The effect of multilinear data fusion on the accuracy of multivariate curve resolution outputs

EN<br />This literature review aims to assess and understand the needs and development of practical guidelines in biology subjects. The characteristics of biology as a science that has objects of study in the form of concrete objects and can be captured by the senses are developed based on empirical experience (real experience). One of the empirical experiences can be done through practical activities. Practical activities carried out are not only oriented towards the final results to be obtained, but involve how the process of finding scientific facts. The literature review analyzed 25 relevant articles and focused on the importance of the need for practical guidelines in biology subjects. Articles were obtained from several databases. The review results showed that several articles developed practical guidelines in the form of modules using 4-D or 3-D models. The results of the validity recapitulation showed the feasibility of the contents of A1-A5 in the valid-very valid category, with a value range of 79% - 96.66%. The average practicality results of A2-A4 can be stated that all of them are in the very practical category based on the assessment scores from the validator. Overall, A1-A5 is a media development product in the form of a practical guide that is suitable for use in the biology learning process because it has met the media suitability standards based on validity and practicality tests obtained from the accumulation of scores by the validator.<br /><br />ID<br />Literature review ini bertujuan untuk menilai dan memahami kebutuhan serta pengembangan panduan praktikum pada mata pelajaran biologi. Karakteristik Biologi sebagai ilmu mempunyai objek kajian berupa benda konkret dan dapat ditangkap indera dikembangkan berdasarkan pengalaman empiris (pengalaman nyata). Pengalaman empiris salah satunya dapat dilakukan melalui kegiatan praktikum. Kegiatan praktikum yang dilakukan tidak hanya berorientasi pada hasil akhir yang akan diperoleh, tetapi melibatkan bagaimana proses untuk menemukan fakta sains. Literature review menganalisis 25 artikel yang relevan dan berfokus pada pentingnya kebutuhan panduan praktikum pada mata pelajaran biologi. Artikel didapatkan dengan dari beberapa database. Hasil review menunjukkan bahwa beberapa artikel mengadakan pengembangan panduan praktikum baik berupa modul dengan menggunakan model 4-D atau 3-D. Hasil rekapitulasi validitas menunjukkan kelayakan isi A1-A5 dalam kategori valid-sangat valid, dengan rentang nilai 79% - 96,66%. Hasil rata-rata praktikalitas dari A2-A4 dapat dinyatakan bahwa seluruhnya masuk ke kategori sangat praktis berdasarkan skor penilaian dari validator. Secara keseluruhan A1-A5 merupakan produk pengembangan media berupa penuntun praktikum yang layak untuk digunakan pada proses pembelajaran biologi karena telah memenuhi standar kelayakan media berdasarkan uji validitas dan praktikalitas yang diperoleh dari akumulasi skor oleh validator.

Near-infrared chemical imaging (NIR-CI) is an emerging tool for process monitoring because it combines the chemical selectivity of vibrational spectroscopy with spatial information. Whereas traditional near-infrared spectroscopy is an attractive technique for water content determination and solid-state investigation of lyophilized products, chemical imaging opens up possibilities for assessing the homogeneity of these critical quality attributes (CQAs) throughout the entire product. In this contribution, we aim to evaluate NIR-CI as a process analytical technology (PAT) tool for at-line inspection of continuously freeze-dried pharmaceutical unit doses based on spin freezing. The chemical images of freeze-dried mannitol samples were resolved via multivariate curve resolution, allowing us to visualize the distribution of mannitol solid forms throughout the entire cake. Second, a mannitol-sucrose formulation was lyophilized with variable drying times for inducing changes in water content. Analyzing the corresponding chemical images via principal component analysis, vial-to-vial variations as well as within-vial inhomogeneity in water content could be detected. Furthermore, a partial least-squares regression model was constructed for quantifying the water content in each pixel of the chemical images. It was hence concluded that NIR-CI is inherently a most promising PAT tool for continuously monitoring freeze-dried samples. Although some practicalities are still to be solved, this analytical technique could be applied in-line for CQA evaluation and for detecting the drying end point.

Advances in spectral imaging instrumentation during the last two decades has lead to higher image fidelity, tighter spatial resolution, narrower spectral resolution, and improved signal to noise ratios. An important sub-classification of spectral imaging is chemical imaging, in which the sought-after information from the sample is its chemical composition. Consequently, chemical imaging can be thought of as a two-step process, spectral image acquisition and the subsequent processing of the spectral image data to generate chemically relevant image contrast. While chemical imaging systems that provide turnkey data acquisition are increasingly widespread, better strategies to analyze the vast datasets they produce are needed. The Generation of chemically relevant image contrast from spectral image data requires multivariate processing algorithms that can categorize spectra according to shape. Conventional chemometric techniques like inverse least squares, classical least squares, multiple linear regression, principle component regression, and multivariate curve resolution are effective for predicting the chemical composition of samples having known constituents, but are less effective when a priori information about the sample is unavailable. To address these problems, we have developed a fully automated non-parametric technique called spectral identity mapping (SIMS) that reduces the dependence of spectral image analysis on training datasets. The qualitative SIMS method provides enhanced spectral shape specificity and improved chemical image contrast. We present SIMS results of infrared spectral image data acquired from polymer coated paper substrates used in the manufacture of pressure sensitive adhesive tapes. In addition, we compare the SIMS results to results from spectral angle mapping (SAM) and cosine correlation analysis (CCA), two closely related techniques.

