Measurement Of Content Research Articles

Eleutheroside B alleviates oxidative stress and neuroinflammation by inhibiting the JAK2/STAT3 signaling pathway in a rat high altitude cerebral edema model

BackgroundHigh altitude cerebral edema (HACE) is a condition where the central nervous system experiences severe impairment as a result of sudden oxygen deprivation at high elevations. At present, effective measures for preventing and treating this condition are still lacking. Eleutheroside B (EB), the primary natural active compound found in the Eleutheroside senticosus, has demonstrated various biological functions. It has also shown significant potential in addressing acute mountain sickness and various neurological disorders. However, additional investigation is required to explore the potential protective effects and its underlying mechanisms of EB on HACE.MethodsThe male rats received pre-treatment with either vehicle, EB 100 mg/kg or 50 mg/kg, Dexamethasone 4 mg/kg, or coumermycin A1 100 μg/kg. To simulate the hypobaric hypoxia environment at a plateau of 6,000 m, a hypobaric hypoxia chamber was utilized. The therapeutic effects of EB were assessed through measurements of brain water content, histopathological observation, and evaluation of oxidative stress and inflammatory factors using immunofluorescence and ELISA. Furthermore, molecular docking, molecular dynamics simulation and Western blot were employed to clarify its molecular mechanism. Through these analyses, the underlying mechanism by which EB on HACE was identified.ResultsPre-treatment with EB demonstrated a significant protective effect against HACE by effectively reducing brain water content, down-regulating HIF-1α and AQP4 protein expression induced by hypoxia and reversing pathological changes in brain tissue and neuron damage. Compared to the group treated with HACE alone, the group pre-treated with EB showed a significant reduction in levels of ROS and MDA, as well as an increase in GSH. In addition, pre-treatment with EB led to a significant decrease in the levels of IL-1β, IL-6, and TNF-α. Molecular docking and dynamics simulations indicated that EB has a strong binding affinity to the JAK2/STAT3 signaling pathway. Western blot further confirmed that EB significantly downregulated the expression of JAK2/STAT3 related proteins in the brain tissue of HACE rats. Additionally, coumermycin A1, an agonist of the JAK2, reversed the anti-oxidative stress and neuroinflammation against HACE of EB.ConclusionEB exerts its antioxidant stress and anti-neuroinflammatory effects by inhibiting the JAK2/STAT3 signaling pathway in a rat HACE model.

Implementation Of IoT-Based Optical Sensors For Real-Time Monitoring In Palm Oil Processing

Optical sensors are widely used in various industrial sectors, including petrochemical and medical industries, with applications ranging from oxygen level measurement, concentration of substances in a liquid, object detection, and more. Optical sensors can be used to detect the water content in oil, such as palm oil or other oils. In an industrial process, especially in the palm oil industry, the water content in oil must meet a maximum standard of 4.5%. Optical sensors can measure water content using various methods, such as Total Internal Reflection (TIR) or Mid-Infrared (MIR), and can be monitored in real-time using IoT-based applications. The utilization of sensitive optical technology takes advantage of changes in the refractive index caused by variations in water content in palm oil. The method employed involves the development of an optical sensor based on the Mid-Infrared principle, which measures the amount of light absorbed by water and the light reaching the sensor for comparison. The results of water content measurements in palm oil that have been conducted can only be implemented for water content measurements of 0-5% in palm oil, with a sensor response that is less than linear above 5% water content. By correcting the non-linearity error of the sensor, the data is reduced to produce measurement results that are closer to the actual water content in palm oil, which will be displayed on local monitoring and real-time or continuous monitoring through IoT using smartphones and PCs wirelessly via IoT-based applications

Comparative analyses of RNA-seq and phytohormone data of sweetpotatoes inoculated with Dickeya dadantii causing bacterial stem and root rot of sweetpotato.

