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Figuring the network’s hidden abnormal behavior can reduce network vulnerability. This paper presents a detailed architecture in which the collected log data of the network can be processed and analyzed. We process and integrate on-campus network information from every router and store the integrated NetFlow log data. Ceph is used as an open-source distributed storage platform that offers high efficiency, high reliability, scalability, and preliminary preprocessing of raw data with Python, removing redundant areas and unification. In the subanalysis, we discover the anomaly event and absolute flow by three times of standard deviation rule. Keras has been used to classify in-time data collected via a cyber-attack and to construct an automatic identifier template through the Recurring Neural Network (RNN) test. The identification accuracy of the optimization model is around 98% in attack detection. Finally, in the MySQL server, the results of the real-time evaluation can be obtained, and the results of the assessment can be displayed via ECharts.

Each software always has log data. Log data is essential for developers and end-users. With log data, we can indicate the information of system error, warning events or whether our system processes are loading successfully. This paper aims to provide a virtualization platform for our campus NetFlow log data in order user can use for further analysis. Our system used Ceph storage system and ELK Stack technology. Ceph provides a vast amount of scalable storage and ELK consists of three components, namely: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search engine in which can be used for searching all kinds of documents. Logstash is used for managing centralize, transform and stash our data to Elasticsearch and Kibana is used for visualizing Elasticsearch data and an excellent tool for a real-time data analytics and decision making. Our data is continuous data. Approximately our data growth up 38 GB per day and our data have grown more than 8TB until now.

Methadone is a racemic compound composed of the R-form and S-form enantiomers. The drug is usually used in maintenance therapy for the heroin-addicted patients. In our previous study, we found that the cytochrome P-450 (CYP) isozyme 2B6 preferentially metabolizes the S-methadone enantiomer. We thus tested whether CYP2B6 gene polymorphisms had any influence on the concentration or clearance of methadone. Ten single nucleotide polymorphisms within this gene region were evaluated in 366 patients undergoing methadone maintenance for at least 3 months. The plasma steady-state levels of racemic methadone and its metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine were then measured in these individuals. The rs10403955 (T allele in intron 1), rs3745274 (G allele in exon 4), rs2279345 (T allele in intron 5), and rs707265 (A allele in exon 9) CYP2B6 allele types were found to be significantly associated with a higher clearance, a lower plasma concentration, and a lower concentration-to-dosage (C/D) ratio of (S)-methadone (P < 0.0017). Two haplotype blocks of a trinucleotide haplotype (rs8100458-rs10500282-rs10403955 in intron 1) and a hexanucleotide haplotype (rs2279342-rs3745274-rs2279343-rs2279345-rs1038376-rs707265 from intron 2 to exon 9) were constructed within CYP2B6. The major combinations of T-T-T and A-G-A-T-A-A of these particular haplotypes showed significant associations with the plasma concentrations of S-methadone and its C/D ratio (P < 0.0001, respectively). We conclude that genetic polymorphisms in the CYP2B6 gene may therefore be indicators of the clearance, plasma concentration and C/D ratio of S-methadone.

Methadone maintenance therapy is an established treatment for heroin dependence. This study tested the influence of functional genetic polymorphisms in CYP2C19 gene encoding a CYP450 enzyme that contributes to methadone metabolism on treatment dose, plasma concentration, and side effects of methadone. Two single nucleotide polymorphisms (SNPs), rs4986893 (exon 4) and rs4244285 (exon 5), were selected and genotyped in 366 patients receiving methadone maintenance therapy in Taiwan. The steady-state plasma concentrations of both methadone and its EDDP metabolite enantiomers were measured. SNP rs4244285 allele was significantly associated with the corrected QT interval (QTc) change in the electrocardiogram (p=0.021), and the Treatment Emergent Symptom Scale (TESS) total score (p=0.021) in patients who continued using heroin, as demonstrated with a positive urine opiate test. Using the gene dose (GD) models where the CYP2C19 SNPs were clustered into poor (0 GD) versus intermediate (1 GD) and extensive (2 GD) metabolizers, we found that the extensive metabolizers required a higher dose of methadone (p=0.035), and showed a lower plasma R-methadone/methadone dose ratio (p=0.007) in urine opiate test negative patients, as well as a greater QTc change (p=0.008) and higher total scores of TESS (p=0.018) in urine opiate test positive patients, than poor metabolizers. These results in a large study sample from Taiwan suggest that the gene dose of CYP2C19 may potentially serve as an indicator for the plasma R-methadone/methadone dose ratio and cardiac side effect in patients receiving methadone maintenance therapy. Further studies of pharmacogenetic variation in methadone pharmacokinetics and pharmacodynamics are warranted in different world populations.

