Index Dispersion Research Articles

Inflammatory bowel disease and white matter microstructure: A bidirectional Mendelian randomization study

BackgroundObservational studies have reported changes in the brain white matter (WM) microstructure in patients with inflammatory bowel disease (IBD); however, it remains uncertain whether the relationship between them is causative. The aim of this study is to reveal the potential causal relationship between IBD and WM microstructure through a bidirectional two-sample Mendelian randomization (MR) analysis. Methods: We extracted genome-wide association study (GWAS) summary statistics for IBD and WM microstructure from published GWASs. Two-sample MR analysis was conducted to explore the bidirectional causal associations between IBD and WM microstructure, followed by a series of sensitivity analyses to assess the robustness of the results. Results: Although forward MR analysis results showed no evidence of causality from microstructural WM to IBD, reverse MR showed that genetically predicted IBD, consisting of ulcerative colitis and Crohn’s disease, has a significant causal effect on the orientation dispersion index (OD) of the right tapetum (β = −0.029, 95% CI = −0.045 to −0.013, p = 3.63 × 10−4). Further sensitivity analysis confirmed the robustness of the association. Conclusion: Our results suggested the potentially causal association of IBD with reduced OD in the right tapetum.

Characteristics of clay dispersion and its influencing factors in saline-sodic soils of Songnen Plain, China

Under the influence of salinity-sodicity stress, soil salinization and sodification tend to be severe and the dispersion of clay particles increases, which threatens agricultural production and food security. To explore the characteristics of clay dispersion in saline-sodic soils and their influencing factors, the quantitative relationship between clay dispersion indices and soil physicochemical parameters in saline-sodic soils of the Songnen Plain in China was investigated, to provide theoretical and data support for clay dispersion control in saline-sodic soils. Forty-two natural soil samples (0–0.2 m) were collected from saline-sodic soils in Songnen Plain, northeast China, and their physicochemical parameters and clay dispersion indices were determined. Correlation analysis, random forest analysis, and multivariate linear regression analysis were used in this study. The results showed that water-dispersible clay (WDC) ranged from 0.60 % to 18.38 % and total clay (TC) ranged from 4.70 % to 20.68 %. The maximum value of the clay dispersion ratio (CDR) is nine times the minimum value. In terms of turbidity, mechanical dispersion turbidity (MDT) ranged from 39.60 to 59,433 NTU, while spontaneous dispersion turbidity (SDT) ranged from 1.11 to 154.67 NTU. In terms of zeta potential, the minimum value of mechanical dispersion ZETA potential (MDZP) was −46.42 mV, and the maximum value was close to 0 mV. There was a significant correlation between soil physicochemical parameters and clay dispersion indices. Exchangeable sodium percentage (ESP) was the most important explanatory variable for CDR, followed by pH, Na+ex, HCO3-, Na+, CEC, CO32-, SAR, CROSS, and SOC, which could help construct the following multiple linear regression model: CDR=0.143+0.015*ESP −0.036*CO32- −0.006*Na+. Exchangeable sodium percentage has the strongest effects on clay dispersion among the soil parameters. Clay dispersion indices vary with soil physicochemical parameters. Compared to MDT, SDT, MDZP, and SDZP, CDR is more suitable for evaluating and predicting the clay dispersion condition in saline-sodic soils.

Investigating corrosion-induced deterioration in bolted steel plate joints using guided wave ultrasonic inspection

AbstractBolted steel plate joints encounter challenges posed by joint corrosion, which impact the quality of interfacial contact among the bolted components. Unfortunately, no correlation between corrosion-induced joint damage and preload, nor an existing numerical model capable of capturing such effects, has been identified. This study aims to utilize guided wave ultrasonic investigation to examine the deterioration of interfacial contact caused by corrosion in bolted joints. Additionally, a contact modification-based numerical approach is presented to capture the effects of changing interfacial stress during joint corrosion. Guided wave mode selection was conducted with some preliminary experiments supplemented with the theory of wave mode dispersion, hence leading to the selection of S0 and A0 mode existing at 300 kHz. The joint was then corroded in a controlled manner using an electrochemical process while simultaneous ultrasonic measurements were taken. The experimental observations highlighted the progressive dispersion in the transmitted A0 mode across the bolted joint, potentially due to changing interfacial stress boundaries between the plates. A damage parameter, termed the dispersion index, was developed based on the energy ratio of different signal sections. A linear change in the dispersion index was observed with the increase in corrosion-induced mass loss. The insight was further established through a numerical investigation by studying the effect of changing bolt preload and the corresponding interfacial stress distribution. The findings revealed that monitoring the changes in the stress distribution at the bolted interface can provide insight into interfacial corrosion. Eventually, destructive tension test results confirmed the effect of joint corrosion on the load-bearing capacity of the joint. The change in failure mode of the pristine and corroded specimen is observed. The reported approach establishes the potential of ultrasonic inspection to investigate the interfacial health of a bolted joint in corroding conditions.

