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Abstract With the rapid development of the civil aviation industry, the demand for secure sharing of civil aviation data is increasing. As a global platform for secure sharing of civil aviation data, the security of the System Wide Information Management (SWIM) system is of great concern. SWIM adopts a service-oriented architecture and realizes the interaction of civil aviation data through a publish-subscribe model. To protect the service privacy while enabling subscribers to subscribe to the service quickly and securely, this paper proposes an efficient Circular Shift and Coalesce-Cuckoo Filter (CSC-CF)-based service Keyword Search (CCKS) scheme assisted by blockchain. This scheme uses the Symmetric-key Hidden Vector Encryption (SHVE) algorithm to encrypt and match service indexes and trapdoors to protect service privacy; the CSC-CF structure is applied to keyword search, which can effectively improve the efficiency of SWIM user subscription service. To improve search accuracy and space utilization, we propose the improved CCKS (ICCKS) scheme by optimizing the query algorithm of CSC-CF and setting a threshold for the number of keyword query failures. ICCKS improves search accuracy by 5–20% compared to CCKS when the filter’s space utilization is between 60 and 90%. Additionally, the scheme stores service topic indexes and registry on the blockchain and implements a smart contract to match indexes and subscription trapdoors, ensuring the integrity and trustworthiness of service topics and registry. Security analysis and experimental simulations demonstrate that the scheme is effective and secure in the SWIM system.

Mechanical softening behaviors of shale in CO2-water–rock interaction are critical for shale gas exploitation and CO2 sequestration. This work investigated the cross-scale mechanical softening of shale triggered by CO2-water–rock interaction. Initially, the mechanical softening of shale following 30 d of exposure to CO2 and water was assessed at the rock-forming mineral scale using nanoindentation. The mechanical alterations of rock-forming minerals, including quartz, muscovite, chlorite, and kaolinite, were analyzed and compared. Subsequently, an accurate grain-based modeling (AGBM) was proposed to upscale the nanoindentation results. Numerical models were generated based on the real microstructure of shale derived from TESCAN integrated minerals analyzer (TIMA) digital images. Mechanical parameters of shale minerals determined by nanoindentation served as input material properties for AGBMs. Finally, numerical simulations of uniaxial compression tests were conducted to investigate the impact of mineral softening on the macroscopic Young’s modulus and uniaxial compressive strength (UCS) of shale. The results present direct evidence of shale mineral softening during CO2-water–rock interaction and explore its influence on the upscale mechanical properties of shale. This paper offers a microscopic perspective for comprehending CO2-water-shale interactions and contributes to the development of a cross-scale mechanical model for shale.

The composition and concentration of volatile organic compounds (VOCs) in exhaled breath are closely related to human health and the analysis of VOCs by collecting human exhaled breath has been widely used in disease surveillance research. This article reviewed the collection, enrichment, and detection methods of exhaled VOCs, which can provide a reference for selecting appropriate technology for follow-up research. The exhaled breath collection devices mainly include sampling bags for mixed exhaled breath and biological volatile organic compound (Bio-VOC) samplers for alveolar air. The pre-enrichment equipment included thermal desorption (TD), solid-phase microextraction device (SPME), and needle trap device (NTD). The detection methods of exhaled VOCs include gas chromatography-mass spectrometry (GC-MS), proton transfer reaction mass spectrometry (PTR-MS), selective ion flow tube mass spectrometry (SIFT-MS), and electronic nose. At present, the collection and enrichment technology of exhaled breath is not mature yet, and its influence on the results of detection is lack of evaluation. In the future, the research on collection and enrichment technology of exhaled breath should be strengthened to further promote the application of exhaled breath in disease surveillance research.

Background: Maduramicin (MAD) is an anticoccidial veterinary drug, but it frequently causes fatal poisonings in poultry, livestock, or humans. However, there is no specific antidote or guidance on first aid for MAD poisoning. Aim: The aim of the present study is to evaluate the acute toxicity and toxicokinetics of MAD after oral exposure, so as to make a foundation for developing diagnostic and therapeutic protocols for human intoxication. Methods: Five groups of rats (eight-to-nine-week-old male Wistar rats) were orally administered MAD via gavage at doses of 0, 4.64, 10.0, 21.5, or 46.4 mg/kg bw for only one time. The survival rates of the rats were observed over the following 14 days to assess acute toxicity. To evaluate the toxic effects of MAD, two doses (4.8 mg/kg bw and 10 mg/kg bw) were orally administered via gavage. Biochemical parameters including creatine kinase, lactate dehydrogenase, aspartate aminotransferase, alanine aminotransferase, urea, creatinine, serum myoglobin, and urinary myoglobin were measured. Liver, kidney, heart, and hind limb skeletal muscle samples from severely poisoned rats were obtained for pathological examination. For toxicokinetic analysis, samples of serum, urine, and feces from the 4.8 mg/kg bw dose group were analyzed using high-performance liquid chromatography-tandem mass spectrometry. Results: The LD50 of MAD in male Wistar rats was determined to be 6.81 mg/kg bw. In the 10 mg/kg bw group, elevated serum urea levels and increased myoglobin levels in both serum and urine indicated renal injury and potential muscle damage. Toxicokinetics in serum revealed that following oral administration of 4.8 mg/kg bw MAD, peak serum concentration of 59.8 ± 8.9 μg/L was achieved at 30.0 ± 13.9 h. MAD exhibited a slow elimination from the blood with an elimination half-life of 72.9 ± 36.8 h and a mean residence time of 79.6 ± 25.5 h. Additionally, fecal excretion of MAD was found to be greater than urinary excretion. Conclusion: MAD is a highly toxic veterinary drug which requires careful handling. The primary effects of poisoning include kidney injury and suspected rhabdomyolysis. It is excreted very slowly after oral administration. Promoting toxin excretion in individuals poisoned by MAD could potentially serve as an effective treatment method until a specific antidote is identified.

