Curve Parameters Research Articles

Oxygen Saturation Curve Analysis in 2298 Hypoxia Awareness Training Tests of Military Aircrew Members in a Hypobaric Chamber.

We aim to provide reference values for military aircrews participating in hypoxia awareness training (HAT). We describe several parameters with potential biomedical interest based on selected segments and slopes of the changes in oxygen saturation (SatO2) during a standard HAT. A retrospective analysis of 2298 records of the SatO2 curve was performed, including 1526 military men aged 30.48 ± 6.47 years during HAT in a hypobaric chamber. HAT consisted of pre-oxygenation at 100% and an ascent to 7620 m, followed by O2 disconnection starting the phase of descent of SatO2 until reaching the time of useful consciousness (TUC), and finally reconnection to 100% O2 in the recovery phase. Using an ad hoc computational procedure, the time taken to reach several defined critical values was computed. These key parameters were the time until desaturation of 97% and 90% (hypoxia) after oxygen mask disconnection (D97/D90) and reconnection (R97/R90) phases, the time of desaturation (TUC-D97) and hypoxia (TUC-D90) during disconnection, the total time in desaturation (L97) or hypoxia (L90), and the slopes of SatO2 drop (SDSAT97 and SDSAT90) and recovery (SRSAT97). The mean of the quartiles according to TUC were compared by ANOVA. The correlations between the different parameters were studied using Pearson's test and the effect size was estimated with ω2. Potentially useful parameters for the HAT study were those with statistical significance (p < 0.05) and a large effect size. D97, D90, R97, and R90 showed significant differences with small effect sizes, while TUC-D97, TUC-D90, L97, L90, and SDSAT97 showed significant differences and large effect sizes. SDSAT97 correlated with TUC (R = 0.79), TUC-D97 (R = 0.81), and TUC-D90 (R = 0.81). In conclusion, several parameters of the SatO2 curve are useful for the study and monitoring of HAT. The SDSAT97 measured during the test can estimate the TUC and thus contribute to taking measures to characterize and protect the aircrew members.

Photosynthetic Performance and Yield Losses of Winter Rapeseed (Brassica napus L. var. napus) Caused by Simulated Hail.

Winter oilseed rape (Brassica napus L.), Europe's foremost oilseed crop, is significantly impacted by hailstorms, leading to substantial yield reductions that are difficult to predict and measure using conventional methods. This research aimed to assess the effectiveness of photosynthetic efficiency analysis for predicting yield loss in winter rapeseed subjected to hail exposure. The aim was to pinpoint the chlorophyll fluorescence parameters most affected by hail stress and identify those that could act as non-invasive biomarkers of yield loss. The study was conducted in partially controlled conditions (greenhouse). Stress was induced in the plants by firing plastic balls with a 6 mm diameter at them using a pneumatic device, which launched the projectiles at speeds of several tens of meters per second. Measurements of both continuous-excitation and pulse-modulated-amplitude chlorophyll fluorescence were engaged to highlight the sensitivity of the induction curve and related parameters to hail stress. Our research uncovered that some parameters such as Fs, Fm', ΦPSII, ETR, Fo, Fv/Fm, and Fv/Fo measured eight days after the application of stress had a strong correlation with final yield, thus laying the groundwork for the creation of new practical protocols in agriculture and the insurance industry to accurately forecast damage to rapeseed crops due to hail stress.

Старение и надежность: как вариации во времени интенсивности отказов влияют на форму кривых дожития стареющих организмов

The article considers the regularities of the theory of reliability, which determine the constancy of the shape of the curves of organisms’ survival. The assumption that the probability of natural death is determined by the probability of accidental failure of a part of a series of homogeneous elements (cells) allows to obtain, analytically and through numerical experiments, survival curves similar to those observed in nature. The use of com-puter modelling methods makes it possible to identify the survival curve parameters determined by the dynamics of the probability of failure of an individual element. The value of one of these parameters, namely the coordinates of the inflection point of human survival curves, indicates that, apparently, both in long-lived species in general and in humans specifically, the ageing promoting mechanism is the progressive deterioration of reliability - the dilapidation of the elements (cells) crucial for ageing.