Analysis of leukemia and forest fires data using new Poisson Quasi-Shanker distribution

In this study, a new two-parameter discrete distribution is introduced by mixing Poisson and Quasi-Shanker distributions. The new model is named Poisson Quasi-Shanker-(PQS) distribution. Some important mathematical properties of the proposed distribution are derived including factorial moments, moment-generating function, variance, and dispersion index. The parameters of PQS distribution are estimated using the maximum likelihood estimation approach. A Monte Carlo simulation is carried out to illustrate the behavior of derived estimators. The applicability of the new model is assessed using two datasets from different areas. It is concluded the proposed distribution is more flexible as compared to the considered competitive distributions.

Dynamics of structural indices and organic carbon pool across a haplic acrisol under secondary tropical rainforest at Umudike Abia State

Differences in vegetation types over a landscape influences the structural behaviour and organic carbon pool of soils thereby affecting site-specific management decisions. This study aimed at establishing the differences in structural indices and organic carbon pool across a soil under secondary rainforest vegetation. Nine replicates of auger and core soil samples were randomly collected from the site at 0 – 20 cm depth. Soil samples were prepared and analysed at a laboratory. Data obtained were subjected to geospatial analysis using a Geographical Information System (GIS) software package. Results showed that changes in organic carbon storage ranged from 40 – 48 ton / ha, BD ranged from 1.39 – 1.42 mg / m3, clay flocculation index ranged from 50 – 68 %, aggregated silt + clay ranged from 9 – 12 %, clay dispersion index ranged from 32 – 42 %, dispersion ratio ranged from 26 – 32 %, mean weight diameter ranged from 0.75 – 1.05 mm, saturated hydraulic conductivity ranged from 3.1 – 3.8 cm / mins and total porosity ranged from 46.4 – 47.6 %. Regions of weak micro aggregaion dominated the land while regions of increased stability of macro aggregates were dominant. Regions of increased soil organic carbon storage occupied about half portion of the land. Greater portion of the land was noted for increased bulk density, reduced total porosity and saturated hydraulic conductivity. Consequently, there were changes in soil structural properties and organic carbon storage across the studied area.

Mapping the neurodevelopmental predictors of psychopathology.

Neuroimaging research has uncovered a multitude of neural abnormalities associated with psychopathology, but few prediction-based studies have been conducted during adolescence, and even fewer used neurobiological features that were extracted across multiple neuroimaging modalities. This gap in the literature is critical, as deriving accurate brain-based models of psychopathology is anessential steptowards understanding key neural mechanisms and identifying high-risk individuals. As such, we trained adaptive tree-boosting algorithms on multimodal neuroimaging features from the Lifespan Human Connectome Developmental (HCP-D) sample that contained 956 participants between the ages of 8 to 22 years old. Our feature space consisted of 1037 anatomical, 1090 functional, and 192 diffusion MRI features, which were used to derive models that separately predicted internalizing symptoms, externalizing symptoms, and the general psychopathology factor. We found that multimodal models were the most accurate, but all brain-based models of psychopathology yielded out-of-sample predictions that were weakly correlated with actual symptoms (r2 < 0.15). White matter microstructural properties, including orientation dispersion indices and intracellular volume fractions, were the most predictive of general psychopathology, followed by cortical thickness and functional connectivity. Spatially, the most predictive features of general psychopathology were primarily localized within the default mode and dorsal attention networks. These results were mostly consistent across all dimensions of psychopathology, except orientation dispersion indices and the default mode network were not as heavily weighted in the prediction of internalizing and externalizing symptoms. Taken with prior literature, it appears that neurobiological features are an important part of the equation for predicting psychopathology but relying exclusively on neural markers is clearly not sufficient, especially among adolescent samples with subclinical symptoms. Consequently, risk factor models of psychopathology may benefit from incorporating additional sources of information that have also been shown to explain individual differences, such as psychosocial factors, environmental stressors, and genetic vulnerabilities.

