JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution

Recent years have witnessed a rapid growth of deep-network based services and applications. A practical and critical problem thus has emerged: how to effectively deploy the deep neural network models such that they can be executed efficiently. Conventional cloud-based approaches usually run the deep models in data center servers, causing large latency because a significant amount of data has to be transferred from the edge of network to the data center. In this paper, we propose JALAD, a joint accuracy- and latency-aware execution framework, which decouples a deep neural network so that a part of it will run at edge devices and the other part inside the conventional cloud, while only a minimum amount of data has to be transferred between them. Though the idea seems straightforward, we are facing challenges including i) how to find the best partition of a deep structure; ii) how to deploy the component at an edge device that only has limited computation power; and iii) how to minimize the overall execution latency. Our answers to these questions are a set of strategies in JALAD, including 1) A normalization based in-layer data compression strategy by jointly considering compression rate and model accuracy; 2) A latency-aware deep decoupling strategy to minimize the overall execution latency; and 3) An edge-cloud structure adaptation strategy that dynamically changes the decoupling for different network conditions. Experiments demonstrate that our solution can significantly reduce the execution latency: it speeds up the overall inference execution with a guaranteed model accuracy loss.Comment: conference, copyright transfered to IEE

Design, synthesis and antifungal activity of novel 1,4-benzoxazin-3-one derivatives containing an acylhydrazone moiety

A series of 1,4-benzoxazin-3-one derivatives containing an acylhydrazone moiety were designed, synthesized and evaluated for their in vitro antifungal activities against Gibberella zeae, Pellicularia sasakii, Phytophthora infestans, Capsicum wilt, and Phytophthora capsica. The structures of target compounds were characterized by 1H NMR, 13H NMR, 19F NMR and HRMS. The preliminary antifungal evaluation of all target compounds showed that some target compounds possessed moderate to good activities against G. zeae, P. sasakii, P. infestans and C. wilt. Among them, compounds 5L and 5o exhibited noticeable inhibition effects against G. zeae with the EC50 values (effective concentration for 50% activity) of 20.06 and 23.17 μg/ml, respectively, which were even nearly double effective than that of hymexazol (40.51 μg/ml). Meanwhile, compound 5q displayed a notable inhibitory effect toward P. sasakii, with the EC50 value of 26.66 μg/ml, which was better than that of hymexazol (32.77 μg/ml). In addition, compound 5r yielded the EC50 value of 15.37 μg/ml against P. infestans, which was less than those of hymexazol (18.35 μg/ml) and carbendazim (34.41 μg/ml). Eventually, compound 5p showed higher inhibitory effect against C. wilt, with EC50 value of 26.76 μg/ml, which was better than that of hymexazol (>50 μg/ml)

Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data

We introduce the Salesforce CausalAI Library, an open-source library for causal analysis using observational data. It supports causal discovery and causal inference for tabular and time series data, of both discrete and continuous types. This library includes algorithms that handle linear and non-linear causal relationships between variables, and uses multi-processing for speed-up. We also include a data generator capable of generating synthetic data with specified structural equation model for both the aforementioned data formats and types, that helps users control the ground-truth causal process while investigating various algorithms. Finally, we provide a user interface (UI) that allows users to perform causal analysis on data without coding. The goal of this library is to provide a fast and flexible solution for a variety of problems in the domain of causality. This technical report describes the Salesforce CausalAI API along with its capabilities, the implementations of the supported algorithms, and experiments demonstrating their performance and speed. Our library is available at \url{https://github.com/salesforce/causalai}

Analysis of geothermal potential in Hangjiahu area based on remote sensing and geographic information system

Geothermal resources are one of the most valuable renewable energy sources because of their stability, reliability, cleanliness, safety and abundant reserves. Efficient and economical remote sensing and GIS (Geographic Information System) technology has high practical value in geothermal resources exploration. However, different study areas have different geothermal formation mechanisms. In the process of establishing the model, which factors are used for modeling and how to quantify the factors reasonably are still problems to be analyzed and studied. Taking Hangjiahu Plain of Zhejiang Province as an example, based on geothermal exploration and remote sensing interpretation data, the correlation between the existing geothermal hot spots and geothermal related factors was evaluated in this paper, such as lithology, fault zone distance, surface water system and its distance, seismic point distance, magmatic rock and volcanic rock distance, surface water, farmland, woodland temperature and so on. The relationship between geothermal potential and distribution characteristics of surface thermal environment, fault activity, surface water system and other factors was explored. AHP (Analytic Hierarchy Process) and BP (Back Propagation) neural network were used for establishing geothermal potential target evaluation models. The potential geothermal areas of Hangjiahu Plain were divided into five grades using geothermal exploration model, and most geothermal drilling sites were distributed in extremely high potential areas and high potential areas. The results show that it is feasible to analyze geothermal potential targets using remote sensing interpretation data and geographic information system analysis databased on analytic hierarchy process analytic hierarchy process and back propagation neural network, and the distribution characteristics of surface thermal environment, fault activity, surface water system and other related factors are also related to geothermal distribution. The prediction results of the model coincide with the existing geothermal drilling sites, which provides a new idea for geothermal exploration

