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Ulcerative colitis (UC) is a chronic non-sp ecific inflammatory disease of the colorectal mucosa. Researchers have associated UC onset with familial genetics, lifestyle behavior, inflammatory immune factors, intestinal microbiota, and the integrity of the intestinal mucosal barrier. The primary therapeutic interventions for UC consist of pharmacological management to control inflammation and promote mucosal healing and surgical interventions. The available drugs effectively control and decelerate the progression of UC in most patients; nonetheless, their long-term administration can exert adverse effects and influence the therapeutic effect. Plant essential oils (EOs) refer to a group of hydrophobic aromatic volatile substances. EOs have garnered considerable attention in both domestic and international research because of their anti-inflammatory, antibacterial, and antioxidant properties. They include peppermint, peppercorns, rosemary, and lavender, among others. Researchers have investigated the role of EOs in medicine and have elucidated their potential to mitigate the detrimental effects of UC through their anti-inflammatory, antioxidant, antidepressant, and anti-insomnia properties as well as their ability to regulate the intestinal flora. Furthermore, EOs exert minimal toxic adverse effects, further enhancing their appeal for therapeutic applications. However, these speculations are based on theoretical experiments, thereby warranting more clinical studies to confirm their effectiveness and safety. In this article, we aim to provide an overview of the advancements in utilizing natural medicine EOs for UC prevention and treatment. We will explore the potential pathogenesis of UC and examine the role of EOs therapy in basic research, quality stability, and management specification of inadequate EOs for UC treatment. We intend to offer novel insights into the use of EOs in UC prevention and management. [ABSTRACT FROM AUTHOR]

The increasing use of molybdate has raised concerns about its potential toxicity in humans. However, the potential toxicity of molybdate under the current level of human exposure remains largely unknown. Endogenous metabolic alterations that are caused in humans by environmental exposure to pollutants are associated with the occurrence and progression of many diseases. This study exposed eight-week-old male C57 mice to sodium molybdate at doses relevant to humans (0.01 and 1 mg/kg/day) for eight weeks. Inductively coupled plasma mass spectrometry (ICP-MS) and ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS) were utilized to assess changes in urine element levels and serum metabolites in mice, respectively. A total of 838 subjects from the NHANES 2017–2018 population database were also included in our study to verify the associations between molybdenum and cadmium found in mice. Analysis of the metabolome in mice revealed that four metabolites in blood serum exhibited significant changes, including 5-aminolevulinic acid, glycolic acid, l-acetylcarnitine, and 2,3-dihydroxypropyl octanoate. Analysis of the elementome revealed a significant increase in urine levels of cadmium after molybdate exposure in mice. Notably, molybdenum also showed a positive correlation with cadmium in humans from the NHANES database. Further analysis identified a positive correlation between cadmium and 2,3-dihydroxypropyl octanoate in mice. In conclusion, these findings suggest that molybdate exposure disrupted amino acid and lipid metabolism, which may be partially mediated by molybdate-altered cadmium levels. The integration of elementome and metabolome data provides sensitive information on molybdate-induced metabolic disorders and associated toxicities at levels relevant to human exposure. [ABSTRACT FROM AUTHOR]

Detection of safety signals based on multiple comparisons of adverse events (AEs) between two treatments in a clinical trial involves evaluations requiring multiplicity adjustment. A Bayesian hierarchical mixture model is a good solution to this problem as it borrows information across AEs within the same System Organ Class (SOC) and modulates extremes due merely to chance. However, the hierarchical model compares only the incidence rates of AEs, regardless of severity. In this article, we propose a three-level Bayesian hierarchical non-proportional odds cumulative logit model. Our model allows for testing the equality of incidence rate and severity for AEs between the control arm and the treatment arm while addressing multiplicities. We conduct simulation study to investigate the operating characteristics of the proposed hierarchical model. The simulation study demonstrates that the proposed method could be implemented as an extension of the Bayesian hierarchical mixture model in detecting AEs with elevated incidence rate and/or elevated severity. To illustrate, we apply our proposed method using the safety data from a phase III, two-arm randomized trial. [ABSTRACT FROM AUTHOR]