Bacterial stem and root rot (BSRR) in sweetpotato caused by Dickeya dadantii is one of the ten major diseases of sweetpotatoes in China. However, the molecular mechanism underlying the resistance of sweetpotato to D. dadantii remains unclear. This study adopted a resistance identification assay that conformed Guangshu87 (GS87) as BSRR-resistant and Xinxiang (XX) as susceptible. Compared to XX, GS87 effectively prevented the invasion and dissemination of D. dadantii in planta. An RNA sequencing (RNA-seq) analysis identified 54,844 expressed unigenes between GS87 and XX at four different stages. Further, it revealed that GS87 was more able to regulate the expressions of more unigenes after the inoculation with D. dadantii, including resistance (R) and transcription factors (TF) genes. Moreover, content measurements of disease resistance-related phytohormones showed that both jasmonic acids (JAs) and salicylic acids (SAs) accumulated in D. dadantii-inoculated sweetpotatoes, and JAs may negatively regulate sweetpotato resistance against D. dadantii and accumulated faster than SAs. Meanwhile, determinations of ROS production rate and relevant enzymatic/non-enzymatic activity highlighted the vital roles of reactive oxygen species (ROS) and superoxide dismutase (SOD) in confering GS87 resistance against D. dadantii. Additionally, several hub genes with high connectivity were highlighted through Protein-Protein interaction (PPI) network analysis. In summary, the findings in this study contribute to the understanding of the different responses of resistant and susceptible sweetpotato cultivars to D. dadantii infection, and it also provide the first insight into the relevant candidate genes and phytohormones involved in the resistance of sweetpotato to D. dadantii.

Biochemical Analysis of Fruiting Bodies of Cordyceps Militaris Grown on Brown Rice

Cordyceps militaris is a medicinal fungus known for its diverse biofunctional properties. This subject has been extensively analyzed over the past decade. The diverse pharmacological potential of C. militaris has garnered significant global interest recently. This research aims to determine the proximate composition of in vitro cultivated C. militaris fruit bodies. The analysis of proximate composition included measurements of crude protein, fat, crude fiber, ash, total carbohydrate, and moisture content. The research focused on quantifying the overall nutritional value of the fruit bodies and evaluating biological efficiency, in addition to key bioactive compounds including cordycepin, ergosterol, and Vitamin D2. The results demonstrated that the carbohydrate content constituted 47.67% of dry weight, the protein content was 30.41%, and the fiber content accounted for 15%. The fruit bodies contained 39.82 mg/kg of cordycepin and 61.73 mg/100g of ergosterol, whereas vitamin D2 was absent in the cordyceps mushroom sample. The findings demonstrate that in-vitro-cultivated C. militaris fruit bodies exhibit considerable nutritional and therapeutic potential.

Non-destructive measurement of chlorophyll content in Sonchus oleraceus L. (Asteraceae) under variations in cultivation and planting season using digital image analysis

Non-destructive measurement of chlorophyll content in Sonchus oleraceus L. (Asteraceae) under variations in cultivation and planting season using digital image analysis

Application of machine learning for reconstruction of multiphase fluid structure measured by a capacitance multi-electrode sensor

Non-invasive real-time measurements of phase content in the reservoir fluid are highly advantageous in the oil and gas industry and remain a current research topic. The paper presents an innovative, self-designed multi-electrode capacitance meter intended for detecting multiphase flow patterns in a low-permittivity medium, such as the reservoir fluid. The ca-pacitance sensor is built with delta-sigma charge modulators capacitance-to-digital converters. Machine learning is applied to convert the capacitance measurements into a tomographic image of the flow pattern. At present, the meter is built with eight electrodes. It is shown that the measurements are repeatable and have a good signal-to-noise ratio. The implemented neural network is capable of correctly reconstructing the tomographic images for a test tube filled with reservoir fluid and placed in various locations inside the test section.

Low-Cost Sensors for the Measurement of Soil Water Content for Rainfall-Induced Shallow Landslide Early Warning Systems

Monitoring soil water content (SWC) can improve the effectiveness of early warning systems (EWSs) designed to mitigate rainfall-induced shallow landslide risk. In extensive areas, like along linear infrastructures, the adoption of cost-effective sensors is critical for the EWS implementation. The present study aims to evaluate the reliability of different low-cost SWC sensors (frequency domain reflectometry and capacitance-based) in capturing soil moisture conditions critical for EWS, without performing soil-specific calibration. The reliability of the low-cost sensors is assessed through a comparative analysis of their measurements against those from high-cost and well-established sensors (time domain reflectometry) over a two-year period in a shallow landslide-prone area of Oltrepò Pavese, Italy. Although no landslides are observed during the monitoring period, meteorological conditions are reconstructed and statistical analysis of sensor’s responses to different rainfall events is conducted. Results indicate that, despite differences in absolute readings, low-cost sensors effectively capture relative SWC variations and demonstrate sensitivity to rainfall events across both cold and warm periods. The presented low-cost sensors can serve as reliable indicators of soil infiltration and saturation levels, highlighting their potential for real-time monitoring within extensive networks for EWS.