Quantitative parameter analysis of pretreatment dual-energy computed tomography in nasopharyngeal carcinoma cervical lymph node characteristics and prediction of radiotherapy sensitivity

BackgroundTreatment efficacy may differ among patients with nasopharyngeal carcinoma (NPC) at similar tumor–node–metastasis stages. Moreover, end-of-treatment tumor regression is a reliable indicator of treatment sensitivity. This study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters could predict sensitivity to neck–lymph node radiotherapy in patients with NPC.MethodsOverall, 388 lymph nodes were collected from 98 patients with NPC who underwent pretreatment DECT. The patients were divided into complete response (CR) and partial response (PR) groups. Clinical characteristics and quantitative DECT parameters were compared between the groups, and the optimal predictive ability of each parameter was determined using receiver operating characteristic (ROC) analysis. A nomogram prediction model was constructed and validated using univariate and binary logistic regression.ResultsDECT parameters were higher in the CR group than in the PR group. The iodine concentration (IC), normalized IC, Mix-0.6, spectral Hounsfield unit curve slope, effective atomic number, and virtual monoenergetic images were significantly different between the groups. The area under the ROC curve of the DECT parameters was 0.73–0.77. Based on the binary logistic regression, a column chart was constructed using 10 predictive factors, including age, sex, N stage, maximum lymph node diameter, arterial phase NIC, venous phase NIC, λHU and spectral Hounsfield units at 70 keV. The area under the ROC curve value of the constructed model was 0.813, with a sensitivity and specificity of 85.6% and 81.3%, respectively.ConclusionQuantitative DECT parameters could effectively predict the sensitivity of NPC to radiotherapy. Therefore, DECT parameters and NPC clinical features can be combined to construct a nomogram with high predictive power and used as a clinical analytical tool.

Effects of Methanolic Leaf-extract of Costus pictus D. Don on Swiss Albino Mice with Hyperglycemia Associated Renal Complications

Effects of Costus pictus leaf extract (CPLE) in ameliorating the adverse outcomes of hyperglycemia-associated renal injury is investigated in Swiss Albino Mice. To induce renal injury associated with hyperglycemia, adult mice were given intraperitoneal injections of Streptozotocin (STZ) dissolved in 0.5mol citrate buffer for five days. Animals were divided into five groups, namely CMC (vehicle control group, receiving only carboxy methyl cellulose), DC (Disease control group, receiving only STZ and without any treatment), GLD (positive control group, receiving standard drug glibenclamide), LD (experimental group treated with CPLE at 250 mg/kg bw) and HD (experimental group treated with CPLE at 500 mg/kg bw). After a rearing/treatment regimen of 4 weeks, animals were sacrificed to analyze various parameters. Oral glucose tolerance test (OGTT) based area under the curve of plasma glucose (AUCglucose), kidney index, lipid profiling, serum, urine parameters (creatinine, albumin, urea), antioxidant studies and kidney histopathology were carried out. It was found that harmful lipids like cholesterol, triglycerides (TG) and low-density lipoprotein-C (LDL-C) levels were significantly elevated in the DC group, whereas LD, HD and GLD showed a tendency towards normalcy. Urine and serum parameters also showed the same trend in treatments and the GLD group, whereas the DC group showed steep abnormalities. Antioxidant study also reveals that treatment with CPLE, balances antioxidant activity by mitigating the effects of reactive oxygen species (ROS). Histopathological investigations displayed significant disruptions in the microstructure of glomeruli of the DC group compared to both the treatments and GLD groups. These preliminary findings indicate that CPLE shows a trend to ameliorate hyperglycemia-associated renal complications and demands further detailed study.

