Linear Correlation Research Articles

Source identification of organic C and N in suspended particulate matter and sediments in plateau lakes as influenced by trophic status using stable isotopic signatures

Understanding the relationship between suspended particulate matter (SPM), sediment organic C, N stable isotopes, and lake trophic state index (TSI) is essential for managing lake pollution and eutrophication. According to the δ13C, δ15N, and C/N we found that the organic C in SPM and sediment of Caohai Lake primarily originated from macrophytes, while N was sourced from chemical fertilizers, phytoplankton, and aquatic plants. Total nitrogen, total phosphorus, NO3−-N, oxidation reduction potential, and Chl.a were identified as key factors influencing the sources and variations of SPM and sediment organic C and N stable isotopes in Caohai Lake, with a significant linear correlation observed between C, N stable isotopes, and TSI in sediments. To mitigate eutrophication in Caohai Lake, it is recommended that farmers apply fertilizers judiciously to minimize nutrient loss and that aquatic plants be regularly harvested to reduce N release from plant residues.

Addressing type Ia supernova color variability with a linear spectral template

Type Ia Supernovae (SNeIa) provided the first evidence of an accelerated expansion of the universe and remain a valuable probe to cosmology. They are deemed standardizable candles due to the observed correlations between their luminosity and photometric quantities. This characteristic can be exploited to estimate cosmological distances after accounting for the observed variations. There is however a remaining dispersion unaccounted for in the current state-of-the-art standardization methods. In an attempt to explore this issue, we propose a simple linear 3-component rest-frame flux description for a light-curve fitter. Since SNIa intrinsic color index variations are expected to be time-dependent, our description builds upon the mathematical expression of the well-known Spectral Adaptive Light Curve Template 2 (SALT2) for rest-frame flux, whilst we drop the exponential factor and add an extra model component with time and wavelength dependencies. The model components are obtained by performing either Principal Component Analysis (PCA) or Factor Analysis (FA) onto a representative training set. The constraining power of the model dubbed Pure Expansion Template for Supernovae (PETS) is evaluated and we found compatible results with SALT2 for Ωm0 and ΩΛ0 within 68% uncertainty between the two models, with PETS’ fit parameters exhibiting non-negligible linear correlations with SALT2’ parameters. For both PCA and FA model versions we verified that the first component mainly describes color index variations, proving it is a dominant effect on SNIa spectra. The model nuisance parameter which multiplies the color index variation-like fit parameter shows evolution with redshift in an initial binned cosmology analysis. This behavior can be due to selection effects and should be further investigated with higher redshift SNeIa samples. Overall, our model shows promise, as there are still a few aspects to be refined; however, it still falls short in reducing the unaccounted dispersion.

Long-range temperature sensing based on forward Brillouin scattering in highly nonlinear fiber

We propose and experimentally implement a long-range forward Brillouin scattering (FBS) temperature sensor, in which a 25-m highly nonlinear fiber (HNLF) is included in a Sagnac ring and is employed as the main sensing unit, and a 40-km standard single-mode fiber (SMF) is used as the transmission channel to connect the main sensing unit to the data processing center. The approach for quickly acquiring an optimal R0, m mode spectrum is presented. After taking into account the signal-to-noise ratio, sensitivity, and Lorentzian spectral shape, the R0, 17 mode was selected to perform temperature sensing. The frequency shift of the long-range and local FBS sensing demonstrates a linear correlation with the temperature change from 30 ℃ to 60 ℃, with respective frequency shift-temperature coefficients of 73.1 kHz/℃ and 73.4 kHz/℃. Impact of the length of the SMF as the main sensing unit and the SMF as the transmission channel on the FBS gain spectrum has also been discussed, respectively. The proposed long-range FBS scheme is expected to find applications in the investigation of submarine oil and gas pipelines, as well as temperature gradients in underwater and mountainous environments.