Association Between Finger Plethysmographic Features and Impedance-Based Thoracic Fluid Content Measurement in a Lower Body Negative Pressure Model of Hemorrhagic Shock.

Timely identification of the need for lifesaving intervention in battlefield conditions may be improved through automated monitoring of the injured warfighter. Technologies that combine maximal noninvasive insight with minimal equipment footprint give the greatest opportunity for deployment at scale with inexperienced providers in forward areas. Finger photoplethysmography (PPG) signatures are associated with impending hemorrhagic shock but may be insufficient alone. Transthoracic impedance (TTI) monitoring is a complementary modality to PPG and able to identify volume loss and estimate functional cardiovascular parameters. We sought to understand how PPG features correlate with volume loss estimation from TTI during lower body negative pressure (LBNP) challenge. We hypothesized that features of the PPG waveform would correlate with thoracic fluid content (TFC) as measured by TTI. We obtained physiologic monitoring data from healthy adult subjects in LBNP hemorrhagic shock models after local Institutional Review Board and DoD Human Research Protection Office approval. Subjects were excluded for pregnancy, age >45 years, and conditions prohibitive of LBNP exposure. Subjects were instrumented with noninvasive sensors, including a finger PPG sensor and a TTI monitor. Subjects underwent a stepwise LBNP exposure program of -10 mmHg every 10 minutes and notified laboratory staff at first sign of near syncope, terminating the sequential program. TTI data were continuously streamed to a custom program written in MATLAB and time synchronized. To calculate PPG measures, we downsampled data to 250 Hz, screened, and parsed each beat. We featurized each beat to include a systolic, diastolic, and dicrotic notch peak, beat length and area under the curve (AUC), peak-to-peak systolic/diastolic interval, and leading/trailing slopes, all normalized to instantaneous heart rate. Thoracic fluid content was normalized to subjects' pre-LBNP baselines. We summarized all PPG features and the TFC using means (SD) generated as a subject average for each step. We used generalized estimating equation models to examine the relationship between TFC and PPG features while controlling for LBNP stage and subject. Thirty-two subjects were enrolled; 4 participants were excluded because of sensor malfunction. Twenty-eight subjects had a mean (SD) age of 25.11 (6.66) years. A total of 35.7% of subjects were female. Photoplethysmography analysis demonstrated a decreased systolic-diastolic peak interval, diastolic peak height, and beat AUC with decreased LBNP pressure. End-stage baseline normalized TFC showed an average decrease of 14.68% (±4.98%) (range: 7.54% to 27.69%). The strongest average correlations between stage TFC and PPG occurred in beat length (0.68) and normalized AUC (0.69). In generalized estimating equation models incorporating all stages, beat length, normalized AUC, and the systolic-diastolic interval were all significantly associated with time as a function of LBNP level (P < .001). Thoracic fluid content began decreasing at 12.8 (4.7) minutes, the normalized AUC decreased at 20.7 (7.2) minutes, the beat length decreased at 20.9 (7.0) minutes, and the systolic-diastolic time interval decreased at 30.6 (16.7) minutes. While both PPG features and impedance-based TFC trend congruently in the perishock state following LBNP exposure, peripheral pulse wave signals lag redistribution of thoracic fluid volume. Photoplethysmography features of beat length and normalized AUC may serve as a surrogate for TFC when direct thoracic sensing is not available.

