Principal Component Analysis Research Articles

Estimation of Time-Since-Deposition of bloodstains on different surfaces using ATR-FTIR Spectroscopy and Chemometrics.

Blood is commonly discovered at crime scenes in various forms, including stains, dried residue, pools, and fingerprints on assorted surfaces. Estimating the age of bloodstains is a crucial aspect of reconstructing crime scenes. This research aimed to investigate how the nature of different surfaces affects the estimation of bloodstain age, utilizing a reliable and non-destructive approach. The study employed ATR-FTIR spectroscopy in conjunction with Chemometric techniques such as PCA (Principal Component Analysis) and OPLSR (Orthogonal Signal Correction Partial Least Square Regression Analysis) to analyze spectral data and develop regression models for estimating bloodstain age on cement, metal, and wooden surfaces for up to eleven days. The chemometric models for bloodstains on all three substrates demonstrated strong performance, with predictive Root Mean Square Error (RMSE) values ranging from 1.1 to 1.43 and R2 values from 0.84 to 0.89. Notably, the model developed for metal surfaces was found to be the most accurate with minimal prediction error. The findings of the study showed that the porosity of the substrates upon which bloodstains were found had a discernible influence on the age-related transformations observed in bloodstains; the majority of which occured within the spectral range of 2800cm- 1 to 3500cm- 1.

Identifying the obstacles facing emergency nurses regarding treating CTAS1 and CTAS2 in Saudi Arabia

BackgroundEmergency nurses play a pivotal role in delivering efficient emergency healthcare, yet they often encounter numerous challenges, especially while managing life-threatening cases, impacting both their well-being and patient satisfaction. This study seeks to identify the prevalent challenges faced by these nurses in Saudi hospitals when handling Canadian Triage and Acuity Scale (CTAS1 and CTAS2) cases, with the aim of mitigating or managing these issues in the future.MethodsThis study incorporated a mixed-method approach to identify obstacles in Emergency Department (ED) nursing treatment of CTAS1 and CTAS2 cases in two major Saudi Arabian hospitals. The research began with qualitative focus group interviews with expert ED nurses, followed by a quantitative survey to measure and explore relationships among the qualitative findings. Data analysis leveraged qualitative thematic analysis and principal component analysis, ensuring rigorous examination and validation of data to drive meaningful conclusions.FindingsFrom expert interviews, key challenges for emergency nurses were identified, including resource management, communication, training compliance, and psychological factors. A survey of 172 nurses further distilled these into five major issues: patient care management, handling critical cases, administration support, patient care delay, and stress from patients’ families.ConclusionThrough a mixed-method approach, this study pinpoints five pivotal challenges confronting emergency nurses in Saudi hospitals. These encompass difficulties in patient care management, the psychological toll of handling critical cases, inadequate administrative support, delays due to extended patient stays, and the stress induced by the presence of patients’ families, all of which significantly impede emergency department efficiency and compromise nurse well-being.

Empowering the rapid authentication of the botanical origin of monofloral honey by coated blade spray mass spectrometry (CBS-MS)

In the quest for a rapid and cost-effective tool for determining the botanical origin of monofloral honey, the analytical capabilities of coated blade spray mass spectrometry (CBS-MS) were investigated. To this aim, the chemical profiles of 64 honey samples from seven different botanical origins (acacia, dandelion, chestnut, rhododendron, citrus, sunflower, and linden) were captured by the absorbent of the coated blades and then analyzed by mass spectrometry. An exploratory analysis was performed by principal component analysis (PCA) to generate a graphical representation of the CBS-MS data that allows the discovery of patterns, outliers, or relations between types of honey in an unsupervised manner. Additionally, the performances of four different classification algorithms (least absolute shrinkage and selection operator (LASSO), random forest (RF), and neural network (NNET) partial least squares discriminant analysis (PLS-DA)) were built up and compared. The performances of the four classifiers were verified by a 50 times-repeated, 5-fold-cross-validation and permutation test. Although all classifiers performed well, the RF showed significantly higher performances in cross-validation (with area under the curve (AUC) of 0.99, overall accuracy 0.94, Kappa 0.93, sensitivity 0.94, and specificity 0.99). Moreover, the permutation tests showed the models were not overfitted. Finally, to determine the molecular identities of the ions that most contribute to the classification, extracts from the same honey samples were prepared, analyzed by liquid chromatography coupled to high resolution tandem mass spectrometry (LC-HRMS/MS), and the most significant features were annotated. This proof-of-principle work warrants a future large-scale study to validate and challenge this CBS-MS-based method with a greater number of honeys from different years and geographical origins.