In clothing e-commerce, the challenge of optimally recommending clothing that suits a user's unique characteristics remains a pressing issue. Many platforms simply recommend best-selling or popular clothing, without taking into account important attributes like user's face color, pupil color, face shape, age, etc. To solve this problem, this paper proposes a personalized clothing recommendation algorithm that incorporates the established 4-Season Color System and user-specific biological characteristics. Firstly, the attributes and colors of clothing are classified by Fnet network, that can learn disjoint label combinations and mitigate the issue of excessive labels. Secondly, on the basis of the 4-Season Color System, the user's face color model is trained by combined MobileNetV3_DTL, which ensures the model's generalization and improves the training speed. Thirdly, user's face shape and age are divided into different categories by an Inception network. Finally, according to the users' face color, age, face shape and other information, personalized clothing is recommended in a coarse-to-fine manner. Experiments on five datasets demonstrate that the algorithm proposed in this paper achieves state-of-the-art results. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) can be affected by cloud change, while cloud‐induced bias errors in ET change remain poorly understood. Here we evaluated seven ET data sets from satellite microwave and optical models, atmospheric reanalysis and land surface models over East Asia. Results showed that although the data sets estimated ET changes overall well under mild cloud increase, all of them had a systematic overestimation (by 73.8%–159.8%) and deteriorated capability of capturing ET change under heavy cloud increase, especially over dense vegetation with large cloud cover. Overestimated incident solar radiation under clouds contributed to the deteriorated performances of ET. Cloud‐induced change in radiation and its errors played larger role in summer ET change over densely vegetated lands, while those in air temperature and relative humidity were dominant jointly over grass and barren lands. These results can serve as a reference for improving ET models and their forcing inputs under clouds. Plain Language Summary: The change of cloud cover affects terrestrial evapotranspiration (ET), which is a fundamental process in the interaction between land and the atmosphere. ET can be estimated from satellite observations, reanalysis data sets and land surface models. Knowing the cloud‐induced errors in the estimation of ET and its drivers can be very helpful for us to improve the ET modeling under the changing cloud conditions. In this study, we evaluated seven ET data sets and their forcing data from clear sky to cloudy sky conditions over East Asia. We quantified the importance of incident radiation, air temperature and relative humidity inputs in ET data sets under cloudy sky using a machine learning algorithm. Our findings revealed that all ET data sets were overestimated systematically under heavy cloud increase. Cloud‐induced change in radiation was more important over densely vegetated lands, while air temperature and relative humidity played larger roles over grass and barren lands. The result highlights the importance of cloud effects on ET estimations. Key Points: Seven evapotranspiration (ET) data sets from satellite microwave and optical models, reanalysis and land surface models were evaluated under cloud changeAll data sets overestimated the absolute ET values and cloud‐induced changes in ET under heavy cloud increase conditionsSummer ET change under clouds was dominated by radiation in the southern dense vegetation, but by temperature and humidity in grass lands [ABSTRACT FROM AUTHOR]

Understanding the change in hydrological response due to urban dynamics is important for better flood preparedness and future sustainable urban planning. This study investigated the influence of urban land cover change on spatiotemporal changes in flood peak discharge and flood volume within a rapidly urbanizing catchment located in Beijing, China. We used Landsat satellite data ranging from 1986 to 2017 to monitor and quantify urban growth. Moreover, the Hydrological Modeling System (HEC-HMS) coupled with meteorological data was utilized to examine the impact of urban growth on hydrological responses. The results revealed that major changes in land use/cover (LULC) were detected in the urban landscape, which increased from 25.22% to 65.48% of the total catchment area, while agricultural land decreased from 64.85% to 25.28% during 1986–2017. The flood peak discharge and flood volume average of the three rainstorms events reached 7.02% and 11.93%, respectively. Furthermore, the changes in flood peak discharge and flood volume were more obvious at the sub-catchment scale. These findings indicate that urban growth enhanced the possible flooding risk in the study catchment. This study improves the understanding of the isolated impacts of urbanization on flooding and provides essential information for sustainable urban planning. [ABSTRACT FROM AUTHOR]

