A
bstract
To sum high-energy leading logarithms in a consistent way, one has to impose the strong ordering in both projectile rapidity and dense target rapidity simultaneously, which results in a ...kinematically improved Balitsky-Kovchegov (BK) equation. We find that beyond this strong ordering region, the important sub-leading double logarithms arise at high order due to the incomplete cancellation between real corrections and virtual corrections in a t-channel calculation. Based on this observation, we further argue that these double logarithms are the Sudakov type ones, and thus can be resummed into an exponential leading to a Sudakov suppressed BK equation.
Abstract
Background
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel β-coronavirus, causes severe pneumonia and has spread throughout the globe rapidly. The disease associated ...with SARS-CoV-2 infection is named coronavirus disease 2019 (COVID-19). To date, real-time reverse-transcription polymerase chain reaction (RT-PCR) is the only test able to confirm this infection. However, the accuracy of RT-PCR depends on several factors; variations in these factors might significantly lower the sensitivity of detection.
Methods
In this study, we developed a peptide-based luminescent immunoassay that detected immunoglobulin (Ig)G and IgM. The assay cutoff value was determined by evaluating the sera from healthy and infected patients for pathogens other than SARS-CoV-2.
Results
To evaluate assay performance, we detected IgG and IgM in the sera from confirmed patients. The positive rate of IgG and IgM was 71.4% and 57.2%, respectively.
Conclusions
Therefore, combining our immunoassay with real-time RT-PCR might enhance the diagnostic accuracy of COVID-19.
A peptide-based magnetic chemiluminescence enzyme immunoassay for the detection of SARS-CoV-2 antibodies was developed; 71.4% (197 of 276) and 57.2% (158 of 276) of the COVID-19 inpatients were positive for IgG and IgM against SARS-CoV-2.
Conventional intrusion detection systems based on supervised learning techniques require a large number of samples for training, while in some scenarios, such as zero-day attacks, security agencies ...can only intercept a limited number of shots of malicious samples. Therefore, there is a need for few-shot detection. In this paper, a detection method based on a meta-learning framework is proposed for this purpose. The proposed method can be used to distinguish and compare a pair of network traffic samples as a basic task of learning, including a normal unaffected sample and a malicious one. To accomplish this task, we design a deep neural network (DNN) named FC-Net, which mainly comprises two parts: feature extraction network and comparison network. FC-Net learns a pair of feature maps for classification from a pair of network traffic samples, then compares the obtained feature maps, and finally determines whether the pair of samples belongs to the same type. To evaluate the proposed detection method, we construct two datasets for few-shot network intrusion detection based on real network traffic data sources, using a specifically developed approach. The experimental results indicate that the proposed detection method is universal and is not limited to specific datasets or attack types. Training and testing on the same datasets demonstrate that the proposed method can achieve the average detection rate up to 98.88%. The outcome of training on one dataset and testing on the other one confirms that the proposed method can achieve better performance. In a few-shot scenario, malicious samples in an untrained dataset can be detected successfully, and the average detection rate is up to 99.62%.
Rapid, sensitive, point-of-care detection of bacteria is extremely important in food safety. To address this requirement, we developed a new surface-enhanced Raman scattering (SERS)-based lateral ...flow (LF) strip biosensor combined with recombinase polymerase amplification (RPA) for simultaneous detection of Listeria monocytogenes and Salmonella enterica serotype Enteritidis. AuMBA@Ag core–shell nanoparticles were used in this SERS-LF. Highly sensitive quantitative detection is achieved by measuring the characteristic peak intensities of SERS tags. Under optimal conditions, the SERS intensities of MBA at 1077 cm–1 on test lines are used to measure S. Enteritidis (y = 1980.6x – 539.3, R 2 = 0.9834) and L. monocytogenes (y = 1696.0x – 844, R 2 = 0.9889), respectively. The limit of detection is 27 CFU/mL for S. Enteritidis and 19 CFU/mL for L. monocytogenes. Significantly, this SERS-LF has high specificity and applicability in the detection of L. monocytogenes and S. Enteritidis in food samples. Therefore, the SERS-LF is a feasible method for the rapid and quantitative detection of a broad range of bacterial pathogens in real food samples.
Tear is an accessible fluid for exploring biomarkers of dry eye disease. This study describes a fast proteomic method by LC-Q-orbitrap-MS analysis with in-strip digestion and investigates the tear ...proteome of dry eye patients. Schirmer's strips were used for collection of tear fluid from patients. These strips were cut into pieces and directly digested with trypsin before mass spectrometry analysis. The data showed that more than 50 proteins were found in tear fluid from dry eye patients. Gene Ontology (GO) annotation showed that most of proteins were transfer/carrier proteins, hydrolyses, enzyme modulators and signaling molecules. Targeted proteomics strategy revealed that 18 proteins were differentially expressed in dry eye patients. Furthermore, it was showed that the common post-translational modification in tear proteins is deamidation of Asn.