Machine learning based severity classification of obstructive sleep apnea patients using awake EEG

Obstructive sleep apnea (OSA) is one of the most widespread breathing-based sleep disorders. Previous studies reported daytime sleepiness, mental fatigue, and cognitive decline in patients with OSA. The diagnosis of OSA is done with laborious overnight polysomnography (PSG) recording. This study aims to classify the severity of OSA patients according to the Apnea-Hypopnea Index (AHI) into mild and moderate to-serve groups (AHI ≥ 15) without using recorded signals during sleep, non-PSG signals and investigate the relevant features. For this purpose, 25 OSA patients participated in 3-minute eyes closed resting state EEG session on the following morning of overnight PSG recording. Time, spectral domain, and nonlinear features were extracted from the delta, theta, and alpha subbands’ of EEG signals. Several machine learning algorithms were used to classify patients’ severity. To investigate optimal feature combinations features were grouped according to their types (Time domain/spectral domain and nonlinear), their electrodes (frontal/central/parietal/occipital), and their subbands (delta/theta/alpha). Also, the Relief method was applied to select the most relevant features. A 5-fold cross validation method was used to generalize the model behaviour. Optimal feature combinations were selected according to classifiers' performances that were evaluated by accuracy, sensitivity, specificity, and area under curve (AUC) parameters when feature sets were used as input. The 15 selected features by the Relief method showed the best performances in the K-Nearest Neighbours (K = 5) classifier [accuracy: 93.33 % ± 5.27 %; sensitivity: 92.30 % ± 4.97 %; specificity: 94.14 % ± 4.24 %; AUC:0.98]. The findings establish that awake resting state EEG records might be used as a faster tool to use OSA severity level.

Damage‐informed ground motion and semi‐empirical fragility assessment

AbstractCalibrating parametric fragility curves via empirical damage data is one of the standard approaches to derive seismic structural vulnerability models. Fragilities based on empirical data require the characterization of the ground motion (GM) intensity at the building sites in the area affected by the earthquake producing the observed damages. This is commonly conducted via ShakeMap, that is, a map of the expected values of a Gaussian random field (GRF) of the logarithms of a GM intensity measure conditional to magnitude, location, and possibly a set of recordings of the earthquake. Once that intensity and damage data at the same sites are available, the typical approach calibrates a two‐parameter fragility model. However, ShakeMap estimates are affected by uncertainty deriving from that of the GM model used to characterize it. Furthermore, such an uncertainty can be reduced by building damage data, which provide information on the shaking intensity at the sites where damage is observed. It is shown herein that if this uncertainty is not addressed, also considering the shaking information provided by damage, the estimates of the fragility parameters obtained using a median ShakeMap only can be biased, and a recommended maximum likelihood estimation procedure – which exploits the expectation maximization algorithm – is provided. These arguments are illustrated via an application considering damage data from the 2009 L'Aquila earthquake in central Italy.

Safe immunosuppression. New tool for personalized immunosuppressant treatment in renal transplantation. A case report

Background: The adjustment of immunosuppressive therapy after kidney transplantation (KT) to avoid graft rejection remains an important challenge for clinicians. It is difficult to achieve a good balance between under-immunosuppression (with an increased risk of graft rejection) and over-immunosuppression (with an increased risk of side effects) by only relying on the available information about immunosuppressive drugs (IMS). Immunobiogram® (IMBG) is a novel in vitro diagnostic test that provides clinicians with information about the patient’s sensitivity to individual IMS. Objective: To present a case report of a patient with renal transplant in the maintenance phase who presented several complications probably related to the immunosuppression during the follow-up, where the use of IMBG as complementary information helped clinicians to guide the therapeutical decision. Methods: IMBG is a first-in-class in vitro immunoassay that involves the culture of the patient peripheral blood mononuclear cells (PBMCs) in a semi-solid 3D matrix, then submitted to immune stimulation. It reveals the capacity of an IMS over a gradient to inhibit the activation of immune cells. The read-out allows the building of a dose-response curve per IMS tested, which is mathematically analyzed by a software using the key curve parameters and finally to be translated into a sensitivity map to IMS. Findings: We present a case report of a 72-year-old patient with a cadaveric donor kidney transplant receiving standard immunosuppressive treatment with mycophenolate, tacrolimus, and corticosteroids. The patient presented several episodes of infections during the follow-up (SARS-CoV2, Cytomegalovirus, spondylodisquitis by Staphylococcus aureus, and emphysematous cystitis) which were managed with different treatment adjustments such as de-escalation of mycophenolate and switching to mTOR. The information provided by the IMBG showed a lack of sensitivity to mTOR which allowed to confirm the final adjustment to a treatment with tacrolimus and corticosteroids, remaining the patient stable since then. Discussion: Despite various adjustments to the immunosuppressive therapy during the follow-up, the patient continued experiencing adverse effects that could be related to an over-immunosuppression state. The IMBG provided pharmacodynamic information that complemented the clinical and pharmacokinetic data available, facilitating the individualization of the treatment. Conclusion: The case highlights the potential of the IMBG as a complementary clinical tool for personalized treatment of kidney transplant patient management.