Direct fluorination utilizing F2/N2 was confirmed to be one of the most efficient approaches to decorate graphene. The conventional opinion holds the view that direct fluorination is a molecular fluorination process, which often makes for the preparation of fluorinated graphene (FG) with heterogenous fluorine distribution. Herein, a fluorination strategy with an atomic fluorination mechanism was developed to modify graphene through thermal predissociation of molecular fluorine into atomic fluorine. By means of theoretical simulation, the thermal dissociation process of F2 was disclosed, and dissociation temperature was determined to be about 140–180 °C. Consequently, an ingenious thermal annealing at 180 °C was employed to splitting F2 into fluorine atoms before the fluorination reaction. Distinguished from the traditional molecular fluorination, atomic fluorination using fluorine atoms enables the preparation of FG with a higher fluorination degree and relatively homogeneous fluorine distribution because of the zero-energy barrier reaction, which was validated by aberration-corrected transmission electron microscopy directly. Furthermore, FG with homogeneous fluorine distribution possesses several advantages over the heterogenous fluorine distribution samples including higher thermal stability, higher thermal conductivity, and better electrical insulation, thereby demonstrating the possibility of their application in the field of thermal conduction and electrical insulation for microelectronics. We believe that this unique fluorination approach and corresponding mechanism can be extended to other carbon materials. [ABSTRACT FROM AUTHOR]

Understanding the cloud impact on forest evapotranspiration (ET) is crucial for studying the interaction of vegetation‐cloud‐atmosphere. Combining long‐term (2003–2010) satellite passive microwave observations and in‐situ measurements, a non‐linear response of canopy‐scale ET to cloud increase was found at a temperate forest in Northeast China. As cloud increased, an initial enhancement (4%–10%) in ET occurred under less cloudy sky, while a significant reduction (>20%) in ET occurred under more cloudy sky. The phenomenon existed under both high and low vegetation water content (VWC) indicated by satellite microwave emissivity difference vegetation index (EDVI). Analysis showed that this was the combined effect from the enhancement (5%–30%) in evaporative fraction (EF) and the reduction (5%–50%) in net radiation under cloud increase. Decoupling analysis based on coefficients (ρ) of path analysis model showed that enhanced EF (ρ > 0.61) rather than radiation (ρ < 0.47) dominated the ET enhancement under less cloudy sky, while the control of reduced radiation became stronger (ρ > 0.63) and could not be compensated by increased EF (ρ < 0.48) under more cloudy sky. EF enhancement under clouds was strongly correlated with the decline in canopy resistance (Rs) which was dominated by vapor pressure deficit (VPD). Higher VWC increased ET via reducing Rs and enlarging EF. This positive effect of VWC was more noticeable under less cloudy sky. Associated mechanisms could be related to the dynamic controls of plant physiology and environmental conditions induced by VWC and clouds. This study highlighted the dynamic effect of clouds and VWC on forest ET and improved our knowledge of vegetation‐cloud interactions. Key Points: The non‐linear response of ET to cloud increase results from increase of evaporative fraction and reduction in net radiationVegetation water content (VWC) significantly affects ET status under various cloud conditions, particularly under clear skyLower VWC can restrain ET under clouds by increasing canopy resistance and lowering evaporative fraction [ABSTRACT FROM AUTHOR]

This paper presents 3–4 and 38–40 GHz wideband channel characteristics for industrial internet‐of‐things (IIoT) scenario based on measurements. The channel measurement equipment applied in the measurements consists of a programmable vector network analyzer and necessary auxiliaries. An extensive amount of data in line‐of‐sight (LoS) and non‐line‐of‐sight (NLoS) scenarios is collected with omnidirectional antennas in both transmitter and receiver ends. With the Space‐Alternating Generalized Expectation‐maximization (SAGE) algorithm, the multipath components (MPCs) of the received signals are extracted to calculate the channel model parameters, for example, channel gain coefficient, delay spread, and Ricean K factor. By studying the statistical characteristics of these parameters, a stochastic channel model in IIoT scenario is initially established and compared with the existing indoor channel models. Moreover, the distinctive characteristics of channel parameters in the millimeter wave band and sub‐6 GHz band in the IIoT scenario are demonstrated. Plain Language Summary: Usually, the industrial environments are complicated and variable, which makes the communications in factory more difficult than those in general indoor scenarios. Hence, more information about the characteristics of the radio propagation in industrial scenarios is needed. This work presents 3–4 and 38–40 GHz wideband channel characteristics for industrial internet‐of‐things (IIoT) scenarios based on measurements, which is helpful to the design of the communication systems and the installation of low‐latency, high‐speed, high‐stability communication facilities on automation production equipment in industrial environments. Key Points: The 3–4 and 38–40 GHz wideband channel models in an industrial internet‐of‐things (IIoT) scenario are presentedThe variance of shadow fading in the IIoT scenario is larger than that in general indoor scenariosThe values of K factors in the IIoT scenario demonstrate significant dependence on the premises of the Rx [ABSTRACT FROM AUTHOR]

