Results Of Principal Component Analysis Research Articles

The ventricular septal defect in tetralogy of Fallot: A multi-centre morphological and statistical shape analysis study

Abstract Background Ventricular septal defects (VSDs) in Tetralogy of Fallot (TOF) are often thought to be ‘large and unrestricted’ but experience suggests they have a more heterogenous morphology. Understanding the morphological variations and dimensions is the first step in modifying surgical closure or optimising potential device design. Purpose The objective of this study was to perform a comprehensive multi-center morphological analysis of the characteristics of the VSD in TOF. Additionally, we sought to perform a preliminary 2D shape analysis and principal component analysis (PCA) on standardised photos of the VSDs. Through this multi-dimensional approach, we aim to elucidate the morphological variations and structural characteristics of the VSD in TOF as a basis for future 3D shape analysis. Methods Of 495 specimens analysed, 460 were included in the morphological analysis. Standardised protocol was applied to assess the characteristics of the VSD: basic measurements of the height, width, inferior limb, and length of the inferior fibrous rim (if perimembranous) were taken and indexed to ventricular length. The degree of aortic override and presence of aorto-mitral continuity were also documented with double outlet right ventricle (DORV) being defined as more than 50% of aorta supported by the right ventricle. Statistical analysis was performed to assess variations in TOF morphology across different age groups and disease phenotypes. Standardised photographs of 130 VSDs were taken from the right ventricle and traced for PCA, in order to assess shape variations among the VSDs. Results Both the length of the inferior limb of the PM VSD and the length of the fibrous rim increased with ventricular length but the rate of change was lower for the fibrous rim. A chi-square analysis comparing the presence of double outlet right ventricle and the presence of a fibrous continuity between the aortic and mitral valves showed no association between these features (p = 0.89). The results of PCA in the indexed datasets showed that the largest variation was in the size of the VSD and then from the shape of the VSD where two distinct morphologies emerged: a classic V-shaped VSD and wide but shallow variant. Discussion Our study challenges conventional definitions and assumptions regarding the morphological characteristics of the VSD in TOF and suggests that components may change size at differing rates. Our study conclusively shows that DORV and TOF can co-exist and the definition of DORV should be made independently of the presence of aorto-mitral continuity. Contrary to the traditional view of TOF featuring large unrestricted VSDs, our findings suggest wide shallow VSDs are common. These findings challenge paradigms and underscore a necessity for the continuing morphological re-evaluation of TOF utilising large datasets with a diverse phenotypic spread.

Quality Evaluation of Kidney Tea Granules From Different Origins Based on TLC, HPLC Fingerprinting, and Quantitative Analysis Combined With Chemical Pattern Recognition.

Kidney tea is an essential herbal medicine. It is widely used to treat conditions such as urinary stones, gallstones, and rheumatoid arthritis. There is currently no standardized or widely accepted research strategy for evaluating the quality of kidney tea granules (KTGs) after granulation. In this study, we aim to establish a comprehensive strategy for evaluating the quality of KTGs produced from different sources of kidney tea. A TLC combined with HPLC method was established to identify the chemical components in KTGs, and HPLC method was used to determine the contents of rosmarinic acid of KTGs. In order to distinguish samples and identify differential components, similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted. TLC and HPLC detection confirmed three chemical components of KTGs, which are rosmarinic acid, caffeic acid, and lithospermic acid. HPLC fingerprint analysis revealed a total of seven common peaks in 15 batches of KTGs. Similarity analysis showed that the similarity of all 15 batches of KTGs was greater than 0.969. The peak areas of the seven common peaks were identified by chemical pattern recognition, and the results showed that most of the KTGs from different origins were clustered together, with small differences between them. The PCA and OPLS-DA results showed that two principal components can represent 82.638% of the common peaks of KTGs, among which peak 5 represents rosmarinic acid, which is the main differential biomarker of KTGs from different regions. Quantitative analysis of rosmarinic acid in KTG samples was performed using HPLC fingerprint conditions and the content of rosmarinic acid in 15 batches of KTGs samples was measured to be between 8.01-14.61 mg/g. This study combines TLC, HPLC, and chemometrics to establish a stable and reliable method that can quickly and effectively identify the components of KTGs, accurately quantify known components in KTGs, and provide reference for the quality evaluation of KTGs.

