An investigation into the recurring patterns of forex time series data

Countless theories have been developed by both researchers and financial analyst in an attempt to explain the fluctuation of forex price. By obtaining an intimate understanding of the forex market, traders will hopefully be able to forecast and react to forex price oscillations on-the-fly towards making a profitable investment. In this paper, an investigation into the underlying theory that there exists repeating patterns within the time series data which forms the basis of technical analysis is conducted. The assumption that certain patterns do develop over time and the forex market does not fluctuate in a random manner is used to establish the fact that history repeats itself in forex trading. The patterns and repetitions unveiled within the forex historical data would be an important element for forex forecasting

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Foreign currency exchange rate prediction using neuro-fuzzy systems

The complex nature of the foreign exchange (FOREX) market along with the increased interest towards the currency exchange market has prompted extensive research from various academic disciplines. With the inclusion of more in-depth analysis and forecasting methods, traders will be able to make an informed decision when trading. Therefore, an approach incorporating the use of historical data along with computational intelligence for analysis and forecasting is proposed in this paper. Firstly, the Gaussian Mixture Model method is applied for data partitioning on historical observations. While the antecedent part of the neuro-fuzzy system of AnYa type is initialised by the partitioning result, the consequent part is trained using the fuzzily weighted RLS algorithm based on the same data. Numerical examples based on the real currency exchange data demonstrated that the proposed approach trained with historical data produce promising results when used to forecast the future foreign exchange rates over a long-term period. Although implemented in an offline environment, it could potentially be utilised in real-time application in the future

Immunodominant IgM and IgG Epitopes Recognized by Antibodies Induced in Enterovirus A71-Associated Hand, Foot and Mouth Disease Patients

<div><p>Enterovirus A71 (EV-A71) is one of the main causative agents of hand, foot and mouth disease (HFMD). Unlike other enteroviruses that cause HFMD, EV-A71 is more frequently associated with severe neurological complications and fatality. To date, no effective licensed antivirals are available to combat EV-A71 infection. Little is known about the immunogenicity of viral non-structural proteins in humans. Previous studies have mainly focused on characterization of epitopes of EV-A71 structural proteins by using immunized animal antisera. In this study, we have characterized human antibody responses against the structural and non-structural proteins of EV-A71. Each viral protein was cloned and expressed in either bacterial or mammalian systems, and tested with antisera by western blot. Results revealed that all structural proteins (VP1-4), and non-structural proteins 2A, 3C and 3D were targets of EV-A71 IgM, whereas EV-A71 IgG recognized all the structural and non-structural proteins. Sixty three synthetic peptides predicted to be immunogenic <i>in silico</i> were synthesized and used for the characterization of EV-A71 linear B-cell epitopes. In total, we identified 22 IgM and four IgG dominant epitopes. Synthetic peptide PEP27, corresponding to residues 142–156 of VP1, was identified as the EV-A71 IgM-specific immunodominant epitope. PEP23, mapped to VP1 41–55, was recognized as the EV-A71 IgG cross-reactive immunodominant epitope. The structural protein VP1 is the major immunodominant site targeted by anti-EV-A71 IgM and IgG antibodies, but epitopes against non-structural proteins were also detected. These data provide new understanding of the immune response to EV-A71 infection, which benefits the development of diagnostic tools, potential therapeutics and subunit vaccine candidates.</p></div

Foreign currency exchange rate prediction using neuro-fuzzy systems

The complex nature of the foreign exchange (FOREX) market along with the increased interest towards the currency exchange market has prompted extensive research from various academic disciplines. With the inclusion of more in-depth analysis and forecasting methods, traders will be able to make an informed decision when trading. Therefore, an approach incorporating the use of historical data along with computational intelligence for analysis and forecasting is proposed in this paper. Firstly, the Gaussian Mixture Model method is applied for data partitioning on historical observations. While the antecedent part of the neuro-fuzzy system of AnYa type is initialised by the partitioning result, the consequent part is trained using the fuzzily weighted RLS algorithm based on the same data. Numerical examples based on the real currency exchange data demonstrated that the proposed approach trained with historical data produce promising results when used to forecast the future foreign exchange rates over a long-term period. Although implemented in an offline environment, it could potentially be utilised in real-time application in the future

Analysis of anti-EV-A71 antibodies recognizing linear B-cell epitopes.