The flow and diffusion of grout within rock fractures, as well as the shear behavior of the grout-rock interface, are notably influenced by grouting conditions, encompassing grouting parameters and geological considerations. Regrettably, owing to constraints imposed by prevailing testing techniques, there exists a scarcity of reports investigating the shear mechanical properties of the grout-rock interface across diverse grouting conditions. This study used a low-field nuclear magnetic resonance (LF-NMR) testing system to conduct permeation grouting tests on fractured sandstones under various grouting conditions, followed by direct shear mechanical tests on the post-grouted samples. The influences of grouting pressure, temperature and confining pressure on the shear mechanical properties of the bonding interface were analyzed. Results showed that higher grouting pressure and temperature conditions led to ductile shear failures due to shear-friction action. An increase in grouting pressure (from 0.5 MPa to 1.3 MPa) increased the peak shear strength and residual shear strength of the post-grouted sample. However, increasing the temperature (from 20 °C to 50 °C) and confining pressure (from 5 MPa to 15 MPa) decreased the peak shear strength and residual shear strength. Meanwhile, with increasing the temperature, both the internal friction angle and cohesion linearly decline, while an increase in confining pressure decreased the internal friction angle but increased cohesion. A shear mechanical model was developed for the bonded interface that accounted for the influences of temperature and confining pressure. Additionally, SEM and XRD examinations yielded valuable insights into the grout filling patterns across various grouting parameters. The findings in this study shed light on the intricacies of grouting performance influenced by grouting conditions, and provide essential guidance for grouting operations in practical engineering.

Solid-state batteries (SSBs) have received widespread attention with their high safety and high energy density characteristics. However, solid-solid contacts in the internal electrode material and the electrode material/solid electrolyte (SE) interfaces, as well as the severe electrochemo-mechanical effects caused by the internal stress due to the volume change of the active material, these problems hinder ion/electron transport within the SSBs, which significantly deteriorates the electrochemical performance. Applying fabrication pressures and stack pressures are effective measures to improve solid-solid contact and solve electrochemo-mechanical problems. Herein, the influences of different pressures on cathode material, anode material, SEs, and electrode/SEs interface are briefly summarized from the perspective of interface ion diffusion, transmission of electrons and ions in internal particles, current density and ion diffusion kinetics, and the volume changes of Li+ stripping/plating based on two physical contact models, and point out the direction for the future research direction of SSBs and advancing industrialization by building the relationship between pressures and SSBs electrochemistry.

This study addresses the challenges of low detection precision and limited generalization across various ripeness levels and varieties for large non-green-ripe citrus fruits in complex scenarios. We present a high-precision and lightweight model, YOLOC-tiny, built upon YOLOv7, which utilizes EfficientNet-B0 as the feature extraction backbone network. To augment sensing capabilities and improve detection accuracy, we embed a spatial and channel composite attention mechanism, the convolutional block attention module (CBAM), into the head’s efficient aggregation network. Additionally, we introduce an adaptive and complete intersection over union regression loss function, designed by integrating the phenotypic features of large non-green-ripe citrus, to mitigate the impact of data noise and efficiently calculate detection loss. Finally, a layer-based adaptive magnitude pruning strategy is employed to further eliminate redundant connections and parameters in the model. Targeting three types of citrus widely planted in Sichuan Province—navel orange, Ehime Jelly orange, and Harumi tangerine—YOLOC-tiny achieves an impressive mean average precision (mAP) of 83.0%, surpassing most other state-of-the-art (SOTA) detectors in the same class. Compared with YOLOv7 and YOLOv8x, its mAP improved by 1.7% and 1.9%, respectively, with a parameter count of only 4.2M. In picking robot deployment applications, YOLOC-tiny attains an accuracy of 92.8% at a rate of 59 frames per second. This study provides a theoretical foundation and technical reference for upgrading and optimizing low-computing-power ground-based robots, such as those used for fruit picking and orchard inspection.

Hengqin, located at the southern end of Zhuhai city and connected to Macao by a bridge and a river, serves as a key platform for promoting Macao's moderately diversified economic development, leveraging the inherent advantages of Guangdong-Macao cooperation. To enhance the capability of responding to public health emergency is very important for the development of cultural tourism and exhibition industries in the Guangdong-Macao In-Depth Cooperation Zone in Hengqin due to high population mobility in the region. In this article, we briefly discussed the role, strength and future development of community engagement-based public health emergency response in the in-depth cooperation zone.

Background: The timing and incidence of recurrent bone metastasis (BM) after radical gastrectomy in patients with gastric cancer (GC) as well as the survival of these patients were not fully understood. The aim of this study was to analyze the data of an observational GC cohort and identify patients who underwent curative gastrectomy and had recurrent BM to describe and clarify the pattern and profile of BM evolution after surgery. Methods: Data were retrieved from a hospital-based GC cohort, and patients who underwent upfront radical gastrectomy were selected. The time points of specific organ metastatic events were recorded, and the person-year incidence rate of metastatic events was calculated. The latency period of BM events after gastrectomy was measured and compared with that of the other two most common metastatic events, liver metastasis (LM) and distant lymph node metastasis (LNM), using analysis of variance. Propensity score matching and subgroup analysis were used for sensitivity analysis. Results: A total of 1324 GC cases underwent radical gastrectomy between January 2011 and December 2021. Of these, 67 BM, 218 LM, and 248 LNM occurred before the last follow-up. The incidence of BM events was 1.7/100 person-years, which was approximately 3-fold lower than that of LM and distant LNM events (5.5 and 6.3 per 100 person-years, respectively). BM events had a significantly longer latency (median time, 16.5 months) than LM and LNM events (11.1 and 12.0 months, respectively). Recurrent BM led to a worse prognosis (median survival, 4.5 months) than those of LM and LNM events (median survival, 7.7 and 7.1 months, respectively). However, no difference in overall survival after gastrectomy was observed among the groups. Conclusions: Compared with other common metastatic events, BM in GC after gastrectomy is a late-onset event indicating poor survival. Trial registration: No. ChiCTR1800019978; http://www.chictr.org.cn/.

