Coordination mechanism of SaaS service supply chain: based on compensation contracts

Purpose: The purpose of this paper is to build new contracts theories of SaaS service supply chain. Software as a Service (SaaS) has become a hot topic in this industry . Compared with traditional manufacturing supply chain and general service supply chain, the new IT service supply chain which based on SaaS has characteristics of both service and IT. And SaaS is completely different from traditional software package model. Therefore the classic contracts, which be widely used in traditional manufacturing supply chain, can’t be directly applied in SaaS service supply chain. The necessary way of IT services developing is to study the SaaS service supply chain combining with characteristics of SaaS. Therefore, It focuses on the coordination of SaaS service supply chain. Design/methodology/approach: It tries to answer the following question: how do the ISV motivate SaaS operators to improve the service level through effective contracts mechanism under conditions of asymmetric information. In order to answer these questions, this paper does some researches including: Under the conditions of information asymmetry, supposing the service level (is related to the degree of effort) of SaaS operator was private information, we construct model of compensation contract, i.e., to motivate SaaS operator to improve service level through transfer payments of compensation price. Findings and Originality/value: The study finds out that when ISV get to “positive feedback”, instead of the traditional market equilibrium, compensation contract (linear) can coordinate satisfactorily the SaaS service supply chain. In the point of “positive feedback”, the marginal revenue equals the marginal cost, but it is not the equilibrium of ISV’profit-maximization. Research limitations/implications: There are some limitations in this research. In the linear compensation contracts, the compensation price is fixed value. If in the contract, we can create a change value which is related to the sales volume of service, the coordination efficiency of compensation will be increased. And in the future, the nonlinear compensation contracts should be researched. Practical implications: In the practical implication, it will promote the development of study and practice of SaaS and IT service industry. And it is beneficial to ISV, platform operators and customers. Originality/value: From the theoretical perspective, this paper put forward some new contracts and motivating mechanism for effective coordination of SaaS service supply chain and the conclusion will enrich content of service supply chain theory system. In theory, it has more significance for further researching on SaaS and service supply chain.Peer Reviewe

An Intelligent Trade Matching System for B2B Marketplace

With the fast growth of B2B sales, an intelligent system is greatly useful for decreasing transaction cost and increasing market efficiency on electronic platforms. In order to improve the quality of transaction processing and customer experience, this paper proposes a knowledge-based system, which employs a Case-Based Reasoning (CBR) technique for trade matching in B2B marketplace as a substitute for the manual matching process. The system function and logical architecture are discussed. And the case repository is proposed to support this CBR approach where the case representation, case base indexing, case base decomposition and the dictionary are argued in details

Next-Generation Sequencing of MicroRNAs for Breast Cancer Detection

It is reported that different microRNA (miRNA) profiles can be detected in the blood of cancer patients. We investigated that whether the key serum miRNAs could discriminate patients with and without breast cancer. This study was divided into three parts: (1) miRNA marker discovery using SOLiD sequencing-based miRNA profiling on cancerous and adjacent noncancerous breast tissue of one breast cancer patient; (2) marker selection and validation by real-time PCR on a small set of serum; (3) gene ontology analysis of the key miRNA target genes. Of genome-wide tissue miRNA expression analysis, five miRNAs were found to be altered more than fivefold by SOLiD sequencing (i.e., miR-29a, miR-23a, miR-23b, miR-192, and miR-21). All the five miRNAs were validated on the 20 breast cancer patients and 20 controls. miR-29a and miR-21 were significantly increased in the serum of breast cancer patients (P < .05). Gene ontology analysis of the target genes revealed enrichment for special biological process categories, that is, signal transduction, development, apoptosis, cell proliferation, and cell adhesion. SOLiD sequencing provides a promising method for cancer-related miRNA profiling. Serum miRNAs may be useful biomarkers for breast cancer detection

Graphene oxide membranes using MOF@Chitosan core-shell nanoparticles as dual modulators for dye separation

Graphene oxide (GO) membranes hold significant promise for the water purification. However, they also face the problem of structural swelling, which limits their use in water treatment applications. In this work, a novel dual-modulated core-shell metal-organic framework@Chitosan (MOF@CS) was successfully synthesized and used as an intercalation cross-linker to optimize the interlayer spacing and stability of GO membranes. Molecular dynamics simulation confirms that MOF@CS, acting as an intercalator, accelerates the water diffusion rate within the channels of the GO layer compared to a pure GO layer. At the same time, Fourier Transform Infrared Spectroscopy analysis reveals that MOF@CS serves as a cross-linker for covalently cross-linking the GO layer. The nanofiltration performance and stability of the improved MOF@CS-GO composite membranes were significantly enhanced. Compared to the pure GO membranes, the MOF@CS-GO composite membranes exhibited enhanced Congo red rejection rates (from 76.5% to 95.6%) while maintaining a high pure water flux (34.5 L·m-2·h-1·bar-1) and good structural stability (stable dye removal performance over 120 h). This dual regulation strategy is expected to effectively solve the swelling problem of GO membranes in aqueous media and open up avenues for advancing their performance

Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry-P\'erot laser with saturable absorber

Photonic neuromorphic computing has emerged as a promising avenue toward building a low-latency and energy-efficient non-von-Neuman computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. However, the nonlinear computation of PSNN remains a significant challenging. Here, we proposed and fabricated a photonic spiking neuron chip based on an integrated Fabry-P\'erot laser with a saturable absorber (FP-SA) for the first time. The nonlinear neuron-like dynamics including temporal integration, threshold and spike generation, refractory period, and cascadability were experimentally demonstrated, which offers an indispensable fundamental building block to construct the PSNN hardware. Furthermore, we proposed time-multiplexed spike encoding to realize functional PSNN far beyond the hardware integration scale limit. PSNNs with single/cascaded photonic spiking neurons were experimentally demonstrated to realize hardware-algorithm collaborative computing, showing capability in performing classification tasks with supervised learning algorithm, which paves the way for multi-layer PSNN for solving complex tasks.Comment: 10 pages, 8 figure

Genome-wide analysis of plant nat-siRNAs reveals insights into their distribution, biogenesis and function

Background: Many eukaryotic genomes encode cis-natural antisense transcripts (cis-NATs). Sense and antisense transcripts may form double-stranded RNAs that are processed by the RNA interference machinery into small interfering RNAs (siRNAs). A few so-called nat-siRNAs have been reported in plants, mammals, Drosophila, and yeasts. However, many questions remain regarding the features and biogenesis of nat-siRNAs. Results: Through deep sequencing, we identified more than 17,000 unique siRNAs corresponding to cis-NATs from biotic and abiotic stress-challenged Arabidopsis thaliana and 56,000 from abiotic stress-treated rice. These siRNAs were enriched in the overlapping regions of NATs and exhibited either site-specific or distributed patterns, often with strand bias. Out of 1,439 and 767 cis-NAT pairs identified in Arabidopsis and rice, respectively, 84 and 119 could generate at least 10 siRNAs per million reads from the overlapping regions. Among them, 16 cis-NAT pairs from Arabidopsis and 34 from rice gave rise to nat-siRNAs exclusively in the overlap regions. Genetic analysis showed that the overlapping double-stranded RNAs could be processed by Dicer-like 1 (DCL1) and/or DCL3. The DCL3-dependent nat-siRNAs were also dependent on RNA-dependent RNA polymerase 2 (RDR2) and plant-specific RNA polymerase IV (PoIIV), whereas only a fraction of DCL1-dependent nat-siRNAs was RDR- and PoIIV-dependent. Furthermore, the levels of some nat-siRNAs were regulated by specific biotic or abiotic stress conditions in Arabidopsis and rice. Conclusions: Our results suggest that nat-siRNAs display distinct distribution patterns and are generated by DCL1 and/or DCL3. Our analysis further supported the existence of nat-siRNAs in plants and advanced our understanding of their characteristics.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000308544200005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Biotechnology &amp; Applied MicrobiologyGenetics &amp; HereditySCI(E)48ARTICLE3null1

Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls

BackgroundThis study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls.MethodsA total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set.ResultsThe final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients.ConclusionThe radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool

The Protective Role of Hyaluronic Acid in Cr(VI)-Induced Oxidative Damage in Corneal Epithelial Cells

Cr(VI) exposure could produce kinds of intermediates and reactive oxygen species, both of which were related to DNA damage. Hyaluronan (HA) has impressive biological functions and was reported to protect corneal epithelial cells against oxidative damage induced by ultraviolet B, benzalkonium chloride, and sodium lauryl sulfate. So the aim of our study was to investigate HA protection on human corneal epithelial (HCE) cells against Cr(VI)-induced toxic effects. The HCE cell lines were exposed to different concentrations of K2Cr2O7 (1.875, 3.75, 7.5, 15.0, and 30 μM) or a combination of K2Cr2O7 and 0.2% HA and incubated with different times (15 min, 30 min, and 60 min). Our data showed that Cr(VI) exposure could cause decreased cell viability, increased DNA damage, and ROS generation to the HCE cell lines. But incubation of HA increased HCE cell survival rates and decreased DNA damage and ROS generation induced by Cr(VI) in a dose- and time-dependent manner. We report for the first time that HA can protect HCE cells against the toxicity of Cr(VI), indicating that it will be a promising therapeutic agent to corneal injuries caused by Cr(VI)