Discussion on the Challenges Surrounding Anti-microbial Resistance, Using Relevant Case-study Examples

The advent of antimicrobial drugs has made a huge contribution to human society, but their commodity nature has given rise to behaviors such as abuse and overuse, leading to the emergence of resistance to antimicrobial drugs and other hazards. Nowadays, the structure of interests formed by various stakeholders in the market circulation of antimicrobial agents has become unbalanced, and government intervention as a breakthrough still faces many challenges. This paper discusses the AMR challenges of government intervention under the interest structure in the context of case studies in the Global North and the Global South areas from the point of view of human health in terms of stagnant R & D processes for novel antimicrobial drugs, a profit-oriented neoliberal atmosphere that mismatches production trends of antimicrobial drugs with market demand, the prevalence of private institutions lacking effective regulation, incomplete government interventions, and the difficulty of pursuing the WHO strategic plan on antimicrobial resistance, etc

Competition and tax evasion : a cross country study

This paper investigates the determinants of informality (tax evasion in particular) utilizing rich cross-country data of firm-level survey from the World Bank, and hypothesizing that competition is a significant factor determining tax evasion behaviors. Competition pressure is a key stimulus to induce questionable manipulations of tax reporting behaviors. However its effect works at a decreasing speed. It is also hypothesized that business obstacles facing firms such as tax administration and corruption play significant roles in explaining tax evasion. This paper further hypothesizes that firm characteristics such as size, age, ownership are important evasion determinants. Empirical results are found supporting these hypotheses above. The analysis controls for country-level effects, for instance the quality of the legal environment. Industry sectors are also controlled and found significant in explaining corporate tax evasion levels

Turbo-like Iterative Multi-user Receiver Design for 5G Non-orthogonal Multiple Access

Non-orthogonal multiple access (NoMA) as an efficient way of radio resource sharing has been identified as a promising technology in 5G to help improving system capacity, user connectivity, and service latency in 5G communications. This paper provides a brief overview of the progress of NoMA transceiver study in 3GPP, with special focus on the design of turbo-like iterative multi-user (MU) receivers. There are various types of MU receivers depending on the combinations of MU detectors and interference cancellation (IC) schemes. Link-level simulations show that expectation propagation algorithm (EPA) with hybrid parallel interference cancellation (PIC) is a promising MU receiver, which can achieve fast convergence and similar performance as message passing algorithm (MPA) with much lower complexity.Comment: Accepted by IEEE 88th Vehicular Technology Conference (IEEE VTC-2018 Fall), 5 pages, 6 figure

A Universal Receiver for Uplink NOMA Systems

Given its capability in efficient radio resource sharing, non-orthogonal multiple access (NOMA) has been identified as a promising technology in 5G to improve the system capacity, user connectivity, and scheduling latency. A dozen of uplink NOMA schemes have been proposed recently and this paper considers the design of a universal receiver suitable for all potential designs of NOMA schemes. Firstly, a general turbo-like iterative receiver structure is introduced, under which, a universal expectation propagation algorithm (EPA) detector with hybrid parallel interference cancellation (PIC) is proposed (EPA in short). Link-level simulations show that the proposed EPA receiver can achieve superior block error rate (BLER) performance with implementation friendly complexity and fast convergence, and is always better than the traditional codeword level MMSE-PIC receiver for various kinds of NOMA schemes.Comment: This paper has been accepted by IEEE/CIC International Conference on Communications in China (ICCC 2018). 5 pages, 4 figure

Nonequilibrium spin injection in monolayer black phosphorus

Monolayer black phosphorus (MBP) is an interesting emerging electronic material with a direct band gap and relatively high carrier mobility. In this work we report a theoretical investigation of nonequilibrium spin injection and spin-polarized quantum transport in MBP from ferromagnetic Ni contacts, in two-dimensional magnetic tunneling structures. We investigate physical properties such as the spin injection efficiency, the tunnel magnetoresistance ratio, spin-polarized currents, charge currents and transmission coefficients as a function of external bias voltage, for two different device contact structures where MBP is contacted by Ni(111) and by Ni(100). While both structures are predicted to give respectable spin-polarized quantum transport, the Ni(100)/MBP/Ni(100) trilayer has the superior properties where the spin injection and magnetoresistance ratio maintains almost a constant value against the bias voltage. The nonequilibrium quantum transport phenomenon is understood by analyzing the transmission spectrum at nonequilibrium.Comment: 6 pages, 6 figure

Research without Re-search: Maximal Update Parametrization Yields Accurate Loss Prediction across Scales

As language models scale up, it becomes increasingly expensive to verify research ideas because conclusions on small models do not trivially transfer to large ones. A possible solution is to establish a generic system that directly predicts some metrics for large models solely based on the results and hyperparameters from small models. Existing methods based on scaling laws require hyperparameter search on the largest models, which is impractical with limited resources. We address this issue by presenting our discoveries indicating that Maximal Update parametrization (muP) enables accurate fitting of scaling laws for hyperparameters close to common loss basins, without any search. Thus, different models can be directly compared on large scales with loss prediction even before the training starts. We propose a new paradigm as a first step towards reliable academic research for any model scale without heavy computation. Code will be publicly available shortly