Subcellular Chemical Imaging: New Avenues in Cell Biology.

PurposeTo perform a review of the literature focusing on rehabilitation protocols in patients with acromioclavicular (AC) joint injuries treated operatively and nonoperatively and to provide an updated rehabilitation treatment algorithm.MethodsStudies were identified by searching the MEDLINE database from 01/1995 to 09/2020. Included studies contained detailed rehabilitation protocols with physiologic rationale for AC joint injuries. Biomechanical studies, technique articles, radiographic studies, systematic reviews, case studies, editorials, and studies that compared nonoperative versus operative treatment without focus on rehabilitation were excluded. Following identification of the literature, an updated treatment algorithm was created.ResultsThe search strategy yielded 1742 studies, of which 1654 studies were excluded based on title, 60 on the abstract, and 25 on the full manuscript. One study was manually identified using article reference lists, yielding four publications presenting detailed rehabilitation protocols based on physiologic rationale. No randomized controlled trials or comparative studies were identified or cited as a basis for these rehabilitation protocols.ConclusionFew detailed rehabilitation protocols in patients with AC joint injuries have been published. These protocols are limited by their standardization, arbitrary timelines, and provide minimal assessment of individual patient characteristics. The quality of patient care can be improved with more practical guidelines that are goal-oriented and allow for critical thinking among clinicians to address individual patient needs. Three common barriers preventing successful rehabilitation were identified and addressed: Pain, Apprehension, and (anterior chest wall) Stiffness to regain Scapular control, effectively termed “PASS” for AC joint rehabilitation.Clinical RelevanceRehabilitation protocols for AC joint injuries should be less formulaic and instead allow for critical thinking and effective communication among clinicians and therapists to address individual patient needs.

Higher computational power, new dimensions of interconnectivity and modern machine learning techniques are necessary for building a fully autonomous car, but exhibit an enormous technical complexity. Research about new approaches and technology for handling this complexity raises a problem: On the one side, researchers advocate transitions and replacements for the current systems mainly without deploying them in real cars on the streets. On the other side applying theoretical approaches without clear evidence of their practical benefits is risky for the practitioners. As a solution to close this gap, researchers should bring their ideas more often into physical cars and support their proposals with measurements from realistic experiments.

Multimodal multisample spectroscopic imaging analysis of tumor tissues using multivariate curve resolution

The emergence of new drug therapy regimens and the completion of several large randomized trials led to significant changes in the clinical guidelines of the Ministry of Health of Russia and the practical guidelines of the Russian Society of Clinical Oncology (RUSSCO) for the treatment of urologic oncology diseases. However, different interpretations of some studies by expert panels and requirements for these documents led to a divergence of some statements in these publications. The article presents executive summaries of the updated clinical and practical prostate cancer treatment guidelines.

Multivariate curve resolution for analysis of Raman hyperspectral imaging data sets for enzyme immobilization

Chemical imaging was used in this study as a powerful analytical tool to characterize pharmaceuticals in solid form. The majority of analyses are evaluated with bilinear modelling using only the pure component spectra or just the chemical images themselves to estimate the concentrations in each pixel, which are far from true quantitative determination. Our aim was to create more accurate concentration images using regression methods. For the first time in chemical imaging, variable selections with interval partial least squares (PLS) and with genetic algorithms (PLS-GA) were applied to increase the efficiency of the models. These were compared to numerous bilinear modelling and multivariate linear regression methods such as univariate regression, classical least squares (CLS), multivariate curve resolution–alternating least squares (MCR-ALS), principal component regression (PCR) and partial least squares (PLS). Two component spray-dried pharmaceuticals were used as a model. The paper is shown that, in contrast to the usual way of using either external validation or cross-validation, both should be performed simultaneously in order to get a clear picture of the prediction errors and to be able to select the appropriate models. Using PLS with variable selection, the root mean square errors were reduced to 3% per pixel by keeping only those peaks that are truly necessary for the estimation of concentrations. It is also shown that interval PLS can point out the best peak for univariate regression, and can thereby be of great help even when regulations allow only univariate models for product quality testing. Variable selection, besides yielding more accurate overall concentrations across a Raman map, also reduces the deviation among pixel concentrations within the images, thereby increasing the sensitivity of homogeneity studies. Copyright © 2015 John Wiley & Sons, Ltd.