Merkel cell carcinoma (MCC) is a neuroendocrine carcinoma originating in the skin. Studies are needed to determine the mechanisms of immune escape in patients with MCC, and malignant cell conditions ...that promote immune evasion. We used Single-cell RNA sequencing (scRNA-seq) to determine cellular features associated with MCC disease trajectory. A longitudinal multi-omics study was performed using scRNA-seq data of peripheral blood harvested from four-time points. Six major cell types and fifteen cell subgroups were identified and confirmed their presence by expression of characteristic markers. The expression patterns and specific changes of different cells at different time points were investigated. Subsequently, bulk RNA data was used to validate key findings. The dynamic characteristics of the cells were identified during the critical period between benign improvement and acquisition of resistance. Combined with the results of the validation cohort, the resistance program expressed in the relapse stage is mainly associated with T cell exhaustion and immune cell crosstalk disorder. Coinciding with immune escape, we also identified a decrease non-classical monocytes and an expansion of classical monocytes with features of high inflammation and immune deficiency. Changes in cellular status, such as depletion of T cells and dysregulation of B cell proliferation and differentiation, may lead to drug resistance in MCC patients. Meanwhile, the widespread decreased antigen presentation ability and immune disorders caused by deletion of MHC class II gene expression should not be ignored.
Although the coupling of GC/MS with atmospheric pressure ionization (API) has been reported in 1970s, the interest in coupling GC with atmospheric pressure ion source was expanded in the last decade. ...The demand of a “soft” ion source for preserving highly diagnostic molecular ion is desirable, as compared to the “hard” ionization technique such as electron ionization (EI) in traditional GC/MS, which fragments the molecule in an extensive way. These API sources include atmospheric pressure chemical ionization (APCI), atmospheric pressure photoionization (APPI), atmospheric pressure laser ionization (APLI), electrospray ionization (ESI) and low temperature plasma (LTP). This review discusses the advantages and drawbacks of this analytical platform. After an introduction in atmospheric pressure ionization the review gives an overview about the history and explains the mechanisms of various atmospheric pressure ionization techniques used in combination with GC such as APCI, APPI, APLI, ESI and LTP. Also new developments made in ion source geometry, ion source miniaturization and multipurpose ion source constructions are discussed and a comparison between GC-FID, GC-EI-MS and GC-API-MS shows the advantages and drawbacks of these techniques. The review ends with an overview of applications realized with GC-API-MS.
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•Atmospheric pressure ion sources (APCI, ESI, APPI, APLC etc) enable the coupling of LC-based high-end MS to GC.•APIs show advantages in selectivity and sensitivity compared with EI in GC-MS.•Accurate mass database in GC-APCI/MS is emerging as an alternative to GC-EI/MS database.
The development of sharing technology makes it possible for expensive lower limb exoskeleton robots to be extensively employed. However, due to the uniqueness of gait pattern, it is challenging for ...lower limb exoskeleton robot to adapt to different wearers' gait patterns. Studies have shown that the gait pattern is affected by many physical factors. This paper proposes an individualized gait pattern generation (IGPG) method for sharing lower limb exoskeleton (SLEX) robot. First, the gait sequences are parameterized to extract gait features. Then, the Gaussian process regression with automatic relevance determination is used to establish the mapping relationships between the body parameters and the gait features, and the weights of each body parameters on gait pattern are also given. The gait features of an unknown subject can be predicted based on the training set. Finally, the individualized gait pattern is reconstructed by autoencoder neural network and scaling process based on predicted gait features. The experimental results show that the gait pattern predicted by IGPG is very similar to the subject's actual trajectory and has been successfully applied on the SLEX robot. With the help of sharing technology, the training set will be increased, and the prediction accuracy of individualized gait pattern will also be improved. Note to Practitioners -The main purpose of this paper is to solve the gait pattern mismatch problem when different people wear an lower limb exoskeleton robot. The gait patterns are different for each individual, and the main gait-related factors include body parameters and walking speed (WS). Therefore, the suitable gait pattern for the wearer is predicted according to their body parameters and target WS in this paper. The detailed prediction process and a full analysis of experimental results are also given. Finally, the generated gait patterns are successfully verified on the lower limb exoskeleton robot.
A novel nitrogen doped hybrid material composed of in situ‐formed graphene natively grown on hierarchical ordered porous carbon is prepared, which successfully combines the advantages of both ...materials, such as high surface area, high mass transfer, and high conductivity. The outstanding structural properties of the resultant material render it an excellent metal‐free catalyst for electrochemical oxygen reduction.
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