Principal Component Analysis Research Articles

Interpretation of yield and quality traits of barley (Hordeum vulgare L.) varieties by heatmap technique

BackgroundBarley (Hordeum vulgare L.) is the most cultivated cool-season cereal after wheat in Türkiye. This can be attributed to its uses in the malt industry, human consumption, and animal nutrition etc. This study investigated yield, physiological, and quality traits of different barley varieties using heatmap and principal component analysis (PCA) technique to identify the varieties with better yield and superior quality. MethodsA total of 12 barley varieties (8 two-row and 4 six-row) were used in the study. The varieties were sown under natural conditions and data relating to yield, physiological and quality traits (grain yield, heading time, plant height, number of spikes m−2, 1000-grain weight, and starch ratio) were recorded. The recorded data were analyzed by PCA and heatmap techniques to determine the better-performing varieties. ResultsSignificant variations were observed among the tested varieties for all evaluated traits (p < 0.01). Heatmap categorized the recorded traits into two clusters, and traits within the same cluster exhibiting interconnectedness. The primary cluster comprised of plant height, heading time, and 1000-grain weight. Similarly, the second significant cluster contained the varieties with similar grain yield, starch ratio, and the number of spikes m−2. The varieties ‘Bozlak’ and ‘Mert’, ‘Aydanhanim’ and ‘Tosunpaşa’, ‘Erciyes’ and ‘Çatalhüyük’, and ‘Sabribey’ and ‘Asutay’, exhibited significant resemblance for the recorded traits. The PCA revealed that 1000-grain weight was associated with the heading time, whereas starch ratio was associated with the grain yield. ‘Erciyes’ (3.58 tons ha−1), ‘Çatalhüyük 2001′ (2.95 tons ha−1), and ‘Bozlak’ (2.72 tons ha−1) recorded the highest yield, whereas ‘Erciyes’ variety resulted in the delayed heading. Similarly, ‘Çatalhüyük’, and ‘Erciyes’ produced the highest number of spikes m−2. Likewise, ‘Çatalhüyük 2001′, and ‘Tosunpaşa’ resulted in the heaviest 1000-grains, while ‘Asutay’ resulted in the highest starch ratio. ConclusionIt is concluded that ‘Çatalhüyük’, ‘Erciyes’, and ‘Tosunpaşa’ are superior varieties in terms of yield-related traits, whereas ‘Asutay’ proved better for starch ratio. Therefore, these varieties could be used in future breeding programs to improve these traits.

Responsive feeding patterns during early childhood in urban areas. Argentina, 2018-2019.

Introduction. Dietary quality involves both the quantity and quality of food offered, the way and the setting in which it is offered, and the responses of the person offering it. The objective of this study was to identify behavioral patterns related to responsive feeding in children aged 6 to 23 months in urban areas from Argentina in 2018-2019. Population and methods. Secondary analysis based on data from the second National Survey on Nutrition and Health of 2018-2019 conducted in a multistage probability sample from urban areas of 5000 inhabitants or more in Argentina. A descriptive analysis and a principal component analysis were performed to identify responsive feeding patterns in 4379 children aged 6 to 23 months. Results. Five responsive feeding patterns were identified; the first 2 dimensions explained 71.1% of inertia (p = 0.013). The pattern with a prevailing possibility of experimentation, autonomy, interaction, and the absence of screens, rewards and distractions was associated with children older than 12 months from the central and south regions (Cuyo, Pampa, Greater Buenos Aires, and Patagonia), whereas the pattern related to a lower autonomy, experimentation, and self-regulation corresponded to children aged 6 to 11 months from the Northwest and Northeast regions. Conclusion. There is evidence of responsive feeding practices that correspond to distinguishable patterns, associated with different stages of life and with the region where the children live.

Revealing the global mechanism related to carnosine synthesis in the pectoralis major of slow-growing Korat chickens using a proteomic approach.

