a simple price-demand relationship. We have observed that benefits increase as demand variability increases, as capacity utilization decreases, and as capacity change costs. However, the holding does not seem to impact the benefits

Automated Claim Matching with Large Language Models: Empowering Fact-Checkers in the Fight Against Misinformation

In today's digital era, the rapid spread of misinformation poses threats to public well-being and societal trust. As online misinformation proliferates, manual verification by fact checkers becomes increasingly challenging. We introduce FACT-GPT (Fact-checking Augmentation with Claim matching Task-oriented Generative Pre-trained Transformer), a framework designed to automate the claim matching phase of fact-checking using Large Language Models (LLMs). This framework identifies new social media content that either supports or contradicts claims previously debunked by fact-checkers. Our approach employs GPT-4 to generate a labeled dataset consisting of simulated social media posts. This data set serves as a training ground for fine-tuning more specialized LLMs. We evaluated FACT-GPT on an extensive dataset of social media content related to public health. The results indicate that our fine-tuned LLMs rival the performance of larger pre-trained LLMs in claim matching tasks, aligning closely with human annotations. This study achieves three key milestones: it provides an automated framework for enhanced fact-checking; demonstrates the potential of LLMs to complement human expertise; offers public resources, including datasets and models, to further research and applications in the fact-checking domain