Search

A series of new 2-cyanopyrrolidine derivatives with constrained imidazolidin ring were synthesized, Their structures were confirmed by 1H NMR spectroscopy and/or mass spectrometry, and their activities were evaluated in vitro. They were proven to possess submicromolar inhibitory activities against dipeptidyl peptidase IV. [ABSTRACT FROM AUTHOR]

A repellent for rats named DC has been successfully synthesized from natural capsaicin and 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) via a one-pot procedure. The chemical structure of obtained DC is confirmed by Fourier transform infrared (FTIR), Raman and nuclear magnetic resonance (NMR). Then DC was incorporated into ethylene vinyl acetate copolymer (EVA) by blending, to endow EVA with rat proof property and present the advantage of non-lethal. The influence of DC on the structure and properties of EVA is investigated systematically by theoretical calculations and various measurements. Thermogravimetric analysis (TGA) reveals that the incorporation of 4 wt% DC into EVA can significantly enhance the char residue yield from 2.80 wt% to 6.84 wt%. In addition, limiting oxygen index (LOI) and the char residues analysis suggest that DC could facilitate the formation of char layers, resulting in the improvement of synergistic flame retardancy for EVA/DC compounds. This work provided novel insights into the preparation of highly efficient non-lethal repellent for rats and its potential application for polymer materials. • A novel non-lethal rat repellent was synthesized from natural capsaicin and DOPO. • DC exhibits the synergistic flame retardant effect for EVA matrix. • DC shows good ability of formation char layers and compatibility with EVA matrix. • The structures and properties of EV A/DC were investigated by MD simulation. [ABSTRACT FROM AUTHOR]

Clarifying the relationship between economic development and human well-being is conducive to promoting high-quality economic development. This study focused on 16 prefecture-level cities in the Qinghai-Xizang Plateau region. The critic weighting method assessed the 2007–2018 human well-being index (HWI). The Tapio decoupling model allowed the study of the human well-being decoupling state. Finally, the drivers of decoupling between economic development and human well-being were analyzed using the Logarithmic Mean Divisia Index method. The results indicated that (1) almost all cities in the study region had an upward 2007–2018 HWI trend, but there were significant differences in growth magnitude and change trend. (2) Economic development and human well-being in the study region in 2007–2018 had expansion negative decoupling, thus, human well-being increased with economic growth, but not as fast as gross domestic product. 9 cities in 2007 showed weak decoupling, expansion connection, and expansion negative decoupling, increasing to 13 cities by 2018, indicating that human well-being development gradually improved from 2007 to 2018. (3) For most cities, the economic scale effect was the most influential factor in the decoupling of economic development and human well-being. Therefore, this study provided policy recommendations for decoupling economic development and human well-being. [ABSTRACT FROM AUTHOR]

• Hierarchical MPC scheme is proposed to regulate the oxygen stoichiometry of the FC. • Vehicle speeds are forecast based on the proposed deep BP neural network model. • Forecasted disturbances are implanted into the states predication to solve the MPC. • O 2 stoichiometry control average error in a driving cycle was mostly less than 0.3%. Fuel cells are a promising solution for increasing driving range of electric vehicles. To guarantee the high efficiency and stable operation of fuel cells, the effective regulation of oxygen and hydrogen reactants is needed. During varied driving conditions, in which the drastic current demand changes may result in insufficient reactant, the fuel cell can even be damaged. In this paper, a hierarchical model predictive control (HMPC) strategy is proposed based on the deep learning for vehicle speed predictions. Speed variation predictions are considered by the MPC to regulate the air supply system and preventing oxygen starvation in the fuel cell stack. The problems of fuel cell oxygen stoichiometry control are, first, stated with the preliminary energy management description as well as with the limitations of the traditional MPC. The deep learning Back Propagation (BP) neural network was then designed as the first-level predictor to forecast the vehicle speed by training with integrated driving cycles, and predict the fuel cell current based on its cathode flow model. Subsequently, the second-level MPC used the current disturbance prediction and filling is introduced to regulate the oxygen mass flow. The simulation results for the MANHATTAN drive cycle demonstrated that the root mean square error (RMSE) for speed predictions was less than 1 km/h. Compared with the conventional MPC, HMPC offers better robustness in the face of influence from current changes induced by speed-variations, and the RMSE of the oxygen stoichiometry control was decreased by 63.37%. [ABSTRACT FROM AUTHOR]

