Resistance of Aedes aegypti (Diptera: Culicidae) Populations to Deltamethrin, Permethrin, and Temephos in Cambodia.

Dengue fever is a major public health concern, including 185,000 annual cases in Cambodia. Aedes aegypti is the primary vector for dengue transmission and is targeted with insecticide treatments. This study characterized the insecticide resistance status of Ae aegypti from rural and urban locations. The susceptibility to temephos, permethrin, and deltamethrin of Ae aegypti was evaluated in accordance with World Health Organization instructions. All the field populations showed lower mortality rate to temephos compared with the sensitive strain with resistance ratio 50 (RR50) varying from 3.3 to 33.78 and RR90 from 4.2 to 47 compared with the sensitive strain, demonstrating a generalized resistance of larvae to the temephos in Cambodia. Ae aegypti adult populations were highly resistant to permethrin regardless of province or rural/urban classification with an average mortality of 0.02%. Seven of the 8 field populations showed resistance to deltamethrin. These results are alarming for dengue vector control, as widespread resistance may compromise the entomological impact of larval control operations. Innovative vector control tools are needed to replace ineffective pesticides in Cambodia

One-Pot Synthesis of Biocompatible CdSe/CdS Quantum Dots and Their Applications as Fluorescent Biological Labels

We developed a novel one-pot polyol approach for the synthesis of biocompatible CdSe quantum dots (QDs) using poly(acrylic acid) (PAA) as a capping ligand at 240°C. The morphological and structural characterization confirmed the formation of biocompatible and monodisperse CdSe QDs with several nanometers in size. The encapsulation of CdS thin layers on the surface of CdSe QDs (CdSe/CdS core–shell QDs) was used for passivating the defect emission (650 nm) and enhancing the fluorescent quantum yields up to 30% of band-to-band emission (530–600 nm). Moreover, the PL emission peak of CdSe/CdS core–shell QDs could be tuned from 530 to 600 nm by the size of CdSe core. The as-prepared CdSe/CdS core–shell QDs with small size, well water solubility, good monodispersity, and bright PL emission showed high performance as fluorescent cell labels in vitro. The viability of QDs-labeled 293T cells was evaluated using a 3-(4,5-dimethylthiazol)-2-diphenyltertrazolium bromide (MTT) assay. The results showed the satisfactory (>80%) biocompatibility of as-synthesized PAA-capped QDs at the Cd concentration of 15 μg/ml

Artificial intelligence and deep learning in ophthalmology

Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to impact on healthcare. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography and visual fields, achieving robust classification performance in the detection of diabetic retinopathy and retinopathy of prematurity, the glaucoma-like disc, macular oedema and age-related macular degeneration. DL in ocular imaging may be used in conjunction with telemedicine as a possible solution to screen, diagnose and monitor major eye diseases for patients in primary care and community settings. Nonetheless, there are also potential challenges with DL application in ophthalmology, including clinical and technical challenges, explainability of the algorithm results, medicolegal issues, and physician and patient acceptance of the AI 'black-box' algorithms. DL could potentially revolutionise how ophthalmology is practised in the future. This review provides a summary of the state-of-the-art DL systems described for ophthalmic applications, potential challenges in clinical deployment and the path forward

Minding impacting events in a model of stochastic variance

We introduce a generalisation of the well-known ARCH process, widely used for generating uncorrelated stochastic time series with long-term non-Gaussian distributions and long-lasting correlations in the (instantaneous) standard deviation exhibiting a clustering profile. Specifically, inspired by the fact that in a variety of systems impacting events are hardly forgot, we split the process into two different regimes: a first one for regular periods where the average volatility of the fluctuations within a certain period of time is below a certain threshold and another one when the local standard deviation outnumbers it. In the former situation we use standard rules for heteroscedastic processes whereas in the latter case the system starts recalling past values that surpassed the threshold. Our results show that for appropriate parameter values the model is able to provide fat tailed probability density functions and strong persistence of the instantaneous variance characterised by large values of the Hurst exponent is greater than 0.8, which are ubiquitous features in complex systems.Comment: 18 pages, 5 figures, 1 table. To published in PLoS on

A Comparison of Weight Initializers in Deep Learning-based Side-channel Analysis

The usage of deep learning in profiled side-channel analysis requires a careful selection of neural network hyperparameters. In recent publications, different network architectures have been presented as efficient profiled methods against protected AES implementations. Indeed, completely different convolutional neural network models have presented similar performance against public side-channel traces databases. In this work, we analyze how weight initializers\u27 choice influences deep neural networks\u27 performance in the profiled side-channel analysis. Our results show that different weight initializers provide radically different behavior. We observe that even high-performing initializers can reach significantly different performance when conducting multiple training phases. Finally, we found that this hyperparameter is more dependent on the choice of dataset than other, commonly examined, hyperparameters. When evaluating the connections with other hyperparameters, the biggest connection is observed with activation functions

Fermionic Coset, Critical Level W^(2)_4-Algebra and Higher Spins

The fermionic coset is a limit of the pure spinor formulation of the AdS5xS5 sigma model as well as a limit of a nonlinear topological A-model, introduced by Berkovits. We study the latter, especially its symmetries, and map them to higher spin algebras. We show the following. The linear A-model possesses affine \AKMSA{pgl}{4}{4}_0 symmetry at critical level and its \AKMSA{psl}{4}{4}_0 current-current perturbation is the nonlinear model. We find that the perturbation preserves $\mathcal{W}^{(2)}_4$-algebra symmetry at critical level. There is a topological algebra associated to \AKMSA{pgl}{4}{4}_0 with the properties that the perturbation is BRST-exact. Further, the BRST-cohomology contains world-sheet supersymmetric symplectic fermions and the non-trivial generators of the $\mathcal{W}^{(2)}_4$-algebra. The Zhu functor maps the linear model to a higher spin theory. We analyze its \SLSA{psl}{4}{4} action and find finite dimensional short multiplets.Comment: 25 page

Genomic analysis of the function of the transcription factor gata3 during development of the Mammalian inner ear

We have studied the function of the zinc finger transcription factor gata3 in auditory system development by analysing temporal profiles of gene expression during differentiation of conditionally immortal cell lines derived to model specific auditory cell types and developmental stages. We tested and applied a novel probabilistic method called the gamma Model for Oligonucleotide Signals to analyse hybridization signals from Affymetrix oligonucleotide arrays. Expression levels estimated by this method correlated closely (p<0.0001) across a 10-fold range with those measured by quantitative RT-PCR for a sample of 61 different genes. In an unbiased list of 26 genes whose temporal profiles clustered most closely with that of gata3 in all cell lines, 10 were linked to Insulin-like Growth Factor signalling, including the serine/threonine kinase Akt/PKB. Knock-down of gata3 in vitro was associated with a decrease in expression of genes linked to IGF-signalling, including IGF1, IGF2 and several IGF-binding proteins. It also led to a small decrease in protein levels of the serine-threonine kinase Akt2/PKB beta, a dramatic increase in Akt1/PKB alpha protein and relocation of Akt1/PKB alpha from the nucleus to the cytoplasm. The cyclin-dependent kinase inhibitor p27(kip1), a known target of PKB/Akt, simultaneously decreased. In heterozygous gata3 null mice the expression of gata3 correlated with high levels of activated Akt/PKB. This functional relationship could explain the diverse function of gata3 during development, the hearing loss associated with gata3 heterozygous null mice and the broader symptoms of human patients with Hearing-Deafness-Renal anomaly syndrome