Long-term safety of photobiomodulation exposure to beta cell line and rat islets in vitro and in vivo

This study evaluates the safety and potential benefits of PBM on pancreatic beta cells and islets. PBM was applied to insulin-secreting cell lines (MIN6) and rat pancreatic islets using a 670 nm light source, continuous output, with a power density of 2.8 mW/cm², from 5 s to several 24 h. Measure of cell viability, insulin secretion, mitochondrial function, ATP content, and cellular respiration were assessed. Additionally, a diabetic rat model is used for islet transplantation (pre-conditioning with PBM or not) experiments. Short and long-term PBM exposure did not affect beta cell islets viability, insulin secretion nor ATP content. While short-term PBM (2 h) increases superoxide ion content, this was not observed for long exposure (24 h). Mitochondrial respirations were slightly decreased after PBM. In the islet transplantation model, both pre-illuminated and non-illuminated islets improved metabolic control in diabetic rats with a safety profile regarding the post-transplantation period. In summary, for the first time, long-term PBM exhibited safety in terms of cell viability, insulin secretion, energetic profiles in vitro, and post-transplantation period in vivo. Further investigation is warranted to explore PBM’s protective effects under conditions of stress, aiding in the development of innovative approaches for cellular therapy.

Mechanical characterization of calcareous sand reinforced by EICP multivariate tests and synergistic biochar reinforcement

The foundation bearing capacity in island reef infrastructure construction is often inadequate due to the poor engineering properties of calcareous sand. Enzyme-induced carbonate precipitation (EICP) has emerged as an efficient and environmentally friendly method to improve these properties, significantly enhancing the mechanical behavior of calcareous sand. However, the effectiveness of EICP is constrained by environmental factors that affect free urease activity and the limited availability of nucleation sites. To further improve the mechanical properties of EICP-reinforced calcareous sand, this study explores the addition of biochar to the sand. The characteristics of the samples were evaluated using unconfined compressive strength tests, calcium carbonate content measurements, and scanning electron microscopy. The results indicate that incorporating biochar into EICP significantly increases calcium carbonate production, strengthens the reinforced sand, and reduces surface porosity. This improvement is attributed to biochar’s surface properties, which provide additional nucleation sites for calcium carbonate formation, enhancing calcium carbonate content and sand strength. However, controlling the biochar content at approximately 5% is crucial to avoid excessive porosity, which could weaken the material. These findings offer a theoretical foundation for applying EICP-biochar-reinforced calcareous sand in engineering projects.

Measurement of sulfur content in coal mining areas by using field-remote sensing data and an integrated deep learning model

High-quality coal emits a smaller amount of harmful substances during the combustion process, which greatly reduces the environmental hazard. The sulfur content of coal is one of the important indicators that determine coal quality. The world’s demand for high-quality coal is increasing. This is challenging for the coal mining industry. Therefore, how to quickly determine the sulfur content of coal in coal mining areas has always been a research difficulty. This study is the first to map the distribution of sulfur content in opencast coal mines using field-remote sensing data, and propose a novel method for evaluating coal mine composition. We collected remote sensing, field visible and near-infrared (Vis-NIR) spectroscopy data and built analytical models based on a tiny neural network based on the convolutional neural network. The experimental results show that the proposed method can effectively analyze the coal sulfur content. The coal recognition accuracy is 99.65%, the root-mean-square error is 0.073 and the R is 0.87, and is better than support vector machines and partial least squares methods. Compared with traditional methods, the proposed method shows many advantages and superior performance.

Wavelength selection enables robust quantification of oil content with near-infrared spectroscopy in pea protein gels produced under varying heating conditions

Thermal processing influences the near-infrared (NIR) spectra of food products, causing inaccuracy when quantifying the composition of the product. In this study, the effect of thermal processing on NIR measurements of the oil content in pea protein isolate (PPI) gels was investigated. Analysis of variance showed that the heating temperature (30°C–120 °C) during the production of PPI gels influenced large parts of the NIR spectra and time (2.5–15 min) only had a limited effect. Stepwise multiple linear regression was used to select a combination of 5 wavelengths that was suitable to create a robust model for the prediction of oil content (Q2 = 0.9928 ± 0.002, root mean standard error of prediction = 0.2806 ± 0.0423 wt%). This combination of wavelengths was shown to reduce the effect of the history of thermal processing on the measurement, improving the accuracy of oil content quantification. This approach can be applied for in-line quantification of the oil content of food products subjected to varying heating conditions using specialized sensors.