<p>(A) IgM antibody determinants identified from acute infection with high neutralization sera. IgG antibody determinants identified from (B) acute infection with high neutralization sera, (C) convalescent sera, and (D) adult sera. Regions of amino acid sequences corresponding to the identified B-cell epitopes are indicated in the schematic diagrams of the EV-A71 genome. The percentage of antibody recognition contributed by each individual EV-A71 epitope is indicated in the pie charts, and was calculated according to the following equation: % antibody recognition = 100 x (OD values from individual peptide group/sum of the OD values from all peptide groups). In this calculation, the avidity and affinity of the peptides to the sera were assumed to be similar. Peptides are colour-coded according to the respective viral proteins.</p

EV-A71-specific IgM and IgG antibody determinants.

<p>(A) EV-A71-specific IgM antibody detection in sera (n = 44) at a dilution of 1:2000 was determined by peptide-based ELISA. Sera were categorized into EV-A71-infected patients (n = 22), non-EV-A71 enterovirus-infected patients (n = 12) and non-HFMD patients (n = 10). Red solid lines represent medians. (B) EV-A71-specific IgG antibody detection in sera (n = 38) at a dilution of 1:500 was determined by peptide-based ELISA. Sera were categorized into EV-A71-infected patients (n = 25), non-EV-A71 enterovirus-infected patients (n = 8) and healthy adults (n = 5). Red solid lines represent medians. One-way ANOVA with Kruskal-Wallis test was used for statistical analysis (*<i>P</i><0.05, **<i>P</i><0.01, ***<i>P</i><0.001). (C) Schematic representation of locations of IgM and IgG antibody determinants in VP1, VP2 and VP3 proteins, based on structural data retrieved from PDB records (identifier 3VBS). (D) The EV-A71 pentamer structure (identifier 3VBS) was generated using UCSF Chimera software. The capsid proteins of EV-A71 are shown in brown (VP1), light grey (VP2), dark grey (VP3) and light pink (VP4). The IgM and IgG antibody determinants are indicated in purple (PEP12), green (PEP19), orange (PEP21), red (PEP25), blue (PEP27) and pink (PEP23).</p

Amino acid sequence alignment of peptides with enteroviruses.

<p>The selected peptides (PEP12, PEP19, PEP21, PEP23, PEP25 and PEP27) were aligned to the corresponding sequences from 12 enterovirus prototype and consensus contemporary sequences (EV-A71, CV-A2 to CV-A8, CV-A10, CV-A12, CV-A14 and CV-A16). Conserved amino acids are indicated by a dash (–) and alignment gaps are shown in grey. The consensus sequences represent the current circulating strains while BrCr, Fleetwood, Olson, High Point, Swartz, Gdula, Parker, Donovan, Kowalik, Texas, G14 and G10 are the prototype virus strains.</p

Antigenic profiles of the human anti-EV-A71 antibodies.

<p>(A) Control cell lysates were loaded into SDS-PAGE gel electrophoresis. Recombinant EV-A71-EGFP cell lysates (structural and non-structural proteins) were probed with anti-GFP-HRP, while recombinant EV-A71 2A cell lysates were stained with Coomassie brilliant blue R-250. EV-A71 virion proteins were immunodetected with EV-A71-specific mAb 3323 (Millipore, USA) and mAb 979 (Millipore, USA), followed by secondary anti-mouse IgG-HRP. The expected band for each individual recombinant protein is indicated by red solid arrows and the protein sizes are shown. (B) Acute infection with no neutralization sera (n = 2) and (C) acute infection with high neutralization sera (n = 12) were used for EV-A71-specific IgM antibody detection. (D) Acute infection with high neutralization sera (n = 12) and (E) convalescent sera (n = 5) were used for EV-A71-specific IgG antibody detection. An estimated 20 μg of proteins was loaded for SDS-PAGE gel electrophoresis. The amount of EV-A71 structural and non-structural protein cell lysates was normalized with anti-GFP-HRP since the presence of inhibitory factors affected accurate quantitation of total proteins. The EV-A71 protein cell lysates and EV-A71 proteins were subjected to SDS-PAGE gel electrophoresis and probed with pooled human sera at a dilution of 1:300. The immunoblot was developed with Clarity Western ECL substrate and detected by chemiluminescence. Protein bands were determined using the Precision Plus Protein WesternC Standard (Bio-Rad, USA). The antigens recognized by EV-A71-infected patient sera are indicated by red solid arrows.</p