Detecting and classifying outliers in big functional data

Advances in Data Analysis and Classification - We propose two new outlier detection methods, for identifying and classifying different types of outliers in (big) functional data sets. The proposed...     

A real-time monitoring approach for bivariate event data

Early detection of changes in the frequency of events is an important task in many fields, such as disease surveillance, monitoring of high-quality processes, reliability monitoring, and public health. This article focuses on detecting changes in multivariate event data by monitoring the time-between-events (TBE). Existing multivariate TBE charts are limited because they only signal after an event occurred for each of the individual processes. This results in delays (i.e., long time-to-signal), especially when we are interested in detecting a change in one or a few processes with different rates. We propose a bivariate TBE chart, which can signal in real-time. We derive analytical expressions for the control limits and average time-to-signal performance, conduct a performance evaluation and compare our chart to an existing method. Our findings showed that our method is an effective approach for monitoring bivariate TBE data and has better detection ability than the existing method under transient shifts and is more generally applicable. A significant benefit of our method is that it signals in real-time and that the control limits are based on analytical expressions. The proposed method is implemented on two real-life datasets from reliability and health surveillance.     

Phospholipids from some common fungi associated with damp building materials

Methods for the analysis of fungal biomass in contaminated building materials have been limited to methods that use viable propagules as well as indicators of total biomass such as fungal glucan and ergosterol. Because of large differences in the survival times of spores, and limitations imposed by the use of agar media to assess fungal cells for the former approach, no quantitative information and poor qualitative information is obtained. The use of the biochemical indicators provides reliable quantitative information but no qualitative data. Analysis of phospholipids of various bacteria and, recently, of fungi common in outdoor air has provided both qualitative and quantitative data on their distributions in various substrates including in outdoor air samples. In this report, we provide new data on the signature lipids of some fungi common on moldy building materials. Using the LC/MS/MS analysis described, an estimate can be made of the fresh weight of fungal cells and the relative abundance of the common genera of fungi typically found on moldy materials.     

Near-ultraviolet photolysis of L-mandelate, formation of reactive oxygen species, inactivation of phage T7 and implications on human health

Compared with ultraviolet B and C, UVA is considered to have little direct effects on biological systems. However, damaging effects of UVA on biological systems are often synergistically enhanced in the presence of sensitizers. Production of reactive oxygen species (ROS) has been implicated in the process. Several ROS have been identified but their involvement in inducing cellular damage is yet to be fully evaluated. Although membranes and proteins are affected, DNA is an important target and a variety of types of damage have been reported. Here, we present evidence that L-mandelate can act as a near UV (NUV) sensitizer, when activated by a lamp emitting 99% UVA and 1% UVB. Although evidence is available that H(2)O(2) and a small amount of *OH are produced, an alternative effect of the sensitization reaction may involve direct electron transfer. Studies have shown that NUV photolysis of mandelate can inactivate phage T7. Employment of tetrazolium blue test to detect superoxide anion may not be sufficient evidence as this agent may be reduced by alternative routes.     

Scanning electrochemical cell microscopy: A natural technique for single entity electrochemistry

Scanning electrochemical cell microscopy (SECCM) is a robust and versatile scanning electrochemical probe microscopy technique that allows direct correlation of structure–activity at the nanoscale. SECCM uses a mobile droplet cell to investigate and visualize electrochemical activity at interfaces with high spatiotemporal resolution, while also providing topographical information. This article highlights diverse contemporary challenges in the field of single entity electrochemistry tackled by the increasing uptake of SECCM globally. Various applications of SECCM in single entity electrochemistry are featured herein, including electrocatalysis, electrodeposition, corrosion science and materials science, with electrode materials spanning particles, polymers, two-dimensional materials and complex polycrystalline substrates. The use of SECCM for patterning structures is also highlighted.     

