A Supervised Embedding and Clustering Anomaly Detection method for classification of Mobile Network Faults

The paper introduces Supervised Embedding and Clustering Anomaly Detection (SEMC-AD), a method designed to efficiently identify faulty alarm logs in a mobile network and alleviate the challenges of manual monitoring caused by the growing volume of alarm logs. SEMC-AD employs a supervised embedding approach based on deep neural networks, utilizing historical alarm logs and their labels to extract numerical representations for each log, effectively addressing the issue of imbalanced classification due to a small proportion of anomalies in the dataset without employing one-hot encoding. The robustness of the embedding is evaluated by plotting the two most significant principle components of the embedded alarm logs, revealing that anomalies form distinct clusters with similar embeddings. Multivariate normal Gaussian clustering is then applied to these components, identifying clusters with a high ratio of anomalies to normal alarms (above 90%) and labeling them as the anomaly group. To classify new alarm logs, we check if their embedded vectors' two most significant principle components fall within the anomaly-labeled clusters. If so, the log is classified as an anomaly. Performance evaluation demonstrates that SEMC-AD outperforms conventional random forest and gradient boosting methods without embedding. SEMC-AD achieves 99% anomaly detection, whereas random forest and XGBoost only detect 86% and 81% of anomalies, respectively. While supervised classification methods may excel in labeled datasets, the results demonstrate that SEMC-AD is more efficient in classifying anomalies in datasets with numerous categorical features, significantly enhancing anomaly detection, reducing operator burden, and improving network maintenance

Inference of hidden structures in complex physical systems by multi-scale clustering

We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. Typically, illuminating orders are revealed by choosing parameters that lead to extremal information theory correlations.Comment: 25 pages, 16 Figures; a review of earlier work

Risk factors for antibacterial resistance of isolates producing extended-epectrum β-Lactamase in Gram Negative Bacilli of hospitalized neonates in Shahid Beheshti hospital

Background: The occurrence of isolates producing extended-spectrum β-lactamase (ESBL) has increased worldwide. Gram-negative bacilli producing the extended-spectrum β-lactamase (ESBL) are responsible for resistance against oxy-imino beta-lactames and monobactams, and may be considered as the major pathogens in the neonatal intensive care units (NICU). The purpose of this study was to determine the rate of beta-lactam antibiotic resistance in fecal flora of newborns and the risk factors leading to their colonization. Materials and Methods: This descriptive study was carried out on 167 hospitalized newborns in Shahid Beheshti Hospital in Kashan in 2006. The fecal isolated gram-negative bacilli were prepared using standard tests. The pattern of sensitivity to antibiotics and the ESBL production was investigated on isolates with the criteria suggested by Clinical Laboratory Standards Institutes (CLSI). Data were analyzed statistically by Fischer’s exact and Chi square tests. Results: Colonization of fecal flora with gram-negative microorganisms was determined in 120 stool samples. Klebsiella pneumonia, Escherichia coli, and microorganisms producing ESBL were identified in 53 (44.2%), 34 (28.3 %), and 35 (29.2%), respectively. 65.7% (23 out of 35) of microorganisms producing ESBL were K.pneumoniae. Risk factors for colonization of gram negative bacilli producing ESBL were birth weight ≤ 2500gr. (P7 days (P<0.0082), administration of cefotaxime (P<0.0247), and C-section delivery (P<0.048). Conclusion: To decrease the morbidity and mortality rates following the infection caused by ESBLs colonized in the intestine of infants, protection of normal non-pathogenic bacterial flora is important. This can be provided by the efficient application of infection control measures, and limitation of antibiotic usage to strict clinical indications

Evaluation of Streptococcal (Type B) rectal colonization incidence in pregnant women at an gestational age greater than 35 weeks and its relationship with infantile premature infection

History and Objectives: Considering the various report on incidence of Streptococcus type-B in rectum and its role in premature infantile infection and lack of information in the region and for determination of its prevalence in pregnant women, this study was carried out in Shabihkhani hospital in Kashan in 2000. Materials and Methods: The descriptive strategy of this study was conducted on 400 pregnant women at a gestational age greater than 35 weeks. For this purpose, a questionnaire was designed for collection of data including age, occupation, academic history, nationality, inhabitation, multiparous state, number of abortion, labor type and antibiotic consumption. Sampling from rectum was done using a sterile swab. Then, it was cultured in special medium and isolated bacteria were identified using biochemical tests. All of the infants up to 48h after labor and those from mothers with signs of positive colonization up to one week were followed up. From the latter group, sampling was done and the related bacteria were identified. For statistical analysis, X² and Fischer tests were used. Results: Out of 400 samples from rectum, 30 cases (7.5) with streptococcus type-B and in 2 cases (6.7) from mothers with positive culture were identified. In addition there was a relationship between streptococcus type-B rectal colonization and premature infantile premature infection (P=0.0055). Conclusion and Recommendations: Considering a 7.5 incidence of this bacterium in rectum and its relationship with type-B streptococcal rectal colonization and premature infections and its complications, it is recommended to conduct more studies in pregnant women

Therapeutic effects of all-trans retinoic acid on experimental autoimmune encephalomyelitis and its role in T-helper lymphocyte responses

Background: Recent studies have demonstrated an essential role for IL-17 in the pathogenesis of experimental autoimmune encephalomyelitis (EAE). Furthermore, it has been shown that FoxP3+Treg cells play an important role in the suppression of autoinflammatory reactions. Although, previous studies have determined the immunomodulatory potentials of all-trans-retinoic acid (ATRA), but these immunomodulations have been mostly justified by alteration in Th1/Th2 cytokines. The present study was carried out to investigate the therapeutic effects of ATRA on EAE and its effects on T-helper cells responses. Methods: EAE was induced by MOG35-55 peptide and complete Freund's adjuvant in female C57BL/6 mice. The mice were allocated to two therapeutic groups (n=7 per group). Treatment with ATRA (500 μg/mouse every other day) was initiated in treatment group on day 12 when they developed a disability score. EAE controls received vehicle alone with the same schedule. Signs of disease were recorded daily until day 33 when the mice were sacrificed. Splenocytes were tested for proliferation by MTT test, cytokine production by ELISA and FoxP3+Treg cell frequency by flowcytometry. Results: ATRA significantly reduced the clinical signs of established EAE. Aside from decreasing lymphocytic proliferation (P<0.05), ATRA significantly inhibited the production of pro-inflammatory IL-17 (P<0.005) as well as IFN-γ (P<0.0005) upon antigen-specific restimulation of splenocytes. FoxP3+Treg cell frequency and IL-10 levels were not altered significantly. However, IFN-γ to IL-10 and IL-17 to IL-10 ratios decreased significantly (P<0.0005). Conclusion: Parallel to reducing autoreactive lymphocyte proliferation and cytokine production in favor of pro-inflammatory cytokines, all-trans-retinoic acid ameliorated established experimental autoimmune encephalomyelitis

Free energy landscapes of DNA and its assemblies: perspectives from coarse-grained modelling

This chapter will provide an overview of how characterising free energy landscapes can provide insights into the biophysical properties of DNA, as well as into the behaviour of the DNA assemblies used in the field of DNA nanotechnology. The landscapes for these complex systems are accessible through the use of accurate coarse-grained descriptions of DNA. Particular foci will be the landscapes associated with DNA self-assembly and mechanical deformation, where the latter can arise from either externally imposed forces or internal stresses