922 research outputs found
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
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