Rapid Method for Simultaneous Determination of γ-Oryzanol Compounds in Rice (Oryza sativa) Grains using UV-Vis Spectroscopy and Chemometrics

Rice (Oryza sativa) contains γ-oryzanol, which consists of 4 main compounds: Cycloartenol ferulate, 2,4-methylenecycloartanyl ferulate, campesterol ferulate, and β-sitosterol ferulate, that contribute to the health benefits of rice. This research aimed to develop a rapid method to determine the 4 major γ-oryzanol compounds in 45 varieties covering pigmented (black and red) and non-pigmented (white) rice grain. The method was developed by integrating UV-Vis spectroscopy with chemometrics, specifically principal component analysis (PCA) and partial least square (PLS) regression. Sampling was performed across the Indonesian archipelago collecting 180 samples, which comprises 60 samples for each type of rice in form of rice husk, bran, whole grain, and polished rice. The results of PCA on the spectroscopic data successfully identified distinction for the 3 types of rice attributable by different type and levels of chemical compound in the grain. White rice exhibited a characteristic absorption at 325 nm while in pigmented (red and black) rice showed a maximum absorbance at 280 nm, indicating the presence of different composition of chemical compounds. A reliable model to predict the 4 major γ-oryzanol compounds was established with R2 calibration, R2 cross-validation, and R2 prediction higher than 0.9 was obtained using the spectroscopic data in the range from 200 to 400 nm. However, the PLS modeling was unsuccessful for red and black rice samples most likely due to the interfering high absorption of red colored compounds. Compared to the existing techniques for analyzing individual compounds of the γ-oryzanol by high-performance liquid chromatography, the newly developed approach using UV-Vis spectroscopy combined with chemometrics is more practical, faster, and cost-efficient and mainly, solvent and residues free. HIGHLIGHTS A rapid method was developed to determine 4 major γ-oryzanol compounds in rice. This method integrates UV-Vis spectroscopy with PCA and PLS regression chemometrics. PCA successfully identified the distinction among white, red, and black rice types. Reliable PLS models were established for white rice with R2 values above 0.9. The developed approach is more practical, faster, and residue-free than HPLC. GRAPHICAL ABSTRACT

Single nucleotide polymorphism (SNP) analysis reveals ancestry and genetic diversity of cultivated and wild grapevines in Croatia

BackgroundCroatia is a geographically small country with a remarkable diversity of cultivated and spontaneous grapevines. Local germplasm has been characterised by microsatellite markers, but a detailed analysis based on single nucleotide polymorphisms (SNPs) is still lacking. Here we characterize the genetic diversity of 149 accessions from three germplasm repositories and four natural sites using 516,101 SNPs to identify complete parent-offspring trios and their relations with spontaneous populations, offering a proof-of-concept for the use of reduced-representation genome sequencing in population genetics and genome-wide association studies (GWAS).ResultsPrincipal component analysis revealed a clear discontinuity between cultivated (V. vinifera subsp. sativa) and spontaneous grapevines, supporting the notion that the latter represent local populations of the wild progenitor (V. vinifera subsp. sylvestris). ADMIXTURE identified three ancestry components. Two sativa components are alternatively predominant in cultivars grown either in northern Adriatic Croatia and Continental Croatia or in Dalmatia (i.e. central and southern Adriatic Croatia). A sylvestris component, which is predominant in accessions from spontaneous populations, is a minor ancestry component in cultivated accessions. TREEMIX provided evidence of unidirectional migration from the vineyards to natural sites, suggesting that gene flow has gone preferentially from the introduced domesticated germplasm into local wild populations rather than vice versa. Identity-by-descent analysis indicated an extensive kinship network, including 14 complete parent-offspring trios, involving only cultivated accessions, six full-sibling relationships and invalidated a presumed pedigree of one of the most important varieties in Croatia, ‘Plavac Mali’. Despite this strong population structure, significant association was found between 143 SNPs and berry skin colour and between 2 SNPs and leaf hairiness, across two previously known genomic regions.ConclusionsThe clear genetic separation between Croatian cultivars and sylvestris ruled out the hypothesis that those cultivars originated from local domestication events. On the other hand, the evidence of a crop-to-wild gene flow signals the need for an urgent adoption of conservation strategies that preserve the residual genetic integrity of wild relatives. The use of this reduced-representation genome sequencing protocol in grapevine enables an accurate pedigree reconstruction and can be recommended for GWAS experiments.