Grouting is a widely used approach to reinforce broken surrounding rock mass during the construction of underground tunnels in fault fracture zones, and its reinforcement effectiveness is highly affected by geostress. In this study, a numerical manifold method (NMM) based simulator has been developed to examine the impact of geostress conditions on grouting reinforcement during tunnel excavation. To develop this simulator, a detection technique for identifying slurry migration channels and an improved fluid-solid coupling (F–S) framework, which considers the influence of fracture properties and geostress states, is developed and incorporated into a zero-thickness cohesive element (ZE) based NMM (Co-NMM) for simulating tunnel excavation. Additionally, to simulate coagulation of injected slurry, a bonding repair algorithm is further proposed based on the ZE model. To verify the accuracy of the proposed simulator, a series of simulations about slurry migration in single fractures and fracture networks are numerically reproduced, and the results align well with analytical and laboratory test results. Furthermore, these numerical results show that neglecting the influence of geostress condition can lead to a serious overestimation of slurry migration range and reinforcement effectiveness. After validations, a series of simulations about tunnel grouting reinforcement and tunnel excavation in fault fracture zones with varying fracture densities under different geostress conditions are conducted. Based on these simulations, the influence of geostress conditions and the optimization of grouting schemes are discussed.

The loss of anchoring force is one of the problems to be solved urgently. The anchorage loss is a key factor causing the failure of anchoring engineering, so it is crucial to study the time-dependent variation of anchoring force. Alternating dry and wet (D-W) conditions have a significant effect on deformation of rock. The anchoring system is composed of anchoring components and rock mass, and thus rock deformation has a significant impact on the loss of anchoring force. Quantifying rock deformation under the effects of D-W cycles is a prerequisite to understanding the factors that influence loss of anchoring force in anchor bolts. In this study, we designed an anchoring device that enabled real-time monitoring of the variation in strain during D-W periods and rock testing. Nuclear magnetic resonance (NMR) measurements showed that under D-W conditions, the increment in porosity was smaller for prestressed rock than unstressed rock. The trends of prestress loss and strain variation are consistent, which can be divided into three characteristic intervals: rapid attenuation stage, slow attenuation stage and relatively stable stage. At the same stress level, the rate of stress loss and strain for the soaking specimen was the highest, while that of the dried specimen was the lowest. In the same D-W cycling conditions, the greater the prestress, the smaller the strain loss rate of the rock, especially under soaking conditions. The characteristics of pore structure and physical mechanical parameters indicated that prestress could effectively suppress damage caused by erosion related to D-W cycles. The study reveals the fluctuation behavior of rock strain and prestress loss under D-W conditions, providing a reference for effectively controlling anchoring loss and ideas for inventing new anchoring components.

Abstract The recently discovered APRO (anti-proliferative protein) family encodes a group of trans-membrane glycoproteins and includes 6 members: TOB1, TOB2, BTG1, BTG2, BTG3 and BTG4. The APRO family is reportedly associated with the initiation and progression of cancers. This study aims to undertake a comprehensive investigation of the APRO family of proteins as a prognostic biomarker in various human tumors. We performed a pan-cancer analysis of the APRO family based on The Cancer Genome Atlas (TCGA). With the bioinformatics methods, we explored the prognostic value of the APRO family and the correlation between APRO family expression and tumor mutation burden (TMB), microsatellite instability (MSI), drug sensitivity, and immunotherapy in numerous cancers. Our results show that the APRO family was primarily down-regulated in cancer samples. The expression of APRO family members was linked with patient prognosis. In addition, APRO family genes showed significant association with immune infiltrate subtypes, tumor microenvironment, and tumor cell stemness. Finally, our study also demonstrated the relationship between APRO family genes and drug sensitivity. This study provides comprehensive information to understand the APRO family’s role as an oncogene and predictor of survival in some tumor types.

SMARCA4-deficient undifferentiated tumor (SMARCA4-dUT) is a devastating subtype of thoracic tumor with SMARCA4 inactivation and is characterized by rapid progression, poor prognosis, and high risk of postoperative recurrence. However, effective treatments for SMARCA4-dUT are lacking. Herein, we describe a patient with SMARCA4-dUT who exhibited an impressive response to the anti-programmed cell death protein-1 (PD-1) antibody (tislelizumab) in combination with conventional chemotherapy (etoposide and cisplatin). To the best of our knowledge, this is the first case of SMARCA4-dUT treated with chemotherapy, comprising etoposide and cisplatin, combined with anti-PD-1 inhibitors. Immunotherapy combined with etoposide and cisplatin may be a promising strategy to treat SMARCA4-dUT.

BackgroundTacrolimus (Tac) is commonly used for postoperative immunosuppressive therapy in transplant patients. However, problems, for example, low bioavailability and unstable plasma concentration, persist for a long time, Studies have reported that the deoxyschizandrin could effectively improve these problems, but the pharmacokinetic parameters (PKs) of Tac combined with deoxyschizandrin are still unknown.MethodIn this study, an UHPLC-MS/MS method has been established for simultaneous quantitation of Tac and deoxyschizandrin. The PKs of Tac influenced by different doses of deoxyschizandrin after single and multiple administrations were analyzed, and the different impact of deoxyschizandrin and Wuzhi capsule on PKs of Tac were compared.ResultThe modified UHPLC-MS/MS method could rapid quantification of Tac and deoxyschizandrin within 2 min using bifendatatum as the internal standard (IS). All items were successfully validated. The Cmax of deoxyschizandrin increased from 148.27 ± 23.20 to 229.13 ± 54.77 ng/mL in rats after multiple administrations for 12 days. After co-administration of 150 mg/mL deoxyschizandrin, Tac had an earlier Tmax and greater Cmax and AUC0–t, and the Cmax and AUC0–t of Tac increased from 14.26 ± 4.73 to 54.48 ± 14.37 ng/mL and from 95.10 ± 32.61 to 315.23 ± 92.22 h/ng/mL, respectively; this relationship was positively proportional to the dosage of deoxyschizandrin. In addition, compared with Wuzhi capsule, the same dose of deoxyschizandrin has a better effective on Tac along with more stable overall PKs.ConclusionAn UHPLC-MS/MS method was established and validated for simultaneous detection of deoxyschizandrin and Tac. Deoxyschizandrin could improve the in vivo exposure level and stability of Tac, besides, this effect is better than Wuzhi capsule in same dose.