Comprehensive Lipidomic Analysis of Three Edible Microalgae Species Based on RPLC-Q-TOF-MS/MS.

Microalgae, integral to marine ecosystems for their rich nutrient content, notably lipids and proteins, were investigated by using reversed-phase liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RPLC-Q-TOF-MS/MS). This study focused on lipid composition in three commonly used microalgae species (Spirulina platensis, Chlorella vulgaris, and Schizochytrium limacinum) for functional food applications. The analysis unveiled more than 700 lipid molecular species, including glycolipids (GLs), phospholipids (PLs), sphingolipids (SLs), glycerolipids, and betaine lipids (BLs). GLs (19.9-64.8%) and glycerolipids (24.1-70.4%) comprised the primary lipid. Some novel lipid content, such as acylated monogalactosyldiacylglycerols (acMGDG) and acylated digalactosyldiacylglycerols (acDGDG), ranged from 0.62 to 9.68%. The analysis revealed substantial GLs, PLs, and glycerolipid variations across microalgae species. Notably, S. platensis and C. vulgaris displayed a predominance of fatty acid (FA) 18:2 and FA 18:3 in GLs, while S. limacinum exhibited a prevalence of FA 16:0, collectively constituting over 60% of the FAs of GLs. In terms of PLs and glycerolipids, S. platensis and C. vulgaris displayed elevated levels of arachidonic acid (AA) and eicosapentaenoic acid (EPA), whereas S. limacinum exhibited a significant presence of docosahexaenoic acid (DHA). Principal component analysis (PCA) revealed MGDG (16:0/18:1), DG (16:0/22:5), Cer (d18:1/20:0), and LPC (16:1) as promising lipid markers for discriminating between these microalgae samples. This study contributes to a comprehensive understanding of lipid profiles in three microalgae species, emphasizing their distinct biochemical characteristics and potentially informing us of their high-value utilization in the food industry.

Difference in Gastrointestinal Cancer Risk and Mortality by Dietary Pattern Analysis: A Systematic Review and Meta-Analysis.

Several studies have demonstrated that dietary patterns identified by a posteriori and hybrid methods are associated with gastrointestinal (GI) cancer risk and mortality. These studies applied different methods for analyzing dietary data and reported inconsistent findings. This systematic review and meta-analysis were aimed to determine the association between dietary patterns, derived using principal component analysis (PCA) and reduced rank regression (RRR), and GI cancer risk and GI cancer-caused mortality. Articles published up to June 2023 in English were eligible for inclusion. The Medline, SCOPUS, Cochrane Library, CINHAL, PsycINFO, ProQuest, and Web of Sciences databases were used to identify prospective studies. The Preferred Reporting Item for Systematic Review and Meta-analysis Protocol 2020 was used to report results. A total of 28 studies were eligible for inclusion. Varied approaches to deriving dietary patterns were used, including PCA (n = 22), RRR (n = 2), combined PCA and RRR (n = 1), cluster analysis (CA; n = 2) and combined PCA and CA (n = 1). Two dietary patterns, "healthy" and "unhealthy," were derived using PCA and RRR. The healthy dietary pattern was characterized by a higher intake of fruits, whole grains, legumes, vegetables, milk, and other dairy products, whereas the unhealthy dietary pattern was characterized by a higher intake of red and processed meat, alcohol, and both refined and sugar-sweetened beverages. The findings indicated that the PCA-derived healthy dietary pattern was associated with an 8% reduced risk (relative risk [RR], 0.92; 95% CI, 0.87-0.98), and the unhealthy dietary pattern was associated with a 14% increased risk (RR, 1.14; 95% CI, 1.07-1.22) of GI cancers. Similarly, the RRR-derived healthy dietary pattern (RR, 0.83; 95% CI, 0.61-1.12) may be associated with reduced risk of GI cancers. In contrast, the RRR-derived unhealthy dietary pattern (RR, 0.93; 95% CI, 0.57-1.52) had no association with a reduced risk of GI cancers. Similarly, evidence suggested that PCA-derived healthy dietary patterns may reduce the risk of death from GI cancers, whereas PCA-derived unhealthy dietary patterns may increase the risk. Findings from prospective studies on the association of PCA-derived dietary patterns and the risk of GI cancers support the evidence of healthy and unhealthy dietary patterns as either protective or risk-increasing factors for GI cancers and for survivorship, respectively. The findings also suggest that the RRR-derived healthy dietary pattern reduces the risk of GI cancers (albeit with low precision), but no association was found for the RRR-derived unhealthy dietary pattern. Prospective studies are required to further clarify disparities in the association between PCA- and RRR-derived dietary patterns and the risk of GI cancers. Systematic review registration: PROSPERO registration no. CRD42022321644.

