From the factory to the field: considerations of product characteristics for insecticide-treated net (ITN) bioefficacy testing

BACKGROUND: Insecticide-treated nets (ITNs) undergo a series of tests to obtain listing by World Health Organization (WHO) Prequalification. These tests characterize the bioefficacy, physical and chemical properties of the ITN. ITN procurers assume that product specifications relate to product performance. Here, ITN test methods and their underlying assumptions are discussed from the perspective of the ITN manufacturing process and product characteristics. METHODS: Data were extracted from WHO Pesticide Evaluation Scheme (WHOPES) meeting reports from 2003 to 2017, supplemented with additional chemical analysis to critically evaluate ITNs bioassays with a focus on sampling, washing and wash resistance, and bioefficacy testing. Production methods for ITNs and their impact on testing outcomes are described. RESULTS AND RECOMMENDATIONS: ITNs are not homogenous products. They vary within panels and between the sides and the roof. Running tests of wash resistance using a before/after tests on the same sample or band within a net reduces test variability. As mosquitoes frequently interact with ITN roofs, additional sampling of the roof when evaluating ITNs is advisable because in nets where roof and sides are of the same material, the contribution of roof sample (20-25%) to the average is less than the tolerance for the specification (25%). Mosquito mortality data cannot be reliably used to evaluate net surface concentration to determine regeneration time (RT) and resistance to washing as nets may regenerate beyond the insecticide concentrations needed to kill 100% of susceptible mosquitoes. Chemical assays to quantify surface concentration are needed. The Wash Resistance Index (WRI) averaged over the first four washes is only informative if the product has a log linear loss rate of insecticide. Using a WRI that excludes the first wash off gives more reliable results. Storage conditions used for product specifications are lower than those encountered under product shipping and storage that may exceed 50 degrees C, and should be reconsidered. Operational monitoring of new ITNs and linking observed product performance, such as bioefficacy after 2 or 3 years of use, with product characteristics, such as WRI, will aid the development of more robust test methods and product specifications for new products coming to market

Unconventional anomalous Hall effect in 3d/5d multilayers mediated by the nonlocal spin-conductivity

We evidenced unconventionnal Anomalous Hall Effects (AHE) in 3d/5d (Co0.2nm/Ni0.6nm)N multilayers grown on a thin Pt layer or thin Au:W alloy. The inversion observed on AHE originates from the opposite sign of the spin-orbit coupling of Pt compared to Ni. Via advanced simulations methods for the description of the spin-current profiles based on the spin-dependent Boltzmann formalism, we extracted the spin Hall angle (SHA) of Pt and (Co/Ni) as well as the relevant transport parameters. The extracted SHA for Pt, +20%, is opposite to the one of (Co/Ni), giving rise to an effective AHE inversion for thin (Co/Ni) multilayers (N < 17). The spin Hall angle in Pt is found to be larger than the one previously measured in combined spin-pumping inverse spin-Hall effect experiments in a geometry of current perpendicular to plane. Whereas magnetic proximity effects cannot explain the effect, spin-current leakage and anisotropic electron scattering at Pt/(Co,Ni) interfaces fit the experiments.Comment: 7 pages, 2 figure

Multistage Random Growing Small-World Networks with Power-law degree Distribution

In this paper, a simply rule that generates scale-free networks with very large clustering coefficient and very small average distance is presented. These networks are called {\bf Multistage Random Growing Networks}(MRGN) as the adding process of a new node to the network is composed of two stages. The analytic results of power-law exponent $\gamma=3$ and clustering coefficient $C=0.81$ are obtained, which agree with the simulation results approximately. In addition, the average distance of the networks increases logarithmical with the number of the network vertices is proved analytically. Since many real-life networks are both scale-free and small-world networks, MRGN may perform well in mimicking reality.Comment: 3 figures, 4 page

Effectiveness of cervical pessary compared to cervical cerclage with or without vaginal progesterone for the prevention of preterm birth in women with twin pregnancies and a short cervix : Study protocol for a two-by-two factorial randomised clinical trial

Peer reviewedPublisher PD

Competing magnetic fluctuations in Sr3Ru2O7 probed by Ti doping

We report the effect of nonmagnetic Ti4+ impurities on the electronic and magnetic properties of Sr3Ru2O7. Small amounts of Ti suppress the characteristic peak in magnetic susceptibility near 16 K and result in a sharp upturn in specific heat. The metamagnetic quantum phase transition and related anomalous features are quickly smeared out by small amounts of Ti. These results provide strong evidence for the existence of competing magnetic fluctuations in the ground state of Sr3Ru2O7. Ti doping suppresses the low temperature antiferromagnetic interactions that arise from Fermi surface nesting, leaving the system in a state dominated by ferromagnetic fluctuations.Comment: 5 pages, 4 figures, 1 tabl

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202