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Abstract Battery electric vehicles (BEVs) have emerged as a promising alternative to traditional internal combustion engine (ICE) vehicles due to benefits in improved fuel economy, lower operating cost, and reduced emission. BEVs use electric motors rather than fossil fuels for propulsion and typically store electric energy in lithium-ion cells. With rising concerns over fossil fuel depletion and the impact of ICE vehicles on the climate, electric mobility is widely considered as the future of sustainable transportation. BEVs promise to drastically reduce greenhouse gas emissions as a result of the transportation sector. However, mass adoption of BEVs faces major barriers due to consumer worries over several important battery-related issues, such as limited range, long charging time, lack of charging stations, and high initial cost. Existing solutions to overcome these barriers, such as building more charging stations, increasing battery capacity, and stationary vehicle-to-vehicle (V2V) charging, often suffer from prohibitive investment costs, incompatibility to existing BEVs, or long travel delays. In this paper, we propose Peer-to-Peer Car Charging (P2C2), a scalable approach for charging BEVs that alleviates the need for elaborate charging infrastructure. The central idea is to enable BEVs to share charge among each other while in motion through coordination with a cloud-based control system. To re-vitalize a BEV fleet, which is continuously in motion, we introduce Mobile Charging Stations (MoCS), which are high-battery-capacity vehicles used to replenish the overall charge in a vehicle network. Unlike existing V2V charging solutions, the charge sharing in P2C2 takes place while the BEVs are in-motion, which aims at minimizing travel time loss. To reduce BEV-to-BEV contact time without increasing manufacturing costs, we propose to use multiple batteries of varying sizes and charge transfer rates. The faster but smaller batteries are used for charge transfer between vehicles, while the slower but larger ones are used for prolonged charge storage. We have designed the overall P2C2 framework and formalized the decision-making process of the cloud-based control system. We have evaluated the effectiveness of P2C2 using a well-characterized simulation platform and observed dramatic improvement in BEV mobility. Additionally, through statistical analysis, we show that a significant reduction in carbon emission is also possible if MoCS can be powered by renewable energy sources.

Abstract Water holding capacity (WHC) is an important sensory attribute that greatly influences meat quality. However, the molecular mechanism that regulates the beef WHC remains to be elucidated. In this study, the longissimus dorsi (LD) muscles of 49 Chinese Simmental beef cattle were measured for meat quality traits and subjected to RNA sequencing. WHC had significant correlation with 35 kg water loss (r = − 0.99, p

Abstract To determine the factors predicting the probability of severe postpartum hemorrhage (SPPH) in women undergoing repeat cesarean delivery (RCD). This multicenter, retrospective cohort study involved women who underwent RCD from January 2017 to December 2017, in 11 public tertiary hospitals within 7 provinces of China. The all-variables model and the multivariable logistic regression model (pre-operative, operative and simple model) were developed to estimate the probability of SPPH in development data and external validated in validation data. Discrimination and calibration were evaluated and clinical impact was determined by decision curve analysis. The study consisted of 11,074 women undergoing RCD. 278 (2.5%) women experienced SPPH. The pre-operative simple model including 9 pre-operative features, the operative simple model including 4 pre-operative and 2 intraoperative features and simple model including only 4 closely related pre-operative features showed AUC 0.888, 0.864 and 0.858 in development data and 0.921, 0.928 and 0.925 in validation data, respectively. Nomograms were developed based on predictive models for SPPH. Predictive tools based on clinical characteristics can be used to estimate the probability of SPPH in patients undergoing RCD and help to allow better preparation and management of these patients by using a multidisciplinary approach of cesarean delivery for obstetrician.

Abstract The photothermal sensitivity of tobacco refers to the degree to which tobacco responds to changes in light and temperature conditions in its growth environment, which is crucial for determining the planting area of cultivars and improving tobacco yield and quality. In order to accurately and effectively evaluate the photothermal sensitivity of tobacco cultivars, this study selected five cultivars and their hybrid combinations with significant differences planted under different ecological conditions from 2021 to 2022 as materials. The experiment was conducted in two locations with significant differences in temperature and light. We measured the agronomic traits and biomass of the experimental materials, and constructed an effective tobacco photothermal sensitivity evaluation model using principal component analysis, membership function, and regression analysis. The reliability of the model was evaluated by utilizing the photosynthetic characteristics, chlorophyll content, and antioxidant enzyme system activity of the experimental materials. The results showed that tobacco biomass is the most important principal component in agricultural traits, and the comprehensive evaluation model for tobacco photothermal sensitivity is: y = 0.4571y1 + 0.2406y2 + 0.1725y3, where the fitting coefficients R2 of y1, y2, and y3 are 0.945, 0.851, and 0.977, respectively; The photothermal sensitivity of the experimental materials was calculated using this model, and the comprehensive ranking of the 11 experimental materials is: G3

Abstract Carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and alpha-fetoprotein (AFP) are widely used tumor markers for colorectal cancer (CRC), but their clinical significance is unknown when the levels of these tumor markers were within the normal range. This retrospective study included 2145 CRC patients. The entire cohort was randomly divided into training and validation datasets. The optimal cut-off values of tumor markers were calculated using X-tile software, and univariate and multivariate analyses were performed to assess its association with overall survival (OS). The nomogram model was constructed and validated. The entire cohort was randomly divided into a training dataset (1502 cases, 70%) and a validation dataset (643 cases,30%). Calculated from the training dataset, the optimal cut-off value was 2.9 ng/mL for CEA, 10.1 ng/mL for CA19-9, 13.4 U/mL for CA125, and 1.8 ng/mL for AFP, respectively. Multivariate analysis revealed that age, tumor location, T stage, N stage, preoperative CA19-9, and CA125 levels were independent prognostic predictors. Even within the normal range, CRC patients with relatively high levels of CA19-9 or CA125 worse OS compared to those with relatively low levels. Then, based on the independent prognostic predictors from multivariate analysis, two models with/without (model I/II) CA19-9 and CA125 were built, model I showed better prediction and reliability than model II. Within the normal range, relatively high levels of preoperative CA19-9 and CA125 were significantly associated with poor OS in CRC patients. The nomogram based on CA19-9 and CA125 levels showed improved predictive accuracy ability for CRC.

Abstract Heterosis is a common biological phenomenon that can be used to optimize yield and quality of crops. Using heterosis breeding, hybrids with suitable nicotine content have been applied to tobacco leaf production. However, the molecular mechanism of the formation of nicotine heterosis has never been explained from the perspective of protein. The DIA proteomics technique was used to compare the differential proteomics of the hybrid Va116 × Basma, showing strong heterosis in nicotine content from its parent lines Va116 and Basma. Proteomics analysis indicated that 65.2% of DEPs showed over-dominant expression patterns, and these DEPs included QS, BBL, GS, ARAF and RFC1 which related to nicotine synthesis. In addition, some DEPs (including GST, ABCE2 and ABCF1 and SLY1) that may be associated with nicotinic transport exhibited significant heterosis over the parental lines. These findings demonstrated that the efficiency of the synthesis and transport of nicotine in hybrids was significantly higher than that in the parent lines, and the accumulation of over-dominant expression proteins may be the cause of heterosis of nicotinic content in hybrids.