Residual and past varinaccuracy measures

Abstract Analysing the information measures’ dispersion index has garnered increasing attention. In this regard, variability of entropy has been explored for residual and past lifetimes. In a recent paper, Balakrishnan et al. (2023, Commun. Stat. Theory Methods, 53, 5574–5592) have studied the variability of the Kerridge inaccuracy measure. The dynamic measures of varinaccuracy, namely residual varinaccuracy and past varinaccuracy, have been introduced in this article. A detailed course of theoretical results has been investigated with examples. Further, some applications of the residual varinaccuracy have been added to show the functionality of the defined measure.

Engineered extracellular vesicles coated with an antimicrobial peptide for advanced control of bacterial sepsis.

Alarming sepsis-related mortality rates present significant challenges to healthcare services globally. Despite advances made in the field, there is still an urgent need to develop innovative approaches that could improve survival rates and reduce the overall cost of treatment for sepsis patients. Therefore, this study aimed to develop a novel multifunctional therapeutic agent for advanced control of bacterial sepsis. Extracellular vesicles (EVs) isolated from lipopolysaccharide (LPS) induced HepG2 (hepatocellular carcinoma cells) (iEV) displayed an average particle size of 171.63±2.77nm, a poly dispersion index (PDI) of 0.32±0.0, and a zeta potential (ZP) of -11.87±0.18mV. Compared to HepG2 EV, LPS induction significantly increases the EV protein concentration, PDI and ZP, reduces the average size and promotes cell proliferation and cytoprotective effects of the isolated EVs (iEVs) against LPS-induced cytotoxicity. Coating of iEV with a cationic antimicrobial peptide (AMP) to form PC-iEV slightly changed their physical properties and shifted their surface charge toward neutral values. This modification improved the antibacterial activity (2-fold lower minimum bactericidal concentration [MBC] values) and biocompatibility of the conjugated peptide while maintaining iEV cytoprotective and anti-inflammatory activities. Our findings indicate the superior anti-inflammatory and antibacterial dual activity of PC-iEV against pathogens associated with sepsis.

Mapping macrostructural and microstructural brain alterations in patients with neuronal intranuclear inclusion disease.

Neuronal intranuclear inclusion disease (NIID) is a rare complex neurodegenerative disorder presents with various radiological features. The study aimed to investigate the structural abnormalities in NIID using multi-shell diffusion MR. Twenty-eight patients with adult-onset NIID and 32 healthy controls were included. Volumetric and diffusion MRI measures, including volume, fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) of six brain structures, including cortex, subcortical GM, cerebral WM, cerebellar GM and WM, and brainstem, were obtained and compared between NIID and healthy controls. Associations between MRI measures and clinical variables were investigated. Brain lesions of NIID included corticomedullary junction lesions on DWI, confluent leukoencephalopathy, lesions on callosum, cerebellar middle peduncle, cerebellar paravermal area and brainstem, and brain atrophy. Compared to healthy controls, NIID showed extensive volume loss of all the six brain regions (all p < 0.001); lower FA in cerebral WM (p < 0.001); higher MD in all WM regions; lower ODI in cortex (p < 0.001); higher ODI in subcortical GM (p < 0.001) and brainstem (p = 0.016); lower ICVF in brainstem (p = 0.001), and cerebral WM (p < 0.001); higher ISOVF in all the brain regions (p < 0.001). Higher MD of cerebellar WM was associated with worse cognitive level as evaluated by MoCA scores (p = 0.011). NIID patients demonstrated widespread brain atrophy but heterogeneous diffusion alterations. Cerebellar WM integrity impairment was correlated with the cognitive decline. The findings of the current study offer a sophisticated picture of brain structural alterations in NIID.

Age dictates brain functional connectivity and axonal integrity following repetitive mild traumatic brain injuries in mice