EPID-03. CURE FRACTION AND LONG TERM SURVIVAL ESTIMATES FOR PEDIATRIC CENTRAL NERVOUS SYSTEM TUMORS IN EUROPE – RESULTS OF THE POPULATION-BASED EUROCARE PROJECT

Abstract BACKGROUND Time trends in cure fractions and up-to-date long-term survival have not been reported for clinically relevant groups of pediatric central nervous system (CNS) tumors although it provides important information for planning long-term clinical follow-up. METHODS We analyzed data on 15,242 children (&amp;lt;15 years) diagnosed with a CNS tumor between 1998-2013 from 31 European countries with follow-up until 31/12/2014. Cure fraction, the proportion of patients not anymore at risk of dying from progression or relapse was estimated using a mixture cure model with a parametric cancer survival curve function and assuming constant long-term mortality from other causes, including other cancers. Additionally, model-based up-to-date 15-year observed survival (OS) was estimated for the period 2010-2013. RESULTS The cure fraction for ependymomas increased from 65% in 1998-2001 to 79% in 2010-2013. However, as a result of the high long-term mortality rate of 16 per 1000 surviving patients per year, ependymomas had an estimated 15-year OS of 62%. For diffuse astrocytomas the cure fraction increased 6 percent-points to 84%, and 15-year OS was 74%. Cure fraction for glioblastomas increased from 15% to 20%. Long-term mortality for surviving glioblastoma patients was null resulting in a comparable projected 15-year OS of 20%. For medulloblastomas the cure fraction increased with 4 percent-points to 56% in 2010-2013, and a comparable 15-year OS of 56%. AT/RTs including PNETs together with high-grade gliomas (HGGs) were the only groups for which the cure fraction did not change over time: 34% and 24%, respectively. Estimated 15-year OS was 28% for AT/RTs including PNETs and 19% for HGGs. CONCLUSIONS As a result of high long-term mortality, the difference between cure fraction and 15-year OS was the highest for ependymomas and diffuse astrocytomas. Further investigation into underlying reasons (e.g., late effects of treatment) are needed to reduce the extra risk of deaths.

Growth and dry matter intake curve analysis of crossbred male calves in Ethiopia

ABSTRACT The study was carried out at Holetta agricultural Research center dairy farm to estimate the growth and dry matter intake curves parameters of different genetic groups of crossbred male calves. A total of 48 weaned Friesian Boran (FB) crossbred calves consisting of 24 male calves having 50% Friesian blood level and another 24 growing calves having 75% Friesian blood level were used for this study. The calves were managed under individual feeding management for a fattening period of 626 days. Body weight and dry matter intake data were fitted into Gompertz nonlinear growth model. Mean values for growth parameters in 50% FB and 75% FB crosses were 727.0 and 730.2 kg; 2.85 and 2.78; 0.0019 and 0.0017 kg/day; 547.95 and 595.68 days; 257.46 and 268.63 kg; for mature weight, integration constant, maturity rate, age at inflection point and body weight at inflection point, respectively. This study revealed that 50% FB crossbred bull calves are fast maturing genotype and had significantly lower DMI at mature age than 75% FB crosses. Generally, 50% FB crossbred bull calves can be used for fattening purpose to meet increasing lean meat demand of consumers in Ethiopia with decreased feed cost under improved feeding system.

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

Contrast-enhanced ultrasound (CEUS): applications from the kidneys to the bladder.