Synthesis of dragonfruit-based silicon nanoparticles at room temperature and their application in the real-time fiber-optic detection of doxorubicin

Doxorubicin (DOX) has been extensively used in cancer chemotherapy as an antibiotic drug, but when DOX concentration exceeds the threshold value, irreversible liver toxicity and cardiotoxicity can be triggered. Therefore, it is a significant theme to detect DOX concentration of patient blood and metabolites for the optimization of drug dosage. Linear correlation between fluorescence quenching of silicon nanoparticles (SiNPs) and DOX concentration enables SiNPs to present good prospect to address this tricky issue. Inspired by these aspects, we put forward a novel method to synthesize dragonfruit-based SiNPs (DSiNPs) at room temperature, and leverage them in the fiber-optic sensing of urine DOX. Firstly, we investigate a simple and green synthesis method of DSiNPs emitting blue-green fluorescence through a one-step redox reaction at room temperature with organosilane as silicon source and fresh dragonfruit juice as reducing agent. Secondly, depending on optical characterization, we demonstrate mechanism of DSiNPs in the detection of DOX. Thirdly, a fiber-optic sensor is used to measure the fluorescence intensity of DSiNPs under diverse salt concentrations, pH values, and illumination time to explore the tolerance of DSiNPs. Fourthly, based on optimization of parameters and validation of specificity, we acquire linear response range of this method to DOX from 0 to 50 μM with detection limit of 3 μM. Finally, this method is leveraged in the detection of urine DOX, and obtained the recovery rates of 92.30 % and 107.30 %. This method holds excellent potential in the clinical analysis of anti-tumor drugs for the advantages of environmental friendliness and simple operation.

Pengaruh Iklan dan Citra Merek Terhadap Keputusan Pembelian Produk Madu Wild Bee

This research aims to analyze advertising and brand image on purchasing decisions for wild bee honey products. This type of research is research with a quantitative approach. The population in this research is all Wild Bee Honey customers. Determining the sample in the study used probability sampling using the Slovin formula so that the number of samples in this study was 97 employees. The data analysis method in this research uses SPSS analysis tools through validity, reliability, classical assumption tests, namely normality test, multicollinearity test, heteroscedasticity test, multiple linear regression, t test, F test and correlation and determination coefficients. The results of this research show that (1) Advertising variables influence purchasing decisions, this is proven by the significance value of 0.000 < 0.05. 2. The Brand Image variable has a significant effect on purchasing decisions, this is proven by the significance value of 0.000 < 0.05. 3. Simultaneous test results show that the advertising and brand image variables influence the decision to purchase wild bee honey. This can be proven by the Fcount result of 113.280 or a significance value of 0.000 < 0.05.

Design and development of a stand-off Raman brassboard (SDU-RRS) for the spectroscopic study of planetary materials

Raman spectroscopy has emerged as a crucial mineral analysis technique in planetary surface exploration missions. Nonetheless, the inherently low Raman scattering efficiency of planetary silicate materials makes it challenging to extract enough Raman information. Theoretical and experimental studies of the remote Raman scattering properties of planetary materials are also urgent requirements for future lunar and planetary explorations. Here, Shandong University Remote Raman Spectrometer (SDU-RRS) was developed to demonstrate the feasibility of lunar remote Raman technology and conduct preliminary research on remote Raman scattering properties. SDU-RRS utilizes a pulsed 532 nm laser, a non-focal Cassegrain telescope, a volume phase holographic grating, an intensified charge-coupled device, and the time-gating technique to detect weak-signal silicate minerals. The spectral resolution obtained with atomic emission lamps was <4.91 cm−1, and the wavelength accuracy was <1 cm−1, across the spectral range of 241–2430 cm−1. SDU-RRS can detect natural augite within a feldspar-olivine-augite matrix at a concentration of 20 % at ∼1 m under ambient lighting conditions. A series of experiments were conducted to evaluate the influence of measurement conditions and physical matrix effects on acquired Raman signals, either qualitatively or quantitatively, on geological materials. The study indicates that the transmission of Raman-scattered light conforms to Lambert’s cosine law, and a linear correlation exists between Raman intensity and laser power. The study also evaluated the impact of grain size, surface roughness, porosity, and shadow-hiding effects. Reducing grain size decreases Raman intensity and broadens Raman spectra. These characteristics are essential for achieving definitive mineralogical information from granular materials by remote Raman spectroscopy in lunar and planetary explorations.