This study aimed to find global mechanisms related to carnosine synthesis in slow-growing Korat chickens (KRC) using a proteomic approach. M. pectoralis major samples were collected from 10-week-old female KRC including low-carnosine (LC, 2,756.6±82.88 μg/g; n = 5) and high-carnosine (HC, 4,212.5 ±82.88 μg/g; n = 5). We identified 152 common proteins, and 8 of these proteins showed differential expression between the LC and HC groups (p<0.05). Heat shock 70 kDa protein 8, Heat shock 70 kDa protein 2, protein disulfide isomerase family A, member 6, and endoplasmic reticulum resident protein 29 were significantly involved in protein processing in the endoplasmic reticulum pathway (false discovery rate<0.05), suggesting that the pathway is related to differential carnosine concentration in the M. pectoralis major of KRC. A high concentration of carnosine in the meat is mainly involved in low abundances of Titin isoform Ch12 and Connectin and high abundances of M-protein to maintain homeostasis during muscle contraction. These consequences improve meat characteristics, which were confirmed by the principal component analysis. Carnosine synthesis may occur when muscle cells need to recover homeostasis after being interfered with carnosine synthesis precursors, leading to improved muscle function. To the best of our knowledge, this is the first study to describe in detail the global molecular mechanisms in divergent carnosine contents in meat based on the proteomic approach.

The effect of packaging material and adjunct culture on the biogenic amine content, microbiological and textural properties of Dutch-type cheese

The aim of the study was to assess the effects of the packaging materials applied (shrink foil, copolymer coating and food wax) in combination with Lacticaseibacillus casei CCDM 198 microbial strain on biochemical, microbiological and textural properties of Dutch-type cheese during ripening (at 12 ± 1 °C for 168 days). A multivariate principal component analysis method based on a correlation matrix was employed to evaluate the relationships between basic chemical properties, textural and microbiological parameters, biogenic amine and free amino acid contents in relation to the packaging material used and the length of the ripening time. The use of different packaging materials did not have a significant effect on the salt content, fat content, and pH values, whereas significant differences were observed for dry matter content and textural properties development. The presence of Lacticaseibacillus casei CCDM 198 strain accelerated proteolysis in all samples. Shrink foil and food wax had similar effects on the development of biogenic amine content during ripening, while considerable differences were observed for the samples wrapped in copolymer coating. Copolymer coating in combination with Lacticaseibacillus casei CCDM 198 strain was able to reduce biogenic amine content by up to 28% after 168 days.

Managing sustainability-oriented innovation in services: proposal of a scale for the future of hotel companies and travel agencies

PurposeThe concept of Sustainability-Oriented Service Innovation (SOSI) has been recently suggested from a conceptual reflection approach in an attempt to integrate innovation and sustainability in services, being an emerging field of innovation in services. This study aims to propose a scale to measure Sustainability-Oriented Service Innovation from the perspective of the company. Because the whole is different from the sum of its different parts, we need to better understand the synergy between sustainability and innovation for the future of tourism companies.Design/methodology/approachUpon a literature review, we propose a scale and explore its dimensionality with data from 268 to 256 Spanish hotel and travel agency managers, respectively. The dimensionality of the scale for measuring Sustainability-Oriented Service Innovation is similar in hotels and travel agencies.FindingsFive factors emerge from the principal component analyses carried out: two dimensions referred to technological and non-technological innovation, respectively, and three dimensions labelled as economic, social and environmental sustainability.Practical implicationsTo guide managers towards their operations, the proposed scale is expected to inspire models to assess the impact of SOSI practices in such a highly competitive industry and to identify the most influencing dimensions on the future performance of the tourism company.Originality/valueTo the best of our knowledge, no scale has been presented so far that brings together the dimensions of technological and non-technological innovation, as well as sustainability from a Triple Bottom Line approach.

Characterization of the Geographical Origin of the Traditional Chinese Fermented Soybean Douchi by Gas Chromatography-Mass Spectrometry (GC-MS) and Chemometrics

Douchi is a highly appreciated product due to its unique flavor, high nutritional value, and health benefits. Douchi from different regions exhibits distinct characteristics. The objective of this study was to investigate the volatile profiles in douchi produced from different geographical origins using gas chromatography-mass spectrometry (GC-MS) and chemometrics. The volatiles were extracted by headspace solid-phase micro-extraction (HS-SPME) and subsequently determined by GC-MS. A comparative analysis was further conducted to identify the variations in volatile compounds among the samples. The correlation between the samples was investigated by employing cluster analysis (CA) and principal component analysis (PCA). An orthogonal partial least squares-discriminant analysis (OPLS-DA) model was established to discriminate samples from different regions and identify key differential compounds. A total of 46 volatile compounds were detected, among which terpenes, alcohols were the main compounds. Furthermore, 14 key differentiating compounds were screened out based on the OPLS-DA modle. The application of GC-MS combined with chemometrics offers a theoretical framework for douchi quality control and classification.

