Synthesis and characterization of conducting polymer nanostructures and their application in sensors

A one-step synthesis technique has been used to fabricate sensors by growing polyaniline nanofibers and polyaniline/metal nanocomposites in the active area of an interdigitated electrode array. Polyaniline nanofiber sensors can be fabricated by irradiating an aqueous precursor solution containing aniline, HCl, a metal salt, and ammonium persulfate (APS) with a high pressure Hg lamp. The sensors are ready for operation after polymerization is complete, and no additional processing steps are necessary. These sensors showed faster and more intensity response to various organic vapors than conventional bulk polyaniline sensors due to their larger surface area. A chemisorption model and a diffusion model were used to fit the sensor response of nanostructured polyaniline sensors. Both models can mathematically fit the sensor response as a function of time. Fitting errors from the two models were in a reasonable range, both allowing reasonable mathematical forms for the time-dependent and concentration behavior. An oligomer-assisted polymerization method was carried out to synthesize polythiophene nanofibers. In this approach, a solution of thiophene, FeCl₃, and terthiophene was dissolved in acetonitrile. Compared to conventional chemical polymerization, a polythiophene oligomer, terthiophene or bithiophene, was added to assist the formation of nanofibers. The polythiophene collected after the 12 h reaction time was found to have nanofibrilar morphology with an average diameter of about 40-50 nm. Unlike other hard-template or soft-template techniques, this method does not require the introduction of a heterogeneous phase --Abstract, page iv

Thoracic Disease Identification and Localization with Limited Supervision

Accurate identification and localization of abnormalities from radiology images play an integral part in clinical diagnosis and treatment planning. Building a highly accurate prediction model for these tasks usually requires a large number of images manually annotated with labels and finding sites of abnormalities. In reality, however, such annotated data are expensive to acquire, especially the ones with location annotations. We need methods that can work well with only a small amount of location annotations. To address this challenge, we present a unified approach that simultaneously performs disease identification and localization through the same underlying model for all images. We demonstrate that our approach can effectively leverage both class information as well as limited location annotation, and significantly outperforms the comparative reference baseline in both classification and localization tasks.Comment: Conference on Computer Vision and Pattern Recognition 2018 (CVPR 2018). V1: CVPR submission; V2: +supplementary; V3: CVPR camera-ready; V4: correction, update reference baseline results according to their latest post; V5: minor correction; V6: Identification results using NIH data splits and various image model

Estimation and Inference for High Dimensional Generalized Linear Models: A Splitting and Smoothing Approach

The focus of modern biomedical studies has gradually shifted to explanation and estimation of joint effects of high dimensional predictors on disease risks. Quantifying uncertainty in these estimates may provide valuable insight into prevention strategies or treatment decisions for both patients and physicians. High dimensional inference, including confidence intervals and hypothesis testing, has sparked much interest. While much work has been done in the linear regression setting, there is lack of literature on inference for high dimensional generalized linear models. We propose a novel and computationally feasible method, which accommodates a variety of outcome types, including normal, binomial, and Poisson data. We use a "splitting and smoothing" approach, which splits samples into two parts, performs variable selection using one part and conducts partial regression with the other part. Averaging the estimates over multiple random splits, we obtain the smoothed estimates, which are numerically stable. We show that the estimates are consistent, asymptotically normal, and construct confidence intervals with proper coverage probabilities for all predictors. We examine the finite sample performance of our method by comparing it with the existing methods and applying it to analyze a lung cancer cohort study

Design, characterization, and sensitivity of the supernova trigger system at Daya Bay

Providing an early warning of galactic supernova explosions from neutrino signals is important in studying supernova dynamics and neutrino physics. A dedicated supernova trigger system has been designed and installed in the data acquisition system at Daya Bay and integrated into the worldwide Supernova Early Warning System (SNEWS). Daya Bay's unique feature of eight identically-designed detectors deployed in three separate experimental halls makes the trigger system naturally robust against cosmogenic backgrounds, enabling a prompt analysis of online triggers and a tight control of the false-alert rate. The trigger system is estimated to be fully sensitive to 1987A-type supernova bursts throughout most of the Milky Way. The significant gain in sensitivity of the eight-detector configuration over a mass-equivalent single detector is also estimated. The experience of this online trigger system is applicable to future projects with spatially distributed detectors.Comment: 8 pages, 6 figures, to be submitted to Astroparticle Physic

Concolic Execution of NMap Scripts for Honeyfarm Generation

Attackers rely upon a vast array of tools for automating attacksagainst vulnerable servers and services. It is often the case thatwhen vulnerabilities are disclosed, scripts for detecting and exploit-ing them in tools such asNmapandMetasploitare released soonafter, leading to the immediate identification and compromise ofvulnerable systems. Honeypots, honeynets, tarpits, and other decep-tive techniques can be used to slow attackers down, however, such approaches have difficulty keeping up with the sheer number of vulnerabilities being discovered and attacking scripts that are being released. To address this issue, this paper describes an approach for applying concolic execution on attacking scripts in Nmap in order to automatically generate lightweight fake versions of the vulnerable services that can fool the scripts. By doing so in an automated and scalable manner, the approach can enable rapid deployment of custom honeyfarms that leverage the results of concolic execution to trick an attacker\u27s script into returning a result chosen by the honeyfarm, making the script unreliable for the use by the attacker