Characterization of Pasture Production Systems in Makueni County of Kenya

Livestock feed is a key factor influencing animal production and productivity as evidenced by the increased demand for animal source foods (ASFs) to feed a growing human population in Kenya. However, there exists untapped potential of pasture commercialization and hence the need to harness the social, economic and environmental benefits in the ASALs for overall rural development. A study was conducted to characterize the existing pasture production systems in Makueni County. A purposive random sampling of 300 respondents drawn from 3 Sub-counties and 12 wards was conducted in Makueni County in January, 2021. The study aimed to characterize existing pasture production systems using a structured questionnaire. Data were analyzed using descriptive and inferential statistics. Multivariate statistical techniques; principal Component Analysis (PCA) and Cluster Analysis (CA) were used to determine whether or not there were significant differences in the pasture production systems in Makueni County. Results of the study showed that majority (97%) of the farmers were small scale farmers (SSFs) who dedicated less than 5 acres of their land to pasture production. The mean age of small- scale farmers was 52 years compared to 55 years for the large-scale farmers (LSFs). Most of the households were male headed (83%). Most of the SSFs household heads had primary level of education level or lower while most of the large-scale household heads had secondary education and above. Majority (35%) of SSFs owned the land under pasture without a title while most of the LSFs had a title. The land under pasture for SSFs was about 2 acres with an average of 102 bales per season while LSFs had about 23 acres under pasture and produced about 1,762 bales per season. Majority (92%) grew local grass varieties and sold their pasture in form of a bale. 58% of SSFs sited NGOs as their main source of grass seeds while LSFs mainly sourced from agrovets Results of PCA revealed that 6 of the 17 components had eigen values greater than 1 and accounted for 58% of the total variance. Based on Euclidian distance, six clusters were determined using the agglomeration schedule. ANOVA analysis of the six profiles were estimated to have p-values of 0.000, suggesting the existence of significance difference between cluster 1 to 6 in relation to the 6 profiles and hence concluding the existence of variations in pasture production systems in Makueni County. Development strategies should focus on knowledge of and improved access to grass seeds to farmers as well as development of standards of the mode of sale of pasture.

Application of Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy in Human Sera: Validate the method for contributing effective strategy for the storage and preservation

The serum is one of the biological specimens that have been extensively studied as biomarkers and is recognized as an effective tool for screening and diagnosing a variety of diseases. Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) is a practical technique utilized in investigating characteristic spectra in infectious diseases cancer, and metabolic status. However, the pre-analytical procedure as storage condition is a crucial phase that directly impacts the accuracy of the result. In this study, we intend to investigate the effects of serum stabilization under both identical and distinct storage conditions on the FTIR spectral patterns, intensity variations, and macromolecule composition. The ten serum samples were stored in 3 different conditions including 4 °C, −20°C, and −80°C for six different time intervals (7, 14, 21, 28, 56, and 84 days). The spectra were obtained by ATR-FTIR spectroscopy. The serum stabilization was studied in two investigations: one focusing on the stability of serum under identical conditions over six different time intervals, and the other examining the stability of serum stored under three distinct conditions. Principal Component Analysis (PCA) and Area Under the Peak (AUP) were used to investigate clusters in different sets of data across five spectral ranges. The macromolecule composition was identified in conjunction with the intensity measurements. The results showed that the same conditions remained stable across six different time intervals, as indicated by the consistent PCA results. In contrast, the stabilization of serum under different temperature condition showed different major intensities across the five selected positive bands, including 1781 cm−1, 1740 cm−1 1727 cm−1 corresponding to lipid region (1800–1700 cm−1), and Amide region (1700 −1500 cm−1) at 1646 cm−1, and 1632 cm−1, when the serum was stored over 28 days. This might involve lipid peroxidation-induced changes in the secondary structure of proteins. Our findings indicated that serum should be stored at −80°C to ensure stabilization and achieve the highest intensity. Additionally, preserving serum under consistent conditions was crucial to minimize variability and prevent external factors from affecting the results.

