Cuscuta chinensis have a significant regulatory effect on plant growth, but the response mechanism of functional traits to the parasitism of C. chinensis and the trade-off relationship between traits and hyperspectral characteristics are not clear. We investigated the functional trait response and hyperspectral characteristics of Euonymus japonicus, the most common urban hedge plant in China, to the parasitism of C. chinensis. The results showed that the parasitism of C. chinensis led to the difference of leaf functional traits: the leaf thickness, stomatal density, and leaf dry matter content were significantly increased, whereas the leaf area, leaf weight, specific leaf area, chlorophyll content index, and leaf tissue density were significantly decreased. Notably, the parasitism of C. chinensis changed the spatial distribution pattern of stomata and promoted the stomata to be evenly distributed. Furthermore, the spectral reflectance of leaves treated with the parasitism of C. chinensis tended to increase. The parasitism of C. chinensis led to the \"blue shift\" of hyperspectral reflectance of leaves. There was a significant correlation between spectral parameters and leaf functional traits, and leaf biomass accounted for 83% of the variation in reflectance of the water stress band. In general, the parasitism of C. chinensis determines the strategic way of plant utilization of resources and affects the change of plant strategy by affecting the difference of traits. Urban plants were more inclined to invest resources in nutrient storage capacity at the expense of resources investment in photosynthetic capacity and defense mechanism. The plant ecological strategy changed from resource acquisition to resource conservation. This finding comes up with a new strategy that urban tree species can modify the plasticity of functional traits for survival and growth under the interference of parasitic plants.

Human milk phospholipids (HMPLs) play an indispensable role in the neurodevelopment and growth of infants. In this study, a total of 37 phospholipid fatty acid (PLFA) species and 139 phospholipid molecular species were detected from human milk and other natural phospholipid sources (including 5 animal-derived species and 2 plant species). Moreover, a similarity evaluation model for HMPLs was established, including phospholipid classes, PLFAs, and phospholipid molecular species, to evaluate their natural substitutes. The closest scores for HMPL substitute in these three dimensions was 0.89, 0.72, and 0.77, which belonged to mare milk, goat milk, and camel milk, respectively. The highest comprehensive similarity score was obtained by camel milk at 0.75, while the lowest score was observed in soybean phospholipid (0.22). Therefore, these results not only monitored the stereochemical structure of HMPLs and their substitutes, but also further provided new insights for the development of infant formulae.

With the tourism industry continuing to boom, the importance of tourism mascots in promoting and publicizing tourism destinations is becoming increasingly prominent. Three core dimensions, market trend, appearance design, and audience feedback, are numerically investigated for deeply iterating tourism mascot design. Further, a subjective and objective evaluation weighting model based on the hierarchical analysis method (AHP) and entropy weighting method is proposed, aiming to utilize the advantages of these methods and ensure the entireness and correctness of results. Taking the mascots of six famous tourist attractions in Xi\'an as an example, the feasibility and effectiveness of the evaluation model are verified. Data analysis and modeling results confirm that the three core evaluation indexes of scalability, innovation, and recommendation should be focused on in the design of tourism mascots in the three dimensions of market trends, appearance design, and audience feedback. The evaluation index scores are 0.1235, 0.1170, and 0.1123, respectively, which further illustrates the priority of mascot design. The evaluation model constructed by the research provides decision-makers with a comprehensive evaluation tool from the perspective of tourist experience, and also effectively assists the optimization process of mascot design. In addition, the model has good versatility and adaptability in structural design and evaluation logic and can be widely used in the optimization and evaluation research of brand mascots.

UNASSIGNED: The prognosis of stroke patients is greatly threatened by malnutrition. However, there is no model to predict the risk of malnutrition in hospitalized stroke patients. This study developed a predictive model for identifying high-risk malnutrition in stroke patients.
UNASSIGNED: Stroke patients from two tertiary hospitals were selected as the objects. Binary logistic regression was used to build the model. The model\'s performance was evaluated using various metrics including the receiver operating characteristic curve, Hosmer-Lemeshow test, sensitivity, specificity, Youden index, clinical decision curve, and risk stratification.
UNASSIGNED: A total of 319 stroke patients were included in the study. Among them, 27% experienced malnutrition while in the hospital. The prediction model included all independent variables, including dysphagia, pneumonia, enteral nutrition, Barthel Index, upper arm circumference, and calf circumference (all p < 0.05). The AUC area in the modeling group was 0.885, while in the verification group, it was 0.797. The prediction model produces greater net clinical benefit when the risk threshold probability is between 0% and 80%, as revealed by the clinical decision curve. All p values of the Hosmer test were > 0.05. The optimal cutoff value for the model was 0.269, with a sensitivity of 0.849 and a specificity of 0.804. After risk stratification, the MRS scores and malnutrition incidences increased significantly with escalating risk levels (p < 0.05) in both modeling and validation groups.
UNASSIGNED: This study developed a prediction model for malnutrition in stroke patients. It has been proven that the model has good differentiation and calibration.