Traumatic brain injuries (TBI) present a major public health challenge, demanding an in-depth understanding of age-specific symptoms and risk factors. Aging not only significantly influences brain function and plasticity but also elevates the risk of hospitalizations and death following TBIs. Repetitive mild TBIs (rmTBI) compound these issues, resulting in cumulative and long-term brain damage in the brain. In this study, we investigate the impact of age on brain network changes and white matter properties following rmTBI by employing a multi-modal approach that integrates resting-state functional magnetic resonance imaging (rsfMRI), graph theory analysis, diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI). Our hypothesis is that the effects of rmTBI are worsened in aged animals, with this group showing more pronounced alterations in brain connectivity and white matter structure. Utilizing the closed-head impact model of engineered rotational acceleration (CHIMERA) model, we conducted rmTBIs or sham (control) procedures on young (2.5–3-months-old) and aged (22-months-old) male and female mice to model high-risk groups. Functional and structural imaging unveiled age-related reductions in communication efficiency between brain regions, while injuries induced opposhigh-risking effects on the small-world index across age groups, influencing network segregation. Functional connectivity analysis also identified alterations in 79 out of 148 brain regions by age, treatment (sham vs. rmTBI), or their interaction. Injuries exerted pronounced effects on sensory integration areas, including insular and motor cortices. Age-related disruptions in white matter integrity were observed, indicating alterations in various diffusion directions (mean diffusivity, radial diffusivity, axial diffusivity, and fractional anisotropy) and density neurite properties (dispersion index, intracellular and isotropic volume fraction). Neuroinflammation, assessed through Iba-1 and GFAP markers, correlated with higher dispersion in the optic tract, suggesting a neuroinflammatory response in injured aged animals compared to sham aged. These findings offer insight into the interplay between age, injuries, and brain connectivity, shedding light on the long-term consequences of rmTBI.

Multi-peak soliton dynamics and decoherence via the attenuation effects and trapping potential based on a fractional nonlinear Schrödinger cubic quintic equation in an optical fiber

Fiber optic research continues to develop due to the need for fast information technology. The input signal in an optical fiber is in the form of a soliton wave that propagates in the fiber with a balanced index of refraction, dispersion, and diffraction. Fiber optics may lose some of the signal over time if they solely use a nonlinear refractive index. This study aims to examine into the dynamics and decoherence of multi-peak solitons caused by electromagnetic signal attenuation and potential trap in the propagation via optical fibers. The methods used start with the stationary solution of the nonlinear Schrödinger Cubic Quintic equation, the Newton-Raphson method, and the fourth-order Runge-Kutta. In stationary solutions, the p (state energy) and ρ (Lèvy index) values affect the number, pulse width, and height of soliton peaks. Increased p and ρ values lead to increased instability, causing the data transmitted into the optical fiber to collapse and become unreadable by the receiver. In the excited state (p > 0), the decoherence phenomenon occurs and causes wave instability and destruction. In term of energy intensity, a stable form of transmission in the ground state has a pattern of continuously weakening, decreasing, and smoothing, while in the excited state there is a spike in the intensity of the electromagnetic wave. Based on this study, multi-peak solitons can only be applied for propagation distances, which tend to be short due to their dynamics and decoherence.

Long-Circulating and Brain-Targeted Liposomes Loaded with Isoliquiritigenin: Formation, Characterization, Pharmacokinetics, and Distribution.

Isoliquiritigenin (ISL) has excellent neuroprotective effects. However, its limitations, including poor solubility, low bioavailability, and low accumulation in the brain, restrict its clinical promotion. In this study, a novel type of ISL-loaded liposome (ISL-LP) modified with the brain-targeting polypeptide angiopep-2 was prepared to improve these properties. The zeta potential, morphology, particle size, encapsulation efficiency, drug loading, and in vitro release of ISL-LP were evaluated. The pharmacokinetics and tissue distribution of ISL and ISL-LP were also investigated. The results demonstrated that ISL-LP had an average particle size of 89.36 ± 5.04 nm, a polymer dispersity index of 0.17 ± 0.03, a zeta potential of -20.27 ± 2.18 mV, and an encapsulation efficiency of 75.04 ± 3.28%. The in vitro release experiments indicate that ISL-LP is a desirable sustained-release system. After intravenous administration, LPC-LP prolonged the circulation time of ISL in vivo and enhanced its relative brain uptake. In conclusion, ISL-LP could serve as a promising brain-targeting system for the treatment and prevention of central nervous system (CNS) disorders.

Rheological and microscopic characterization and correlation analysis of asphalt under high-intensity ultraviolet radiation

