Paying for Delay or Something Else?--The Potential Anticompetitive Effect of Reverse Payment Patent Settlements in the Pharmaceutical Industry under article 101 TFEU

This thesis discusses the recent hot topic in the intersection of IP law and competition law; “pay-for-delay” agreements in the pharmaceutical industry. Such agreements arise in patent disputes where originator manufacturers (‘Originators’) claim patent infringement by the generic manufactures (‘Generics’). However, patent infringing defendants end up paying the plaintiff large sums of money, accompanied with the generic’s agreement to delay or refrain from challenging the patent and launching generic drugs. Due to the fact that the parties may have agreed to not compete by sharing monopoly profits, pay-for-delay deals could lead to an artificially higher market price which detriments consumer welfare. Whether all suspicious pay-for-delay deals are anti-competitive has been controversial in the academic field and the courts in the US. As the EU has only recently started its study and investigations into the issue, it is worthwhile to study: whether such deals are anti-competitive in themselves, to what extent they could be anti-competitive under the EU competition law and how should they be examined to reach the optimum result for competition law implementation. Section 1 of this thesis will firstly give a general picture of the history of pay-for-delay deals in EU and US. Section 2 will further offer the legal context and the industry features that fertilize the emergence of pay-for-delay deals. Section 2.5 summarizes the change of attitude of US courts and the investigations in Europe. Through studies into the judgement/decisions of these cases, Section 3 proposes a system of classification for pay-for-delay, which puts pay-for-delay deals into high-risk, medium-risk and low-risk categories. The rationale and method of such classification will also be included. The thesis ends with the conclusion that not all the agreements that meet the superficial criteria of pay-for-delay agreements (restriction on generic entry and reverse value transfer) are of anti-competitive effect. Some may be the reasonable result of a genuine patent dispute and will not leave anti-competitive impacts on the market. It is thus necessary to classify these agreements by their level of anti-competitive risk and that they should be scrutinized differently in accordance with the classification they fall into

Ultramicromorphological observation of Usnea longissima Ach.

The Usnea longissima Ach. grew as an epiphyte on Abies georgei and was collected at an altitude of 3640 m above sea level from the Pudacuo National Park in the Shangri-La County of the Diqing Tibetan Autonomous Prefecture in the Yunnan Province of China. Scanning electron microscopy revealed the ultramicro-organisation of the U. longissima. We observed that the interior of the specimen contained a large amount of cubic and needle-like secretions; images of the cross-section of the central axis show many densely distributed holes, and the longitudinal section of the central axis revealed many vessellike structures, similar to vessels in plants; some hyphae specialised into ring-shaped. These structures have not been reported even in other Usnea. This study gives us more comprehensive understanding of the structure and function of lichens.Key words: Usnea longissima Ach., ultramicromorphological observation, scanning electron microscopy

Reduction of Hox Gene Expression by Histone H1 Depletion

The evolutionarily conserved homeotic (Hox) genes are organized in clusters and expressed collinearly to specify body patterning during embryonic development. Chromatin reorganization and decompaction are intimately connected with Hox gene activation. Linker histone H1 plays a key role in facilitating folding of higher order chromatin structure. Previous studies have shown that deletion of three somatic H1 subtypes together leads to embryonic lethality and that H1c/H1d/H1e triple knockout (TKO) embryonic stem cells (ESCs) display bulk chromatin decompaction. To investigate the potential role of H1 and higher order chromatin folding in the regulation of Hox gene expression, we systematically analyzed the expression of all 39 Hox genes in triple H1 null mouse embryos and ESCs by quantitative RT-PCR. Surprisingly, we find that H1 depletion causes significant reduction in the expression of a broad range of Hox genes in embryos and ESCs. To examine if any of the three H1 subtypes (H1c, H1d and H1e) is responsible for decreased expression of Hox gene in triple-H1 null ESCs, we derived and characterized H1c−/−, H1d−/−, and H1e−/− single-H1 null ESCs. We show that deletion of individual H1 subtypes results in down-regulation of specific Hox genes in ESCs. Finally we demonstrate that, in triple-H1- and single-H1- null ESCs, the levels of H3K4 trimethylation (H3K4me3) and H3K27 trimethylation (H3K27me3) were affected at specific Hox genes with decreased expression. Our data demonstrate that marked reduction in total H1 levels causes significant reduction in both expression and the level of active histone mark H3K4me3 at many Hox genes and that individual H1 subtypes may also contribute to the regulation of specific Hox gene expression. We suggest possible mechanisms for such an unexpected role of histone H1 in Hox gene regulation