Translation and psychometric properties of the Arabic version of the ageism scale for dental students (ASDS-Ar): A multi-institutional validation.

Ageism represents an important barrier to high-quality healthcare for older adults. The present study sought to translate and validate the Arabic version of the Ageism Scale for Dental Students (ASDS-Arabic). The 27-item ASDS tool was translated from English into Arabic following recommended cross-sectional forward and backward translation guidelines. The translated version was subjected to the content validity ratio (CVR) and sent to dental students in 21 institutes from 10 different Arab countries. Principal components analysis (PCA) was used to assess the dimensionality of the scale, and Cronbach's alpha was used to determine internal consistency reliability. The discriminant validity of the scale was assessed using the independent t-test. Confirmatory factor analysis (CFA) was also undertaken. Based on CVR, three items were removed. The 24-item Arabic version was completed by 3284 dental students. PCA and CFA retained 17 items in six components, explaining 50.3% of the total variance, with acceptable reliability, validity and discrimination. The first component "Adherence of older patients with dental treatment and instructions," included four items with a Cronbach α of 0.64 and scored 4.3 ± 0.8. The second component "Feasibility of the treatment plan," included three items with a Cronbach α of 0.66 and scored from 2.6 ± 1.2 to 2.9 ± 1.1. The third component "Cost of and responsibility for the dental treatment" included four items with a Cronbach α of 0.47 and scored 4.4 ± 0.8 to 4.5 ± 0.8. The fourth component "Medical history of older patients" included two items with a Cronbach α of 0.70 and scored 4.0 ± 1.0 to 4.1 ± 1.0. The fifth Component "Feeling towards older patients" included two items with a Cronbach α of 0.672 and scored 2.6 ± 1.2 to 2.0 ± 1.4. The sixth Component "Confidence and experience in treating older patients" included two items with a Cronbach α of 0.33 and scored 4.4 ± 1 to 4.6 ± 1. This preliminary validation of the ASDS-Ar resulted in a new 17-item scale with six components with acceptable validity, reliability and discrimination.

In Silico Exploration of Isoxazole Derivatives of Usnic Acid: Novel Therapeutic Prospects Against α-Amylase for Diabetes Treatment.

Diabetes mellitus (DM) a metabolic disorder characterized by high blood sugar levels causing damage to various organs over time. Current anti-diabetic drugs have limitations and side effects, prompting a search for new inhibitors targeting the α-amylase enzyme. This study aims to discover such inhibitors from thirty isoxazole derivatives of usnic acid using in silico approaches. The potential inhibitory effects of compounds were investigated using ADMET, molecular docking, molecular dynamic simulation, principal component analysis and density functional theory studies. ADMET analysis exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities with no significant side effects which were then investigated using molecular docking experiment to determine the lead compound with the best binding affinity for the α-amylase enzyme. All compounds showed good binding affinity against α-amylase enzyme (-7.9 to -9.2 kcal/mol) where compound-13 showed the best binding affinity of -9.2 kcal/mol forming hydrogen bonds with Leu162, Tyr62, Glu233 and Asp300 amino acids. Furthermore, the binding posture and the stability of the compound-13-α-amylase enzyme complex was confirmed by molecular dynamic simulation experiment. Moreover, compound-13 showed binding energy value of -27.92 ± 5.61 kcal/mol, which indicated it could be an α-amylase inhibitor. Additionally, the reactivity of compound-13 was further confirmed by density functional theory analysis. The above findings suggest compound-13 to be a potential α-amylase inhibitor in DM. And setting the stage for further in vitro and in vivo experimental validation.