The melting and crystallization behaviors, morphology, and mechanical properties of polypropylene (PP)/surface-treated calcium sulfate (CaSO4) whisker (T-CSW), β-PP/T-CSW, and β-PP/polypropylene- graft-maleic anhydride (PP-g-MAH)/T-CSW composites had been investigated via differential scanning calorimetry (DSC), wide angle X-ray diffraction (WAXD), polarized light microscopy (PLM), scanning electron microscopy (SEM), and mechanical tests. We found that T-CSW was an α-nucleating agent and increased the crystallization temperatures of PP, but PP-g-MAH and high loadings of T-CSW had weakly negative effects on the crystallization rates of PP. The T-CSW restrained the formation of β-spherulites, and the spherulitic size decreased in the composites. PP-g-MAH improved the compatibility and adhesion between T-CSW and the matrix. The notched impact strength was improved, and the tensile strength was enhanced at low levels of T-CSW, while the flexural modulus was weakened for β-PP/T-CSW and β-PP/PP-g-MAH/T-CSW composites versus PP/T-CSW composites. POLYM. COMPOS., 37:2121-2132, 2016. © 2015 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

β-Polypropylene composites containing talc treated by titanate coupling agent (T-talc) and maleic anhydride grafted PP (PP- g-MAH) were prepared by melt compounding. The crystallization, morphology, and mechanical properties of the composites were investigated by means of differential scanning calorimetry (DSC), wide angle X-ray diffraction (WAXD), polarized light microscopy (PLM), scanning electron microscopy (SEM), and mechanical tests. It is found that β nucleating agent (NT-C) induces the formation of β-phase but T-talc suppresses the formation of β-modification. Both NT-C and T-talc greatly decrease the spherulitic size of PP. PP- g-MAH has a weak restraint on the formation of β-form PP but it improves the compatibility between T-talc and PP matrix. Izod notched impact strength of β-PP/T-talc composite is higher than that of PP/T-talc composite at each loading, indicating the toughening effect of β-PP. Incorporation of PP- g-MAH into β-PP/T-talc composite further increases the impact strength when T-talc concentration is below 2.5 wt %. The non-isothermal crystallization kinetics of β-PP composites is well described by Jeziorny's and Mo's methods, respectively. The activation energies (Δ E) of non-isothermal crystallization were calculated by Kissinger method. It is found that NT-C and T-talc accelerate the crystallization rate of PP but PP- g-MAH has a slightly negative influence on the crystallization rate of β-PP. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013 [ABSTRACT FROM AUTHOR]

β-Polypropylene composites containing calcium carbonate treated by titanate coupling agent (T-CaCO3) and maleic anhydride grafted PP (PP- g-MAH) were prepared by melt compounding. The crystallization, morphology and mechanical properties of the composites were investigated by means of differential scanning calorimetry, wide-angle X-ray diffraction, polarized light microscopy, scanning electron microscopy and mechanical tests. It is found that both T-CaCO3 and NT-C are able to induce the formation of β-phase, and NT-C greatly increases the β content and decreases the spherulitic size of PP. PP- g-MAH facilitates the formation of β-form PP and improves the compatibility between T-CaCO3 and PP. Izod notched impact strength of β-PP/T-CaCO3 composite is higher than that of PP/T-CaCO3 composite, indicating the synergistic toughening effect of T-CaCO3 and β-PP. Incorporation of PP- g-MAH into β-PP/T-CaCO3 composite further increases the content of β-crystal PP and improves the impact strength and tensile strength when T-CaCO3 concentration is below 5 wt%. The nonisothermal crystallization kinetics of β-PP composites is well described by Jeziorny's and Mo's methods. It is found that NT-C and T-CaCO3 accelerate the crystallization rate of PP but the influence of PP- g-MAH on crystallization rate of β-PP composite is marginal. POLYM. COMPOS., 2012. © 2012 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]