Measures to prevent nosocomial transmissions of COVID-19 based on interpersonal contact data

BACKGROUND: With the global spreading of Coronavirus disease (COVID-19), many primary care medical workers have been infected, particularly in the early stages of this pandemic. Although extensive studies have explored the COVID-19 transmission patterns and (non-) pharmaceutical intervention to protect the general public, limited research has analysed the measures to prevent nosocomial transmission based upon detailed interpersonal contacts between medical staff and patients. AIM: This paper aims to develop and evaluate proactive prevention measures to contain the nosocomial transmission of COVID-19. The specific objectives are (1) to understand the virus transmission via interpersonal contacts among medical staff and patients; (2) to define proactive measures to reduce the risk of infection of medical staff and (3) evaluate the effectiveness of these measures to control the COVID-19 epidemic in hospitals. METHODS: We observed the operation of a typical primary hospital in China to understand the interpersonal contacts among medical staff and patients. We defined effective distance as the indicator for risk of transmission. Then three proactive measures were proposed based upon the observations, including a medical staff rotation system, the establishment of a separate fever clinic and medical staff working alone. Finally, the impacts of these measures are evaluated with a modified Susceptible-Exposure-Infected-Removed model accommodating the situation of hospitals and asymptomatic and latent infection of COVID-19. The case study was conducted with the hospital observed in December 2019 and February 2020. FINDINGS: The implementation of the medical staff rotation system has the most significant impact on containing the epidemic. The establishment of a separate fever clinic and medical staff working alone also benefits from inhibiting the epidemic outbreak. The simulation finds that if effective prevention and control measures are not taken in time, it will lead to a surge of infection cases in all asymptomatic probabilities and incubation periods

Research on Water Pollution Control Based on STM32 Intelligent Vehicle

In order to solve the high cost and low efficiency of different degrees of pollution control of natural water resources in China at this stage, photocatalytic water purification technology is adopted to reduce the cost of water pollution treatment and improve the treatment efficiency, and an intelligent vehicle equipped with photocatalytic materials is proposed, which is equipped with industrial cameras, communication positioning modules and sensors, and realizes dynamic planning of navigation routes by improving ant colony algorithms, computer vision recognition, ultrasonic obstacle avoidance, and realizes photocatalytic fixed-point purification. Predict advanced photoelectric catalytic performance based on density functional theory and machine learning, solve the problem of BiVO4 photo corrosion and instability, and achieve efficient water purification at low cost

DexCatch: Learning to Catch Arbitrary Objects with Dexterous Hands

Achieving human-like dexterous manipulation remains a crucial area of research in robotics. Current research focuses on improving the success rate of pick-and-place tasks. Compared with pick-and-place, throw-catching behavior has the potential to increase picking speed without transporting objects to their destination. However, dynamic dexterous manipulation poses a major challenge for stable control due to a large number of dynamic contacts. In this paper, we propose a Stability-Constrained Reinforcement Learning (SCRL) algorithm to learn to catch diverse objects with dexterous hands. The SCRL algorithm outperforms baselines by a large margin, and the learned policies show strong zero-shot transfer performance on unseen objects. Remarkably, even though the object in a hand facing sideward is extremely unstable due to the lack of support from the palm, our method can still achieve a high level of success in the most challenging task. Video demonstrations of learned behaviors and the code can be found on the supplementary website

Efficient Exploration Using Extra Safety Budget in Constrained Policy Optimization

Reinforcement learning (RL) has achieved promising results on most robotic control tasks. Safety of learning-based controllers is an essential notion of ensuring the effectiveness of the controllers. Current methods adopt whole consistency constraints during the training, thus resulting in inefficient exploration in the early stage. In this paper, we propose an algorithm named Constrained Policy Optimization with Extra Safety Budget (ESB-CPO) to strike a balance between the exploration efficiency and the constraints satisfaction. In the early stage, our method loosens the practical constraints of unsafe transitions (adding extra safety budget) with the aid of a new metric we propose. With the training process, the constraints in our optimization problem become tighter. Meanwhile, theoretical analysis and practical experiments demonstrate that our method gradually meets the cost limit's demand in the final training stage. When evaluated on Safety-Gym and Bullet-Safety-Gym benchmarks, our method has shown its advantages over baseline algorithms in terms of safety and optimality. Remarkably, our method gains remarkable performance improvement under the same cost limit compared with baselines.Comment: 7 pages, 8 figure