Intrinsic satisfaction and turnover intentions: the moderating roles of collegial and managerial values congruence

PurposeThis paper investigates the moderating role of values congruence, an element of person–organisation (P–O) fit, on the relationship between intrinsic work satisfaction and anticipated employee turnover. The model uses data from employees of the Australian Public Service (APS).Design/methodology/approachThe study draws upon data from the APS’s annual Employee Census for 2018. We first use principal component analysis (PCA) to derive measures of collegial values congruence, managerial values congruence, intrinsic satisfaction and extrinsic satisfaction. The study then uses ordinary least squares (OLS) regression analysis to examine the main effects of intrinsic and extrinsic satisfaction, collegial and managerial values congruence as well as their interaction effects on anticipated future employee tenure.FindingsOur results show the significant linear effects of intrinsic satisfaction, extrinsic satisfaction and managerial values congruence on anticipated tenure. Collegial values congruence, however, did not show a significant linear effect. Interaction effects were then tested, and both collegial and managerial values congruence were shown to moderate the relationship between intrinsic satisfaction and anticipated tenure. Higher levels of both forms of values congruence buffered the negative impact of lower intrinsic satisfaction on turnover intention.Research limitations/implicationsThe study is limited by its reliance on cross-sectional self-reported data within a specific and atypical organisational context (the Australian Public Service, or APS). Additionally, the cross-sectional nature of the data limits the establishment of causal inferences. Future research could explore longitudinal data and examine other potential moderators of the turnover intention.Practical implicationsUnderstanding the moderating role of values congruence, and in particular P–O fit, can develop organisational strategies that aim to reduce turnover by emphasizing the alignment between employee values and organisational, collegial and supervisor culture and values.Originality/valueThis study contributes to the relevant literature by showing the importance of values congruence in partially offsetting the negative effects of low intrinsic satisfaction on anticipated turnover. This is particularly relevant in the public sector context. The examination of both collegial and managerial values congruence provides a more nuanced understanding of the mechanisms that drive turnover intention.

Molecular identification and morphological variations of Amblyomma lepidum imported to Egypt, with notes about its potential distribution under climate change.

The tick Amblyomma lepidum is an ectoparasite of veterinary importance due to its role in transmitting livestock diseases in Africa, including heartwater. This study was conducted in 2023 to monitor Amblyomma spp. infestation in dromedary camels imported from Somalia, Ethiopia, and Sudan to Egypt. This study inspected 200 camels at the Giza governorate's camel market that had been imported from Somalia, 200 from Ethiopia, and 200 from Sudan for tick infestation. Specimens were identified using morphological characteristics and phylogenetic analyses of the 12S and 16S rRNA genes. Clusters were calculated using an unweighted pair-group method with arithmetic averages (UPGMA) dendrogram to group the specimens according to their morphometric characteristics. The morphometric analysis compared the body shape of ticks collected from different countries by analyzing dorsal features. Principal component analysis (PCA) and canonical variate analysis (CVA) were performed to obtain body shape variation among specimens from different countries. Results indicated that camels were infested by 57 males Amblyomma lepidum, and no female specimens were observed; among these specimens, one may have a morphological abnormality. The results suggest that A. lepidum specimens collected from camels imported to Egypt from African countries exhibit locally adapted morphology with variations among specimens, particularly variations in body size. This adaptation suggests minimal potential for genetic divergence. Ecological niche modeling was used to predict the areas in Africa with suitable climates for A. lepidum. The study confirmed that East African countries might have the most favorable climatic conditions for A. lepidum to thrive. Interestingly, the amount of rain during the wettest quarter (Bio16) had the strongest influence on the tick's potential distribution, with suitability decreasing sharply as rainfall increased. Future predictions indicate that the climatic habitat suitability for A. lepidum will decrease under changing climate conditions. However, historical, current, and future predictions indicate no suitable climatic habitats for A. lepidum in Egypt. These findings demand continuous surveillance of A. lepidum in camel populations and the development of targeted strategies to manage tick infestations and prevent the spread of heartwater disease.