Abstract Background Mushroom poisoning is a major public health issue in China. The integration of medical resources from different institutes of different levels is crucial in reducing the harm of mushroom poisoning. However, few studies have provided comprehensive implementation procedures and postimplementation effectiveness evaluations. To reduce the harm caused by mushroom poisoning, a network system for the prevention and treatment of mushroom poisoning (NSPTMP) was established in Chuxiong, Yunnan Province, a high-risk area for mushroom poisoning. Methods The NSPTMP consists of three types of institutions, namely, centers for disease prevention, hospitals, and health administration departments, with each kind of institution comprising prefecture, county/city, town, and village levels. After three years of implementation, the network was evaluated by comparing the indices before and after network implementation using data from the “Foodborne Disease Outbreak Surveillance System” and 17 hospitals in Chuxiong. The indices included the fatalities caused by mushroom poisoning, the composition ratios of different types of mushrooms for both outpatients and inpatients and the hospitalization rates. Results Compared to the average fatality rate of mushroom poisoning from 2015 to 2017, the average fatality rate from 2018 to 2020 significantly decreased from 0.57 to 0.06% (P

While numerous studies have revealed the impact of different bullying behaviors, such as victimization and perpetration, on the psychological development of adolescents, the exploration of the correlates of positive/negative bystander behaviors and their potential underlying mechanisms remains scarce in China. The present study aims to compare the relationships between mental health and positive versus negative bystander behavior and to clarify whether self-efficacy and coping styles mediate the relationships between mental health and bullying dynamics. The current study was conducted on 11,734 students from 18 secondary schools in Suzhou, China (Meanage = 15.00, SDage = 1.47; 53.8% boys). The information on bullying victimization, perpetration, positive/negative bystander behaviors, as well as self-efficacy, coping styles and mental health variables (including depression, anxiety, sleep disturbance, suicide risk), were collected. Negative bystander behavior was positively associated with mental health problems, while positive bystander behavior was negatively associated with these factors. Also, further analysis showed that coping styles and self-efficacy mediated the relationship between different bullying behaviors and mental health outcomes. The results highlighted the comparison of the correlates of positive and negative bystander behaviors, which were comparably crucial to those of victims and perpetrators for prevention and intervention efforts. Promoting adaptive coping styles and self-efficacy to buffer the deleterious psychological consequences of bullying behavior in adolescents was also important.

The geometry of an orifice is a major determinant of nozzle internal flow and cavitation, which directly govern spray atomization and consequently affect combustion and fuel economy in internal combustion engines. In this study, simulation models of the nozzle at different angles between the normal and the injection hole inlet cross-section and the injection hole axis, as well as with different injection hole cone angles (a positive angle between the injection hole axis and its walls implies a divergent hole), were investigated by means of a previously developed numerical model that was validated based on experimental data from X-ray image technology. The results indicate that as the angle between the normal and the injection hole inlet cross-section and the injection hole axis increases, the cavitation asymmetry within the injection hole intensifies, accompanied by a decrease in the gas volume fraction. On one side of the injection hole, the hydraulic flip width expands, while, on the other side of the injection hole, the flow state gradually changes from hydraulic flip to super-cavitation flow, transitional cavitation and fully reattached flow. The divergent orifice layout intensifies cavitation, and the higher the positive injection hole cone angle, the bigger the hydraulic flip width. The convergent layout of the injection hole suppresses cavitation, and cavitation inside the nozzle disappears completely when the injection hole cone angle is less than −10°.

Accurately quantifying large-scale evapotranspiration (ET) is of significant scientific importance. In this study, the Shuttleworth–Wallace (SW) model incorporates gross primary productivity (GPP) values from the near-infrared reflectance of vegetation (NIRv) GPP product (NIRvGPP). Monthly ET estimations for the Yellow River Basin (YRB) were obtained using the SW models with GPP derived from the GLASS GPP product (GLASSGPP) and NIRvGPP, as well as GLASS ET and CR ET products (SW_GLASSGPP ET, SW_NIRvGPP ET, GLASS ET, and CR ET). The study analyzes the annual spatio-temporal patterns of these products, evaluates their accuracy and uncertainty, and examines the applicability of a fused ET estimation. The results revealed: (1) differences exist in ET estimations among GLASS ET, CR ET, SW_GLASSGPP ET, and SW_NIRvGPP ET; (2) monthly GLASS ET, CR ET, SW_GLASSGPP ET, and SW_NIRvGPP ET align well with the monthly ETWB, with SW_GLASSGPP ET and SW_NIRvGPP ET outperforming GLASS ET and CR ET; (3) average uncertainties of GLASS ET, CR ET, SW_GLASSGPP ET, and SW_NIRvGPP ET display different spatial variation patterns; and (4) compared to GLASS ET, CR ET, SW_GLASSGPP ET, and SW_NIRvGPP ET, the fused ET estimation achieves the best performance within the YRB. HIGHLIGHTS The SW model was improved by incorporating NIRv GPP values.; The four different ET estimations were fused by the BTCH method.; Different ET estimations were evaluated by water balance and TCH methods.; The ET estimations by the improved SW model outperformed those by GLASS ET and CR ET.; The fused ET performed best in terms of accuracy and uncertainty.;