Abstract A045: Pan-viral serological characterization in African Americans and European Americans with Hepatocellular Carcinoma

Abstract Hepatocellular carcinoma (HCC) is often diagnosed at late-stages, particularly among African Americans (AA). Poor screening and diagnosis are key factors that contribute to worse prognoses and disproportionately high mortality rates. We propose investigating viral exposure history as a potential useful screening method. Additionally, by accounting for neighborhood deprivation index (NDI), a metric for differences in socio-economic statuses, we can potentially mitigate this disparity. With NDI and viral exposure history, our study aims to assess HCC prognoses in racially disparate populations. We used a technique called VirScan, which conjugates Phage-Immunoprecipitation (PhIP) and DNA-sequencing, to profile the antibody repertoire against a viral epitope library. Analyzing serum and plasma samples from population controls (PC), individuals at high-risk for developing HCC (HR), and HCC cases, we performed VirScan on 524 AA (272 PC, 205 HR, and 47 HCC) and 342 European Americans (EA) (141 PC, 130 HR, and 71 HCC) participants from the NCI-UMD cohort between 2009-2020 from the greater Baltimore area (NCT00913757; clinicaltrials.gov). We used XGBoost, a machine- learning model, to classify viral features that can discriminate HCC cases from PC group. XGBoost predicted 31 important viral features which distinguish HCC from PC. Of the 31 viral features, 6 viruses were different between AA and EA (FDR &amp;lt; 0.05). To determine the extent to which socio-economic factors contribute to the cancer disparities, we gathered variables from the 1999 census tract as contributors to deprivation. We used Principal Component Analysis (PCA) to determine loadings of these contributor variables; composite of the final variables is derived as NDI. Comparing across groups, we find that average NDI is highest in HR group (x = 0.33), followed by HCC group (x = 0.21), then PC group (x = 0.19). We find that NDI for AA is significantly higher in HCC group (p = 1.3e-09), HR group (p &amp;lt; 2.2e-16), and PC group (p = 5.0e-10) when compared to that of EA. Thus, we demonstrate that both the viral exposure history and NDI of an individual might be useful in prognoses of HCC. This approach could be used to examine the disparities we see in both incidence and mortality of HCC between AA and EA. Citation Format: Theressa Ewa, Whitney Leet, Limin Wang, Marshonna Forgues, Xin Wei Wang. Pan-viral serological characterization in African Americans and European Americans with Hepatocellular Carcinoma [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A045.

Abstract A037: Understanding the role of neighborhood deprivation in racial and urban-rural disparities in triple negative breast cancer

Abstract Background: Triple negative breast cancer (TNBC) accounts for 15% of all breast cancers and is one of the most aggressive disease subtypes. Disparities in TNBC exist, where US Black women and women living in urban environments are more likely to be diagnosed with TNBC than their White or rural counterparts. Reasons for these disparities are not completely understood. Social determinants of health, such as the neighborhood environment, have been implicated as potential contributors to breast cancer disparities. To improve our understanding of disparities in TNBC, we examined neighborhood deprivation in relation to breast cancer subtype, according to race and rurality. Methods: We identified 40,095 non-Hispanic Black and White women diagnosed with invasive breast cancer in 2010-2017 in the Georgia Cancer Registry. Neighborhood deprivation was measured by the Neighborhood Deprivation Index (NDI), a composite measure of neighborhood poverty, income, housing, unemployment, occupation, and education derived through principal component analysis using 2011-2015 block group-level American Community Survey data. Georgia Department of Public Health data were used to measure county-level rurality. We estimated case-only multivariable odds ratios (OR) and 95% confidence intervals (CI) for the separate associations between NDI, in quintiles, and each breast cancer subtype (TNBC, ERBB2+, or luminal B vs. luminal A breast cancer), overall and according to race and rurality. Results: Of the 40,095 non-Hispanic Black (31.5%) and White (68.5%) women, 5,328 were diagnosed with TNBC, 1,926 with ERBB2+, 4,958 with luminal B, and 27,883 with luminal A breast cancer. Compared to living in the least deprived neighborhoods, living in the most deprived neighborhoods was associated with a 33% (OR= 1.33, 95% CI 1.19-1.48) increased odds of TNBC vs. luminal A breast cancer. Race and rurality did not modify the association. However, estimates were less pronounced among non-Hispanic Black (OR=1.18, 95% CI 1.00-1.39) compared to non-Hispanic White (OR=1.40, 95% CI 1.18- 1.65) women and among women living in urban (OR=1.33, 95% CI 1.18-1.50) compared to rural (OR=1.52, 95% CI 1.15-2.03) counties. Neighborhood deprivation was associated with an increase in ERBB2+ breast cancer (OR=1.19, 95% CI 1.00-1.40), which was confined to non- Hispanic White women (OR=1.29, 95% CI 1.00-1.66) and women living in urban counties (OR=1.25, 95% CI 1.04-1.52). The OR for luminal B breast cancer was 1.08 (95% CI 0.96- 1.21). Although race did not modify this relationship, an association was observed only among women living in urban counties (OR=1.14, 95% CI 1.00-1.29). Conclusions: In this population of Georgia breast cancer patients, neighborhood deprivation was associated with an increase in TNBC, regardless of race or rurality. The weaker associations among non-Hispanic Black women and women living in urban counties suggests that other factors, in addition to neighborhood deprivation, may play an important role in TNBC development among Black women and women residing in urban environments. Citation Format: Lauren E. Barber, Jasmine M. Miller-Kleinhenz, Maret L. Maliniak, Leah Moubadder, Jeffrey M. Switchenko, Lauren E. McCullough. Understanding the role of neighborhood deprivation in racial and urban-rural disparities in triple negative breast cancer [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A037.