Tetra­kis­(μ-benzoato-κ2 O:O′)bis{[4-(di­methyl­amino)­pyridine-κN 1]zinc(II)}

In the centrosymmetric binuclear title complex, [Zn2(C7H5O2)4(C7H10N2)2], the Zn atoms [Zn⋯Zn = 3.0037 (6) Å] are bridged by four benzoate ligands. Each of the Zn atoms assumes an approximately square-pyramidal environment, with four O atoms in a plane and the pyridine N atom at the apical site

A new classification system of lithic-rich tight sandstone and its application to diagnosis high-quality reservoirs

        Lithic-rich tight sandstone is one of the most enrichment lithofacies in the Sulige gas field. Clarifying the enrichment mechanism of high-quality lithic-rich tight sandstone is important to economic and efficient development of the tight gas reservoir. This paper introduces a new classification method, which is based on the origin of particles and interstitial materials and their control on reservoir pores growth. Lithic-rich tight sandstone can be subdivided into three types: sedimentary lithic sandstone, diagenetic lithic sandstone and event-type lithic sandstone. The genetic mechanism of a high-quality reservoir is studied by this new method. Research shows that the sedimentary lithic sandstone has high contents of plastic lithics, strong compaction effects of early diagenesis, large porosity reduction and almost no dissolution-induced porosity. The diagenetic lithic sandstone has high contents of rigid lithics and strong compaction effects. Organic acids promote alteration of a large amount of feldspars into kaolinite, while such sandstones are highly cemented. It is seen with moderate porosity reduction and moderate dissolution-attributed porosity growth. Event-type lithic sandstone also has high contents of rigid debris and strong compaction effects. Synsedimentary volcanic dust materials of subaerial deposition are altered into illite through smectite and illite-smectite mixed-layer clay under the effects of acids, which generate many pores and results in large dissolution-attributed porosity growth. Research shows that the sedimentary lithic sandstone has poor physical properties and is identified as the unfavorable reservoir; the diagenetic lithic sandstone having medium physical properties, as the relatively favorable reservoir; the event-type lithic sandstone having good physical properties, as the favorable reservoir. The research route and results have laid a solid geological foundation for better development of lithic-rich tight sandstone reservoirs.Cited as: Liu, Y., Xian, C., Li, Z., Wang, J., Ren, F. A new classification system of lithic-rich tight sandstone and its application to diagnosis high-quality reservoirs. Advances in Geo-Energy Research, 2020, 4(3): 286-295, doi: 10.46690/ager.2020.03.0

Carnosol Modulates Th17 Cell Differentiation and Microglial Switch in Experimental Autoimmune Encephalomyelitis

Medicinal plants as a rich pool for developing novel small molecule therapeutic medicine have been used for thousands of years. Carnosol as a bioactive diterpene compound originated from Rosmarinus officinalis (Rosemary) and Salvia officinalis, herbs extensively applied in traditional medicine for the treatment of multiple autoimmune diseases (1). In this study, we investigated the therapeutic effects and molecule mechanism of carnosol in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS). Carnosol treatment significantly alleviated clinical development in the myelin oligodendrocyte glycoprotein (MOG35–55) peptide-induced EAE model, markedly decreased inflammatory cell infiltration into the central nervous system and reduced demyelination. Further, carnosol inhibited Th17 cell differentiation and signal transducer and activator of transcription 3 phosphorylation, and blocked transcription factor NF-κB nuclear translocation. In the passive-EAE model, carnosol treatment also significantly prevented Th17 cell pathogenicity. Moreover, carnosol exerted its therapeutic effects in the chronic stage of EAE, and, remarkably, switched the phenotypes of infiltrated macrophage/microglia. Taken together, our results show that carnosol has enormous potential for development as a therapeutic agent for autoimmune diseases such as MS

1-[4-(4-Chloro­but­oxy)-2-hy­droxy­phen­yl]ethanone

In the title compound, C12H15ClO3, the eth­oxy group is nearly coplanar with the benzene ring, making a dihedral angle of 9.03 (4)°, and is involved in an intra­molecular O—H⋯O hydrogen bond to the neighbouring hy­droxy group

Polyaniline Nanofiber-Based Gas Sensors

There has been recent interest in conducting polymers that have very promising chemical and electrical applications. Some of these polymers have shown great potential for use in sensors.1 Polyaniline is one particular example of a prospective material. In our laboratory, we have studied the synthesis of polyaniline nanofibers. We have carried out one-pot syntheses to obtain polyaniline nanofibers in aqueous solutions where the polymerization was influenced by γ-radiation2 or UV-radiation.3 This polymer can also be patterned with an appropriate photo mask. In our present report, polyaniline nanofiber thin film sensors have been fabricated in one step by employing UV-irradiation and those sensors showed high sensitivity. Changes in conductivity were monitored with an electrometer as a function of time after the materials had been exposed to different gases. This simple gas sensing device can be used to detect many different gaseous types