Testosterone hormone levels and breast muscle performance of Pelung chickens after zinc sulfate and synthetic testosterone supplementation

Background and Aim: Pelung chicken Gallus gallus gallus (Linnaeus, 1758) is a chicken endemic to Cianjur, West Java, Indonesia. This study aimed to determine the effects of zinc sulfate (ZnSO4) and synthetic testosterone supplementations for 56 days on testosterone hormone levels and breast muscle performance in Pelung chickens. Materials and Methods: This study used 12 Pelung chickens with three treatment groups (G) and four replications, namely, control (G0), ZnSO4 0.9 mg/kg (G1), and synthetic testosterone 3 mg/day (G2). Chickens were acclimatized for 7 days and then supplemented for 56 days. Drinking water and commercial standard feed were provided ad libitum. Blood was collected through the brachial vein for the analysis of testosterone levels using the enzyme-linked immunosorbent assay. The samples were collected every 14 days; on days 0, 14, 28, 42, and 56. Breast muscles were collected for texture analysis, and breast muscle preparations were made with hematoxylin-eosin staining to measure the fascicle area (FA), number of myofibers in one fascicle (NMOF), and myofiber area (MA). The collected data were analyzed using analysis of variance at a 95% confidence level with the help of Statistical Package for the Social Sciences v.29.0. Furthermore, principal component analysis (PCA) was performed with the help of Minitab v. 19. Results: Statistical analysis results on 56 days of testosterone level parameters showed that G2 was significantly different from all treatments (p < 0.05). The results of statistical analysis on Pelung chicken breast muscle performance, especially hardness, chewiness, FA, NMOF, and MA, were significantly different (p < 0.05) compared with the other treatments. The results of PCA showed that the testosterone level parameters were positively correlated with FA, NMOF, MA, hardness, and chewiness, whereas the fracture parameters were negatively correlated with all parameters except the springiness index and were significantly different between the G2 group and the other groups (p < 0.05). Conclusion: It can be concluded that supplementing synthetic testosterone 3 mg/day body weight for 56 days can improve testosterone levels and breast muscle performance, especially hardness, chewiness, FA, NMOF, and MA in Pelung chickens. Keywords: muscle, Pelung chicken, performance, testosterone, texture.

Determination of gelatin from marshmallows using a combination of fourier transform infrared (ATR-FTIR) spectroscopic and chemometrics for halal authentication

Marshmallow is a foam that contains aerated sugar, which is stabilized with gelatin or egg albumin. In this research, a Fourier Transform Infra-Red (ATR-FTIR) spectroscopy combined with the Chemometrics methods is developed to distinguish the presence of porcine gelatin in marshmallows, which can then be used to identify halal products. This method provides fast and rapid testing of halal products. Marshmallows were made with varying concentrations of bovine and porcine gelatine as the reference. Commercial marshmallows were collected in the online marketplace by purposive sampling. Isolated gelatin was analyzed using the ATR-FTIR spectrophotometer, and data analysis was continued using PCA (Principal Component Analysis). The results showed that bovine gelatin absorbed at a wavenumber of 1638 cm-1, while porcine gelatin produced a sharp absorption at 1697 and 1654 cm-1. The results of PCA analysis show that 100% of bovine gelatin marshmallows (S100) have areas different from marshmallows containing a mixture of porcine gelatin. The PCA results of four samples (A1, A2, A3, and A4) show they are in the same area as 100% bovine gelatin marshmallows (S100). This shows that it is suspected that the four marshmallow samples tested did not contain porcine gelatin. The multivariate regression curve showed that the pattern of linear absorbance changes along with porcine gelatin concentrations with the highest coefficient equation is from wavenumber 1093.97 cm-1. Keywords: ATR-FTIR, Bovine gelatin, Chemometric, Marshmallow, Porcine gelatin

Comparative Analysis of Frying Performance: Assessing Stability, Nutritional Value, and Safety of High-Oleic Rapeseed Oils.

Frying is a critical process in the food industry, where selecting appropriate vegetable oils is key to achieving optimal results. In this study, French fries were fried at 175 °C with five different oils, the changes in the physicochemical indexes and free radical scavenging rate of the oils during the frying process were investigated, and the most suitable oils for frying were identified through comparative analysis using principal component analysis (PCA). We assessed the frying performances of hot-pressed high-oleic-acid rapeseed oil (HHRO), cold-pressed high-oleic-acid rapeseed oil (CHRO), soybean oil, rice bran oil, and palm oil utilizing principal component analysis over an 18 h period. The HHRO and CHRO showed lower acid values (0.31, 0.26 mg/g), peroxide values (2.09, 1.96 g/100 g), p-anisidine values (152.48, 178.88 g/mL), and total polar compound percentages (27.60%, 32.10%) than other oils. Furthermore, both the HHRO and CHRO demonstrated enhanced free radical scavenging abilities, indicative of their higher antioxidant capacities, as corroborated by the PCA results. Benzopyridine, 3-monochloropropane-1,2-diol ester, squalene, tocopherols, and polyphenol from the HHRO and CHRO during frying were compared. A comprehensive examination of harmful substances versus nutrient retention during frying revealed that the HHRO contained fewer hazardous compounds, while CHRO retained more nutrients. Therefore, this study analyzes the oxidation regulation of HHRO in frying applications, highlights the prospects of HHRO for frying in terms of health and economy, and contributes valuable insights for informed vegetable oil selection within the food industry.