• This study proposed an "ES-HWB" assessment method based on carbon flows. • This study revealed the relationships between ES and HWB. • The developments of ES and HWBare uneven. • The trends in impacts of different types of ES on HWB are different. • It is necessary to maintain a stable carbon flow in natural ecosystems. The current understanding of how ecosystem services flow affects human well-being is not sufficient. As an important component of the biogeochemical cycle, carbon flows through various natural and artificial processes. Therefore, carbon can be used as a research vector to explore the relationship between ecosystem services and human well-being. This study proposed a method for a quantitative assessment of "ecosystem services-human well-being" based on carbon flows. The assessment of the changes in ecosystem services and human well-being based on carbon in the Manas River Basin from 1990 to 2015 revealed the complex relationship between ecosystem services and human well-being. The results were as follows: (1) The development of ecosystem services was uneven, with increasing provisioning services and decreasing regulating, supporting and cultural services. (2) The basic materials for a good life and health in human well-being showed an upward trend, and the security indicator showed a downward trend. (3) The indicators of the basic materials for a good life and health were significantly positively correlated with provisioning services and were significantly negatively correlated with the other three services. Moreover, the internal structure of the security and health indicators were malformed. (4) Over time, the impact of provisioning services on the well-being indicators has gradually weakened, and the influence of regulating, supporting and cultural services has continually increased. In general, this study evaluated the complex relationship between ecosystem services and human well-being through carbon flow quantification, which can not only unify the dimensions for comparison, but also eliminate the impact of subjective factors to achieve a scientific nature. It is not only helpful to provide theoretical and practical basis for scientific management of Manas River Basin, but also to explore a larger scale and a wider area in the world through selecting indicators according to local conditions. [ABSTRACT FROM AUTHOR]

A hybrid power system consists of a fuel cell and an energy storage device like a battery and/or a supercapacitor possessing high energy and power density that beneficially drives electric vehicle motor. The structures of the fuel cell-based power system are complicated and costly, and in energy management strategies (EMSs), the fuel cell's characteristics are usually neglected. In this study, a variable structure battery (VSB) scheme is proposed to enhance the hybrid power system, and an incremental fuzzy logic method is developed by considering the efficiency and power change rate of fuel cell to balance the power system load. The principle of VSB is firstly introduced and validated by discharge and charge experiments. Subsequently, parameters matching of the fuel cell hybrid power system according to the proposed VSB are designed and modeled. To protect the fuel cell as well as ensure the efficiency, a fuzzy logic EMS is formulated via setting the fuel cell operating in a high efficiency and generating an incremental power output within the affordable power slope. The comparison between a traditional deterministic rules-based EMS and the designed fuzzy logic was implemented by numerical simulation in three different operation conditions: NEDC, UDDS, and user-defined driving cycle. The results indicated that the incremental fuzzy logic EMS smoothed the fuel cell power and kept the high efficiency. The proposed VSB and incremental fuzzy logic EMS may have a potential application in fuel cell vehicles. • A variable structure battery (VSB) is proposed to be integrated with the fuel cell. • The VSB was validated via experiment to show improved discharge/charge performance. • An incremental fuzzy logic EMS is applied based on fuel cell efficiency & lifespan. • Two EMSs for real-time simulations of fuel cell-based power system were compared. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ecosystem health (EH) and urbanization of the 260cities of China were assessed. • Urbanization and EH have been significantly and slightly improved respectively. • Urbanization mainly affected EH by changing the demand for ecosystem services. • The urban development type was mainly the medium-level balanced. • The drivers of the coupling relationship were explored using a Geodetector. Sustainable urban development is one of the most urgent problems worldwide, especially in China, which is in rapid urbanization. Reducing the negative impacts of urbanization and improving the relationship between the two have become research priorities. Using 260 cities in China as the research object, this study evaluated the level and temporal and spatial variation of urbanization and natural ecosystem health, explored the relationships between them, and influence mechanism of urbanization on natural ecosystem health. The results showed that the level of population urbanization, social urbanization, economic urbanization and land urbanization was significantly improved in 2000 compared to 2015, and the spatial distribution was higher in the east of China than in the west. The overall level of ecosystem health improved slightly throughout the same period, and its spatial distribution was higher in the north of China than in the south. In terms of the four dimensions of ecosystem health, the ecosystem services and organization were improved, and the ecological environment and elasticity were decreased. Urbanization mainly affected ecosystem health by changing the demand for the quantity and type of ecosystem services through the growth and aggregation of population. However, under the comprehensive effect of the four dimensions of urbanization on natural ecosystem health, the overall constraint intensity of urbanization on natural ecosystem health was relatively stable. The coupling and coordination level between urbanization and natural ecosystem health showed improvement from 2000 to 2015, and the social and economic factors were highly influential. According to the level of urbanization and natural ecosystem health, all cities were classified, which showed the urban development was mainly the medium-level balanced. On this basis, management suggestions were put forward for each type of city. By analyzing the action process and mechanism between urban development and natural ecosystem health, it provides a theoretical basis for in-depth understanding and coordinating the relationship of the urban ecological economy. [ABSTRACT FROM AUTHOR]

