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Spline Cúbico para el Tratamiento Funcional de la Radiación Solar Global
摘要： The article shows the calculation of cubic splines that defines the behavior of the global solar radiation on a high Andean equatorial location. The spline smoothing is developed in a normed orthogonal functional space, where the discretized data (ti,xi) are transformed into functions X(t). The analysis of univariate and multivariate data allows studying natural phenomena from finite sets of numerical values. Data collection involves not only getting values, but also includes the processes or functions that give rise to them. Bootstrap resampling was used for detecting outliers with which annual, month and by climatic periods averages are obtained. Functional monthly averages of global solar radiation show the presence of two forms of behavior during the period studied.
关键词： functional data analysis,statistical analysis,global solar radiation,meteorological data,bootstrap,cubic spline
更新于2025-09-23 15:23:52
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Raman Spectroscopic and Microscopic Analysis for Monitoring Renal Osteodystrophy Signatures
摘要： Defining the pathogenesis of renal osteodystrophy (ROD) and its treatment efficacy are difficult, since many factors potentially affect bone quality. In this study, confocal Raman microscopy and parallel statistical analysis were used to identify differences in bone composition between healthy and ROD bone tissues through direct visualization of three main compositional parametric ratios, namely, calcium content, mineral-to-matrix, and carbonate-to-matrix. Besides the substantially lower values found in ROD specimens for these representative ratios, an obvious accumulation of phenylalanine is Raman spectroscopically observed for the first time in ROD samples and reported here. Thus, elevated phenylalanine could also be considered as an indicator of the disease. Since the image results are based on tens of thousands of spectra per sample, not only are the average ratios statistically significantly different for normal and ROD bone, but the method is clearly powerful in distinguishing between the two types of samples. Furthermore, the statistical outcomes demonstrate that only a relatively small number of spectra need to be recorded in order to classify the samples. This work thus opens the possibility of future development of in vivo Raman sensors for assessment of bone structure, remodeling, and mineralization, where different biomarkers are simultaneously detected with unprecedented accuracy.
关键词： Raman spectroscopy,bone composition,statistical analysis,renal osteodystrophy
更新于2025-09-23 15:23:52
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Assessment of different combinations of meteorological parameters for predicting daily global solar radiation using artificial neural networks
摘要： In this study, for determining the best-input scenarios of the used parameters in predicting the Daily Global Solar Radiation (DGSR), a new approach based on Artificial Neural Networks (ANNs) was presented. The proposed approach is based on comparisons between all possible input combinations for determining the best scenarios that can give perfect correlations and approximations with DGSR. Recorded data from 35 stations belonging to different climatic zones (27 in Morocco and 8 in neighboring countries) were reported for training and testing the obtained results. The used input parameters include geographical coordinates, sun declination, day length, day number, clearness index (KI), Top Of Atmosphere (TOA), average ambient temperature (Ta), maximum temperature (Tmax), minimum temperature (Tmin), difference temperature (ΔT), temperature ratio (TR), relative humidity (Rh) and wind speed (Ws). The results revealed 128 best-input scenarios, where the first relevant input combination was found for KI, Ta, ΔT, TR and TOA. This result indicated that the best-input scenario for predicting DGSR is based only on three climatological parameters: KI, function of Ta f(Ta) and TOA. In addition, based on these found best-input scenarios and on the least square regression (LSR) technique, 128 new linear relationships between DGSR and the found best-input combinations were developed. The statistical analysis expressed through statistical criteria indicated perfect correlations and approximations between the predicted and measured values of DGSR.