This paper presents the development of a new small programming language named SIMPLE, Simple Imperative-Model Programming Language for Education. The motivations for the development of this new language stems from the lack of literature for practical efforts and guidelines to develop programming languages bottom-up from scratch. We believe that exposing students to the process of creating a programming language carries significant educational benefits and real experience in a serious project. Further, we discuss the language grammar and demonstrate its main elements and features. The new language has been tested extensively using 60+ programs designed to evaluate all elements of the language

Modern analytical instruments provide measurement data arrays with full of hidden and redundant information. Multivariate curve resolution (MCR) techniques decompose data set to physic‐chemically meaningful abstract profiles. On the other hand, for such data matrices, Borgen‐Rajkó self‐modeling curve resolution (SMCR) techniques reveal all possible solutions analytically under the minimal assumption. Although Lawton‐Sylvestre (LS) and Borgen methods have been proposed for the non‐negative curve resolution of two‐component and three‐component systems, there is still a great deal of interest to include further restrictions on the Borgen‐Rajkó SMCR. As modern hyphenated analytical instruments produce multiway (eg, three‐way) arrays, multiway analysis (eg, trilinear decomposition) was received much more popularity by chemists.This contribution is decicated to the extension of the Borgen algorithm to the trilinear data sets. The Borgen method incorporating trilinearity constraint is approached in an analogy to the trilinear Lawton‐Sylvester method. The proposed analytical triadic decomposition is applied to the simulated three‐way arrays with full rank and rank overlap (a type of rank deficiency) loadings. Finally, the proposed algorithm is further exemplified with a three‐component spectrofluorimetric study of acid‐base equilibrium of the pyridoxine. Investigating feasible regions of the simulated and experimental three‐component arrays reveal interesting additional information.

Chemical imaging and depth profiling of skin is useful for studying various biological phenomena. Although secondary ion images of biomolecules such as phosphocholine and cholesterol distributions on skin samples are easily obtained with time‐of‐flight secondary ion mass spectrometry (TOF‐SIMS), the observation of proteins or minor ingredients is often difficult. In this study, TOF‐SIMS imaging data of skin samples were analyzed with multivariate curve resolution (MCR) to obtain information on reagents applied to the middorsal skin of mice. The skin was sliced with a cryostat and placed on indium‐tin oxide glass plates. The samples were measured with TOF‐SIMS using Bi3++, and then the obtained data were analyzed with MCR. As a result, distributions of secondary ions related to the reagents were suggested by MCR results, although they were not obtained by a manual analysis using respective peaks. Copyright © 2012 John Wiley & Sons, Ltd.

The quality control of pellets homogeneity cannot be assessed by conventional techniques and near infrared-chemical imaging combined with multivariate curve resolution with alternating least squares is an attractive alternative. In this study, composition and spatial distribution of pellets components were determined after assessment of experimental parameters. The use of a 25 μm intermediate pixel size, an initial estimation matrix with instrumental signals for pure substances and individual matrices provided a model with explained variance of more than 99% and a value of 0.00263 for percentage of lack of fit. In addition, the similarity between the pure substances spectra and those recovered by the model were 0.9501 for sucrose, 0.9480 for starch, 0.9910 for ketoprofen and 0.5941 for SiO2. Chemical images were generated and show that the pellet is composed of an inert nucleus of starch and cellulose, surrounded by a ketoprofen layer. All this information was obtained quickly, in minutes, being an excellent alternative for pellets analysis.

The use of performance enhancing drugs is a widespread phenomenon in professional and leisure sports. A spectroscopic study was carried out on anabolic tablets labelled as 5 mg methandienone tablets provided by police departments. The analytical approach was based on a two-step methodology: a fast analysis of tablets using near infrared (NIR) spectroscopy to assess sample homogeneity based on their global composition, followed by Raman chemical imaging of one sample per NIR profile to obtain information on sample formulation. NIR spectroscopy assisted by a principal components analysis (PCA) enabled fast discrimination of different profiles based on the excipient formulation. Raman hyperspectral imaging and multivariate curve resolution - alternating least square (MCR-ALS) provided chemical images of the distribution of the active substance and excipients within tablets and facilitated identification of the active compounds. The combination of NIR spectroscopy and Raman chemical imaging highlighted dose-to-dose variations and succeeded in the discrimination of four different formulations out of eight similar samples of anabolic tablets. Some samples contained either methandienone or methyltestosterone whereas one sample did not contain an active substance. Other ingredients were sucrose, lactose, starch or talc. Both techniques were fast and non-destructive and therefore can be carried out as exploratory methods prior to destructive screening methods. Copyright © 2015 John Wiley & Sons, Ltd.