In the process of promoting hydrogen energy in the automotive field, priority should be given to addressing the safety concerns associated with its use. Ventilation is an important means to prevent the accumulation caused by hydrogen leakage in hydrogen fuel cell buses. The effects of the relative positions of two events on hydrogen dispersion in a space with multiple obstacles is studied to investigate the ventilation effect of the hydrogen fuel cell bus with seats in this paper. Two leakage scenarios, micro leakage rate of 1.4 g/s and severe leakage rate of 35.8 g/s, were set up in this study to investigate the distribution of hydrogen concentration. In these two scenarios, the primary vent is fixed at the top of the space, and the position of the secondary vent is changed. For micro leaks, the results indicate that ventilation scheme with auxiliary air vents located above the windshield can prevent the combustible area of hydrogen from continuously expanding after spreading to the top of the space and is most conducive to reducing the combustible area in the passenger cabin of the hydrogen fuel cell bus. For severe leaks with a hydrogen leakage rate of 38.5 g/s, the relative position of the dual vents has no significant effect on leaking hydrogen dispersion, and ventilation scheme in this study for the micro leakage is not sufficient to effectively reduce hydrogen concentration. The findings of this research hold significant reference value for advancing hydrogen energy within the automotive field. • Ventilation scheme with vent2 at uppermost of farthest side wall from leak has best effect with micro leakage. • For severe leakage (38.5 g/s), combustible areas spread rapidly, filling the space; vent 2's position has no significant effect. • Vent 2 at the bottom will no longer be a good ventilation scheme if there are obstacles in the bus. • The ventilation scheme with the primary vent at the rear cabin top and auxiliary vent above the windshield is most effective in reducing hydrogen leakage danger. [ABSTRACT FROM AUTHOR]

The operation of fuel cell (FC) necessitates ensuring safety across various aspects. The high coupling of state parameters poses challenges in pinpointing potential risks implicit in the state, rendering failures difficult to prevent. Existing FC failure analysis methods could qualitatively overview the evolution of failures or establish parameter thresholds, but fall short in safety assessment of the operating state. In this paper, a novel safety region method is developed. This method considers both safety and operational constraints concerning output voltage, air pressure, water transfer, and heat dissipation, translating these constraints into boundary surfaces. In the safety region, the safety distance serves as an indicator to characterize risk tolerance level, quantifying the safety of operating states and forming a series of safety contour maps. Finally, the power contours are depicted on the safety contour map, the optimal direction and goal are proposed to improve safety during FC operation. • A safety region for the fuel cell safety assessment is proposed first. • The safety region model considers a variety of fuel cell failures. • The safety distance represents the anti-interference ability of the system. • The safety region points out the optimal direction for safety improvement. [ABSTRACT FROM AUTHOR]

Thermal protection component and jet vane of aircraft with trajectory transfer ability are attacked by heat flow from variable direction. To understand the dynamic ablation characteristics, C/C-SiC-AlSi and C/C-SiC-ZrB 2 -AlSi were ablated in plasma at cyclic changing impacted angle (±45o) and compared with the conventional test at steady state. Accompanied with higher and fluctuant surface temperatures, the periodical changed stress from scouring accelerated the consumption of AlSi matrix and strengthened the mechanical denudation of carbon fiber, which led to severer ablations in the dynamic environment. • C/C-SiC-AlSi and C/C-SiC-ZrB 2 -AlSi were dynamic ablated in plasma. • The ablation in dynamic condition was severer than that in steady environment. • AlSi consumption and fiber denudation were strengthened in dynamic condition. [ABSTRACT FROM AUTHOR]

• Estimated battery SOH using CNN model based on the raw data. • A high tolerance to the partial charging condition. • Introduced transfer learning method to reduce the offline training data. • Satisfied generality to different types of batteries. State of health (SOH) estimation is essential to the health diagnostic of lithium-ion battery. The data-driven approach with charging feature extraction is promising for online SOH estimation and has been widely explored over years. However, their deployment can be barriered by the lack of complete charging data in real-world applications. Motivated by this, this paper proposes an artificial intelligence-based SOH estimator using the transient phase between constant current (CC) and constant voltage (CV) charging, which is easily obtained in real-world charging scenarios. Specifically, a convolutional neural network (CNN) model is proposed to explain the relationship between the charging data and the SOH. Following this endeavor, the transfer learning is exploited for model mitigation and SOH estimation on different battery types, relying on much reduced amount of data for efficient CNN model re-training. The validation experiments are conducted based on the aging data obtained on LiNiCoAlO 2 (NCA) and LiCoO 2 (LCO) cells. Results suggest that the proposed method realizes accurate SOH estimation requiring only a short segment from the CC-CV transient phase, so that can meet a broad range of real-world charging scenarios. Moreover, the efficient model transfer promises expected performance with different battery types. The short version of the paper was presented at ICAE2021, Nov 29 - Dec 5, 2021. This paper is a substantial extension of the short version of the conference paper. [ABSTRACT FROM AUTHOR]