Transcriptome analysis to identify genes related to programmed cell death resulted from manipulating of BnaFAH ortholog by CRISPR/Cas9 in Brassica napus

Fumarylacetoacetate hydrolase (FAH) catalyzes the final step of the tyrosine degradation pathway. In this study, we isolated and characterized two homologous BnaFAH genes in Brassica napus L. variant Westar, and then used CRISPR/Cas9-mediated targeted mutagenesis to generate a series of transgene-free mutant lines either with single or double-null bnafah alleles. Among these mutant lines, the aacc (bnafah) double-null mutant line, rather than the aaCC (bnaa06fah) mutant line, exhibited programmed cell death (PCD) under short days (SD). Histochemical staining and content measurement confirmed that the accumulation of reactive oxygen species (ROS) in bnafah was significantly higher than that in bnaa06fah. To further elucidate the mechanism of PCD, we performed transcriptomic analyses of bnaa06fah and bnafah at different SD stages. A heatmap cluster of differentially expressed genes (DEGs) revealed that PCD may be related to various redox regulatory genes involved in antioxidant activity, ROS-responsive regulation and calcium signaling. Combined with the results of previous studies, our work revealed that the expression levels of BnaC04CAT2, BnaA09/C09SAL1, BnaA08/C08ACO2, BnaA07/C06ERO1, BnaA08ACA1, BnaC04BIK1, BnaA09CRK36 and BnaA03CPK4 were significantly different and that these genes might be candidate hub genes for PCD. Together, our results underscore the ability of different PCD phenotypes to alter BnaFAH orthologs through gene editing and further elucidated the molecular mechanisms of oxidative stress-induced PCD in plants.

High correlation of quantitative susceptibility mapping and echo intensity measurements of nigral iron overload in Parkinson's disease.

Quantitative susceptibility mapping (QSM) and transcranial sonography (TCS) offer proximal evaluations of iron load in the substantia nigra. Our prospective study aimed to investigate the relationship between QSM and TCS measurements of nigral iron content in patients with Parkinson's disease (PD). In secondary analyses, we wanted to explore the correlation of substantia nigra imaging data with clinical and laboratory findings. Eighteen magnetic resonance imaging and TCS examinations were performed in 15 PD patients at various disease stages. Susceptibility measures of substantia nigra were calculated from referenced QSM maps. Echogenicity of substantia nigra on TCS was measured planimetrically (echogenic area) and by digitized analysis (echo-intensity). Iron-related blood serum parameters were measured. Clinical assessments included the Unified PD Rating Scale and non-motor symptom scales. Substantia nigra susceptibility correlated with echogenic area (Pearson correlation, r = 0.53, p = 0.001) and echo-intensity (r = 0.78, p < 0.001). Individual asymmetry indices correlated between susceptibility and echogenic area measurements (r = 0.50, p = 0.042) and, more clearly, between susceptibility and echo-intensity measurements (r = 0.85, p < 0.001). Substantia nigra susceptibility (individual mean of bilateral measurements) correlated with serum transferrin saturation (Spearman test, r = 0.78, p < 0.001) and, by trend, with serum iron (r = 0.69, p = 0.004). Nigral echogenicity was not clearly related to serum values associated with iron metabolism. Susceptibility and echogenicity measurements were unrelated to PD duration, motor subtype, and severity of motor and non-motor symptoms. The present results support the assumption that iron accumulation is involved in the increase of nigral echogenicity in PD. Nigral echo-intensity probably reflects ferritin-bound iron, e.g. stored in microglia.

A Theoretical Framework to Quantify Ecosystem Pressure-Volume Relationships.