Near-ultraviolet photolysis of beta-phenylpyruvic acid generates free radicals and results in DNA damage

Ultraviolet A (UVA) light (315-400 nm) is ubiquitously found in our environment and constitutes about 95% of the total solar UV; all UVC and most UVB being absorbed by the stratospheric ozone layer. Compared with UVB and C, UVA does not show any direct effect on biological systems. Indirect effects of UVA, however, have been recognised overwhelmingly and this includes photosensitization of biological and non-biological compounds and production of free radicals many of which include oxygen and are hence known as reactive oxygen species or ROS. Several types of free radicals have been identified although their impacts on various macro- and micro-biomolecules are yet to be fully elucidated. beta-Phenylpyruvic acid is ubiquitously found in eukaryotic cells as a metabolite of phenylalanine, which is subsequently converted to phenyllactate and/or to 2-hydroxyphenylacetate and mandelate. In patients suffering from phenylketonuria the hydroxylation of phenylalanine to tyrosine is defective due to lack of phenylalanine hydroxylase. These result in accumulation and excretion of this compound in the urine. Here we present evidence that photolysis of beta-phenylpyruvic acid by a skin tanning lamp, emitting 99% UVA (315-400 nm) and 1% UVB (290-315 nm) generates carboxyl radicals (CO(2)(*)) and also possibly causes direct electron transfer (or type 1) reactions. Electron paramagnetic resonance was used to detect the free radicals. To determine the biological effects of this photolytic reaction, T7 was exposed to these photolytic reactive agents and found to lead to high levels of phage inactivation. Damage to DNA and/or components such as tail fibre proteins may be involved in T7 inactivation. In addition, our unpublished data suggest that certain phenylketonuria cell lines are more sensitive to PPA+NUV, lending importance to photolytic studies of this agent.     

Isotope-Labeled RNA Building Blocks for NMR Structure and Dynamics Studies

RNA structural research lags behind that of proteins, preventing a robust understanding of RNA functions. NMR spectroscopy is an apt technique for probing the structures and dynamics of RNA molecules in solution at atomic resolution. Still, RNA analysis by NMR suffers from spectral overlap and line broadening, both of which worsen for larger RNAs. Incorporation of stable isotope labels into RNA has provided several solutions to these challenges. In this review, we summarize the benefits and limitations of various methods used to obtain isotope-labeled RNA building blocks and how they are used to prepare isotope-labeled RNA for NMR structure and dynamics studies.     

Performance and comparison of fiber vibration sensing using SAC-OCDMA with direct decoding techniques

Intensity modulated fiber vibrations sensing using Khazani Syed (KS) and Modified Quadratic Congruence Code (MQC) code for quasi distributed vibration measurement have been evaluated. The systems employed Spectral Direct (SD) Decoding for Spectral Amplitude Coding-Optical Code Division Multiple Access (SAC-OCDMA). SAC-OCDMA is adopted because of its enormous impact in dealing with Multiple Access Interference (MAI). The setup was carried out for three sensor points in three consecutive measurements. The performance of the sensing system with the KS and MQC codes were compared at the same weight and number of code sequence. It was observed that the applied vibration frequencies were obtained at the receivers and the signal employing MQC are received at slightly better power than KS code. However, KS code setup employed less number of components and therefore, reduce the cost and complexity of achieving quasi-distributed vibration sensing.     

Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer’s Diseases via Pharmacophore Modeling,Auto-QSAR,and Molecular Docking Approaches

Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC₅₀ values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R² = 0.86 and Q² = 0.73), pls_38 (R² = 0.77 and Q² = 0.72), kpls_desc_44 (R² = 0.81 and Q² = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.     

Halpern-type iterative process for solving split common fixed point and monotone variational inclusion problem between Banach spaces

In this paper, we study the split common fixed point and monotone variational inclusion problem in uniformly convex and 2-uniformly smooth Banach spaces. We propose a Halpern-type algorithm with two self-adaptive stepsizes for obtaining solution of the problem and prove strong convergence theorem for the algorithm. Many existing results in literature are derived as corollary to our main result. In addition, we apply our main result to split common minimization problem and fixed point problem and illustrate the efficiency and performance of our algorithm with a numerical example. The main result in this paper extends and generalizes many recent related results in the literature in this direction.