Real-time RT-PCR Assay for the detection of Tahyna Virus

A real-time RT-PCR （RT-qPCR） assay for the detection of Tahyna virus was developed to monitor Tahyna virus infection in field-collected vector mosquito samples. The targets selected for the assay were S segment sequences encoding the nucleocapsid protein from the Tahyna virus. Primers and probes were selected in conserved regions by aligning genetic sequences from various Tahyna virus strains available from GenBank. The sensitivity of the RT-qPCR approach was compared to that of a standard plaque assay in BHK cells. RT-qPCR assay can detect 4.8 PFU of titrated Tahyna virus. Assay specificities were determined by testing a battery of arboviruses, including representative strains of Tahyna virus and other arthropod-borne viruses from China. Seven strains of Tahyna virus were confirmed as positive; the other seven species of arboviruses could not be detected by RT-qPCR. Additionally, the assay was used to detect Tahyna viral RNA in pooled mosquito samples. The RT-qPCR assay detected Tahyna virus in a sensitive, specific, and rapid manner; these findings support the use of the assay in viral surveillance.

Real-time RT-PCR Assay for the Detection of Culex flavivirus

Based on the Culex flavivirus (CxFV) E gene sequences in GenBank, CxFV-specific primers and probes were designed for real-time reverse transcription-polymerase chain reaction (RT-qPCR). The specificity test revealed that CxFV could be detected using RT-qPCR with the specific CxFV primers and probes; other species of arboviruses were not detected. The stability test demonstrated a coefficient of variation of <1.5%. A quantitative standard curve for CxFV RT-qPCR was established. Quantitative standard curve analysis revealed that the lower detection limit of the RT-qPCR system is 100 copies/mu L. Moreover, RT-qPCR was used to detect CxFV viral RNA in mosquito pool samples. In conclusion, we established a real-time RT-PCR assay for CxFV detection, and this assay is more sensitive and efficient than general RT-PCR. This technology may be used to monitor changes in the environmental virus levels.

Multiple reaction monitoring for the detection of disease-related synaptic proteins

Synaptic dysfunction occurs early in Alzheimer＇s disease （AD） and is acknowledged as a primary pathologic target for treatment. Synaptic degeneration is the pathological feature most strongly correlated with loss of cognitive function ante mortern （Terry et al., 1991）. Synapses are heavily damaged in hippocampal and neocortical regions of AD brain, whereas motor and occipital cortices are relatively spared （Honer et al., 1992）. Despite extensive work, the molecular mechanisms underlying synaptic degeneration are largely unknown.

An Efficient Stabbing Based Intrusion Detection Framework for Sensor Networks

Intelligent Intrusion Detection System(IIDS)for networks provide a resourceful solution to network security than conventional intrusion defence mechanisms like a firewall.The efficiency of IIDS highly relies on the algorithm performance.The enhancements towards these methods are utilized to enhance the classification accuracy and diminish the testing and training time of these algorithms.Here,a novel and intelligent learning approach are known as the stabbing of intrusion with learning framework(SILF),is proposed to learn the attack features and reduce the dimensionality.It also reduces the testing and training time effectively and enhances Linear Support Vector Machine(l-SVM).It constructs an auto-encoder method,an efficient learning approach for feature construction unsupervised manner.Here,the inclusive certified signature(ICS)is added to the encoder and decoder to preserve the sensitive data without being harmed by the attackers.By training the samples in the preliminary stage,the selected features are provided into the classifier(lSVM)to enhance the prediction ability for intrusion and classification accuracy.Thus,the model efficiency is learned linearly.The multi-classification is examined and compared with various classifier approaches like conventional SVM,Random Forest(RF),Recurrent Neural Network(RNN),STL-IDS and game theory.The outcomes show that the proposed l-SVM has triggered the prediction rate by effectual testing and training and proves that the model is more efficient than the traditional approaches in terms of performance metrics like accuracy,precision,recall,F-measure,pvalue,MCC and so on.The proposed SILF enhances network intrusion detection and offers a novel research methodology for intrusion detection.Here,the simulation is done with a MATLAB environment where the proposed model shows a better trade-off compared to prevailing approaches.

Identifying Money Laundering Process Using Indicators： The Case of Albania

The main purpose of this study is to develop a mathematical model for calculating the probability of money laundering process, by monitoring the behavior of the client using 70 indicators of money laundering. The scientific method used in this study （received from the Modern Criminology） has great investigative power and it is widely applicable. Hopefully the practical application of this study will increase greatly the probability of detection and punishment of the clients who are implicated in the process of money laundering. In particular, this study will be useful for banks, Financial Intelligence Unit （FIU） of Albania, Department of Economic Crime at the Ministry of Domestic Affairs and Albanian State Intelligence Service （SIS）. Also, the investigation of money laundering will be a useful tool to detect other crimes, such as drug trafficking, human trafficking, illegal arms trade, etc. The prevention of money laundering is simultaneously a powerful strike against terrorism both on national and international levels.

Noise suppression for the detection laser of a nuclear magnetic resonance gyroscope based on a liquid crystal variable retarder

Nuclear magnetic resonance gyroscopes （NMRGs） are a kind of rotation-speed sensor that senses the angular velocity by measuring a frequency shift in the Larmor pre- cession of the nuclear spin in a constant magnetic field.

Clinical utility of whole genome sequencing for the detection of mitochondrial genome mutations

Genetic mitochondrial disorders are a heterogenous group of multi-system disorders caused by an imbalance in mitochondrial function(Moggio et al.,2014;Wallace,2018).In contrast to the nuclear genome,each cell contains hundreds,or even thousands,of mtDNA molecules(Veltri et al.,1990;Calvo et al.,2006).Thus,a mixture of different mtDNA sequences can co-exist within the same individual,a situation referred to as he terop las my.The level of heteroplasmy in an individual often affects the penetrance and phenotypic severity of the diseases.Consequently,detection of sequence heteroplasmy is essential for the proper clinical interpretation of mitochondrial diseases(Stewart and Chinnery,2015).

Application of Conglutinin-ELISA for the detection of Circulating Immune Complexes in Sera of Patients with Epidemic Hemorrhagic Fever.

Conglutinin was extracted and purified from bovine’s sera and was used in ELISA for the detection of circulating immune complexes in the sera of patients suffering from epidemic hemorrhagic fever (EHF). The detected rates of circu-

The detection of carbon monoxide in an extremely metal-poor galaxy

Subject Code:A03A Chinese team led by Prof.Shi Yong(施勇)at the School of Astronomy and Space Science,Nanjing University,reported the first detection of emission from carbon monoxide in an extremely metal-poor galaxy,which was published in Nature Communication(2016,7:13789).This work is under the support by the National Natural Science Foundation of China.

Detection of Magnetic Field Gradient and Single Spin Using Optically Levitated Nano-Particle in Vacuum

Optically levitated nano-particle with spins is a promising system for high-precision measurement and quantum information processing. We theoretically analyze the ratio between the fluctuation of particle's displacement caused by spins in magnetic field and caused by molecular collisions of the residual air. When the ratio is larger than unity, the displacement fluctuation of spins flipping can be remarkably detected. By theoretical analysis and numerical simulation, we propose and validate a scheme for the detection of gradient of the magnetic field by levitating ferromagnetic nano-particle, and also put forward a realizable detection scheme of the single spin by levitating nano-diamond particle with single nitrogen-vacancy(NV) centers.