'Water potential' is the biophysically relevant measure of water status in vegetation relating to stomatal, canopy and hydraulic conductance, as well as mortality thresholds; yet, this cannot be directly related to measured and modelled fluxes of water at plot- to landscape-scale without understanding its relationship with 'water content'. The capacity for detecting vegetation water content via microwave remote sensing further increases the need to understand the link between water content and ecosystem function. In this review, we explore how the fundamental measures of water status, water potential and water content are linked at ecosystem-scale drawing on the existing theory of pressure-volume (PV) relationships. We define and evaluate the concept and limitations of applying PV relationships to ecosystems where the quantity of water can vary on short timescales with respect to plant water status, and over longer timescales and over larger areas due to structural changes in vegetation. As a proof of concept, plot-scale aboveground vegetation PV curves were generated from equilibrium (e.g., predawn) water potentials and water content of the above ground biomass of nine plots, including tropical rainforest, savanna, temperate forest, and a long-term Amazonian rainforest drought experiment. Initial findings suggest that the stored water and ecosystem capacitance scale linearly with biomass across diverse systems, while the relative values of ecosystem hydraulic capacitance and physiologically accessible water storage do not vary systematically with biomass. The bottom-up scaling approach to ecosystem water relations identified the need to characterise the distribution of water potentials within a community and also revealed the relevance of community-level plant tissue fractions to ecosystem water relations. We believe that this theory will be instrumental in linking our detailed understanding of biophysical processes at tissue-scale to the scale at which land surface models operate and at which tower-based, airborne and satellite remote sensing can provide information.

Investigation on the impact of the spatial arrangement of individuals in a standing-type in-vivo monitoring system

An automated standing type Quick Scan Whole Body Monitor (QS-WBM) has been developed for the measurement of internal radioactive contamination due to high energy photon (HEP) emitters (Eϒ >200keV). Individuals are monitored while standing on a platform inside QS-WBM at specified reference position. Instances may occur where individuals deviate from their monitoring position, potentially leading to errors in the measurement of the body content. Positional inaccuracies are estimated in three potential scenarios: lateral displacement of the individual, movement perpendicular to the detector face, and forward bending of the torso. The Monte Carlo particle transport code FLUKA is used for estimation of efficiencies for selected radionuclides across various geometrical positions for adult male radiation workers. Approximately, 8% variation in calibration factors (CFs) is noted for lateral movements up to 15 cm from the centerline regardless of the energy, while perpendicular movements from reference position exhibit variations ranging from 14 to 60 %. This study helps in quantifying uncertainties in the estimation of body content and dose, arising from deviations in position of individuals in QS-WBM enclosure during monitoring.

Development of a brief stigma and perceptions questionnaire for pharmacists: An exploratory factor analysis approach in New York state counties enrolled in the healing communities study

IntroductionLittle is known about how pharmacists' attitudes and stigma toward naloxone and Medication for opioid use disorder (MOUD) influence effective linkage to treatment. We examine the psychometrics of a new Pharmacist Opioid Use Disorder Perceptions Questionnaire (P-OUDP-Q), a multidimensional measure to examine pharmacists' stigma and perceptions related to MOUD in the New York State (NYS) site of the HEALing Communities Study. MethodsThe study recruited a sample of 324 pharmacists from 16 counties in NYS between January and June 2022. A 74-item questionnaire assessed pharmacists' familiarity with opioid-related medications, protocols, policies and attitudes regarding their role, confidence, and beliefs centered around delivery of MOUD and naloxone in the community. Exploratory factor analysis assessed individual and community-level factors associated with four underlying constructs. Factor scores were compared across the demographic predictors. Variables factor loadings <0.4 were eliminated from the factor analysis and the process was reiterated. ResultsEighty-six percent (n = 280) of the pharmacists were white. A little over half, 57 % (n = 186), were female, 35 % (n = 113) were 30–35 years old. The mean number of years practicing (SD) was 18 (SD: 13). Exploratory factor analysis identified four underlying constructs: (1) practice confidence, (2) practice familiarity, (3) practice attitudes, and (4) methadone attitudes. Statistically significant (p < .05) mean factor scale score differences by race were observed for practice familiarity (white reporting higher than non-white); by pharmacy size for practice familiarity (across all groups; non-significant Tukey post-hoc) and practice attitudes (hospital/clinic greater than big chain pharmacies); by gender (males greater than females) for practice familiarity and methadone attitudes; by poverty quartile for practice attitudes (lowest less than highest quartile); and urban versus rural pharmacist county setting for practice familiarity (rural greater than urban). ConclusionsFindings show the P-OUDP-Q is a concise measure of pharmacists' perceptions of their role in dispensing MOUD and naloxone, including distinct “stigma” dimensions, which is valuable for use with pharmacists in communities highly impacted by the opioid epidemic. The development and validation of a reliable measure to assess pharmacists' perceptions of stigma and barriers represents a valuable contribution to the field, to inform the design/implementation of targeted interventions and support systems.