Abstract The system wide information management (SWIM) system infrastructure layer uses information‐centric networking (ICN) to implement the cache routing and sharing of air traffic information data. The SWIM network searches and forwards routes on the basis of content names. The variable length, hierarchical name structure, and routing updates caused by the frequent publication and deletion of content make the implementation of fast name routing lookup algorithms a significant but arduous task. To address this problem, this study designed a name matching mechanism on the basis of the hybrid structure of the Bloom filter and the Tree. Compared with the traditional Bloom filter search scheme, this search mechanism reduces the quantity of Bloom filter insertion entries and reduces the possibility of hash collisions. Compared with the traditional Tree search scheme, the proposed mechanism can effectively solve the problem of numerous memory accesses caused by extremely long name prefixes, improving the query efficiency. In addition, the proposed composite structure is compared with several methods, such as DIPIT and NPT, by analyzing the effects of layering, global delay and search speed. The experimental results show that the proposed structure has a favourable performance in terms of storage overhead and search speed.

A novel poly(ether block amide) (PEBA) based solid-state polymer electrolyte (SPE) was prepared using a casting method, in which 20wt% lithium (Li) bis-(trifluoromethanesulfonyl)imide (LiTFSI) and aluminum oxide (Al2O3) nanoparticles were used as the Li salt and solid plasticizer, respectively. In the case of addition of 3wt% Al2O3 nanoparticles, ion conductivity of the obtained PEBA 2533–20wt% LiTFSI-3wt% Al2O3 SPE was 3.57 × 10−5 S cm−1 at 25 °C. Furthermore, the Li symmetrical battery assembled with it showed excellent cycling stability (1000 h) at 0.1 mA cm−2. While, the assembled all-solid-state Li/PEBA 2533–20% LiTFSI-3wt% Al2O3/LiFePO4 (areal capacity: 0.15 mAh cm−2) battery maintained 94.9% of the maximal capacity (133.9 mAh g−1@0.1 mA cm−2) at 60 °C even after 650 cycles with a superior average coulombic efficiency (CE) of 99.84%. By using X-ray photoelectron spectroscope (XPS), self-aggregation layer (SAL) of polyamide 12 (PA12) of PEBA 2533 was discovered, which should contribute to promoting the robustness of lithium fluoride (LiF) enriched solid-electrolyte interphase (SEI) layer. In addition, it is considered that the state of interface between SPE and cathode should be the cause of voltage polarization of the full cell.

By establishing oxy-fuel combustion, direct water injection and waste heat recovery within conventional diesel engine, the compression ignition-internal combustion Rankine cycle (CI-ICRC) concept can be realized. It is capable of achieving ultra-high thermal efficiency and low emission. There have been studies on DWI timing in homogeneous charge compression ignition (HCCI) mode, but no systematic researches within CI-ICRC. Therefore, a prototype CI-ICRC engine is established in this work, the cycle performance (including in-cylinder pressure, heat release rate, brake thermal efficiency, etc.) and emission characteristics under different DWI timings are compared. The prototype engine was operated at 800 r/min. DWI temperature, pressure and duration are kept constant at 433 K, 35 MPa and 2 ms. The results indicate that DWI before combustion is more effective in reducing combustion intensity. The optimum DWI timing within this study is 320℃A, while the brake thermal efficiency (BTE) reaches the maximum of 46.6 % with a coefficient of variation close to 1 %. NOx and soot emissions are optimized but CO and HC emissions slightly increased with the utilization of DWI. The experimental results can provide guidance for future CI-ICRC engine optimization, and can also be utilized in providing reference information for DWI utilization within other novel internal combustion engine (ICE) concepts.

Abstract Anthropogenic dust is an important constituent of airborne particles in the urban environment but its ice nucleation activity remains poorly investigated. Here, we studied the sources and ice nucleating properties of size‐resolved particles in the urban atmosphere under mixed‐phase cloud conditions. The heat‐resistant ice nucleating particles (INPs) unexpectedly contributed ∼70% of the supermicron INPs at temperatures below −15°C. A detailed chemical composition analysis of size‐resolved particles revealed that these INPs were associated with anthropogenic dust, such as traffic‐influenced road dust. A parameterization based on supermicron particles was developed to predict the anthropogenic dust INP concentration, given their correlations on concentration and similarity in chemical compositions. Once integrated into global models, this parameterization holds the potential to assess the contribution of anthropogenic dust to INPs on a global scale. Given the considerable presence of anthropogenic dust in the atmosphere and its significant role as INPs, we suggest it may be an important aerosol source influencing cloud microphysics and warrant further investigations.

The daily gross primary productivity (GPP) and evapotranspiration (ET) in the Xilingol grassland ecosystem of Inner Mongolia were simulated using the BioGeochemical Cycles (Biome-BGC) model for 2003–2019 and under future climate-change scenarios. The system was optimized using the System Response Parameter Calibration Method (SRPCM). The temporal variations of GPP, ET and water use efficiency (WUE) were investigated, and the impacts of precipitation and temperature were explored. Results showed that (i) the BIOME-BGC model performed better when optimized using the SRPCM than by applying the Model-Independent Parameter Estimation approach (PEST); (ii) GPP and ET at annual and seasonal scales showed an insignificant increasing trend; (iii) WUE at the annual scale and in growing seasons showed an insignificant increasing trend and a slight decreasing trend in non-growing seasons; (iv) annual GPP and ET were more sensitive to changes in precipitation than changes in temperature with WUE keeping relatively stable with years; (v) precipitation is a critically controlling factor for GPP and ET in growing seasons and for ET and WUE in non-growing seasons; and (vi) combined temperature and precipitation changes had greater impacts on GPP/ET/WUE than individual changes. HIGHLIGHTS The SRPCM was proposed for parameter optimization of the BIOME-BGC model.; The variations of GPP, ET and WUE in 2003–2019 were explored on multiple time-scales.; GPP, ET and WUE in growing seasons played a decisive role in annual GPP and ET.; Daily WUE within 0–2 g/kg dominated in both non-/growing seasons during 2003–2019.; The combined rise of temperature and precipitation has greater impacts on GPP/ET/WUE than only temperature or precipitation rise.;