Species discrimination of β-phenylethylamine, NaCl and NaOH based on Ultraviolet spectroscopy and principal component analysis combined with improved clustering by fast search and find of density peaks algorithm

This paper aimed at putting forward an approach integrating the improved clustering by fast search and find of density peaks (I-CFSFDP) algorithm with Ultraviolet (UV) spectroscopy for identifying the species of NaCl, NaOH, β-phenylethylamine(PEA) and their mixtures. For solving the issue that the clustering precision of the CFSFDP algorithm relies on the density forecast of the dataset and the manually selection of the truncated distance dc. The idea of kernel density forecast was adopted to the I-CFSFDP algorithm. The I-CFSFDP algorithm can observe the clusters of arbitrary shapes and use an adaptive method to evaluate the truncated distance dc, thereby generating more accurate clusters and identifying the core points in the clusters effectively. The dimensions of the UV spectra was reduced with principal component analysis (PCA), and the results of PCA were invoked as the input of the I-CFSFDP algorithm. Meanwhile, the effect of PCA-I-CFSFDP was evaluated by recall, accuracy, F-Score and precision. Besides, the DBSCAN and PCA-CFSFDP algorithms were used to compare with the PCA-I-CFSFDP algorithm. All of the classification outcomes displayed that the PCA-I-CFSFDP algorithm has better performance than the DBSCAN and PCA-CFSFDP algorithms. Therefore, the PCA-I-CFSFDP algorithm integrated with UV spectroscopy is a simple, quick and credible identification approach for detecting PEA, NaCl, NaOH and the mixtures.

An untargeted comparative metabolomics analysis of infants with and without late-onset breast milk jaundice.

Late-onset breast milk jaundice (LBMJ) is a common form of hyperbilirubinemia, which can result in serious complications for newborns with persistently high bilirubin levels. The aim of this study was to investigate the differences in fecal metabolites between breastfed infants with and without LBMJ in order to elucidate potential biological mechanisms. Biological samples were collected from 12 infants with LBMJ and 12 healthy individuals. Ultra-high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF/MS) was utilized for non-targeted determination of fecal metabolites. Principal components analysis (PCA), cluster analysis, and differential metabolite analysis were performed in both positive ion mode and negative ion mode for the two groups. Additionally, the KEGG database was employed to comprehensively analyze the pathways of differential metabolites. There were no significant differences in maternal and neonatal demographic characteristics between the two groups (p > 0.05). The results of PCA and cluster heat map analysis in both modes showed that there were significant differences in metabolites between the two groups. Among 751 differential metabolites (DMs) detected in positive ion mode, 720 were up-regulated in the case group while 31 were down-regulated. In negative ion mode, 1891 DMs were detected, including 817 up-regulated metabolites and 1074 down-regulated metabolites in the case group. Analysis of differential metabolic pathways showed that the DMs of the two groups were mainly annotated and enriched in Biotin metabolism, N-Glycan biosynthesis, Taurine and hypotaurine metabolism, Pyrimidine metabolism, and Pentose and glucuronate interconversions. Significant differences exist in fecal metabolites between LBMJ infants and healthy controls. The study of differential metabolic pathways provides insights into the mechanism of LBMJ.

The analysis of the essential metal contents in khat (Catha edulis Forsk) from Meru County, Kenya