Permo-Triassic detrital records of South China and implications for the Indosinian events in East Asia

This work was supported by the National Natural Science Foundation of China (Grant No. 41602105, 41672106 and 41530966) and China Postdoctoral Science Foundation (Grant No. 2016M590655), the Fundamental Research Funds for the Central Universities, Ocean University of China. Peter Cawood acknowledges support from the Australian Research Council grant FL160100168.Provenance analyses of Lower to Middle Triassic strata from the Greater Youjiang Basin along with the Permian strata of Hainan Island, provide a record of the collisional assembly of the South China Craton and Indochina Block and their incorporation into Asia. Detrital zircons from Lower and Middle Triassic samples show similar overall age spectra ranging from Archean to Triassic with major age groups at 300–250 Ma, 480–420 Ma, and 1200–900 Ma, as well as at 400–300 Ma in one Triassic sample. Permian siltstones from Hainan Island, to the southeast of the Greater Youjiang Basin, record different age spectra with major age groups at 400–300 Ma and 530–420 Ma and subordinate components at 1200–900 Ma and 1900–1700 Ma. These age data in combination with available paleocurrent data and regional geological relations suggest that Precambrian detrital zircons were derived from the Precambrian basement or recycled from the overlying early Paleozoic sedimentary rocks that contain Precambrian detritus. Early Paleozoic detrital zircons were derived from igneous rocks in the South China Craton. Devonian-Triassic detrital zircons in the Triassic strata were likely sourced from coeval magmatic activity related to closure of Paleo-Tethys branch ocean that lay to the southwest, whereas 400–300 Ma detrital zircons in the Permian siltstones of Hainan Island were likely derived from a Paleozoic magmatic arc source that extended along the eastern-southeastern margin of China from Hainan Island to Japan in response to subduction of the Paleo-Pacific oceanic crust. Detrital zircon, trace element, and sandstone modal data for Permo-Triassic strata from the Greater Youjiang Basin indicate that the basin evolved from a trailing-edge passive margin setting to a peripheral foreland basin during closure of the Paleo-Tethys Ocean and collision between Indochina and South China. The initiation time of the foreland basin decreases from southeast to southwest across the basin, probably reflecting oblique collision. In contrast, the Permian strata on Hainan Island record a provenance history distinct from the Greater Youjiang Basin, which is related to late Paleozoic to Mesozoic subduction of the Paleo-Pacific Plate beneath South China.PostprintPeer reviewe

Direct imaging of fluorescence enhancement in the gap between two gold nanodisks

We present an analysis of the optical coupling between two gold nanodisks by near-field fluorescence microscopy. This is achieved by simultaneously scanning and measuring the light emitted by a single Er3þ/Yb3þ doped nanocrystal glued at the end of an atomic force microscope tip. The excitation of the nanocrystal was performed at k ¼ 975 nm via upconversion, and fluorescence was detected in the visible part of the spectrum at k ¼ 550 nm. For an isolated nanodisk, the near-field presents a two-lobe pattern oriented along the direction of the incident polarization. For two nanodisks with a sizable separation distance (385 nm) illuminated with the polarization along the interparticle axis, we observe a negative effect of the coupling with a slight decrease in fluorescence in the gap. For smaller gap values (195, 95, and 55 nm), a strong increase in fluorescence is observed as well as a reduced spatial localization of the field as the distance decreases. Finally, when the disks touch each other (0 nm), the dipolar–dipolar interaction between them disappears and no fluorescence enhancement occurs. A new plasmon mode is created at another wavelength. Our experimental results are in good agreement with numerical simulations of the nearfield intensity distribution at the excitation wavelength on the surface of the structures. Combining fluorescence mapping and far-field scattering spectroscopy should be of strong interest to develop bio-chemical sensors based on field enhancement effects.The authors thank the support from the DIM Nano-K program from “Region Ile de France,” from the Idex Paris Sciences & Lettres through Grant No. ANR-10-IDEX-0001-02 PSL from the CNRS and the CSIC through the Spanish-French program PICS (Grant Nos. SolarNano PICS07687 and PIC2016FR2), and from the Spanish Ministerio de Ciencia e Innovacion through Grant No. PID2019-109905GA-C22.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Transcriptomic Response to Nitric Oxide Treatment in Larix olgensis Henry

Larix olgensis Henry is an important coniferous species found in plantation forests in northeastern China, but it is vulnerable to pathogens. Nitric oxide (NO) is an important molecule involved in plant resistance to pathogens. To study the regulatory role of NO at the transcriptional level, we characterized the transcriptomic response of L. olgensis seedlings to sodium nitroprusside (SNP, NO donor) using Illumina sequencing and de novo transcriptome assembly. A significant number of putative metabolic pathways and functions associated with the unique sequences were identified. Genes related to plant pathogen infection (FLS2, WRKY33, MAPKKK, and PR1) were upregulated with SNP treatment. This report describes the potential contribution of NO to disease resistance in L. olgensis as induced by biotic stress. Our results provide a substantial contribution to the genomic and transcriptomic resources for L. olgensis, as well as expanding our understanding of the involvement of NO in defense responses at the transcriptional level