Improved localization and segmentation of spinal bone metastases in MRI with nnUNet radiomics

ObjectiveVariability exists in the subjective delineation of tumor areas in MRI scans of patients with spinal bone metastases. This research aims to investigate the efficacy of the nnUNet radiomics model for automatic segmentation and identification of spinal bone metastases. MethodsA cohort of 118 patients diagnosed with spinal bone metastases at our institution between January 2020 and December 2023 was enrolled. They were randomly divided into a training set (n = 78) and a test set (n = 40). The nnUNet radiomics segmentation model was developed, employing manual delineations of tumor areas by physicians as the reference standard. Both methods were utilized to compute tumor area measurements, and the segmentation performance and consistency of the nnUNet model were assessed. ResultsThe nnUNet model demonstrated effective localization and segmentation of metastases, including smaller lesions. The Dice coefficients for the training and test sets were 0.926 and 0.824, respectively. Within the test set, the Dice coefficients for lumbar and thoracic vertebrae were 0.838 and 0.785, respectively. Strong linear correlation was observed between the nnUNet model segmentation and physician-delineated tumor areas in 40 patients (R2 = 0.998, P < 0.001). ConclusionsThe nnUNet model exhibits efficacy in automatically localizing and segmenting spinal bone metastases in MRI scans.

Supramolecular colorimetric sensor array combined with machine learning for benzimidazoles fungicides discrimination and prediction

Due to their slight structural differences, the rapid identification of benzimidazole fungicides is challenging. In this study, three benzimidazole fungicides (FBZ, CBZ and TBZ) with similar structures were added to the 2C30@3Q[8] host–guest complex. The solutions changed color, suggesting that a reaction occurred. Based on this host–guest interaction, a supramolecular colorimetric sensor array was constructed by extracting the red, green and blue (RGB) color change of the host–guest complex in response to fungicides. Linear discriminant analysis (LDA) identified and distinguished the benzimidazole fungicides with similar structures. The supramolecular colorimetric sensor array was in the 1–20 μM range. The Euclidean distance of the array showed excellent linear correlation with the fungicide concentration, with a 10−7 mol/L detection limit and a signal-to-noise ratio of 3. The colorimetric sensor array clearly distinguished between the binary and ternary fungicide mixes. The sensor array was integrated with machine learning to predict TBZ concentrations in river water. The applicability of the supramolecular colorimetry sensor array was verified by distinguishing and identifying three benzimidazole fungicides in river water and fruit skin.

From SPECT/CT towards absolute quantification? - the case of unilateral condylar hyperplasia of the mandible

BackgroundUnilateral condylar hyperplasia (UCH) of the mandible is a rare condition characterized by asymmetric growth of the mandibular condyles. Bone scintigraphy with SPECT(/CT) is commonly used to diagnose UCH and guide treatment. Still, varying results have been reported using the traditional threshold of 55%:45% in relative tracer uptake. While absolute quantification of uptake on SPECT/CT could improve results, optimal correction and reconstruction settings are currently unknown.MethodsThree anthropomorphic phantoms representing UCH were developed from patient CT volumes and produced using 3D printing technology. Fillable spherical inserts of different sizes (Ø: 8–15 mm) were placed in the condylar positions representing symmetrical and asymmetrical distributions. Recovery coefficients were determined for SPECT/CT using various reconstruction corrections, including attenuation and scatter correction (ACSC), resolution modeling (RM), and partial volume correction (PVC) using phantom measurements. Uptake ratios between condyles and condyle to clivus were evaluated. Finally, the impact of these correction techniques on absolute activity and diagnostic accuracy was assessed in a retrospective patient cohort for the diagnostic threshold of 55%:45%.ResultsThe activity was only partially recovered in all spherical inserts (range: 22.5–64.9%). However, RM improved relative recovery by 20.2–62.3% compared to ACSC. In the symmetric phantoms, the 95% confidence interval (CI) of condyle ratios included the diagnostic threshold (57.6%:42.4%) for UCH when using ACSC potentially leading to false positives, but not for ACSCRM datasets. Partial volume corrections coefficients from the NEMA IQ phantom was positionally dependent, with improvements seen performing PVC using coefficients derived from anthropomorphic phantoms. Retrospective application in a patient cohort showed only a weak linear correlation (R²: 0.25–0.67) and large limits of agreement (9.6–12.5%) between different reconstructions. Up to 44% of patients were reclassified using the 55%:45% threshold. Using clinical outcome data, ACSCRM had highest sensitivity (91%; 95% CI 59–100%) and specificity (66%; 95% CI 47–81%), significantly improving specificity (P = 0.038).ConclusionsAnthropomorphic phantoms were shown to be essential in determining optimal settings for acquisition, reconstruction, and analysis. SPECT/CT reconstructions with attenuation and scatter correction and resolution modeling are recommended and could improve specificity when using the 55%:45% threshold to assess condylar growth.