Abstract Colon cancer (CC) has a poor 5-year survival rate though the treatment techniques and strategies have been improved. Succinylation and long noncoding RNAs (lncRNAs) have prognostic value for CC patients. We analyzed and obtained succinylation-related lncRNA by co-expression in CC. A novel succinylation-related lncRNA model was developed by univariate and Least absolute shrinkage and selection operator (Lasso) regression analysis and we used principal component analysis (PCA), functional enrichment annotation, tumor immune environment, drug sensitivity and nomogram to verify the model, respectively. Six succinylation-related lncRNAs in our model were finally confirmed to distinguish the survival status of CC and showed statistically significant differences in training set, testing set, and entire set. The prognosis of with this model was associated with age, gender, M0 stage, N2 stage, T3 + T4 stage and Stage III + IV. The high-risk group showed a higher mutation rate than the low-risk group. We constructed a model to predict overall survival for 1-, 3-, and 5-year with AUCs of 0.694, 0.729, and 0.802, respectively. The high-risk group was sensitive to Cisplatin and Temozolomide compounds. Our study provided novel insights into the value of the succinylation-related lncRNA signature as a predictor of prognosis, which had high clinical application value in the future.

Background: Staphylococcus aureus is an opportunistic pathogen responsible for various infections with diverse clinical presentation and severity. The α-hemolysin is a major virulence factor in the pathogenesis of S. aureus infections.Objective: To produce a chimeric fusion protein for hemolytic detection of the S. aureus isolates and as a component of a multi-antigen vaccine.Methods: The fused strategy employed a flexible linker to incorporate the possible B cell and T cell determinants into one chimera (HlaD). The humoral and cellular response to the HlaD in mice was assessed to reveal a non-significant difference compared with the full-length α-hemolysin mutant (Hla H35L).Results: The results of the protective effect, the mimetic lung cell injury, and bacterial clearness demonstrated that the mice vaccinated with the HlaD alleviated the severity of the infection of the S. aureus, and the HlaD could similarly function with Hla H35L.Conclusion: The chimeric fusion (HlaD) provided a diagnostic antigen for hemolysis of the S. aureus strains and a potential vaccine component.

Abstract The inconsistent response curve of delicate micro/nanofiber (MNF) sensors during cycling measurement is one of the main factors which greatly limit their practical application. In this paper, we proposed a temperature sensor based on the copper rod-supported helical microfiber (HMF). The HMF sensors exhibited different light intensity-temperature response relationships in single-cycle measurements. Two neural networks, the deep belief network (DBN) and the backpropagation neural network (BPNN), were employed respectively to predict the temperature of the HMF sensor in different sensing processes. The input variables of the network were the sensor geometric parameters (the microfiber diameter, wrapped length, coiled turns, and helical angle) and the output optical intensity under different working processes. The root mean square error (RMSE) and Pearson correlation coefficient (R) were used to evaluate the predictive ability of the networks. The DBN with two restricted Boltzmann machines (RBMs) provided the best temperature prediction results (RMSE and R of the heating process are 0.9705 °C and 0.9969, while the values of RMSE and R of the cooling process are 0.786 6 °C and 0.997 7, respectively). The prediction results obtained by the optimal BPNN (five hidden layers, 10 neurons in each layer, RMSE=1.126 6 °C, R=0.995 7) were slightly inferior to those obtained by the DBN. The neural network could accurately and reliably predict the response of the HMF sensor in cycling operation, which provided the possibility for the flexible application of the complex MNF sensor in a wide sensing range.

In this paper, simulation modeling was carried out using Sentaurus Technology Computer-Aided Design. Two types of high electron mobility transistors (HEMT), an AlGaN/GaN/AlGaN double heterojunction and AlGaN/GaN single heterojunction, were designed and compared. The breakdown characteristics and damage mechanisms of the two devices under the injection of high-power microwaves (HPM) were studied. The variation in current density and peak temperature inside the device was analyzed. The effect of Al components at different layers of the device on the breakdown of HEMTs is discussed. The effect and law of the power damage threshold versus pulse width when the device was subjected to HPM signals was verified. It was shown that the GaN HEMT was prone to thermal breakdown below the gate, near the carrier channels. A moderate increase in the Al component can effectively increased the breakdown voltage of the device. Compared with the single heterojunction, the double heterojunction HEMT devices were more sensitive to Al components. The high domain-limiting characteristics effectively inhibited the overflow of channel electrons into the buffer layer, which in turn regulated the current density inside the device and improved the temperature distribution. The leakage current was reduced and the device switching characteristics and breakdown voltage were improved. Moreover, the double heterojunction device had little effect on HPM power damage and high damage resistance. Therefore, a theoretical foundation is proposed in this paper, indicating that double heterojunction devices are more stable compared to single heterojunction devices and are more suitable for applications in aviation equipment operating in high-frequency and high-voltage environments. In addition, double heterojunction GaN devices have higher radiation resistance than SiC devices of the same generation.