关键词： Best scenarios,ANNs,Least square regression,Statistical analysis,Solar radiation modelling,Forecasting
更新于2025-09-23 15:23:52
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Modeling and optimization of characterization of nanostructure anodized aluminium oxide membranes
摘要： This study indicates the importance of statistical analysis and modeling to investigate the synthesis and optimization of anodized aluminium oxide (AAO) properties for template-assisted synthesis of nanostructure particles. The response surface methodology was used to optimize pore size and porosity of AAO. The impacts of four main parameters including type of acidic electrolyte, concentration of acid, bath temperature and electrical potential of anodization on characterization of AAO were investigated. Statistical analysis showed that the linear and quadratic terms of these variables had significant effects. Based on the statistical analysis, a possible mechanism of the anodization was proposed. The proposed mechanism helped us to develop an analytical model. The analytical model could predict the experimental results with an appropriate accuracy. Results indicated the rate-limiting reaction in anodization process is water dissociation which was conducted at the pore bottom of the AAO. In addition, concentrated electrical field at pore base induced water splitting so that the activation energy of water dissociation decreased ten times and reached to 9898.5 J/mol.
关键词： Statistical analysis,Anodized aluminium oxide,Electrochemical synthesis,Pore perforation,Nanoporous materials
更新于2025-09-23 15:23:52
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Sensitive and Direct DNA Mutation Detection by Surface-enhanced Raman Spectroscopy using Rational Designed and Tunable Plasmonic Nanostructures
摘要： Efficient DNA mutation-detection methods are required for diagnosis, personalized therapy development, and prognosis assessment for diseases such as cancer. To address this issue, we proposed a straightforward approach by combining active plasmonic nanostructures, surface enhanced Raman spectroscopy (SERS), and polymerase chain reaction (PCR), with a statistical tool to identify and classify BRAF wild type (WT) and V600E mutant genes. The nanostructures provide enhanced sensitivity, while PCR offers the high specificity towards target DNA. A series of positively charged plasmonic nanostructures including gold/silver nanospheres, nanoshells, nanoflowers and nanostars, were synthesized with a one-pot strategy and characterized. By changing the shape of nanostructures, we are able to vary the surface plasmon resonance from 551 nm to 693 nm. The gold/silver nanostar showed the highest SERS activity, which was employed for DNA mutation detection. We reproducibly analyzed as few as 100 copies of target DNA sequences using gold/silver nanostars, thus demonstrating the high sensitivity of the direct SERS detection. By means of statistical analysis (principal component analysis-linear discriminant analysis, PCA-LDA), this method was successfully applied to differentiate the WT and V600E mutant both from whole genome DNA (gDNA) lysed from cell line and from cell-free DNA (cfDNA) collected from cell culture media. We further proved that this assay is capable of specifically amplifying and accurately classifying a real plasma sample. Thus, this direct SERS strategy combined with the active plasmonic nanostructures has the potential for wide applications as an alternative tool for sensitively monitoring and evaluating clinical important nucleotide biomarkers.
关键词： PCR,statistical analysis,plasmonic nanostructures,surface-enhanced Raman spectroscopy,DNA mutation detection
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE SENSORS - Montreal, QC, Canada (2019.10.27-2019.10.30)] 2019 IEEE SENSORS - Industrial gas analytics using a compact ultraviolet laser
摘要： In this paper, we propose a simple, yet reliable methodology to expedite yield estimation and optimization of microwave structures. In our approach, the analysis of the entire response of the structure at hand (e.g., S-parameters as a function of frequency) is replaced by response surface modeling of suitably selected feature points. On the one hand, this is sufficient to determine whether a design satisfies given performance specifications. On the other, by exploiting the almost linear dependence of the feature points on the designable parameters of the structure, reliable yield estimates can be realized at low computational cost. Our methodology is verified using two examples of waveguide filters and one microstrip hairpin filter and compared with conventional Monte Carlo analysis based on repetitive electromagnetic simulations, as well as with statistical analysis exploiting linear response expansions around the nominal design. Finally, we perform yield-driven design optimizations on these filters.