Toward the identification of laggard rural areas: an evolutionary resilience approach

ABSTRACT Based on the evolutionary resilience approach and using Principal Component Analysis, this paper proposes a composite weighted index to measure levels of rural resilience and, in addition, to unravel why some rural areas are less resilient than others. Taking the region of Cantabria (northern Spain) at the municipal level as a sort of ‘laboratory’, the overall results unveil poor levels of resilience and suggest that the main factors limiting resilience are related to cultural interest, rural potential, natural endowment, and connectivity. Our findings also reveal considerable spatial heterogeneity across the different domains of resilience. As a specific contribution, the study brings together rural resilience levels and population growth (as population decline is the first direct consequence of a lack of resilience) in order to define different categories of rural territories, among which laggard rural areas are singled out as areas to be targeted for political intervention. When focusing on such areas, a crucial finding of the paper is that some municipalities that are lagging behind have not been included by the Regional Government as being at severe risk of depopulation, meaning that they cannot benefit from close public monitoring and fiscal support.

Preparation and Evaluation of Clarithromycin Taste-Masking Dry Suspension Using Hot Melt Extrusion Based on Solid Dispersion Technology.

Clarithromycin (CLA) is the preferred drug for treating respiratory infections in pediatric patients, but it has the drawbacks of extreme bitterness and poor water solubility. The purpose of this study was to improve solubility and mask the extreme bitterness of CLA. We use Hot Melt Extrusion (HME) to convert CLA and Eudragit® E100 into Solid Dispersion (SD). Differential scanning calorimetry (DSC) and Powder X-ray diffraction (PXRD) were used to identify the crystalline form of the prepared SDs, which showed that the crystalline CLA was converted to an amorphous form. At the same time, an increase in dissolution rate was observed, which is one of the properties of SD. The results showed that the prepared SD significantly increased the dissolution rate of crystalline CLA. Subsequently, the SD of CLA was prepared into a dry suspension with excellent suspending properties and a taste-masking effect. The bitterness bubble chart and taste radar chart showed that the SD achieved the bitter taste masking of CLA. Principal components analysis (PCA) of the data generated by the electronic tongue showed that the bitter taste of CLA was significantly suppressed using the polymer Eudragit® E100. Subsequently, a dry suspension was prepared from the SD of CLA. In conclusion, this work illustrated the importance of HME for preparing amorphous SD of CLA, which can solve the problems of bitterness-masking and poor solubility. It is also significant for the development of compliant pediatric formulations.

Investigation of sorptive interactions between volatile organic compounds and supramolecules at dynamic oscillation using bulk acoustic wave resonator virtual sensor arrays

Supramolecules are considered as promising materials for volatile organic compounds (VOCs) sensing applications. The proper understanding of the sorption process taking place in host-guest interactions is critical in improving the pattern recognition of supramolecules-based sensing arrays. Here, we report a novel approach to investigate the dynamic host-guest recognition process by employing a bulk acoustic wave (BAW) resonator capable of producing multiple oscillation amplitudes and simultaneously recording multiple responses to VOCs. Self-assembled monolayers (SAMs) of β-cyclodextrin (β-CD) were modified on four BAW sensors to demonstrate the gas-surface interactions regarding oscillation amplitude and SAM length. Based on the method, a virtual sensor array (VSA) type electronic nose (e-nose) can be realized by pattern recognition of multiple responses at different oscillation amplitudes of a single sensor. VOCs analysis was realized respectively by using principal component analysis (PCA) for individual VOC identification and linear discriminant analysis (LDA) for VOCs mixtures classification.