Permanent magnet synchronous motor demagnetization fault diagnosis based on PCA-ISSA-PNN

Aiming at the demagnetization fault problem of the permanent magnet synchronous motor (PMSM), a demagnetization fault diagnosis method based on the combination of the principal component analysis (PCA) algorithm, the improved sparrow search algorithm (ISSA), and the probabilistic neural network (PNN) algorithm is proposed. First, the principal components of phase currents are extracted using PCA. Second, ISSA is used to optimize the smoothing coefficients of the PNN algorithm, and the optimized PNN algorithm is combined with PCA to obtain the PCA-ISSA-PNN fault diagnosis model. Finally, the established fault diagnosis model was tested using the current data collected from the experiments and compared with the fault diagnosis indexes and optimization performance of the conventional PNN, PCA-PNN, PCA-GA (genetic algorithm)-PNN, PCA-DA (dragonfly algorithm)-PNN, PCA-GTO (artificial gorilla troop optimizer)-PNN, PCA-AHA-PNN, and PCA-SSA-PNN. The test results show that the fault diagnosis accuracy of PCA-ISSA-PNN reaches 95.83%, and the fault diagnosis indexes are significantly higher than those of PNN, PCA-PNN, PCA-GA-PNN, and PCA-DA-PNN; its optimization performance is also significantly better than that of PCA-GTO-PNN, PCA-AHA-PNN, and PCA-SSA-PNN, which verifies the accuracy and efficiency of the proposed method.

A hybrid PCA acceleration method for rapid real-time 2D MRI

Abstract Objective: To develop a 2D MR acceleration method utilizing Principal Component Analysis (PCA) in a hybrid fashion for rapid real-time applications. &amp;#xD;Approach: Retrospective testing was performed on 10 lung, 10 liver and 10 prostate 3T MRI data sets for image quality and target contourability. Sampling of k-space is performed by acquiring central (low-frequency) data in every frame while the high-frequency data is incoherently undersampled such that all of k-space is acquired in a pre-determined number of frames. Firstly, Principal Components (PCs) representative of intra-frame correlations between central and outer k-space data are used to estimate unsampled data in the frame of interest. Then to add further stability, PCs representative of time-domain fluctuations within a reconstruction window of the most recent frames are fit to outer k-space data (including above estimations) to obtain final estimates in the frame of interest. Accelerated reconstructions between 3x and 8x were tested for image quality and contourability along with the optimal number of PCs for fitting. &amp;#xD;Main Results: It was found that at higher acceleration rates, image quality did not deteriorate significantly. Similarly, it was found that the images were of sufficient quality to contour a target using auto-contouring software at all tested acceleration rates and sites. SSIM values were found to be ≥ 0.91 at all accelerations tested. Similarly dice coefficients at the different sites were found to be ≥ 0.89 even at 8x accelerations which is on par with or better than intra-observer variation.&amp;#xD;Significance: This method appears to produce improved image quality and contourability compared to previous PCA methods while also allowing a greater number of PCs to be used in reconstruction. The method can be run using a simple single-channel coil and does not require significant computing power to meet real-time interventional standards (reconstruction times ~50 ms/frame on Intel i5 CPU). &amp;#xD;

Unraveling Promising Genetic Variability Associated with Strong Culm and Yield Parameters in Inter Sub-Specific Cross Derived Recombinant Inbred Lines in Rice (Oryza sativa L.)