The paper discusses the concept of a proprietary decision-making model that allows for determining whether the planned development in areas not protected by flood embankments and at risk of flooding can be shaped in a safe manner. The model was used to evaluate the possibility of shaping the development in flood-risk areas on the example of one of the types of Olęder villages - a dispersed village located in the floodplains of the Warta River (western Poland). So far, there has been no comprehensive evaluation method supporting proper spatial planning for flood-risk areas. The use of multi-criteria analysis methods enabled to specify the key criteria of this evaluation, which form the basis of the decision-making support system. Additionally, the elaborated method enables to determine whether the localities under study can retain their current functional nature and if there is a potential for further spatial development based on the characteristics of an Olęder village. The presented methodology can be easily adapted to other cultural areas located in countries with different levels of development, traditions, landscape or climate.

Psoriasis is a common inflammatory skin disease that seriously affects the patient\'s quality of life. The diagnosis of psoriasis is mainly based on clinical and pathological features, and the assessment depends on the psoriasis area and severity index (PASI). However, there are few reliable and accurate evaluation methods to assess lesion severity and therapeutic effects. This work identified 17 model genes from GEO datasets and established 6 psoriasis evaluation models by LASSO regression, linear regression, and random forest separately. Models were trained and evaluated in different GEO datasets. All 6 models accurately classified psoriatic lesions and non-lesional skin in training and testing data, and showed good AUC. In biologics-treated samples, the model scores were positively correlated with the severity of lesions and negatively correlated with treatment length. Thus, models have the potential to assess the therapeutic effects. In addition, the expression of model genes was examined in keratinocytes, skin of IMQ-induced psoriatic mice, and lesions of psoriasis patients. The RNA and protein levels of model genes increased in cytokine-stimulated keratinocytes and psoriatic lesions as expected. This work provides new methods to assess the lesion severity and therapeutic effects of biologics in psoriasis.

Ni-Mn@KL ozone catalyst was prepared for the efficient treatment of reverse osmosis membrane concentrates. The working conditions and reaction mechanism of the ozone-catalyzed oxidation by Ni-Mn@KL were systematically studied. Then, a comprehensive CRITIC weighting-coupling coordination evaluation model was established. Ni-Mn@KL was characterized by scanning electron microscopy, BET, X-ray diffraction, X-ray photoelectron spectroscopy, energy-dispersive spectrometry, and X-ray fluorescence spectrometry and found to have large specific surface area and homogeneous surface dispersion of striped particles. Under the optimum working conditions with an initial pH of 7.9 (raw water), a reaction height-to-diameter ratio of 10:1, an ozone-aeration intensity of 0.3 L/min, and a catalyst filling rate of 10%, the maximum COD removal rate was 60.5%. Free-radical quenching experiments showed that OH oxidation played a dominant role in the Ni-Mn@KL-catalyzed ozone-oxidation system, and the reaction system conformed to the second-order reaction kinetics law. Ni-Mn@KL catalysts were further confirmed to have good catalytic performance and mechanical performance after repeated utilization. PRACTITIONER POINTS: Ni-Mn@KL catalyst can achieve effective treatment of RO film concentrated liquid. High COD removal rate of RO membrane concentrated liquid was obtained at low cost. Ni-Mn@KL catalyst promotes ozone decomposition to produce ·OH and O2 -· oxidized organic matter. The Ni-Mn@KL catalyst can maintain good stability after repeated use. A CRITIC weight-coupling coordination model was established to evaluate the catalytic ozonation.

We aimed to obtain the optimal formula for human milk fat substitute (HMFS) through a combination of software and an evaluation model and further verify its practicability through an animal experiment. The results showed that a total of 33 fatty acid (FA) and 63 triglyceride (TAG) molecular species were detected in vegetable oils. Palmitic acid, oleic acid, linoleic acid, 18:1/16:0/18:1, 18:2/16:0/18:2, 18:1/18:1/18:1 and 18:1/18:2/18:1, were the main molecular species among the FAs and TAGs in the vegetable oils. Based on the HMFS evaluation model, the optimal mixed vegetable oil formula was blended with 21.3% palm oil, 2.8% linseed oil, 2.6% soybean oil, 29.9% rapeseed oil and 43.4% maize oil, with the highest score of 83.146. Moreover, there was no difference in the weight, blood routine indices or calcium and magnesium concentrations in the feces of the mice between the homemade mixed vegetable oil (HMVO) group and the commercial mixed vegetable oil (CMVO) group, while nervonic acid (C24:1) and octanoic acid (C8:0) were absorbed easily in the HMVO group. Therefore, these results demonstrate that the mixing of the different vegetable oils was feasible via a combination of computer software and an evaluation model and provided a new way to produce HMFS.

The growing generation of construction and demolition waste (CDW) has emerged as a prominent challenge on global environmental agendas. However, the effectiveness of CDW management (CDWM) strategies varies among cities. Existing literature predominantly evaluates the effectiveness of CDWM at the project level, offering a localized perspective that fails to capture a city\'s comprehensive CDWM profile. This localized focus has certain limitations. To fill this gap in city-scale evaluations, this study introduces a novel model for assessing CDWM effectiveness at the municipal level. An empirical investigation was conducted across 11 cities within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) to operationalize this model. The model defines five distinct levels of CDWM effectiveness. Findings indicate that Hong Kong consistently achieves the highest level (level I), while the majority of cities fall within levels III and IV. This pattern suggests that CDWM effectiveness in the GBA is moderately developed, with uneven progress in CDW management outcomes and supporting systems. Essentially, there is a lack of synchronous development of CDWM results and guarantee systems. The proposed evaluation model enriches existing CDWM research field and offers a framework that may inform future studies in other countries.

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