BackgroundChemical composition of plants has attracted considerable interest in recent years with considerable research tailored into determining metal contents in food substances. Particularly, essential elements which are necessary for normal human body functioning and are strongly recommended in optimal proportions for better health. This study determined the levels of essential elements; calcium (Ca), magnesium (Mg), sodium (Na), potassium (K) and manganese (Mn) in eleven khat (Catha edulis Forsk) samples collected from Meru County. Methodology1.0 g of dry ground khat samples were wet-digested in a solvent mixture of 10 mL of HCl, HNO3 and 20 vol of H2O2 for 3 h at variable temperature of 50–90 °C and later reconstituted in 25 mL 0.05 molL−1 HCl before analysis. The samples were analyzed using inductively coupled plasma atomic emission spectrometry (ICP AES) after acid digestion whereas Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to investigate elemental characteristics and determine the sources of essential metals in khat. In addition, Pearson correlation coefficient (PCC) was used to evaluate the relationships between the essential metals. ResultsSpinach leaves certified reference material (CRM 1750a) was analyzed and the percentage recoveries (%) of 98.4 and 101.7 determined showing that the digestion method employed in this work had adequate accuracy. The validated method was employed for the analysis of all the khat samples. The analyzed metal concentration ranges (mg100g−1) in fresh-weight basis per day of five metals were 160.9–267.3, 44.6–81.7, 2.0–3.0, 237.6–393.6, and 220.3 -349.0 for Ca, Mg, Mn, K, and Na, respectively. Both HCA and PCA results showed that these elements could be linked to natural soils and anthropogenic sources. PCC reported significant correlations between Na and K indicating they may have been derived from the same source. The daily metal intakes were below the World Health Organization (WHO) permissible limits implying no associated health risks for khat users. ConclusionBased on the findings of this study, the consumption of khat from regions of Meru County may be a potential source for essential elements required for human biological processes.

Soil quality assessment in the Araban plain across various land use types

BackgroundSoil is an important resource for improving the quality of human well-being and creating sustainable environmental awareness. Therefore, it is imperative to protect the soil health. This study determined quality of the soils in the Araban plain, Türkiye using three different methods, i.e., principal component analysis (PCA), analytic hierarchy process (AHP), and expert opinion (EO). The major aim was to determine the most appropriate method for determining soil quality and recommending soil protection practices for improving quality. MethodsThis study was conducted on an area of approximately 25,000 ha. A total of 230 soil samples (7 pasture areas, 56 orchards, and 167 arable crops) were analyzed to determine key soil quality indicators. A minimum dataset consisting of parameters that best represent the soils of the region was created. Subsequently, PCA was used to predict soil quality with the optimal accuracy using the least amount of data. The EO was incorporated to validate the PCA results. The AHP was used to assign weights to the parameters. Indicators at all sampling points were converted to unitless scorers. These scores were then formulated as soil quality index (SQI) using the weighted summation method. ResultsOrganic matter (OM) exerted the highest impact on soil quality. Significant variations in SQI values were observed among arable land, orchards land and pastureland (P < 0.01). Significant variations were recorded in SQI values of the assessment methods employed in this study. The lowest (0.552) and highest (0.829) SQI values were recorded for AHP and EO, respectively. Overall, streamlining indicators through PCA gave the most accurate result for SQI value. Subsequently, SQI determination should involve weighing with AHP, particularly towards EO. ConclusionThe AHP was found to be the most appropriate method for evaluating soil quality in Araban. This integrated approach ensures a robust evaluation of soil quality, facilitating more accurate and nuanced insights for informed land management decisions. Overall, 92.61 % of the region’s soil had poor and medium soil quality. Therefore, increasing OM content and aggregate stability are suggested to improve soil quality in the study region.

Exploring GIS-Based Modeling for Assessing Social Vulnerability to Ganga Riverbank Erosion, India

Riverside communities along the lower Ganges in India face significant threats like riverbank erosion, floods, and climate change impacts. Despite extensive research on riverbank erosion in the region, a key gap remains in understanding how erosion and climate change jointly affect local communities. Additionally, research prioritizing village-level studies and strategies is urgently needed for effective management of the study area. This study aimed to compute a GIS-based Social Vulnerability Index (SociVI) by assessing 10 components and 31 sub-components at the village level. We used spatial analysis techniques like Moran's I and Getis-Ord G* to identify hotspots and clustering patterns among variables and SociVI values. Principal component analysis (PCA) and multi-correlation statistics determined the most significant component. Our fieldwork involved surveying 1,641 households, 547 focus group discussions, and 12 key informant interviews across 547 villages. The SociVI analysis revealed that residents on the left bank of the river, particularly in the upper section of the Farakka barrage, and those living in the char villages were highly susceptible to social vulnerability. Scores ranged from 0.67 to 0.88, with 34 villages (6.22%) on the left bank and 8 villages (1.46%) on the right bank showing notably high SociVI values. Furthermore, our hot spot analysis identified 51 villages (9.32%) as hot spots with 99% confidence, 7.13% of which were located on the left bank and 2.19% on the right bank. According to the PCA results, demographics (PC1), riverbank calamities (PC2), displacement of households (PC3), and climatic variability (PC4) emerged as the most significant factors. This study's findings are crucial, highlighting critical areas and villages requiring focused efforts to reduce local vulnerability and bolster adaptation capacities amid these challenges.