Strengthening the rice culm through genetic improvement has been an important target in breeding to abate the lodging problem in rice. The present investigation was attempted to study the variability, genetic parameters and trait association in recombinant inbred lines (RILs) derived from inter sub-specific cross of elite indica mega variety ‘Swarna’ and Tropical japonica strong culm accession ‘IRGC 39111’. Analysis of Variance (ANOVA) displayed significant variation in RILs for all the traits studied. The investigation revealed high estimates of GCV and PCV along with high heritability and genetic advance as percent of mean (GAM) for all culm strength (CS) traits revealing the role of additive gene effect and selection of these traits shall be effective in rice improvement. Correlation studies revealed that the internode breaking weight (IBW) and bending moment at breaking(M) had a high significant positive correlation with all the CS traits, panicle weight and grain yield. Thus, the direct selection of positively associated traits can improve the lodging resistance in rice. The principal component analysis (PCA) showed that, seven principal components (PCs) out of 23 traits attributed approximately 92.9% of the total cumulative variability. The traits culm thickness (CT), Internode breaking weight (IBW), section modulus (SM), bending stress (BS), Bending moment at breaking (M) contributed maximum to the total diversity and the lines with higher trait values for the aforementioned traits could be utilized as donors to improve the culm strength and its attributing traits in future breeding programs. From this study, it is evident that tropical japonica lines can be a great source of genetic diversification for rice improvement.

Dietary pattern trajectories in early childhood and their associations with patterns of maternal feeding practices in a multi-ethnic Asian cohort

BackgroundMaternal feeding practices play a major role in children’s dietary intakes. However, there is limited data on the associations between trajectories of dietary patterns (DPs) and patterns of maternal feeding practices during early childhood.MethodsUsing data from a multi-ethnic Asian cohort study, namely the Growing Up in Singapore Towards healthy Outcomes (GUSTO), dietary intakes were measured using Food Frequency Questionnaires in children at 18 months, 5 and 7 years of age. Maternal feeding practices were assessed using validated questionnaires at 15 months, 3 and 5 years of age. Principal component analysis was used to derive 2 major DPs at all time-points as well as patterns of maternal feeding practices. Group-based trajectory modelling was used to identify trajectory groups for the derived DPs. Multivariable logistic regression examined associations between patterns of maternal feeding practices and DP trajectory groups.ResultsTwo DPs, namely the ‘healthy’ and ‘less healthy’ were consistently derived at 18 months, 5 and 7 years of age. From each DP, 2 stable DP trajectory groups were further identified between 18 months and 7 years of age. For the ‘healthy’ DP trajectory, majority of the children (Group 1) formed a consistent average adherence trajectory group (91.8%) while the remaining children (Group 2) showed a higher but decreasing adherence (8.2%) to this DP. For the ‘less healthy’ DP trajectory, most children (Group 1) formed a consistent average adherence trajectory (95.5%), while the remainder (Group 2) showed consistent higher adherence to this ‘less healthy’ DP (4.5%). Two patterns of maternal feeding practices were derived and labelled as ‘structured with autonomy support’ and ‘coercive control’, respectively, at ages 15 months, 3 and 5 years. Children whose mothers showed high adherence to the structured with autonomy support feeding practices at age 5 years were significantly more likely to be associated with the higher but decreasing ‘healthy’ DP trajectory group [OR = 3.62 (95% CI: 1.64, 7.99)].ConclusionsA small number of children in this multi-ethnic study showed high adherence to the ‘healthy’ or ‘less healthy’ DP trajectory groups, respectively, while the majority showed average adherence to either of these trajectories. The positive association between structured with autonomy support maternal feeding practices and higher z-scores for the healthy DP trajectory highlights the importance of guiding parents on appropriate feeding practices.