Contrast-enhanced ultrasound (CEUS) is an advanced ultrasound (US) technique utilizing ultrasound contrast agents (UCAs) to provide detailed visualization of anatomic and vascular architecture, including the depiction of microcirculation. CEUS has been well-established in echocardiography and imaging of focal hepatic lesions and recent studies have also shown the utility of CEUS in non-hepatic applications like the urinary system. The updated guidelines by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) from 2018 describe the use of CEUS for non-hepatic applications. CEUS' excellent safety profile and spatial resolution make it a superior modality to conventional US and is often comparable and even superior to CECT in some instances. In comparison to other cross-sectional imaging modalities such as CECT or MRI, CEUS offers a safe (by virtue of non-nephrotoxic US contrast agents), accurate, cost-efficient, readily available, and a quick means of evaluation of multiple pathologies of the urinary system. CEUS also has the potential to reduce the overall economic burden on patients requiring long-term follow-up due to its low cost as compared to CT or MRI techniques. This comprehensive review focuses on the applications of CEUS in evaluating the urinary system from the kidneys to the urinary bladder. CEUS can be utilized in the kidney to evaluate complex cystic lesions, indeterminate lesions, pseudotumors (vs solid renal tumors), renal infections, and renal ischemic disorders. Additionally, CEUS has also been utilized in evaluating renal transplants. In the urinary bladder, CEUS is extremely useful in differentiating a bladder hematoma and bladder cancer when conventional US techniques show equivocal results. Quantitative parameters of time-intensity curves (TICs) of CEUS examinations have also been studied to stage and grade bladder cancers. Although promising, further research is needed to definitively stage bladder cancers and classify them as muscle-invasive or non-muscle invasive using quantitative CEUS to guide appropriate intervention. CEUS has been very effective in the classification of cystic renal lesions, however, further research is needed in differentiating benign from malignant renal masses.

Qualitative and quantitative assessment of non-clear cell renal cell carcinoma using contrast-enhanced ultrasound

BackgroundNon-clear cell renal cell carcinoma (nccRCC) represents a rare form of renal cell carcinoma (RCC) in the clinic. It is now understood that contrast-enhanced ultrasound (CEUS) exhibits diverse manifestations and can be prone to misdiagnosis. Therefore, summarizing the distinctive features of contrast-enhanced ultrasonography is essential for differentiation from ccRCC.ObjectiveThis study aims to evaluate the diagnostic efficacy of qualitative and quantitative CEUS in diagnosing nccRCC to enhance our understanding of this condition.MethodsWe conducted a retrospective analysis of 21 patients with confirmed nccRCC following surgery and assessed the characteristic conventional ultrasound and CEUS imaging features. The paired Wilcoxon signed-rank sum test was employed to compare differences in CEUS time-intensity curve (TIC) parameters between the lesions and the normal renal cortex.ResultsRoutine ultrasound revealed the following primary characteristics in the 21 nccRCC cases: hypoechoic appearance (10/21, 47.6%), absence of liquefaction (18/21, 66.7%), regular shape (19/21, 90.5%), clear boundaries (21/21, 100%), and absence of calcification (17/21, 81%). Color Doppler flow imaging (CDFI) indicated a low blood flow signal (only 1 case of grade III). Qualitative CEUS analysis demonstrated that nccRCC predominantly exhibited slow progression (76.1%), fast washout (57%), uniformity (61.9%), low enhancement (71.5%), and ring enhancement (61.9%). Quantitative CEUS analysis revealed that parameters such as PE, WiAUC, mTTI, WiR, WiPI, WoAUC, WiWoAUC, and WOR in the lesions were significantly lower than those in the normal renal cortex (Z=-3.980, -3.563, -2.427, -3.389, -3.980, -3.493, -3.528, -2.763, P < 0.001, < 0.001, = 0.015, = 0.001, < 0.001, < 0.001, < 0.001, = 0.006). However, there were no significant differences in RT, TTP, FT, or QOF (all P > 0.05).ConclusionnccRCC exhibits distinctive CEUS characteristics, including slow progression, fast washout, low homogeneity enhancement, and ring enhancement, which can aid in distinguishing nccRCC from ccRCC.