Directional fracture patterns of excavated jointed rock mass within rough discrete fractures

The influence of the fractures on the anisotropic mechanical behavior of excavated fractured rock mass is important for the stability of rock tunnels. Rough joints were generated using fractal principles, and the Monte Carlo method was employed to create joint network faces. Biaxial compression numerical simulations were conducted using the discrete element method to analyze the behavior of the rock mass containing these networks. Quantitative analysis was carried out to evaluate the strength variability and total number of cracks in the jointed rock mass. A linear regression analysis was conducted to establish the relationship between rock strength and excavation size. The findings demonstrate significant disparities between the linear and fractal models regarding rock damage mode, stress–strain curves, and crack evolution patterns. Tensile rupture and local shear damage were found to be the primary fracture modes for the fractured rock tunnels, forming a V-shaped damage zone within the central tunnel. The shape of this zone was influenced by fracture direction and excavation ratio. Excavation at the center of the rock mass substantially impacted the variability of rock strength and the occurrence of internal cracks. An increase in the slope ratio led to a greater variability of rock mass strength, transitioning from nearly isotropic to weakly anisotropic behavior. The total number of cracks exhibited a W-shaped trend, initially increasing and later decreasing as the slope ratio decreased. Additionally, a clear linear correlation was observed between rock strength and excavation ratio at the center of the rock mass.

Achieving SOC Conservation without Land-Use Changes between Agriculture and Forests

Global land-use changes impact soil’s ability to perform essential functions. This study investigates whether soil organic carbon (SOC) can be conserved without altering land use in traditional farming systems and degraded natural forests, focusing on ‘disturbed’ agricultural soils and ‘undisturbed’ forest soils. We also examine the influence of dominant crops on SOC within the top 30 cm of soil in data-deficient regions of Nepal. Using a multi-stage cluster sampling design, we tested 12 regression models to identify the best relationships among variables such as SOC, soil bulk density (BD), pH, dominant crops, climate, topography, and management practices. Our analysis revealed similar SOC levels in both disturbed and undisturbed soils, indicating significant degradation in forested areas, whereas traditional farming systems could support SOC and preserve farm-based indigenous knowledge alongside food security. Further, SOC stocks varied significantly (p &lt; 0.05) across different cropping systems, suggesting that managing dominant crops could be a strategy to optimize SOC, with these crops serving as indicators. Additionally, our results show that the weak linear correlation between SOC and BD in regularly disturbed soils, such as farmlands, where anthropogenic activities frequently alter soil bulk density, may be misleading when estimating bulk density-dependent SOC. This finding suggests the need for further research into varying degrees of anthropogenic disturbance in soil to confirm these results. While the site-specific nature of the findings warrants caution with respect to generalization, they provide valuable insights for carbon monitoring, climate actions, ecosystem health, and land-use management in similar traditional farming systems and degraded forests, particularly in data-poor regions.

Simultaneous determination of free DL-amino acids in human hair with a novel DBD-M-Pro derivatization by UHPLC-HRMS: An application in diabetes patients

Human hair is a non-invasive biological sample that is easy to collect and store and can reflect long-term body health. However, the correlation between DL-amino acids and metabolic diseases in hair samples has not been studied. Therefore, we propose a novel UHPLC-HRMS method for analyzing seven free chiral amino acids (DL-Thr, DL-Glu, DL-Ala, DL-Val, DL-Pro, DL-Leu, and DL-Phe) simultaneously in hair samples by derivatization of chiral probe 4-(N,N-dmethylaminosulfonyl)-2,1,3-benzoxadiazole-trans-2-methyl-L-proline (DBD-M-Pro) labeled with targeted amino functional groups. Gradient elution was carried out using an ACQUITYTM BEH C18 (100×2.1 mm,1.7 μm) column with a mobile phase of 0.15 % formic acid (FA) in 10 mM ammonium acetate (CH3-COONH4) and 0.2 % FA in acetonitrile. The labelled DL-amino acid diastereoisomers could be completely separated, with a resolution (Rs) of 1.59–11.44. These amino acids show a strong linear correlation within the range of 3.1–99.2 pmol (R2 ≥ 0.9990). Intraday and interday precision was 1.87 %–14.87 %. The average recovery was 96.12 %–105.33 %. The limit of detection (LOD) ranged from 0.29 to 2.11 pmol. We then employed the method to determine the concentration of free chiral amino acids in hair samples from 30 healthy volunteers (HVs) and 30 diabetes patients (DPs). Male diabetes patients had significantly higher levels of L-Thr, L-Val, L-Leu (p < 0.05), and D-Ala (p < 0.01) in their hair samples than male healthy volunteers and female diabetes patients had significantly higher levels of D-Ala (p < 0.05) in their hair samples than female healthy volunteers. This is the first study to confirm the feasibility of using free DL-amino acids in human hair as potential biomarkers for diabetes.