Aim: To test whether the genetic polymorphisms within the gene encoding the UGT2B7 gene may have an impact on methadone treatment. Materials & methods: Twelve SNPs in UGT2B7 were selected. 366 methadone maintenance treatment patients in Taiwan were recruited and genotyped. Results: In a genotype recessive model, rs6600879, rs6600880, rs4554144, rs11940316, rs7438135, rs7662029, rs7668258, rs7439366, rs4292394 and rs6600893 showed significant associations with severity of withdrawal symptoms (permutation p < 0.002), pupil size (permutation p < 0.048) and tremor (permutation p < 0.008). Haplotypes of GATCAGCCGC and CTCTGATTCT were significantly associated with pupil size score and tremor score (p < 0.034). Conclusion: These results suggest that SNPs of the UGT2B7 gene may play important roles in opiate withdrawal symptoms. Original submitted 10 February 2012; Revision submitted 23 April 2012

Methadone, a synthetic racemic opioid that primarily works as a μ-opioid receptor (OPRM1) agonist, is commonly used for the treatment of heroin addiction. Genetic association studies have reported that the OPRM1 gene is involved in the physiology of heroin and alcohol addiction. Our current study is designed to test the hypothesis that genetic polymorphisms in the OPRM1 gene region are associated with methadone dosage, plasma concentrations, treatment responses, adverse reactions and withdrawal symptoms in a methadone maintenance treatment (MMT) cohort from Taiwan. Fifteen OPRM1 single nucleotide polymorphisms (SNPs) were selected and genotyped using DNA samples from 366 MMT patients. The plasma concentrations of methadone and its metabolite were measured by high performance liquid chromatography. The results obtained using dominant model analysis indicate that the OPRM1 SNPs rs1074287, rs6912029, rs12209447, rs510769, rs3798676, rs7748401, rs495491, rs10457090, rs589046, rs3778152, rs563649, and rs2075572 are significantly associated with change-in-libido side effects (adjusted p0.042). Using recessive model analysis, these SNPs were also found to be significantly associated with insomnia side effects in this cohort (p0.009). The significance of the insomnia findings was mainly contributed by a subgroup of patients who had a positive urine morphine test (p0.022), and by individuals who did not use benzodiazepine hypnotics (p0.034). Our current data thus suggest that genetic polymorphisms in OPRM1 may influence the change-in-libido and insomnia side effects sometimes found in MMT patients.

Aim: Methadone maintenance therapy is one of the standard treatments for heroin addiction. The isozyme CYP3A4 of the CYP system is one of the metabolic enzymes, as well as CYP2B6, responsible for the metabolism of methadone. The aim of the present study is to evaluate the potential use of genetic polymorphisms in CYP3A4 as biomarkers for the prediction of methadone treatment responses. Materials & methods: A total of 366 Han Chinese methadone maintenance treatment patients in Taiwan were recruited in this study. Main clinical assessments included the clinical opioid withdrawal scale (COWS), the treatment emergent symptom scale (TESS) and the plasma concentrations of methadone and its metabolites. Genetic associations of six SNPs in the CYP3A4 gene were calculated using a general linear model. Results: Genotypes and allele types of rs4646440 and rs2242480 were found to be significantly associated with the severity of withdrawal symptoms rated by COWS (p = 0.012, 0.0096, 0.017 and 0.012, respectively) as well as the side effects rated by TESS (p = 0.0089, 0.028, 0.0027 and 0.0085, respectively). The allele types associated with more severe withdrawal symptoms are also associated with more severe side effects and less betel nut (Areca catechu) use (p = 0.009 for rs4646440, p = 0.0063 for rs2242480). Further analyses on specific withdrawal symptoms in COWS showed that the genetic variants in rs4646440 are significantly associated with heart rate (allele type p = 0.0019). Conclusion: These results suggested that genetic variants in the CYP3A4 gene may be useful indicators for the severity of side effects and withdrawal symptoms for methadone treatment. Original submitted 2 May 2011; Revision submitted 8 July 2011

Telemonitoring and remote healthcare are two ICT techniques promise to deliver cost effective long-term healthcare services to the aging population worldwide. Anticipating an emerging market opportunity, NCTU Kannon project team is creating Custos, an open composeable platform for developing remote on-demand healthcare applications using smart phones and wireless sensor networks. Custos is integrated readily with Internet web services and UPnP digital-home platform so that it can be used to detect abnormal health conditions through multi-sensor data fusion, adapt environment conditions to user needs, dispatch medical alerts and instigate remedial actions via SMS/RSS communication. Moreover, Custos is easy to program because it uses Sun SPOT and Squawk Java J2ME as its sensor/actuator hub. In this position paper, we present the design principles, system architecture and operation concepts of Custos as well as a pilot plan for clinical trials in the Geriatric Psychiatry Ward of Wei-Gong Memorial Hospital in Miaoli, Taiwan.