A comprehensive and innovative chemometric approach: Archaeometric analysis of the sherds from the Neolithic Period to the Chalcolithic and early Bronze Age with the full deployment of FTIR's molecular spectroscopic capabilities

In this study, the mineralogical composition of 284 sherds obtained from the sites of Yeşilova Höyük and Yassıtepe Höyük, two of the oldest settlements in Western Anatolia, and corresponding to a wide period starting from the Neolithic period to the Chalcolithic and Early Bronze Age (EBA), was studied by attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy. FTIR data was used to classify the sherds and state their firing conditions as a result of determining their mineralogical composition using principal component analysis (PCA), multivariate curve resolution (MCR), and hierarchical cluster analysis (HCA). According to the PCA results, the second-order derivative FTIR spectrum with 19 smoothing points in the range of 1300–400 cm−1 was determined to be the most successful model in classifying sherds. As a result of MCR, which allows comparison of standard minerals obtained within the scope of the study, it was determined that kaolinite, illite, chlorite, and some feldspar types were dominant in the sherds. According to HCA analysis, all sherds except five of them exhibited a similar mineralogical structure. According to the derivative spectra, it was seen that the sherds had a composition consisting of kaolinite, illite, hematite, chlorite, and some feldspar types at different rates. Upon examining the data, it becomes evident that the sherds are composed of nearly identical minerals and might have been fired in an oxidizing atmosphere. Even while 279 sherds had many mineralogical traits, N-061, EB-030, N-043, C-068, and N-059 were found to have distinct proportions of comparable minerals, including more kaolinite, illite, calcite, and chlorite. Regarding color, additives, and the amount of ceramic pastes present, these five sherds differ from the others. This suggests that there might have been attempts at manufacture or pots brought in from outside the Yeşilova Höyük-Yassıtepe Höyük sites. The results provided from the derivative spectra showed that all sherds except five of them have been fired at about at temperatures slightly above 450–500 °C due to their relatively low kaolinite character, but below 800 °C because diopside and similar high-temperature minerals could not be detected. The five sherds may have been fired at a temperature of around 450–500 °C due to the presence of a high character of kaolinite, illite, and chlorite. It was understood that the residents of the sites of Yeşilova Höyük and Yassıtepe Höyük produced their ceramics using the same raw materials and the same production methods from the Neolithic period to EBA thanks to FTIR and chemometrics, which are very good tools for analyzing large numbers of sherds with low cost and fast analysis time.

Design E-Learning User Interface On Website-Based Edspert.Id With Kansei Engineering Methods

The development of information technology has encouraged people to rely on information systems, especially through websites. Websites provide easy access to information and learning with various educational materials. Although e-learning has been implemented in many educational websites, Edspert. id, a company in the education sector, has not implemented it yet. User interface design development is one of the important processes in e-learning website development. A user interface that is easy to use will improve the learning experience of learners. This research proposes a solution to design the user interface of Edspert.id e-learning website by using the Kansei Engineering method. This approach has been done beforefor web-based e-learning based on users' emotions. Principal component analysis (PCA) is used to reduce Kansei Word variables that are relevant to users' emotions. The e-learning website element design was then designed based on the PCA results. The next step is to determine the design elements in the e-learning design. Then, partial Least Square (PLS) was used to analyze the relationship between Kansei Word and element design. The results show that there multiuser interface design has two concepts whose element designs are in accordance with user needs.

Origin of spring water chemistry and its appropriateness for drinking requirements in a semi-arid environment (Ain Larbi, Algeria)

ABSTRACT A comparative assessment of water quality for drinking purposes was conducted in Ain Larbi area using the Weighted Arithmetic Water Quality Index (WA-WQI). The origin of minerals is assessed by a saturation index approach and the Gibbs diagram. Also, mineral correlation process and ion exchange mechanism are detected by the Principal Component Analysis (PCA). The PCA results indicate that the groundwater quality in the Ain Larbi study area primarily results from weathering and geochemical alteration of rock. The saturation index and Gibbs diagram support these findings. The WA-WQI was calculated for each station based on physicochemical parameters. During the wet season, three out of five classes of WQI were observed in the present study, including excellent (25%), good (70%), and poor (5%). In the dry season, the classes excellent (25%), good (30%), and poor (45%) were represented. The present situation demonstrates how hydrogeological regimes and water–rock interactions affect groundwater ion concentrations. Our results contribute to identifying drinking water requirements in the Ain Larbi region, promoting sustainable water management.