Response and disease resistance evaluation of sorghum seedlings under anthracnose stress

Sorghum is the world’s fifth-largest cereal crop, and anthracnose (Colletotrichum sublineola) is the main disease affecting sorghum. However, systematic research on the cellular structure, physiological and biochemical, and genes related to anthracnose resistance and disease resistance evaluation in sorghum is lacking in the field. Upon inoculation with anthracnose (C. sublineola) spores, disease-resistant sorghum (gz93) developed a relative lesion area (RLA) that was significantly smaller than that of the disease-susceptible sorghum (gz234). The leaf thickness, length and profile area of leaf mesophyll cells, upper and lower epidermal cells decreased in the lesion area, with a greater reduction observed in gz234 than in gz93. The damage caused by C. sublineola resulted in a greater decrease in the net photosynthetic rate (Pn) in gz234 than in gz93, with early-stage reduction due to stomatal limitation and late-stage reduction caused by lesions. Overall, the activities of superoxide dismutase (SOD) and catalase (CAT), the content of proline (Pro), abscisic acid (ABA), jasmonic acid (JA), salicylic acid (SA), and gibberellic acid (GA3), are higher in gz93 than in gz234 and may be positively correlated with disease resistance. While malondialdehyde (MDA) may be negatively correlated with disease resistance. Disease-resistant genes are significantly overexpressed in gz93, with significant expression changes in gz234, which is related to disease resistance in sorghum. Correlation analysis indicates that GA3, MDA, peroxidase (POD), and disease-resistance genes can serve as reference indicators for disease severity. The regression equation RLA = 0.029 + 8.02 × 10−6 JA–0.016 GA3 can predict and explain RLA. Principal component analysis (PCA), with the top 5 principal components for physiological and biochemical indicators and the top 2 principal components for disease-resistant genes, can explain 82.37% and 89.11% of their total variance, reducing the number of evaluation indicators. This study provides a basis for research on the mechanisms and breeding of sorghum with resistance to anthracnose.

Risk of developing Type 2 Diabetes Mellitus in a vulnerable community in northern Argentina

Introduction: Prevention of diabetes requires sustained lifestyle changes as well as identification of groups at higher risk. Objective: The aim of this research was to estimate the risk of diabetes in vulnerable subjects from a primary care center in northern Argentina, with no known glucose abnormalities, using the FINDRISC questionnaire, investigate the relationship between survey variables and the final score, and explore its association with metabolic risk factors and body composition. Methodology: This cross-sectional design included 498 patients without type 2 diabetes or known glycemic abnormalities. All subjects underwent a complete medical history and completed the FINDRISC questionnaire. Results: The predominant age group was 18-45 years old. Around 64% were physically active and 44% reported daily consumption of fruit and vegetables. Most of them had a BMI higher than 25 kg/m2. Regarding the risk of developing type 2 diabetes in the next 10 years, 24.3% were at low risk and the remaining fraction was distributed in slightly elevated, moderate, high and very high risk. All variables influenced the individuals' variance (p &lt; 0.05). The hierarchical clustering and principal component analysis (PCA) revealed that elevated FINDRISC score was strongly associated with: age &gt; 65 years, fasting blood glucose, BMI ? 30 kg/m2 and antihypertensives use. CONCLUTION: We found a high percentage of obesity and overweight, as well as a high risk of cardiometabolic disease and of developing T2D. In addition, in the population studied, the variables that compose the FINDRISC did not influence the highest score in the same way.

Simultaneous iodine and barium imaging with photon-counting CT

Photon-counting computed tomography (PCCT) could potentially offer significant improvements in image quality over conventional CT. This study leverages PCCT technology to achieve simultaneous multi-contrast imaging of barium (Z=56) and iodine (Z=53), addressing the limitations of conventional CT in differentiating materials with similar atomic numbers. Using a bench-top PCCT system with a cadmium zinc telluride (CZT) detector, experiments were conducted with various phantom setups and 1-5\% contrast agent concentrations and in a biological sample. Energy thresholds were adjusted to the K-edge absorption energies of barium (37.4 keV) and iodine (33.2 keV) to capture multi-energy CT images. K-edge decomposition was performed with K-edge subtraction and principal component analysis (PCA) techniques, demonstrating clear differentiation and accurate quantification of contrast agents in phantom combinations and the biological sample. The PCCT system successfully differentiated and quantified barium and iodine, with high correlations ($R^2 \approx 1$) between true and reconstructed concentrations. PCA outperformed K-edge subtraction by providing a superior capability to differentiate barium and iodine, particularly when calcium was present in the scanned object. These findings highlight the potential of PCCT for reliable, detailed imaging in clinical and research applications, particularly for contrast agents with close atomic numbers.