Preparation of preservation paper containing essential oil microemulsion and its application in maintain the quality of post-harvest peaches

Post-harvest peaches are highly susceptible to fungal infections leading to spoilage. This study investigates the utilization of three edible plant essential oils (EOs) with antifungal properties for the preservation of peaches, along with an evaluation of their preservative efficacy. Initially, GC-MS was employed to identify the primary constituents of the EOs, revealing a predominance of phenols, alcohols, hydrocarbons and aldehydes. Principal component analysis was conducted to compare the chemical compositions of the EOs from the plants used in this study with those obtained from other regions. This analysis facilitates the quality assessment of the plant materials in the later stages of the research. In vitro antimicrobial assays indicated that the three EOs independently exhibited their respective antifungal activities against 7 fungi responsible for peach spoilage. The Response Surface Methodology was then applied to optimize the blend ratio of the composite EOs (CEOs) for maximum antifungal efficacy. Concurrently, this study validated the rationality of a second-order polynomial model that correlates the peach decay index with the concentration of the CEOs. To enhance the bioavailability of the CEOs, a pseudo-ternary phase diagram was employed to formulate the CEOs into a microemulsion. Based on the RSM optimization results for the CEOs, the optimal mass ratio of the components within the microemulsion was determined. Using this microemulsion as a base, preservative films were developed that demonstrated a significant preservation effect on peaches, highlighting the immense potential of this research in the food industry.

Validity and Reliability of the German Vocal Fatigue Index in Adults With Voice Disorders.

Vocal fatigue-related symptoms, frequent in patients with voice disorders, are reliably quantifiable with the Vocal Fatigue Index (VFI) in several languages. The main aim of this work was to investigate the content and construct validity of the German Vocal Fatigue Index (VFI-D) by comparison with the German Voice Handicap Index 9 international (VHI9i) and the Vocal Tract Discomfort Scale (VTD). Moreover, the scale and retest reliability were investigated. In a prospective cohort study at two tertiary care hospitals, 93 adults with all types of voice complaints filled out the VFI-D, the VHI-9i, and the VTD. Eighty-one adults (Mage = 53.5 years, SD = 15.7) completed them one time, and additional 12 patients (Mage = 53.8 years, SD = 15.6) did a test-retest, completed them twice at an interval of 1 week. The validity was assessed by Spearman's rho and Mokken scaling and the reliability by a factor analysis and a two-tailed t test. Mokken scaling has proven the VFI-D as one-dimensional questionnaire (one cluster, r = .95). All VFI-D items could be assigned to one of three factors according to principal component and principal axis factor analysis. Although Factor 1 related best to the VHI9i (∅ rs = .76) and Factor 2 to the VTD (∅ rs = .74), Factor 3 correlated moderately with the VHI9i (rs = .34) and weakly with the VTD (rs = .25). Results from the first and second VFI-D completion agreed strongly (t = -1.78, p = .10). In this study, the content and construct validity of the VFI-D were confirmed. Also, both scale reliability with identical factors as those in the original study and retest reliability were verified. The VHI9i and VTD were highly indicative of VFI-D Factors 1 and 2, respectively. No correlation between Factor 3 and the other questionnaires was determined. Future research should evaluate which characteristics are specific to vocal fatigue versus general voice disorder-related symptoms.

Insights into the genomic homogeneity of Moroccan indigenous sheep breeds though the lens of runs of homozygosity

Numerous studies have indicated that Morocco’s indigenous sheep breeds are genetically homogenous, posing a risk to their survival in the challenging harsh climate conditions where they predominantly inhabit. To understand the genetic behind genetic homogeneity through the lens of runs of homozygosity (ROH), we analyzed the whole genome sequences of five indigenous sheep breeds (Beni Guil, Ouled Djellal, D’man, Sardi, Timahdite and Admixed).The results from principal component, admixture, Fst, and neighbour joining tree analyses consistently showed a homogenous genetic structure. This structure was characterized by an average length of 1.83 Mb for runs of homozygosity (ROH) segments, with a limited number of long ROH segments (24–48 Mb and > 48 Mb). The most common ROH segments were those ranging from 1–6 Mb. The most significant regions of homozygosity (ROH Islands) were mostly observed in two chromosomes, namely Chr1 and Chr5. Specifically, ROH Islands were exclusively discovered in the Ouled Djellal breed on Chr1, whereas Chr5 exhibited ROH Islands in all breeds. The analysis of ROH Island and iHS technique was employed to detect signatures of selection on Chr1 and Chr5. The results indicate that Chr5 had a high level of homogeneity, with the same genes being discovered across all breeds. In contrast, Chr1 displays some genetic variances between breeds. Genes identified on Chr5 included SLC39A1, IL23A, CAST, IL5, IL13, and IL4 which are responsible for immune response while genes identified on Chr1 include SOD1, SLAMF9, RTP4, CLDN1, and PRKAA2. ROH segment profile and effective population sizes patterns suggests that the genetic uniformity of studied breeds is the outcome of events that transpired between 250 and 300 generations ago. This research not only contributes to the understanding of ROH distribution across breeds but helps design and implement native sheep breeding and conservation strategies in Morocco. Future research, incorporating a broader sample size and utilizing the pangenome for reference, is recommended to further elucidate these breeds’ genomic landscapes and adaptive mechanisms.

