A Sequential Monte Carlo Approach for Online Stock Market Prediction Using Hidden Markov Models

A sequential Monte Carlo (SMC) algorithm prediction approach is developed based on joint probability distribution in hidden Markov Models (HMM). SMC methods, a general class of Monte Carlo methods, are typically used for sampling from sequences of distributions and simple examples of these algorithms are found extensively throughout the tracking and signal processing literature. Recent developments indicate that these techniques have much more general applicability and can be applied very effectively to statistical inference problems. Due to the problem involved in estimating the parameter of HMM, the HMM is represented in a state space model and the sequential Monte Carlo (SMC) method is used. Predictions are made using the SMC method in HMM and the corresponding on-line algorithm is developed. Daily stock price data from the banking sector of the Nigerian Stock Exchange (NSE) (price index between the years 1 January 2005 to 31 December 2008) are analyzed; experimental results reveal that the method proposed is effective

Xenophobia and its implications for social order in Africa

Xenophobia, a form of discrimination practiced in countries, particularly in South Africa, is one of the major challenges confronting the modern day society. This paper examines xenophobia as a menace showing at the same time that this discriminatory practice  bifurcates societies by creating a dichotomy amidst the various occupants of the  society, thereby giving room for “otherness” rather than “orderliness”. The paper also highlights the philosophical implications of this societal bifurcation, particularly to the human community. Seeking a plausible way of addressing this challenge, the paper concludes by emphasizing the relevance of the value of tolerance in curbing xenophobia.Keywords: Xenophobia, Social discrimination, Tolerance, order and other, Africa

Financial Integration and Financial Development: Evidence from Sub-Saharan African (SSA) Countries

The study examined the effects of financial integration on financial development for 49 Sub-Saharan Africa (SSA) countries for the period 2002 to 2021. Five independent metrics of financial development and two financial integration measures were utilized to ensure robustness of the anticipated results. Using a dynamic panel GMM-SYS estimation technique, it was discovered that the impacts of financial integration on financial development in SSA are highly dependent on the proxies employed to capture these two variables of financial integration. Financial integration has a beneficial influence on private sector credit, domestic credit, liquid liabilities, and finance size, when proxied by the interest rate spread. However, this measure of financial integration limits the volume of financial activity of financial intermediaries as it’s negatively correlated. Similarly, when measured using gross private capital flows, financial integration has statistically positive effects on financial development as measured by liquid liabilities but has a negative impact on financial development as measured by finance activity and financial size in Sub-Saharan African nations. The general implication of these findings is that the influence of financial integration on financial development in SSA is complex. However, before reaching a firm conclusion about the relationship between these two variables, several transmission mechanisms by which former influences the latter, as well as their various proxies, must be considere

Regional differences in the coupling between resting cerebral blood flow and metabolism may indicate action preparedness as a default state.

Although most functional neuroimaging studies examine task effects, interest intensifies in the "default" resting brain. Resting conditions show consistent regional activity, yet oxygen extraction fraction constancy across regions. We compared resting cerebral metabolic rates of glucose (CMRgl) measured with 18F-labeled 2-fluoro-2-deoxy-D-glucose to cerebral blood flow (CBF) 15O-H2O measures, using the same positron emission tomography scanner in 2 samples (n = 60 and 30) of healthy right-handed adults. Region to whole-brain ratios were calculated for 35 standard regions of interest, and compared between CBF and CMRgl to determine perfusion relative to metabolism. Primary visual and auditory areas showed coupling between CBF and CMRgl, limbic and subcortical regions--basal ganglia, thalamus and posterior fossa structures--were hyperperfused, whereas association cortices were hypoperfused. Hyperperfusion was higher in left than right hemisphere for most cortical and subcallosal limbic regions, but symmetric in cingulate, basal ganglia and somatomotor regions. Hyperperfused regions are perhaps those where activation is anticipated at short notice, whereas downstream cortical modulatory regions have longer "lead times" for deployment. The novel observation of systematic uncoupling of CBF and CMRgl may help elucidate the potential biological significance of the "default" resting state. Whether greater left hemispheric hyperperfusion reflects lateral dominance needs further examination