A novel dynamic predictive maintenance framework for gearboxes utilizing nonlinear Wiener process

Abstract In the context of advancing industrial automation, gearboxes, as pivotal components in power transmission systems, have a direct bearing on the operational efficiency and safety of the entire machinery. This study introduces a novel dynamic predictive maintenance framework for gearboxes using a nonlinear Wiener process. Comprehensive experiments validate the framework, demonstrating significant reductions in maintenance costs and improvements in reliability. First, a full-life degradation experiment was executed on the gearbox, leveraging the root mean square (RMS) value of the vibration signal as an indicator of system degradation. Subsequently, the signals from four vibration sensors were synthesized and normalized through Kernel Principal Component Analysis (KPCA), thereby enabling a more nuanced representation of the gearbox's degradation profile. The degradation trajectory was then modeled using a nonlinear Wiener process framework. The Wiener process's parameters and state variables were iteratively refined utilizing an online filtering algorithm grounded in Bayesian inference. This facilitated the derivation of the probability density function for the remaining useful life (RUL), thereby enabling a robust prediction of the gearbox's RUL. Finally, to minimize maintenance costs per unit of time, an optimization model for dynamic maintenance decision-making was formulated. The optimal maintenance timing was ascertained by solving this model. The empirical findings of this investigation demonstrate the efficacy of the proposed approach in executing dynamic predictive maintenance for gearboxes. This research endeavors to furnish novel theoretical underpinnings and pragmatic directives for the field of predictive maintenance in the context of gearboxes.

Unravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters

BackgroundSalt stress is a prominent abiotic stressor that imposes constraints on grain yield and quality across various crops, including wheat (Triticum aestivum). This study focused on assessing the genetic diversity of 20 wheat genotypes categorized as tolerant, moderately tolerant, and sensitive with three genotypes of unknown tolerance. To address salinity stress-related problems, different morpho-physiological, osmoprotectant, biochemical, yield, and grain quality-related parameters were analyzed under control (pH 8.0, EC 3.9) and saline-sodic (pH 9.4, EC 4.02) conditions in field.ResultsFindings revealed noteworthy variations among the genotypes in response to salinity stress. Greater accumulation of Na+ and lower K+ content were observed in response to salt stress in the sensitive varieties HD1941 and K9162. Proline, a stress indicator, exhibited significantly (p ≤ 0.05) greater accumulation in response to salinity stress, particularly in the tolerant cultivars KRL210 and KH65. Salt stress induced the most significant decrease (p ≤ 0.05) in spike length, thousand-grain weight, and hectolitre weight coupled with increased protein content in sensitive varieties, resulting in diminished yield.ConclusionCorrelation analysis of parameters under salinity stress showed that SOD, proline, and K+ contents can be used as the most efficient screening criteria for salinity stress during early developmental stages. Principal component analysis revealed that DBW187, DBW303, and DBW222 varieties were tolerant to salinity stress and exhibited an effective antioxidant system against salinity. This study will facilitate salt-tolerant wheat breeding in terms of the identification of tolerant lines by screening for limited traits in a wide range of germplasms.

Integrating Hyperspectral Reflectance-Based Phenotyping and SSR Marker-Based Genotyping for Assessing the Salt Tolerance of Wheat Genotypes under Real Field Conditions

Wheat breeding programs are currently focusing on using non-destructive and cost-effective hyperspectral sensing tools to expeditiously and accurately phenotype large collections of genotypes. This approach is expected to accelerate the development of the abiotic stress tolerance of genotypes in breeding programs. This study aimed to assess salt tolerance in wheat genotypes using non-destructive canopy spectral reflectance measurements as an alternative to direct laborious and time-consuming phenological selection criteria. Eight wheat genotypes and sixteen F8 RILs were tested under 150 mM NaCl in real field conditions for two years. Fourteen spectral reflectance indices (SRIs) were calculated from the spectral data, including vegetation SRIs and water SRIs. The effectiveness of these indices in assessing salt tolerance was compared with four morpho-physiological traits using genetic parameters, SSR markers, the Mantel test, hierarchical clustering heatmaps, stepwise multiple linear regression, and principal component analysis (PCA). The results showed significant differences (p ≤ 0.001) among RILs/cultivars for both traits and SRIs. The heritability, genetic gain, and genotypic and phenotypic coefficients of variability for most SRIs were comparable to those of measured traits. The SRIs effectively differentiated between salt-tolerant and sensitive genotypes and exhibited strong correlations with SSR markers (R2 = 0.56–0.89), similar to the measured traits and allelic data of 34 SSRs. A strong correlation (r = 0.27, p &lt; 0.0001) was found between the similarity coefficients of SRIs and SSR data, which was higher than that between measured traits and SSR data (r = 0.20, p &lt; 0.0003) based on the Mantel test. The PCA indicated that all vegetation SRIs and most water SRIs were grouped with measured traits in a positive direction and effectively identified the salt-tolerant RILs/cultivars. The PLSR models, which were based on all SRIs, accurately and robustly estimated the various morpho-physiological traits compared to using individual SRIs. The study suggests that various SRIs can be integrated with PLSR in wheat breeding programs as a cost-effective and non-destructive tool for phenotyping and screening large wheat populations for salt tolerance in a short time frame. This approach can replace the need for traditional morpho-physiological traits and accelerate the development of salt-tolerant wheat genotypes.

