Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

Profiling engineered data with robust mining methods continues attracting attention in knowledge engineering systems. The purpose of this article is to propose a simple technique that deals with non-linear multi-factorial multi-characteristic screening suitable for knowledge discovery studies. The method is designed to proactively seek and quantify significant information content in engineered mini-datasets. This is achieved by deploying replicated fractional-factorial sampling schemes. Compiled multi-response data are converted to a single master-response effectuated by a series of distribution-free transformations and multi-compressed data fusions. The resulting amalgamated master response is deciphered by non-linear multi-factorial stealth stochastics intended for saturated schemes. The stealth properties of our method target processing datasets which might be overwhelmed by a lack of knowledge about the nature of reference distributions at play. Stealth features are triggered to overcome restrictions regarding the data normality conformance, the effect sparsity assumption and the inherent collapse of the ‘unexplainable error’ connotation in saturated arrays. The technique is showcased by profiling four ordinary controlling factors that influence webpage content performance by collecting data from a commercial browser monitoring service on a large scale web host. The examined effects are: (1) the number of Cascading Style Sheets files, (2) the number of JavaScript files, (3) the number of Image files, and (4) the Domain Name System Aliasing. The webpage performance level was screened against three popular characteristics: (1) the time to first visual, (2) the total loading time, and (3) the customer satisfaction. Our robust multi-response data mining technique is elucidated for a ten-replicate run study dictated by an L₉(3⁴) orthogonal array scheme where any uncontrolled noise embedded contribution has not been necessarily excluded.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

SIMS as a subnanometer probe: A new tool for chemical profile analysis of grafted molecules

The complexity of modern engineered surfaces requires the development of very powerful methods to analyze and characterize them. We demonstrate that it is possible to obtain chemical information about the skeleton of organic molecules constituting SAMs grafted on a silicon surface by using a new type of SIMS method. A profile can be achieved by the investigation of the temporal variation of secondary ion intensities that correspond to the fractional parts of the molecule constituting the SAMs. The equivalent ablation rate is less than 0.5 nm/min.     

Quantitative Depth Profiling of K-Doped Fullerene Films Using XPS and SIMS

 Phenomena accompanying electrochemical doping of solid fullerene films with potassium were studied by sputter ion depth profiling (XPS and SIMS). The potassium distribution was determined, and artifacts associated with possible damage of the layer composition caused by ion impact were investigated and discussed. To compare the charge transfer while reductive doping is taking place at fullerene/solution interface with doping from gas phase, model layers were prepared and doped by potassium under UHV conditions. It was found that sputtering by Ar⁺ primary ions yields both accurate information on the alkaline metal distribution and on its concentration. Sputtering by O⁺ ions led to an enrichment of potassium, apparently due to the reactivity of oxygen with the fullerene matrix. It is shown that the reductive doping starts at the fullerene/solution interface. The concentration of potassium in the doped films was found to be lower than expected from the charge transferred during the electrochemical reduction. Other phase transformations such as hydrogenation are discussed. Received March 4, 2002; accepted July 26, 2002     

A graph-theoretic approach to modeling metabolic pathways

Summary The metabolic pathways of medazepam, oxazepam, and diazepam were modeled using graph-theoretic transforms which are incorporable into computer-assisted metabolic analysis programs. The information, represented in the form of a graph-theoretic transform kit, which was obtained from these pathways was then used to predict the metabolites of other benzodiazepine compounds. The transform kits gave statistically significant predictions with respect to a statistical method for evaluating the performance of the transform kits.     

Extension of multivariate regression trees to interval data. Application to electricity load profiling

Summary  Several data can be presented as interval curves where intervals reflect a within variability. In particular, this representation is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load profiling consists in assigning a daily load curve to a customer based on their characteristics such as energy requirement. Within the load profiling scope, this paper investigates the extension of multivariate regression trees to the case of interval dependent (or response) variables. The tree method aims at setting up simultaneously load profiles and their assignment rules based on independent variables. The extension of multivariate regression trees to interval responses is detailed and a global approach is defined. It consists in a first stage of a dimension reduction of the interval response variables. Thereafter, the extension of the tree method is applied to the first principal interval components. Outputs are the classes of the interval curves where each class is characterized both by an interval load profile (e.g. the class prototype) and an assignment rule based on the independent variables.     

The role of TLC in the screening of inherited metabolic diseases

Summary Thin-layer chromatography (TLC) is a rapid, reliable and inexpensive screening technique for diagnosis of inherited metabolic diseases (IMD). Our screening program encompasses five main situations where the use of TLC is considered to be vindicated: (i) analysis of amino acids; (ii) screening for sugar defects; (iii) detection of pathological oligosaccharidurias; (iv) screening for organic acid disorders; and (v) detection of abnormalities in tryptophan metabolism. Examples are presented of chromatograms obtained from pathological samples. Presented at the 21^st ISC held in Stuttgart, Germany, 15^th–20^th September, 1996     

Evaluation of the sputtering rate variation in SIMS ultra‐shallow depth profiling using multiple short‐period delta layers

We have developed multiple short‐period delta layers as a reference material for SIMS ultra‐shallow depth profiling. Boron nitride delta layers and silicon spacer layers were sputter‐deposited alternately, with a silicon spacer thickness of 1–5 nm. These delta‐doped layers were used to measure the sputtering rate change in the initial stage of oxygen ion bombardment. A significant variation of sputtering rate was observed in the initial 3 nm or less. The sputtering rate in the initial 3 nm was estimated to be about four times larger than the steady‐state value for 1000 eV oxygen ions. Copyright © 2003 John Wiley & Sons, Ltd.     

Interpretation of the Metabolic Enthalpy Change, ΔHmet,Calculated for Microbial Growth Reactions in Soils

The microcalorimetric method was used to calculate the metabolic enthalpy change per mol of glucose degraded by soil microorganisms, ΔH _met. This parameter has been calculated by microcalorimetry for many organic, inorganic and biochemical reactions, but there is only some information about its quantification for microbial growth reactions in soils. Values of ΔH _met were calculated for different soil samples collected in Galicia (Spain) and Campinas (Săo Paolo, Brazil). Exponential microbial growth was stimulated in all soil samples by the addition of glucose and power-time curves were recorded. Results showed changes in the values of ΔH _met calculated for all the soil samples, suggesting a dependence of this value with the microbial growth rate constant, with the percentage of growth, with the initial number of microorganisms of soil samples, with the quantity of glucose added and with the strain of bacteria growing in soil. The interpretation of variations of ΔH _met provides important qualitative and quantitative information. It reports data that allow to interpret from a qualitative point of view, the increase in biomass as a consequence of the degradation of the organic matter in soil, to understand changes in the percentages of soil organic matter and to know if the microbial population growing in differential soil samples is homogeneous. Therefore, to report that value would be very important in ecological studies, but beforehand, it is necessary to solve some problems that can appear in the experiments done to make the quantification . This revised version was published online in August 2006 with corrections to the Cover Date.