New Parametric 2D Curves for Modeling Prostate Shape in Magnetic Resonance Images

Geometric shape models often help to extract specific contours in digital images (the segmentation process) with major precision. Motivated by this idea, we introduce two models for the representation of prostate shape in the axial plane of magnetic resonance images. In more detail, the models are two parametric closed curves of the plane. The analytic study of the models includes the geometric role of the parameters describing the curves, symmetries, invariants, special cases, elliptic Fourier descriptors, conditions for simple curves and area of the enclosed surfaces. The models were validated for prostate shapes by fitting the curves to prostate contours delineated by a radiologist and measuring the errors with the mean distance, the Hausdorff distance and the Dice similarity coefficient. Validation was also conducted by comparing our models with the deformed superellipse model used in literature. Our models are equivalent in fitting metrics to the deformed superellipse model; however, they have the advantage of a more straightforward formulation and they depend on fewer parameters, implying a reduced computational time for the fitting process. Due to the validation, our models may be applied for developing innovative and performing segmentation methods or improving existing ones.

VESCL: an open source 2D vessel contouring library.

VESCL (pronounced 'vessel') is a novel vessel contouring library for computer-assisted 2D vessel contouring and segmentation. VESCL facilitates manual vessel segmentation in 2D medical images to generate gold-standard datasets for training, testing, and validating automatic vessel segmentation. VESCL is an open-source C++ library designed for easy integration into medical image processing systems. VESCL provides an intuitive interface for drawing variable-width parametric curves along vessels in 2D images. It includes highly optimized localized filtering to automatically fit drawn curves to the nearest vessel centerline and automatically determine the varying vessel width along each curve. To support a variety of segmentation paradigms, VESCL can export multiple segmentation representations including binary segmentations, occupancy maps, and distance fields. VESCL provides sub-pixel resolution for vessel centerlines and vessel widths. It is optimized to segment small vessels with single- or sub-pixel widths that are visible to the human eye but hard to segment automatically via conventional filters. When tested on neurovascular digital subtraction angiography (DSA), VESCL's intuitive hand-drawn input with automatic curve fitting increased the speed of fully manual segmentation by 22× over conventional methods and by 3× over the best publicly available computer-assisted manual segmentation method. Accuracy was shown to be within the range of inter-operator variability of gold standard manually segmented data from a publicly available dataset of neurovascular DSA images as measured using Dice scores. Preliminary tests showed similar improvements for segmenting DSA of coronary arteries and RGB images of retinal arteries. VESCL is an open-source C++ library for contouring vessels in 2D images which can be used to reduce the tedious, labor-intensive process of manually generating gold-standard segmentations for training, testing, and comparing automatic segmentation methods.

Shape optimization of autonomous underwater helicopters based on different parameter curves and various optimization algorithms

This study aimed to compare the non-uniform rational B-spline (NURBS) and Bezier curves to design the shape of an autonomous underwater helicopter (AUH). Currently, there is no established method for AUH shape design. The optimal solutions obtained from both curves were compared to evaluate their performance. A parametric model was constructed to determine the design variables of the two curves. Computational fluid dynamics was used to solve the resistance values of different shapes. Sample points were generated using the design of the experimental approach, and an approximate model was established using the radial basis function neural network method. Based on the combinatorial optimization strategy, three intelligent optimization algorithms were used for the global search. Then, the resulting solution was used as the starting point for a local search to obtain the global optimal solution. The resistance optimal solutions achieved by employing the NURBS and Bezier curves were 25.2% and 24.1% smaller than the initial values, respectively. These findings indicate that, within the design parameters of this study, the shape design approach using the NURBS curve yields superior performance for the AUH.

Testing the ecological footprint of economic growth in developing countries. The case of Vietnam

AbstractThis study focuses on the relationship between economic growth and environmental degradation, by testing the Environmental Kuznets Curve hypothesis in Vietnam, a main export‐oriented country that features a long period of economic growth. The main originality of this work is that, unlike previous studies, it uses ecological footprint as the main indicator for environmental degradation. This allows to reconsider the results from previous studies that only focus on CO2 emissions performances. The cointegration between the analysed variables is investigated using the autoregressive distributed lag (ARDL) approach. To determine the parameters of the Environmental Kuznets Curve in the sample, this work additionally analyses long‐ and short‐run estimations. The paper shows that the EKC hypothesis holds in the long term for Vietnam when using ecological footprint. Nevertheless, it also shows that not only growth but also primary energy consumption contributes to increased environmental destruction. An active ecological policy and the decrease of fossil energy use seem necessary to allow Vietnam to keep a high level of economic growth and reduce environmental degradation.