Analysis of lard in cod liver oil emulsion using FTIR spectroscopy combined principal component analysis

Cod liver oil (CLO) contains essential fatty acids and has a high price in the market. Therefore, CLO can be targeted for adulteration to increase economic profits. One of the substances used for adulteration of CLO is lard. This study aimed to analyze the spectral profile of lard and CLO in cod liver oil emulsion using Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis (PCA). Lard and CLO were mixed with a range of concentrations of 0-100% used as the control. CLO emulsions were made with a composition of lard and CLO in concentrations similar to those of the control. To analyze the lard and CLO spectrum, lard and CLO were extracted from the emulsion using liquid-liquid extraction, and then the oil extracted from the emulsion was analyzed using FTIR spectroscopy and PCA. Fourier transform infrared spectrum absorption at region 1117–1098 cm-1 is specific to identifying the different spectrums of CLO and lard. The results of PCA showed that clustering between similar oil content and a combination of FTIR and PCA is effective in distinguishing the spectrum of lard and CLO in cod liver oil emulsion.

Geochemistry of Cenozoic coals from Sarawak Basin, Malaysia: implications for paleoclimate, depositional conditions, and controls on petroleum potential

Forty Tertiary coals from Mukah-Balingian and Merit-Pila coalfields of the Sarawak Basin, Malaysia were investigated using bulk and molecular geochemical techniques such as proximate analysis, gas chromatography-mass spectrometry, elemental analyser, isotope ratio mass spectrometry, and inductively coupled plasma mass spectrometry to reconstruct their paleovegetation, paleoclimate, and environments of deposition. In addition, principal component analysis (PCA) of selected geochemical parameters was carried out to determine the controlling influences on the petroleum potential of the humic coals. δ13C values and the abundance of terpenoids imply the predominant contribution of angiosperms to the paleoflora. Bimetal proxies (Sr/Ba, Sr/Cu, and C-value), and δD values are generally suggestive of a warm and humid climate during the accumulation of the paleopeats. However, n-alkane proxies (Pwax, Paq, n-C23/n-C29, etc.) and polycyclic aromatic hydrocarbons (PAHs) distribution suggest that Balingian coals accumulated under relatively drier and strongly seasonal paleoclimate in the Late Pliocene. When compared with published global average abundances, the investigated coals are mostly depleted in major oxides and trace elements, suggesting peat accumulation in freshwater-influenced environments. Nonetheless, higher (> 0.5 wt%) total sulfur content in some Mukah-Balingian coals suggests some degree of epigenetic marine influence. Furthermore, the low to moderately-high ash contents of the Sarawak Basin coals indicate the presence of ombrotrophic and rheotrophic peat deposits. PCA result of selected geochemical proxies suggests that source input, paleoflora, and marine incursions are not major controlling influences on the petroleum potential. However, climatic, and depositional conditions appear to slightly influence the petroleum potential of the studied humic coals.

Coastline Automatic Extraction from Medium-Resolution Satellite Images Using Principal Component Analysis (PCA)-Based Approach

In recent decades several methods have been developed to extract coastlines from remotely sensed images. In fact, this is one of the principal fields of remote sensing research that continues to receive attention, as testified by the thousands of scientific articles present in the main databases, such as SCOPUS, WoS, etc. The main issue is to automatize the whole process or at least a great part of it, so as to minimize the human error connected to photointerpretation and identification of training sites to support the classification of objects (basically soil and water) present in the observed scene. This article proposes a new fully automatic methodological approach for coastline extraction: it is based on the unsupervised classification of the most decorrelated fictitious band derived from Principal Component Analysis (PCA) applied to the satellite images. The experiments are carried out on datasets characterized by images with different geometric resolution, i.e., Landsat 9 Operational Land Imager (OLI) multispectral images (pixel size: 30 m), a Sentinel-2 dataset including blue, green, red and Near Infrared (NIR) bands (pixel size: 10 m) and a Sentinel-2 dataset including red edge, narrow NIR and Short-Wave Infrared (SWIR) bands (pixel size: 20 m). The results are very encouraging, given that the comparison between each extracted coastline and the corresponding real one generates, in all cases, residues that present a Root Mean Squared Error (RMSE) lower than the pixel size of the considered dataset. In addition, the PCA results are better than those achieved with Normalized Difference Water Index (NDWI) and Modified NDWI (MNDWI) applications.