Parameter Estimation of a Class of Hidden Markov Model with Diagnostics

A stochastic volatility (SV) problem is formulated as a state space form of a Hidden Markov model (HMM). The SV model assumes that the distribution of asset returns conditional on the latent volatility is normal. This article analyzes the SV model with the student-t distribution and the generalized error distribution (GED) and compares these distributions with a mixture of normal distributions from Kim and Stoffer (2008). A Sequential Monte Carlo with Expectation Maximization (SMCEM) algorithm technique was used to estimate parameters for the extended volatility model; the Akaike Information Criteria (AIC) and forecast statistics were calculated to compare distribution fit. Distribution performance was assessed using simulation study and real data. Results show that, although comparable to the normal mixture SV model, the Student-t and GED were empirically more successful

Blood group and Rhesus antigens among Blood donors attending the Central Blood Bank, Sudan

Background: It is well known that the Rhesus system remains the second most clinically important blood group system after the ABO. There is no published work regarding the frequency of various Rhesus antigens among Sudanese population.Objectives: In order to minimize Rhesus allo-immunization among blood recipients a cross sectional study was conducted to determine the frequency of various Rhesus antigens among the blood donors attending the Central Blood Bank in Khartoum.Methods: Two hundred male blood donors were enrolled in the study. ABO and Rhesus typing were performed using the classical slide method and gel micro typing system.Results: The frequency percentage of ABO blood phenotypes in the total samples were as follows: O(51.5%), A (29.5%), B (16%), and AB (6%); whereas the frequency percentage of Rh antigens were D (93%), e (79.5%), c (68.5%), C, (27%), E (18.5%).Conclusion: We concluded that the frequency of the Rh antigens can be shown in this order D > e > c > C > E. Special precautions need to be undertaken to minimize any possible allo-immunization by such antigens.Keywords: Frequency, Rhesus antigens, phenotyping, Blood group

Combined targeting of TGF-beta, EGFR and HER2 suppresses lymphangiogenesis and metastasis in a pancreatic cancer model

Pancreatic ductal adenocarcinomas (PDAC) are aggressive with frequent lymphatic spread. By analysis of data from The Cancer Genome Atlas, we determined that ∼35% of PDACs have a pro-angiogenic gene signature. We now show that the same PDACs exhibit increased expression of lymphangiogenic genes and lymphatic endothelial cell (LEC) markers, and that LEC abundance in human PDACs correlates with endothelial cell microvessel density. Lymphangiogenic genes and LECs are also elevated in murine PDACs arising in the KRC (mutated Kras; deleted RB) and KIC (mutated Kras; deleted INK4a) genetic models. Moreover, pancreatic cancer cells (PCCs) derived from KRC tumors express and secrete high levels of lymphangiogenic factors, including the EGF receptor ligand, amphiregulin. Importantly, TGF-β1 increases lymphangiogenic genes and amphiregulin expression in KRC PCCs but not in murine PCCs that lack SMAD4, and combinatorial targeting of the TGF-β type I receptor (TβRI) with LY2157299 and EGFR/HER2 with lapatanib suppresses tumor growth and metastasis in a syngeneic orthotopic model, and attenuates tumor lymphangiogenesis and angiogenesis while reducing lymphangiogenic genes and amphiregulin and enhancing apoptosis. Therefore, this combination could be beneficial in PDACs with lymphangiogenic or angiogenic gene signatures

Computational and experimental elucidation of the boosted stability and antibacterial activity of ZIF-67 upon optimized encapsulation with polyoxometalates

Water microbial purification is one of the hottest topics that threats human morbidity and mortality. It is indispensable to purify water using antimicrobial agents combined with several technologies and systems. Herein, we introduce a class of nanosized metal organic framework; Zeolitic imidazolate framework (ZIF-67) cages encapsulated with polyoxometalates synthesized via facile one-step co-precipitation method. We employed two types of polyoxometalates bioactive agents; phosphotungstic acid (PTA) and phosphomolybdic acid (PMA) that act as novel antibacterial purification agents. Several characterization techniques were utilized to investigate the morphological, structural, chemical, and physical properties such as FESEM, EDS, FTIR, XRD, and N₂ adsorption/desorption isotherms techniques. The antibacterial assessment was evaluated using colony forming unit (CFU) against both Escherichia coli and Staphylococcus aureus as models of Gram-negative and Gram-positive bacteria, respectively. The PTA@ZIF-67 showed higher microbial inhibition against both Gram-positive and Gram-negative bacteria by 98.8% and 84.6%, respectively. Furthermore, computational modeling using density functional theory was conducted to evaluate the antibacterial efficacy of PTA when compared to PMA. The computational and experimental findings demonstrate that the fabricated POM@ZIF-67 materials exhibited outstanding bactericidal effect against both Gram-negative and Gram-positive bacteria and effectively purify contaminated water