The lower radiation intensity (2–20 W/m2) was widely used for asphalt ultraviolet (UV) aging. The effect of high-intensity radiation on asphalt properties and microscopic morphology is unknown. This study investigated the rheological behavior, microscopic characterization, and correlation analysis of SBS modified asphalt under high-intensity UV radiation. Rheological properties tests encompassed temperature sweep (TS), multiple stress creep recovery (MSCR), and frequency sweep (FS). Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Gel Permeation Chromatography (GPC) tests were performed to reveal the microscopic characterization. In the early stages of UV aging, the rutting factor of asphalt was increased. The increment decreased as the UV aging time increased. The UV aging process did not alter the temperature sensitivity of asphalt. The complex shear modulus was influenced by UV radiation duration and loading frequency. Extended exposure to high-intensity UV radiation resulted in the formation of microcracks on the surface of the asphalt. The maximum molecular weight of the UV-aged asphalt was higher than that of the original asphalt. The degraded SBS modifier deteriorated the homogeneity of asphalt. The sulfoxide aging index, carbonyl aging index, number-average molecular weight (Mn), weight average molecular weight (Mw), and polymer dispersity index (PDI) presented a better correlation with rheological behavior indexes. The correlation between small molecule size (SMS), medium molecule size (MMS), and large molecule size (LMS) with rutting factor and complex shear modulus was poor. It was worth mentioning that the correlation between the MSCR test results and microscopic performance indicators was the best. Especially for the recovery rate and Jnr at 3.2 kPa, the mean absolute value of the correlation coefficient was 0.953.

Comparative utility of MRI and EEG for early detection of cortical dysmaturation after postnatal systemic inflammation in the neonatal rat

BackgroundExposure to postnatal systemic inflammation is associated with increased risk of brain injury in preterm infants, leading to impaired maturation of the cerebral cortex and adverse neurodevelopmental outcomes. However, the optimal method for identifying cortical dysmaturation is unclear. Herein, we compared the utility of electroencephalography (EEG), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) at different recovery times after systemic inflammation in newborn rats. MethodsSprague Dawley rat pups of both sexes received single-daily lipopolysaccharide (LPS; 0.3 mg/kg i.p.; n = 51) or saline (n = 55) injections on postnatal days (P)1, 2, and 3. A subset of these animals were implanted with EEG electrodes. Cortical EEG was recorded for 30 min from unanesthetized, unrestrained pups at P7, P14, and P21, and in separate groups, brain tissues were collected at these ages for ex-vivo MRI analysis (9.4 T) and Golgi–Cox staining (to assess neuronal morphology) in the motor cortex. ResultsPostnatal inflammation was associated with reduced cortical pyramidal neuron arborization from P7, P14, and P21. These changes were associated with dysmature EEG features (e.g., persistence of delta waveforms, higher EEG amplitude, reduced spectral edge frequency) at P7 and P14, and higher EEG power in the theta and alpha ranges at P21. By contrast, there were no changes in cortical DTI or NODDI in LPS rats at P7 or P14, while there was an increase in cortical fractional anisotropy (FA) and decrease in orientation dispersion index (ODI) at P21. ConclusionsEEG may be useful for identifying the early evolution of impaired cortical development after early life postnatal systemic inflammation, while DTI and NODDI seem to be more suited to assessing established cortical changes.

Brain effects of mild COVID-19 in healthy young adults: A pilot study

Rationale and objectivesThis study examined the brain effects of mild severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection which are incompletely understood. Our objective was to ascertain within-person changes associated with mild coronavirus disease 2019 (COVID-19) in otherwise healthy adults. Materials and methodsWe leveraged existing pre-pandemic baseline neuroimaging and neurocognitive data, and collected follow-up data from uninfected controls and individuals with prior mild COVID-19, during December 2020 and January 2021, when vaccines were not yet available. We compared change during follow-up in patients (n = 5) versus controls (n = 15). ResultsWe identified a decrease of intracellular volume fraction (ICVF), decrease of isotropic volume fraction (ISO) and decrease of orientation dispersion index (ODI) in multiple inferior frontal regions of interest in COVID-19 patients; this longitudinal change was significantly different from the control group which demonstrated increases in equivalent measures. This pattern suggests injury with neuronal loss and/or inflammation as underlying mechanisms. Neurocognitive studies identified a pattern of cognitive decline (processing speed, executive function, verbal learning, working memory) in patients, that did not reach significance. ConclusionOur pilot data suggests that mild COVID-19 may result in brain pathology and impact neurocognitive function in younger adults in a manner parallel to prior findings in older individuals. Though findings may not generalize to other SARS-CoV-2 variants, larger longitudinal studies of mild COVID-19 should be undertaken to understand the potential clinical implications of these findings over the longer term.