Although the past twenty years have witnessed China's remarkable economic development, the cost in terms of greenhouse gas emissions and a deteriorating environment has been enormous. Numerous studies have revealed the influence of household factors on household carbon dioxide emissions (HCEs) and called for a reduction of HCEs to mitigate climate change, but few have focused on assessing the most significant household driving factors of HCEs. Using statistical data between 2005 and 2019 in Jiangsu, China, this study developed an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model to assess the most significant driving factors of HCEs. The results show that the most significant driving factors are household size, total population, unemployment, and urbanisation rate. The study found that HCEs are positively impacted by household size while negatively impacted by the unemployment rate. Based on the study's findings, the following suggestions are proposed to lower HCEs: (i) establish an optimal consumption concept to guide residents towards consuming reasonably; (ii) cultivate a low-carbon concept among residents and promote low-carbon emissions living; and (iii) pay close attention to population structure factors and formulate effective measures accordingly. The study provides insightful information on the key driving factors of HCEs, which can facilitate achieving carbon emissions neutrality. • H1: The driving factors of household CO 2 emissions (HCEs) are identified. • H2: An extended STIRPAT model is developed for assessing the driving factors. • H3: The household factors are ranked resulted from the ridge regression analysis. • H4: The household size is the most significant positive factor of HCEs. • H5: Unemployment has a negative impact on HCEs. [ABSTRACT FROM AUTHOR]

Anion exchange membranes (AEMs) are a core component for energy conversion technologies such as fuel cells and water electrolyzers. Unfortunately, the functional cations in AEM often suffer from inferior durability in caustic media, especially at elevated temperatures or highly concentrated alkaline solutions. Therefore, the exploitation of novel cations that can endure highly alkaline environments while with synthetic feasibility and good ion conducting property is desired. Herein, a simple and easily available pyrazolium cation was evaluated and was alkaline stable in 5 M NaOH (aq) at 80 °C for at least 240 h, which is substantially stable than its structural isomer, imidazolium. The alkaline stability of pyrazolium was rationalized through analyses of the degradation energy barriers calculated by density functional theory. The excellent alkaline stability of pyrazolium cation encouraged the fabrication of AEMs functionalizing with pyrazolium head group anchored to poly(arylene alkylene) architecture. In contrast to imidazolium-based counterpart, pyrazolium cation enable the AEM with higher base stability, retaining ～80% of its initial conductivity after a 1000-h treatment in 1 M NaOH (aq) at 80 °C. Moreover, the AEM based on pyrazolium showed a high hydroxide ion conductivity up to 120 mS cm−1 at 80 °C and a high peak power density of 502 mW cm−2 after assembled into a H 2 –O 2 fuel cell device. [Display omitted] • Pyrazolium cation was proved to be an alkali-stable anion conductor for AEM. • The pyrazolium-based AEM retained 77% of its initial conductivity after a 1000-h aging. • A peak power density of 502 mW cm−2 was achieved for pyrazolium-based AEM. [ABSTRACT FROM AUTHOR]