关键词： microwave component modeling,yield-driven design,electromagnetic (EM) modeling,yield estimation,tolerance-aware design,Design centering,statistical analysis
更新于2025-09-23 15:19:57
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Metabolomic approach for rapid differentiation of Fritillaria bulbs by matrix-assisted laser desorption/ionization mass spectrometry and multivariate statistical analysis
摘要： The bulbs of Fritillaria have been used for centuries as food and medicinal products in many Asian countries. Different Fritillaria species have distinct pharmacological effects despite of their similar appearances. Effective differentiation of Fritillaria species can avoid adulteration and is crucial to its clinical uses. In this paper, a hybrid method of matrix assisted laser desorption/ionization mass spectrometry and multivariate statistical analysis was developed for the rapid and reliable differentiation of Fritillaria species for the first time. Significantly different patterns for five Fritillaria species were obtained by MALDI-MS after instant sample extractions. Different groups of Fritillaria were confidently differentiated via an orthogonal partial least square model. In addition, a metabolomic taxonomy of five Fritillaria species was obtained based on MALDI-MS data.
关键词： Fritillaria,metabolic profiling,MALDI-MS,multivariate statistical analysis,chemical taxonomy
更新于2025-09-23 15:19:57
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How Reproducible are Electrochemical Impedance Spectroscopic Data for Dye-Sensitized Solar Cells?
摘要： Dye-sensitized solar cell (DSC) technology has been broadly investigated over the past few decades. The sandwich-type structure of the DSC makes the manufacturing undemanding under laboratory conditions but results in the need for reproducible measurements for acceptable DSC characterization. Electrochemical impedance spectroscopy (EIS) offers the possibility to study complex electronic systems and is commonly used for solar cells. There is a tendency in the literature to present impedance data only for one representative device. At the same time, as current density–voltage plots illustrate, measurements can vary within one set of DSCs with identical components. We present multiple DSC impedance measurements on “identical” devices prepared using two different dyes and present a statistical analysis regarding the reproducibility.
关键词： dye,statistical analysis,dye-sensitized solar cells,electrochemical impedance spectroscopy
更新于2025-09-23 15:19:57
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Uniformity and isotropy of speckle pattern cause the doubled random error phenomenon in digital image correlation
摘要： For subset-based digital image correlation, the random error of second-order shape function roughly doubles that of first-order shape function, termed doubled random error phenomenon. In this work, we suggest that the fundamental cause of this phenomenon is the uniformity and isotropy of speckle pattern. Specially, we prove that the ratio of random error of second-order shape function to that of first-order shape function, from a view of statistic, is expected to be √7∕2 (≈1.87), which is quite close to the empirical value 2. Numerical experiments demonstrate the correctness of propose theoretical analysis.
关键词： Speckle pattern,Digital image correlation,Random error,Statistical analysis
更新于2025-09-23 15:19:57
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Can Multispectral Information Improve Remotely Sensed Estimates of Total Suspended Solids? A Statistical Study in Chesapeake Bay
摘要： Total suspended solids (TSS) is an important environmental parameter to monitor in the Chesapeake Bay due to its effects on submerged aquatic vegetation, pathogen abundance, and habitat damage for other aquatic life. Chesapeake Bay is home to an extensive and continuous network of in situ water quality monitoring stations that include TSS measurements. Satellite remote sensing can address the limited spatial and temporal extent of in situ sampling and has proven to be a valuable tool for monitoring water quality in estuarine systems. Most algorithms that derive TSS concentration in estuarine environments from satellite ocean color sensors utilize only the red and near-infrared bands due to the observed correlation with TSS concentration. In this study, we investigate whether utilizing additional wavelengths from the Moderate Resolution Imaging Spectroradiometer (MODIS) as inputs to various statistical and machine learning models can improve satellite-derived TSS estimates in the Chesapeake Bay. After optimizing the best performing multispectral model, a Random Forest regression, we compare its results to those from a widely used single-band algorithm for the Chesapeake Bay. We find that the Random Forest model modestly outperforms the single-band algorithm on a holdout cross-validation dataset and offers particular advantages under high TSS conditions. We also find that both methods are similarly generalizable throughout various partitions of space and time. The multispectral Random Forest model is, however, more data intensive than the single band algorithm, so the objectives of the application will ultimately determine which method is more appropriate.
关键词： water quality,total suspended solids,ocean color,satellite remote sensing,statistical analysis,Random Forest,Chesapeake Bay,multispectral,machine learning
更新于2025-09-19 17:15:36