Nutritional Qualities, Metabolite Contents, and Antioxidant Capacities of Yardlong Beans (Vigna unguiculata subsp. sesquipedalis) of Different Pod and Seed Colors

Studying the effects of genetic and environmental factors on plant biochemical components helps in selecting the best varieties for the food industry and breeding programs. This study analyzed the nutritional qualities, secondary metabolites, and antioxidant activities of 14 field-grown yardlong beans accessions and how they are affected by differences in pod and seed colors. The analyzed parameters varied significantly among the yardlong bean accessions, with variances ranging from 1.36% in total unsaturated fatty acid content to 51.01% in DPPH• scavenging activity. Accessions YLB4, YLB7, and YLB14 performed the best, showing antioxidant indices of 100.00, 70.10, and 67.88%, respectively. Among these, YLB14 showed a characteristic property, having the highest levels of vitamin C (2.62 mg/g) and omega-6 to omega-3 ratio (2.67). It also had the second highest dietary fiber (21.45%), stearic acid (4.44%), and linoleic acid (40.39%) contents, as well as the lowest thrombogenicity index (0.38). Although cluster and principal component analyses did not clearly separate the yardlong beans based on pod or seed color, analysis of variance revealed that these factors and their interaction had significant effects on total phenol, DPPH• scavenging activity, ABTS•+ scavenging activity, and reducing power. In contrast, the nutritional parameters, except for dietary fiber, were not significantly affected by pod and seed color variations. Therefore, consuming yardlong beans of different pod and seed colors may not affect the overall nutrient intake. In general, this study identified yardlong beans with green pods and black seeds as good sources of antioxidants. Accordingly, further metabolomics and genomics studies are suggested to thoroughly explore their characteristics.

Women’s autonomy, neonatal, infant and under-five mortality in the Upper East Region of Ghana

Child mortality remains a major health challenge in Sub-Saharan Africa. Child survival is greatly influenced by household circumstances and mother’s healthcare choices. Notwithstanding tremendous investment in women empowerment in Ghana, there is limited empirical evidence on whether women’s autonomy translates into better child mortality outcomes. To examine the association between women’s autonomy and neonatal, infant and under-five mortality in the Upper East Region of Ghana. Data were obtained from a randomized cluster household survey among 15–49 years old women in seven districts in the Upper East Region. Data analysis was restricted to 3,243 women who reported ever having given birth. Based on Principal Component Analysis (PCA), we constructed an autonomy index categorized into least, moderate, and high autonomy based on responses to six questions regarding household decision-making. Bivariate and multivariate logistic regressions were used to assess the association of women’s autonomy status and mortality outcomes. Attaining secondary education or higher was significantly associated with infant mortality (adjusted odds ratio (aOR) = 0.39, CI = 0.16, 0.94) and under-five mortality (aOR = 0.39, CI = 0.18–0.87). Also, maternal age was significantly associated with neonatal, infant, and under-five mortality, while living in rural setting was significantly associated with lower risk of neonatal (aOR = 0.38, CI = 0.19–0.75) and under-five (aOR = 0.63, CI = 0.48–0.83) mortality. However, we found that compared to women with least autonomy, infants of those with moderate autonomy (aOR = 1.76, CI 1.07–2.89) and high autonomy (aOR = 1.75; CI = 1.04–2.93) were significantly more likely to die. In this study setting, women’s autonomy was not predictive of child mortality. Interventions that aim to improve child mortality should pay attention to community and family level factors that promote increase utilization of essential early childhood interventions.