With reference to the trajectory-based operation (TBO) requirements proposed by the International Civil Aviation Organization (ICAO), this paper concentrates on the study of four-dimensional trajectory (4D Trajectory) prediction technology in busy terminal airspace, proposing a data-driven 4D trajectory prediction model. Initially, we propose a Spatial Gap Fill (Spat Fill) method to reconstruct each aircraft’s trajectory, resulting in a consistent time interval, noise-free, high-quality trajectory dataset. Subsequently, we design a hybrid neural network based on the seq2seq model, named Attention-TCN-GRU. This consists of an encoding section for extracting features from the data of historical trajectories, an attention module for obtaining the multilevel periodicity in the flight history trajectories, and a decoding section for recursively generating the predicted trajectory sequences, using the output of the coding part as the initial input. The proposed model can effectively capture long-term and short-term dependencies and repetitiveness between trajectories, enhancing the accuracy of 4D trajectory predictions. We utilize a real ADS-B trajectory dataset from the airspace of a busy terminal for validation. The experimental results indicate that the data-driven 4D trajectory prediction model introduced in this study achieves higher predictive accuracy, outperforming some of the current data-driven trajectory prediction methods.

Summary: Incomplete combustion of fossil fuels and biomass burning emit large amounts of soot particles into the troposphere. The condensation process is considered to influence the size (Dp) and mixing state of soot particles, which affects their solar absorption efficiency and lifetimes. However, quantifying aging evolution of soot remains hampered in the real world because of complicated sources and observation technologies. In the Himalayas, we isolated soot sourced from transboundary transport of biomass burning and revealed soot aging mechanisms through microscopic observations. Most of coated soot particles stabilized one soot core under Dp

The compression ignition internal combustion Rankine cycle (CI-ICRC) is a novel combustion cycle that integrates oxy-fuel combustion, direct water injection (DWI), and waste heat recovery into diesel cycle to achieve ultra-high thermal efficiency and zero emissions. NOX formation is eliminated by utilizing oxygen instead of air, and water is injected into the cylinder to improve thermal efficiency. To achieve over 50% indicated thermal efficiency in the CI-ICRC engine, a thermodynamic model of the CI-ICRC engine is established in this paper to explore the potential thermal efficiency and boundary under different DWI strategies. Theoretical results demonstrate that the thermal efficiency of CI-ICRC engine is mostly affected by DWI mass and temperature, the thermal efficiency is dramatically enhanced as DWI mass and temperature increase. Under a water-to-fuel ratio of 20 and DWI temperature of 423K, the calculated thermal efficiency reaches 76.8%. Moreover, exhaust waste heat is mainly recovered through DWI, which increases the working fluid within the combustion chamber, thereby increasing the expansion work and improving cyclic thermal efficiency. Additionally, specific heat ratio of the mixture within the cylinder can be enhanced by 0.04 through DWI, improving the thermal efficiency by 9% at an in-cylinder temperature of 800 K.

Abstract Background Gastric cancer liver metastasis (GCLM) patients usually accompany by abnormal serum liver function tests (LFTs) more or less; however, the prognostic value of LFTs is not fully understood. This study aimed to develop a liver chemistry score (LCS) based on LFTs and incorporate it into prognosis determination for GCLM patients who received palliative chemotherapy. Methods Data were derived from hospitalized GCLM patients in two general hospitals in China. LCS was generated based on the results of LFTs by LASSO regression. Cutoff value of the score was determined by restricted cubic spline. The score was then incorporated into Cox regression analysis to construct a predictive nomogram; the model was then evaluated internally and externally by AUC of time‐dependent receiver operating characteristic curves (ROC) and calibration curves. Results Three hundred and thirty‐six and 72 patients were included in development and validation cohort, respectively. LASSO regression analysis in development cohort finally reached a two‐parametric LCS calculated on AST and ALP levels as 0.03343515 × ln (AST, U/L) + 0.02687997 × ln (ALP, U/L), and 0.232 was set as optimal cutoff value. Patients in low (LCS

IntroductionInsect pests from the family Papilionidae (IPPs) are a seasonal threat to citrus orchards, causing damage to young leaves, affecting canopy formation and fruiting. Existing pest detection models used by orchard plant protection equipment lack a balance between inference speed and accuracy.MethodsTo address this issue, we propose an adaptive spatial feature fusion and lightweight detection model for IPPs, called ASFL-YOLOX. Our model includes several optimizations, such as the use of the Tanh-Softplus activation function, integration of the efficient channel attention mechanism, adoption of the adaptive spatial feature fusion module, and implementation of the soft Dlou non-maximum suppression algorithm. We also propose a structured pruning curation technique to eliminate unnecessary connections and network parameters.ResultsExperimental results demonstrate that ASFL-YOLOX outperforms previous models in terms of inference speed and accuracy. Our model shows an increase in inference speed by 29 FPS compared to YOLOv7-x, a higher mAP of approximately 10% than YOLOv7-tiny, and a faster inference frame rate on embedded platforms compared to SSD300 and Faster R-CNN. We compressed the model parameters of ASFL-YOLOX by 88.97%, reducing the number of floating point operations per second from 141.90G to 30.87G while achieving an mAP higher than 95%.DiscussionOur model can accurately and quickly detect fruit tree pest stress in unstructured orchards and is suitable for transplantation to embedded systems. This can provide technical support for pest identification and localization systems for orchard plant protection equipment.

Low carbon is a key driver for the future development of power systems. This paper proposes a carbon-energy synergetic approach for economic dispatch in energy power systems. Firstly, by integrating multi-energy conversion models and carbon emission flow theories, a coupled interactive mechanism model is constructed. Building upon this foundation, an economic optimization dispatch model for comprehensive energy power systems is introduced, leveraging the synergistic value of carbon energy. This method supports economic dispatch in comprehensive energy power systems, considering both security and economic requirements while reducing carbon emissions. This integrated approach offers a promising solution for achieving low-carbon operational objectives and supporting the transition to sustainable energy infrastructure. Typical case studies in this paper validate the effectiveness of the proposed method.