SWATH-MS based proteomics reveals the role of photosynthesis related proteins and secondary metabolic pathways in the colored leaves of sweet olive (Osmanthus fragrans)

Colored leaves, a notable horticultural trait, have high research and ornamental value. The evergreen sweet olive (Osmanthus fragrans), one of the top ten traditional flowers in China, has been cultivated for more than two thousand years. However, in recent years, an increasing number of O. fragrans cultivars with colored leaves have been cultivated for their ornamental value. To study the molecular mechanism underlying the observed changes in leaf color, we selected O. fragrans ‘Yinbi Shuanghui’ (Y), which has yellow-white leaves, and O. fragrans ‘Sijigui’ (S), which has green leaves, as materials. Pigment content measurement showed that the chlorophyll, carotenoid and anthocyanin contents in Y were lower than in S. According to the SWATH-MS sequencing results, a total of 3,959 proteins were quantitatively identified, 1,300 of which were differentially expressed proteins (DEPs), including 782 up-regulated and 518 down-regulated proteins in Y compared to S. Functional enrichment analysis of DEPs revealed that down-regulated expression of photosynthesis related proteins may lead to the inhibition of chlorophyll synthesis in Y, this may be the main cause of leaf color change. Moreover, a protein interaction prediction model also showed that proteins such as PetC, PsbO, PsbP, and PsbQ were key proteins in the interaction network, and the up-regulated proteins participating in the anthocyanin and carotenoid pathways may be related to the formation of yellow-white leaves. Taken together, our findings represent the first SWATH-MS-based proteomic report on colored leaf O. fragrans and reveal that chlorophyll synthesis and secondary metabolism pathways contribute to the changes in leaf color.

Examination of the Dry Density Importances in TDR Use and of the ASTM D6780 Standard Based on a New Calibration Procedure

Abstract The use of time domain reflectometry (TDR) to monitor soil water content at either field or laboratory scales is highly common. Regarding the soil dry density, ρd, effect on the TDR application, three main approaches are found in the literature: (1) Ignore the density issue and use calibration to evaluate the water content regardless of the density. This approach is basic, yet common. (2) Include soil density in the calibration equation and use calibration for the water content as a function of both the TDR output and soil density. In this approach, the soil density should be provided from an independent source. (3) Determined ρd from the TDR waveform. In this case both water content and ρd are set from the TDR analysis. In cases where the ρd is not available, in order to use TDR for water content measurement, a decision has to be made whether to address the density issue although it requires resources, or to neglect it. This article reviews this issue and validates the density effect using an efficient TDR calibration methodology. A calibration scheme that controls ρd of the specimen has been developed and applied. The methodology creates continuous calibration curves over a range of volumetric water content from a single test specimen. Based on the results, it has been demonstrated that the soil density has a major effect on the TDR output and it cannot be ignored. In addition, this article presents a unique examination of ASTM D6780, Standard Test Methods for Water Content and Density of Soil In Situ by Time Domain Reflectometry (TDR). The ASTM dry density estimation was found to provide reliable results; however, the gravimetric water contents estimation gives unsatisfactory results, especially for low densities.

A Flame Image Soft Sensor for Oxygen Content Prediction Based on Denoising Diffusion Probabilistic Model

High-precision oxygen content measurement is crucial for statistical analysis of combustion chemical reaction. Deep learning based soft sensor is a new class of intelligent tools for monitoring combustion oxygen content. But in the actual production, data for sensors are often insufficient. A new soft sensing model is proposed to display the excellent performance of denoising diffusion probabilistic model (DDPM) in data generation. Firstly, a UNet based soft sensor is designed by integrating self-attention mechanism into the convolution layers. Then, a denoising loss function is designed to link the feature extraction process of soft sensor model with the reverse denoising process of DDPM, and the noise prediction neural network of DDPM is used to improve the feature extractability of the soft sensor model. Finally, the proposed model is compared with common models. The effectiveness and superiority of the proposed soft sensing model for oxygen content prediction, especially in the case with a small sample size, are both confirmed by the results.