On weighted Amarendra distribution with properties and applications

In this paper some statistical properties including nature of hazard function, mean residual life function, and moments based descriptive statistical constants including coefficient of variation, skweness, kurtosis and index of dispersion of the weighted Amarendra distribution has been discussed. Two methods of estimation, namely, maximum likelihood estimation and maximum product spacing estimation have been discussed. The simulation study has been presented to know the consistency of the estimator of parameters given by the two methods of estimation. Confidence intervals of the parameters are given. The goodness of fit of the distribution has been demonstrated with two real lifetime datasets and the goodness of fit shows that weighted Amarendra distribution provides better fit over weighted Pratibha distribution, weighted Komal distribution, weighted Lindley distribution, weighted Garima distribution, weighted Sujatha distribution, weighted Akash distribution and Gamma distribution.

Examining the Stability and Predictive Utility of Across- and Within-Domain Intra-Individual Variability in Mild Cognitive Impairment.

Dispersion is a form of intra-individual variability across neuropsychological tests that has been shown to predict cognitive decline. However, few studies have investigated the stability and predictive utility of both across- and within-domain dispersion. The current study aims to fill these gaps in the literature by examining multiple indices of dispersion in a longitudinal clinical sample of individuals diagnosed with mild cognitive impairment (MCI) at baseline. Two hundred thirty-eight MCI patients from a cognitive disorders clinic underwent testing at baseline and after approximately 1.5 years. Linear regression was used to examine whether baseline across- and within-domain dispersion predicted cognitive decline in individuals whose diagnostic classification progressed to dementia (i.e., MCI-Decline) and those who retained an MCI diagnosis at follow-up (i.e., MCI-Stable). Cognitive decline was operationalized dichotomously using group status and continuously using standardized regression-based (SRB) z-scores. Dispersion variables at baseline and follow-up were positively correlated in both groups, with the exception of within-domain executive functioning and language dispersion in the MCI-Decline group. None of the dispersion variables predicted diagnostic conversion to MCI. Using SRB z-scores, greater across-domain dispersion predicted greater overall cognitive decline at follow-up, but this was not the case for within-domain variables with the exception of visuospatial skills. Results suggest that across- and within-domain dispersion are relatively stable across time, and that across-domain dispersion is predictive of subtle cognitive decline in patients with MCI. However, these results also highlight that findings may differ based on the tests included in dispersion calculations.

Spatio-temporal clustering of extreme floods in Great Britain

ABSTRACT Quantifying the tendency of flood events to demonstrate clustering in time and space is crucial for flood risk assessments. We analyse the temporal (TC) and spatial (SC) coherence of floods in 554 catchments over Great Britain. TC was assessed using the dispersion-index and Conway-Maxwell-Poisson regression, with both methods applied to aggregation windows of 1–5 years. SC was investigated using the flood susceptibility index. Results show that i) most of the UK peak floods are overdispersed and ii) a positive relationship exists between winter mean North Atlantic Oscillation anomalies and the annual number of peak floods across western Britain. The susceptibility to widespread floods is higher for the southeast parts of Britain and for the Clyde-Forth valleys, and it increases with catchment permeability and with the influence of lakes/reservoirs. These findings are relevant to enhance existing flood hazard estimation methods and, in turn, will lead to more realistic flood risk quantification.

Polyacrylate epoxide oligomers with robust photo‐crosslinked and thermomechanical properties enabled by controlling copolymerizing molecular weight distribution

AbstractPhoto‐triggering curing coatings have advantages of improving production efficiency, reducing pollution emissions, and contributing to green environmental protection. However, making the trade‐off between appropriate viscosity and UV‐curing properties in a high‐performing polymer system remains a formidable challenge. In this paper, firstly, a series of acrylate copolymer oligomers (named as PAAR) were synthesized using methyl methacrylate (MMA), butyl acrylate (BA), and glycidyl methacrylate (GMA), then methacrylic acid (MAA) was grafted utilizing the reaction between carboxyl group in MAA with epoxy group in oligomer to introduce double bonds. By adjusting the oligomer molecular weight to control the viscosity and changing the GMA ratio to obtain suitable double bonds content. As a result, the number molecular weight (Mn) of the thus‐obtained PAAR oligomers were less than 3000 Da, and the polymer dispersity indexes (PDI) were lower than 1.8. Photo‐polymerization kinetics revealed that the coating prepared using the oligomers could be fully cross‐linked by UV light triggering within 60 s, achieving a high transparency of 90% along with favorable thermal and mechanical properties. Furthermore, it was confirmed that the water resistance on the surface of the cured films and hydrophobicity were more influenced by the presence of hydroxyl groups.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study

BackgroundNew daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH.MethodsThis study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson’s correlation analysis between the NODDI indicators and clinical characteristics.ResultsCompared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction.ConclusionsOur research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.