Analysis of the genetic structure of populations of the terrestrial mollusk <i>Caucasotachea vindobonensis</i> (Helicidae) in conditions at the eastern border of the range using microsatellite markers

BACKGROUND: Assessing the genetic structure of populations of rare and vulnerable species provides useful information for developing conservation strategies. AIM: The aim of the study was to study the genetic structure of Caucasotachea vindobonensis populations in the south of the Central Russian Upland using SSR markers. MATERIALS AND METHODS: Genetic structure of the populations was studied using eight microsatellite markers, first identified by the authors for the species under study. Fragment analysis of PCR products was carried out on an automatic capillary DNA sequencer Nanophore 05 (Russia). A total of 498 individuals from 24 populations were studied. RESULTS: A total of 59 alleles were isolated in the eight studied SSR loci, of which 21 (36%) turned out to be private. At the same time, private alleles were found in eleven studied populations, which is 46% of their total number. According to the data obtained, the effective number of alleles (Ae) averaged 1.6 ± 0.06, the Shannon index (I) was 0.45 ± 0.03, and the level of expected heterozygosity (He) was 0.27 ± 0.021. A high level of spatial subdivision of population gene pools was noted (Fst = 0.47 ± 0.08) with a fairly low level of gene flow (Nm = 1.15 ± 0.91). PCA analysis showed that the populations of the central and eastern parts of the south of the Central Russian Upland form a closely related group, different from other populations of the region. Calculation of the effective abundance using the LD method showed that Ne varies in different groups of snails from 0.6 to infinity. CONCLUSIONS: Populations of C. vindobonensis in the south of the Central Russian Upland live in conditions of significant isolation, as evidenced by the high degree of differentiation of the studied groups. The analysis of principal components based on genetic distances according to Nei and Wright’s F-statistics indicate a pronounced division of populations in the study area into two clusters, which is probably associated with the historical features of landscape formation. Calculation of effective numbers indicates the high viability of the majority of the studied populations. At the same time, some groups of snails are clearly in a depressed state, which is reflected in low levels of genetic diversity and their effective size.

Carbon emissions from road transportation in China: from past to the future.

Road transportation is an important contributor to carbon emissions. China's car ownership is rapidly increasing, ranking first worldwide; however, there are limited data about carbon emission inventories. This study assesses carbon emissions from road transportation from the past to the future across China, using market survey, COPERT (Computer Programme to Calculate Emissions from Road Transport) model, and a combination method of principal component analysis and backpropagation neural network. From 2000 to 2020, the national carbon emissions from road transportation grew from 11.9 to 33.8 Mt CO2e, accounting for 0.47% of national total emissions by then. Trucks generally emit a higher proportion (77.3%) of total emissions than passenger cars (18.9%); however, the emission proportion of passenger cars (18.9-31.0%) has increased yearly. The carbon emissions at the prefecture level show an urban agglomeration trend, decreasing from the eastern coastal areas to central China. Future car ownership is expected to grow rapidly at 3.1% during 2021-2049, but only half of that growth rate during 2051-2060. Those vehicles are expected to contribute carbon emissions of 27.2-39.1 Mt CO2e under different scenarios in 2060. Scientifically reducing emissions and innovatively reducing the carbon emission coefficient, combined with a reasonable new energy vehicle growth scenario, are efficient methods for reducing national carbon levels. This study demonstrates that the uncertainty is within an acceptable range. This work details the carbon emission inventories associated with road transportation in China and provides basic data for developing a better carbon reduction policy for China's car industry.