A Comparative Study on the Texture of Exposed Aggregate Concrete (EAC) Pavements Using Different Measurement Techniques.

This paper presents issues related to the assessment of the texture of aggregate concrete (EAC) surfaces using various methods for its verification. Microtexture was assessed using the British Pendulum Tester (BPT) and Dynamic Friction Tester (DFT). Two laser profilometers were used to assess macrotexture, circular texture meter (CTM) and stationary laser profilograph (SPL), as well as the commonly known volumetric method. Measurements were carried out on left and right tracks and in between them on five test sections of expressways. Based on the analyses performed, it was found that the results obtained by the DFT were less sensitive to changes in microtexture between individual tracks compared to the results obtained by the BPT. The BPN values in the left track were lower than those in the right track. However, the difference between the DFT20 results in these spots was insignificant. Both MPD and MTD values did not show significant differences between the right and left tracks. However, some differences were observed between the MPD parameters obtained using the CTM and SPL. This resulted from the different frequency and length of the scanned surface profile. However, the differences were at an acceptable level. A very high linear correlation was obtained in the case of BPN and DFT20 values (r - 0.719), and in the case of MPD and MTD values, the correlation was almost certain (r above 0.900). Based on a comparative analysis of the models estimating mean texture depth (MTD/ETD), a significant difference was observed between models based on EAC pavement results and those based on asphalt surfaces.

Simultaneous Far-ultraviolet and Near-ultraviolet Observations of T Tauri Stars with UVIT/AstroSat: Probing the Accretion Process in Young Stars

We present results from simultaneous far-ultraviolet (FUV) and near-ultraviolet (NUV) observations of T Tauri stars (TTSs) in the Taurus molecular cloud with UVIT/AstroSat. This is the very first UVIT study of TTSs. From the spectral energy distribution of TTSs from FUV to IR, we show that classical TTSs (CTTSs) emit significantly higher UV excess compared to weak-line TTSs (WTTSs). The equivalent blackbody temperatures corresponding to the UV excess in CTTSs (>104 K) are also found to be relatively higher than those in WTTSs (<9250 K). From the UV excess, we have reclassified two WTTSs (BS Tau and V836 Tau) as CTTSs, which has been supported by the follow-up optical spectroscopic study using the Himalayan Chandra Telescope, showing strong Hα line emission. We find that CTTSs show strong excess emission in both the FUV (>107) and NUV (>103) bands, while WTTSs show strong excess only in the FUV (≲105), suggesting that excess emission in the NUV can be used as a tool to classify the TTSs. We also find a linear correlation between UV luminosity (a primary indicator of mass accretion) and Hα luminosity (a secondary indicator of mass accretion) with a slope of 1.20 ± 0.22 and intercept of 2.16 ± 0.70.

X-Ray Winds in Nearby-to-distant Galaxies (X-WING). I. Legacy Surveys of Galaxies with Ultrafast Outflows and Warm Absorbers in z ∼ 0–4

As an inaugural investigation under the X-ray Winds In Nearby-to-distant Galaxies (X-WING) program, we assembled a data set comprising 132 active galactic nuclei (AGNs) spanning redshifts z ∼ 0–4 characterized by blueshifted absorption lines indicative of X-ray winds. Through an exhaustive review of previous research, we compiled the outflow parameters for 583 X-ray winds, encompassing key attributes such as outflow velocities (V out), ionization parameters (ξ), and hydrogen column densities. By leveraging the parameters V out and ξ, we systematically categorized the winds into three distinct groups: ultrafast outflows (UFOs), low-ionization parameter (low-IP) UFOs, and warm absorbers (WAs). Strikingly, a discernible absence of linear correlations in the outflow parameters, coupled with distributions approaching instrumental detection limits, was observed. Another notable finding was the identification of a velocity gap around V out ∼ 10,000 km s−1. This gap was particularly evident in the winds detected via absorption lines within the ≲2 keV band, indicating disparate origins for low-IP UFOs and WAs. In cases involving Fe xxv/Fe xxvi lines, where the gap might be attributed to potential confusion between emission/absorption lines and the Fe K-edge, the possibility of UFOs and galactic-scale WAs being disconnected is considered. An examination of the outflow and dust sublimation radii revealed a distinction: UFOs appear to consist of dust-free material, whereas WAs likely comprise dusty gas. From 2024, the X-Ray Imaging and Spectroscopy Mission is poised to alleviate observational biases, providing insights into the authenticity of the identified gap, a pivotal question in comprehending AGN feedback from UFOs.