Consistent curves in the -world: optimal bonds portfolio

We derive arbitrage-free conditions for a parametric yield curve in the P -world, where market prices of risk are present. As in the Heath–Jarrow–Morton (HJM) theory, we impose the bonds evolution to be free of arbitrage opportunities. However, in the classical HJM theory, first volatilities are specified, and subsequently the drift of the forward curve is obtained up to the market prices of risk that must be specified exogenously. Here, the problem is inverted: we first impose a family of shapes upon the yield curve and subsequently derive market prices of risk in a self-consistent manner and hence the market prices of risk follow a stochastic differential equation obtained directly from the curve dynamics. Leveraging this framework, we formulate a bonds-portfolio optimization as a stochastic control problem with the Hamilton–Jacobi–Bellman (H-J-B) equation. We discover that in this case, the H-J-B equation is essentially different than the classical obtained in optimal investment problems.

Lipoprotein Combine Index as a Better Marker for NAFLD Identification Than Traditional Lipid Parameters.

The association between traditional lipid parameters and non-alcoholic fatty liver disease (NAFLD) has been extensively discussed. This study aims to evaluate and compare the lipoprotein combine index (LCI) and traditional lipid parameters [total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C)] to identify NAFLD. The analysis included 14,251 participants from the NAfld in the Gifu Area, Longitudinal Analysis (NAGALA). Logistic regression models were employed to calculate standardized odds ratios (ORs) and 95% confidence intervals (CIs) for assessing and comparing the association of LCI and traditional lipid parameters with NAFLD. Additionally, receiver operating characteristic (ROC) curves were used to calculate the area under the curve (AUC) for LCI and traditional lipid parameters in identifying NAFLD. After adjusting for various confounders, we found that LCI was positively associated with NAFLD (OR=2.25, 95% CI 1.92-2.63), and this association was stronger than that of traditional lipid parameters [OR: TC1.23, TG1.73 LDL-C1.10]. Further subgroup analyses revealed that the association of LCI with NAFLD was stronger than other traditional lipid parameters in all subgroups, including men and women, overweight/obese [body mass index (BMI)≥25 kg/m2] and non-obese (BMI<25 kg/m2), and older (age≥45 years) and younger (age<45 years) participants. Additionally, ROC analysis indicated that LCI (AUC=0.8118) had significantly higher accuracy (All DeLong P<0.05) in identifying NAFLD compared to traditional lipid parameters (AUC: TC0.6309; TG0.7969; LDL-C0.6941); HDL-C0.7587). Sensitivity analysis further confirmed the robustness of the study findings. This study revealed for the first time a positive correlation between LCI and NAFLD. Compared to traditional lipid parameters, LCI has a higher correlation with NAFLD. Additionally, further ROC analysis demonstrated that LCI had higher accuracy in identifying NAFLD compared to traditional lipid parameters, suggesting that LCI may be a better marker for NAFLD identification than traditional lipid parameters.

Noisy kinetic-exchange opinion model with aging.

We study the critical behavior of a noisy kinetic opinion model subject to resilience to change depending on aging, defined as the number of interactions before a change of opinion state. In this model, the opinion of each agent can take three discrete values, the extreme ones ±1, and also the intermediate value 0, and it can evolve through kinetic exchange when interacting with another agent, or independently, by stochastic choice (noise). The probability of change by pairwise interactions depends on the age that the agent has remained in the same state, according to a given kernel. We particularly develop the cases where the probability decays either algebraically or exponentially with the age, and we also consider the anti-aging scenario where the probability increases with the age, meaning that it is more likely to change mind the longer the persistence in the current state. For the opinion dynamics in a complete graph, we obtain analytical predictions for the critical curves of the order parameters, in perfect agreement with agent-based simulations. We observe that sufficiently weak aging (slow change of the kernel with the age) favors partial consensus with respect to the aging-insensitive scenario, while for sufficiently strong aging, as well as for anti-aging, the opposite trend is observed.