Statistical analysis of water quality change by total maximum daily load policy stage

This study aimed to derive major pollutants for standard watersheds with relatively high pollution levels and identify their trends. Hence, the water quality index (WQI) and multivariate statistical techniques were used to analyze the water quality evaluation of standard watershed during the total maximum daily load (TMDL) policy period implemented since 2004. The WQI was calculated for 41 standard watersheds, divided into 14 main streams and 27 tributaries. Consequently, in the main stream, WQI decreased as it moved downstream after the MS5 site. In the tributary, WQI values were found to be low at TS11, TS15, TS16, and TS17 sites. However, the Mann–Kendall test results indicated that the overall WQI value was increasing, suggesting that the water quality of the study basin was improving as the TMDL policy phase progressed. Principal component analysis of the group with relatively low WQI among the standard watersheds revealed that water temperature, dissolved oxygen, total phosphorus, chemical oxygen demand, biochemical oxygen demand, and electrical conductivity were the main variables in the main stream cluster. In the tributary stream cluster, total phosphorus, dissolved oxygen, total suspended solids, total nitrogen, and electrical conductivity showed high loading values. This study proposed a series of methods to provide the basic data required for watershed management through detailed water quality assessment methods, statistical techniques for deriving major pollutants, and trend analysis of water quality evaluation.

The graded multidimensional geometry of phenotypic variation and progression in neurodegenerative syndromes.

Clinical variants of Alzheimer's disease and frontotemporal lobar degeneration display a spectrum of cognitive-behavioural changes varying between individuals and over time. Understanding the landscape of these graded individual-/group-level longitudinal variations is critical for precise phenotyping; however, this remains challenging to model. Addressing this challenge, we leverage the National Alzheimer's Coordinating Center database to derive a unified geometric framework of graded longitudinal phenotypic variation in Alzheimer's disease and frontotemporal lobar degeneration. We included three time-point, cognitive-behavioural and clinical data from 390 typical, atypical and intermediate Alzheimer's disease and frontotemporal lobar degeneration variants (114 typical Alzheimer's disease; 107 behavioural variant frontotemporal dementia; 42 motor variants of frontotemporal lobar degeneration; and 103 primary progressive aphasia patients). On this data, we applied advanced data-science approaches to derive low-dimensional geometric spaces capturing core features underpinning clinical progression of Alzheimer's disease and frontotemporal lobar degeneration syndromes. To do so, we first used principal component analysis to derive six axes of graded longitudinal phenotypic variation capturing patient-specific movement along and across these axes. Then, we distilled these axes into a visualisable 2D manifold of longitudinal phenotypic variation using Uniform Manifold Approximation and Projection. Both geometries together enabled the assimilation and inter-relation of paradigmatic and mixed cases, capturing dynamic individual trajectories, and linking syndromic variability to neuropathology and key clinical end-points such as survival. Through these low-dimensional geometries, we show that (i) specific syndromes (Alzheimer's disease and primary progressive aphasia) converge over time into a de-differentiated pooled phenotype, while others (frontotemporal dementia variants) diverge to look different from this generic phenotype; (ii) phenotypic diversification is predicted by simultaneous progression along multiple axes, varying in a graded manner between individuals and syndromes; and (iii) movement along specific principal axes predicts survival at 36 months in a syndrome-specific manner and in individual pathological groupings. The resultant mapping of dynamics underlying cognitive-behavioural evolution potentially holds paradigm-changing implications to predicting phenotypic diversification and phenotype-neurobiological mapping in Alzheimer's disease and frontotemporal lobar degeneration.

Analysis of machine learning-based music recommendation system using Spotify datasets

The field of musical exploration grows rapidly with the rapid development of technology in the digital era. In this paper, the application of machine learning in music recommendation systems is mainly focused on and the existing data sets about Spotify are used to analyze and show how machine learning achieves musical personality recommendations. This paper mainly uses principal component analysis and the K-means clustering algorithm to realize the goal. Principal component analysis (PCA) helps people to reduce the dimensionality of the whole dataset, and this method helps people to retain key information and reduce the complexity of the data. The k-means clustering algorithm divides the songs into different clusters. These clusters show consistency in musical features, and the dots will cluster together. By visualization of the clusters, people can deeply interpret the relationship between distinct music genres and discover the areas of music and songs that users are interested in. This research not only explains how music exploration is implemented but also promotes the development of personalized music recommendation systems.