Analysis of Ca1-xSrxCO3 phases generated by competitive Sr2+ replacement in pre-formed aragonite

The ratio of Sr/Ca ions in marine biogenic minerals is considered advantageous for tracking geochemical and biomineralization processes that occur in the oceans. It is debatable, though, whether the ratio in biominerals such as coral skeleton is simply related to values in the seawater environment or controlled by the organism. Recent data show that coral larvae produce partially disordered immature aragonite in Mg-containing Sr-poor calcifying fluids, which transforms into well-ordered aragonite in Mg-depleted Sr-enriched environments, upon animal metamorphosis into the sessile polyp state.Inspired by the process in young coral, we explored in vitro substitution of Ca by Sr in aragonite by exposing aragonite crystals precipitated a priori to Sr solutions with variable concentrations. The resulting biphasic material, comprised of Sr-doped aragonite and Ca-doped strontianite, was carefully analyzed for foreign cation substitution in each polymorph. This allowed to establish a linear correlation between Sr levels in mineralizing solutions and Sr in aragonite as well as Ca in strontianite. It indicated that ca. 5-fold higher Sr solution concentration is needed for substitution in the crystal to reach the level found in corals. It also provided with Sr levels required for a putative strontianite phase to form.

Experimental study and thermodynamic modeling of CO2+CH4 gas mixture hydrate phase equilibria for gas separation efficiency

Gas separation is a critical application of gas hydrates, and accurately predicting separation performance is crucial. In this study, we used thermodynamic calculations to predict the equilibrium phase of gas hydrates for various mole fractions of CO2 + CH4 gas mixtures. We also determined the mole fraction of each gas component trapped within the hydrate clathrate. To predict the equilibrium points, we used the Soave–Redlich–Kwong（(SRK) equation of state for the gas phase, the nonrandom two-liquid (NRTL)model for the liquid phase, and the Chen–Guo model for the hydrate phase. We modified the hydrate fugacity formula and introduced a new function to improve the accuracy of the Chen–Guo model. By incorporating experimental equilibrium results from our study and another study, we developed a correlation based on gas mixture composition and temperature, resulting in highly accurate predictions. The use of this new correlation for hydrate fugacity calculation significantly improved precision, as evidenced by an average absolute deviation percent of calculated pressures (AADP) of 1.34% for pure CO2 and 1.25% for CH4. When considering the 27 data points of different CO2 + CH4 mixtures, the AADP% was 1.98%.To implement the model to predict equilibrium phases, we used the Chen–Guo framework to determine the mole fraction of each gas component in the hydrate mixture. Interestingly, we discovered a linear correlation between the CO2 mole fraction in the hydrate and equilibrium pressure, with a slope of approximately 0.001 and a y-intercept of less than one, for all gas compositions. Therefore, we can conclude that low thermodynamic conditions (temperature and pressure) result in a high CO2 mole fraction in the hydrate phase and great separation efficiency.

Responses of Leaf Expansion, Plant Transpiration and Leaf Senescence of Different Soybean (Glycine max. (L.) Merr.) Genotypes to Soil Water Deficit