Introduction and Importance: The decision between orthodontic camouflage therapy and orthodontic-orthognathic surgical treatment for developing skeletal Class III malocclusion presents a significant challenge for orthodontists., Case Presentation: This case report describes the camouflage treatment of a severe skeletal Class III adolescent at the post-pubertal stage., Clinical Discussion: Protraction facemask combined with a bonded acrylic splint expander was initially used to correct the developing skeletal Class III malocclusion. Then the patient received fixed appliance therapy. The duration of active treatment was 14 months. Anterior crossbite was corrected, along with stable occlusion and harmonious facial condition. The results remain stable at the 5-year follow-up period., Conclusion: Treatment with protraction facemask followed by fixed appliance therapy was possibly effective in a long-term observation, even in skeletal Class III adolescent at the post-pubertal stage., Competing Interests: Declaration of competing interest No conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: This study aimed to investigate the knowledge, attitude, and practice (KAP) of depression among university students., Methods: A cross-sectional survey was carried out across randomly selected universities in Shandong Province from October 25, 2023, to November 8, 2023. Demographic information and KAP scores were assessed through the administration of questionnaires. The reliability of the questionnaire was confirmed with a Cronbach's alpha coefficient of 0.816 and the Kaiser-Meyer-Olkin measure of 0.894., Results: This study included 2448 university students, with 1489 (60.8%) females. The median scores for KAP were 20 (Interquartile Range (IQR): 17-21), 26 (IQR: 23-28), and 35 (IQR: 32-38), respectively. Multivariate regression analysis indicated that being a junior (odds ratio [OR] = 0.720, 95% Confidence Interval (CI): 0.538-0.965, p = .028), senior or above (OR = 0.474, 95% CI: 0.325-0.691, p < .001), having divorced parents (OR = 0.618, 95% CI: 0.409-0.933, p = .022), having direct relatives with depression (OR = 0.710, 95% CI: 0.589-0.856, p < .001), and lacking intimate friends (OR = 0.344, 95% CI: 0.245-0.484, p < .001) were negatively associated with practice. Only having an attitude score of ≥26 (OR = 5.076, 95% CI: 4.230-6.091, p < .001) was significantly and positively associated with practice., Conclusion: University students had insufficient knowledge, positive attitude, and passive practice toward depression. Clinical interventions should focus on enhancing the understanding and management of depression among university students, particularly through targeted educational programs and support groups, to bridge the gap between knowledge and practice and foster a proactive approach to mental health care., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

Background: Erythropoietin-producing human hepatocellular (Eph) receptors stand out as the most expansive group of receptor tyrosine kinases (RTKs). Accumulating evidence suggests that within this expansive family, the EphA subset is implicated in driving cancer cell progression, proliferation, invasion, and metastasis, making it a promising target for anticancer treatment. Nonetheless, the extent of EphA family involvement across diverse cancers, along with its intricate interplay with immunity and the tumor microenvironment (TME), remains to be fully illuminated., Methods: The relationships between EphA gene expression and patient survival, immunological subtypes, and TME characteristics were investigated based on The Cancer Genome Atlas (TCGA) database. The analyses employed various R packages., Results: A significant difference in expression was identified for most EphA genes when comparing cancer tissues and non-cancer tissues. These genes independently functioned as prognostic factors spanning multiple cancer types. Moreover, a significant correlation surfaced between EphA gene expression and immune subtypes, except for EphA5, EphA6, and EphA8. EphA3 independently influenced the prognosis of papillary renal cell carcinoma (KIRP). This particular gene exhibited links with immune infiltration subtypes and clinicopathologic parameters, holding promise as a valuable biomarker for predicting prognosis and responsiveness to immunotherapy in patients with KIRP., Conclusion: By meticulously scrutinizing the panorama of EphA genes in a spectrum of cancers, this study supplemented a complete map of the effect of EphA family in Pan-cancer and suggested that EphA family may be a potential target for cancer therapy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Cui, Liu, Wang and Xiang.)

Background and Objectives: Dynamic handwriting analysis, due to its noninvasive and readily accessible nature, has emerged as a vital adjunctive method for the early diagnosis of Parkinson's disease (PD). An essential step involves analysing subtle variations in signals to quantify PD dysgraphia. Although previous studies have explored extracting features from the overall signal, they may ignore the potential importance of local signal segments. In this study, we propose a lightweight network architecture to analyse dynamic handwriting signal segments of patients and present visual diagnostic results, providing an efficient diagnostic method., Methods: To analyse subtle variations in handwriting, we investigate time-dependent patterns in local representation of handwriting signals. Specifically, we segment the handwriting signal into fixed-length sequential segments and design a compact one-dimensional (1D) hybrid network to extract discriminative temporal features for classifying each local segment. Finally, the category of the handwriting signal is fully diagnosed through a majority voting scheme., Results: The proposed method achieves impressive diagnostic performance on the new DraWritePD dataset (with an accuracy of 96.2%, sensitivity of 94.5% and specificity of 97.3%) and the well-established PaHaW dataset (with an accuracy of 90.7%, sensitivity of 94.3% and specificity of 87.5%). Moreover, the network architecture stands out for its excellent lightweight design, occupying a mere 0.084M parameters, with only 0.59M floating-point operations. It also exhibits nearly real-time CPU inference performance, with the inference time for a single handwriting signal ranging from 0.106 to 0.220 s., Conclusions: We present a series of experiments with extensive analysis, which systematically demonstrate the effectiveness and efficiency of the proposed method in quantifying dysgraphia for a precise diagnosis of PD., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)