ABSTRACTThe responses of eco‐physiological processes such as leaf expansion, plant transpiration and senescence to soil water deficit have been reported to be genotype‐dependent in different crops. To study such responses in soybean (Glycine max. (L.) Merr.), a 2‐year (2017 and 2021) outdoor pot experiment was carried out on the Heliaphen automated phenotyping platform at INRAE in Toulouse (France). Six soybean cultivars (Sultana‐MG 000, ES Pallador‐MG I, Isidor‐MG I, Santana‐MG I/II, Blancas‐MG II and Ecudor‐MG II) belonging to four maturity groups (MG) commonly grown in Europe were subjected to progressive soil water deficit from the reproductive stage R1 for 17 and 23 days in 2017 and 2021, respectively. The fraction of transpirable soil water (FTSW) was used as an indicator of soil water deficit. Non‐linear regression was used to calculate FTSWt, that is, the FTSW threshold for which the rate of the eco‐physiological process in stressed plants starts to diverge from a reference value. According to FTSWt, the three eco‐physiological processes showed significant differences in sensitivity to water deficit: leaf expansion exhibits the highest sensitivity and the widest range (FTSWt: 0.44–0.93), followed by plant transpiration (FTSWt: 0.17–0.56), with leaf senescence showing the narrowest range (FTSWt: 0.05–0.16). Among six cultivars, regarding leaf expansion, Cvs Santana (FTSWt = 0.48 in 2017; FTSWt = 0.44 in 2021), Blancas (FTSWt = 0.51 in 2017; FTSWt = 0.48 in 2021) and Ecudor (FTSWt = 0.46 in 2017; FTSWt = 0.52 in 2021) in late MGs (I/II to II) exhibited higher tolerance to soil drying. Conversely, the cv. Sultana in the earliest MG (000) showed the highest sensitivity (FTSWt = 0.91 in 2017; FTSWt = 0.93 in 2021) to water deficit. However, concerning the FTSWt values for plant transpiration (0.17–0.56 in 2017; 0.19–0.31 in 2021) and senescence (0.05–0.16 in 2017; 0.06–0.16 in 2021), their range did not demonstrate a correlated trend with the MG. In addition, a negative linear correlation was observed between values of FTSWt of normalised leaf expansion at the whole‐plant level (NLE) and specific leaf area (SLA) measured on irrigated plants for both years. This suggests that genotypes with high values of SLA could be associated with higher tolerance of leaf expansion to soil water deficit. Such a non‐destructive phenotyping method under outdoor conditions could bring new information to variety testing process and provide paths for integrating genotypic variability into crop growth models used for simulating soybean eco‐physiological responses to water deficit across the plant, field and even regional scales.

Reevaluating Economic Drivers of Household Food Waste: Insights, Tools, and Implications Based on European GDP Correlations

This article examines the relationship between household food waste and Gross Domestic Product (GDP) in various European regions, aiming to determine how economic prosperity influences the levels of household food waste. Using comparative analysis of secondary and tertiary data, a synthetic indicator (IpFW) was developed to assess the interaction between GDP per capita and household food waste per capita. Linear correlation analysis was also applied for better interpretation of the data. Despite expectations, higher GDP is not consistently correlated with lower household food waste, challenging economic prosperity and environmental stewardship assumptions. This research highlights the complexity of the interaction between economic factors and household food waste management, revealing a lack of significant correlation even at the regional level. The findings indicate a need to re-evaluate current policies and highlight that improving food supply chains and influencing consumer behavior can promote more sustainable consumption patterns, which is in line with the Sustainable Development Goals.

Neutrophil-lymphocyte ratio and systemic immune-inflammation index as predictors of cardiovascular risk and mortality in prediabetes and diabetes: a population-based study.

The neutrophil-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) are emerging inflammatory markers related to cardiovascular outcomes. This study investigated their relationships with cardiovascular disease (CVD) and mortality among individuals with prediabetes or diabetes and assessed their predictive roles. A cohort of 6871 individuals with diabetes or prediabetes from the NHANES (2001-2018) was included. Weighted multivariate logistic regression models assessed NLR and SII associations with CVD risk, while survey-weighted Cox proportional hazards models evaluated their links to mortality. The predictive accuracy of the biomarkers for mortality was quantified by receiver-operating characteristic (ROC) curve analysis. Individuals in the higher NLR and SII groups exhibited a high incidence of CVD. A total of 1146 deaths occurred throughout an average follow-up duration of 191months, of which 382 were caused by CVD. Participants with higher NLR markedly increased the risk of all-cause (HR = 1.82) and cardiovascular mortality (HR = 2.07). A similar result was observed in the higher SII group. RCS analysis identified a linear correlation between NLR and CVD risk and mortality (p > 0.05), while SII showed a nonlinear correlation (p < 0.05). ROC results demonstrated that NLR exhibited a higher predictive ability in mortality than SII. Elevated levels of NLR and SII correlated with an increased risk of CVD and both all-cause and cardiovascular mortality in individuals with diabetes or prediabetes. The NLR appears to be particularly valuable for assessing risk and predicting outcomes in these patients.