Epidermal growth factor receptor (EGFR) mutations have been frequently detected in patients with pulmonary adenocarcinoma. EGFR Exon 19Del and 21L858R mutations are the two most common EGFR mutations. EGFR-tyrosine kinase inhibitors (TKIs) are widely employed to treat patients with non-small cell lung cancer (NSCLC) harboring EGFR mutations. Recently, there has been rapid growth in clinical trials assessing neoadjuvant targeted therapy, indicating good application prospects owing to high efficiency and low toxicity. Herein, we discuss the case of a 56-year-old male patient who was initially diagnosed with stage IIIA pulmonary adenocarcinoma (AJCC,8th edition) of the left lower lung with an EGFR Exon 19Del mutation. The patient was treated with osimertinib but failed to undergo timely review and surgery. Subsequently, the patient underwent two cycles of neoadjuvant chemotherapy (NAC) combined with neoadjuvant targeted therapy. After the tumor load and size had significantly decreased, radical surgery was successfully performed under thoracoscopy. However, postoperative pathology revealed carcinosarcoma, pT2aN0M0, stage IB, and the pathological response was 50%. The present case report provides practical clinical evidence for the application of neoadjuvant targeted therapy combined with chemotherapy for locally advanced primary pulmonary carcinosarcoma with EGFR mutation.

Abstract Aiming at the low rate and strong concealment of low‐rate Denial of Service (LDoS) attacks, the calculation of traffic Hurst index is combined with traffic classification, and a machine learning LDoS attack detection method based on search sorting is proposed. The method first calculates the segmentation Hurst exponent of each flow, and constructs a traffic similarity matrix as a statistical feature. Then, using the improved model XGBoost of the Gradient Boosting Decision Tree (GBDT), the traffic is classified and predicted. The network angle distinguishes between normal traffic and abnormal Origin‐Destination (OD) flows containing LDoS attacks, thereby achieving the purpose of detecting LDoS attacks. The method in this study was validated using the US public network dataset Abilene. The experimental results show that the global LDoS attack traffic detection method based on the Hurst index and GBDT algorithm achieves better detection results under different attack rates.

The new particle formation (NPF) process is a significant source of atmospheric secondary particles, which has remarkable impacts on the regional air quality and global radiative forcing. Most NPF studies conduct their measurements at a single site, which can hardly provide information about the regionality of NPF events at large scales (>100 km). During the 2022 Winter Olympic and Paralympic Games, simultaneous measurements of particle number size distributions and NPF-associated precursors were conducted at a mountainous site close to the Winter Olympic Village in Chongli (CL), Zhangjiakou, and an urban site in Beijing (BJ) located 150 km southeast of the CL site. High NPF frequencies were observed at the CL (50%) and BJ (52%) sites; however, the fraction of concurrent NPF events was smaller than the results in other regions. In addition, the wind distributions exhibited distinct air mass origins at the two sites during the concurrent NPF events. Compared with the BJ site, the NPF growth rates were higher at the CL site due to higher levels of volatile organic compounds (VOCs) and radiation. Surprisingly, the formation rates at the CL site were lower than at the BJ site, even with a higher sulfuric acid concentration and lower CS, which may be attributed to lower dimethylamine concentrations in the mountainous area. This study reveals that, although NPF events are commonly thought to occur on regional scales, their intensity and mechanisms may have significant spatial inhomogeneity. Further studies are required to reduce the uncertainty when expanding the mechanisms based on the urban conditions to regional or global scales in the models.

African swine fever (ASF) is one of the most severe diseases caused by the ASF virus (ASFV), causing massive economic losses to the global pig industry. Serological tests are important in ASF epidemiological surveillance, and more antigen targets are needed to meet market demand for ASFV antibody detection. In the present study, ASFV p15 protein was fusion-expressed in Escherichia coli (E. coli) with elastin-like polypeptide (ELP), and the ELP-p15 protein was purified using a simple inverse transition cycling (ITC) process. The ELP tag was cleaved off using tobacco etch virus protease (TEVp), resulting in a tag-free p15 protein. Western blot analysis demonstrated that the p15 protein reacted strongly with ASFV-positive serum. The p15 protein was used as a coating antigen in an indirect ELISA (iELISA) for detecting ASFV antibodies. The p15-iELISA method demonstrated high specificity to ASFV-positive sera, with a maximum detection dilution of 1:1600. Moreover, the method exhibited good reproducibility, with less intra-assay and inter-assay CV values than 10%. Therefore, p15-iELISA offers a novel approach for accurately detecting ASFV antibodies with significant clinical application potential.

To figure out the energy attenuation of micro/nanofibers (MNFs) more flexibly and conveniently, a backpropagation neural network (BPNN) is proposed to forecast the output intensity of rhodamine B (RhB) doped polymer microfibers (PMFs). According to the diameter, doping concentration, and propagation distance (L), we realize the L-dependence of output energy predictions for the excitation light (IE) and fluorescence (IF) of the doped PMFs. Hundreds of propagation distance-intensity data pairs acquired from dozens of RhB doped PMFs are used for the BPNN training. The prediction ability of the model is evaluated by the root-mean-square error (RMSE), the mean absolute percentage error (MAPE), and R2. The output intensity prediction performance of BPNN is compared with the traditional exponential-fitting (EF) method. The prediction results indicate that the two-hidden-layer network with one and seventeen neurons respectively provides the best performance. After training, BPNN gives a good intensity prediction for both the IE (RMSE = 3.16×10−2, MAPE = 7.3%, and R2 = 0.9802) and the IF (RMSE = 0.91×10−2, MAPE = 0.89%, and R2 = 0.9696) from the output end of the PMF with different diameters and doping concentrations. The energy losses of the two kinds of light from different doped PMFs are also calculated based on the predicted values, which are similar to the ones obtained from the EF method. The approach based on the BPNN prediction for the energy attenuation of the PMFs shows superiority in flexibility and applicability toward the traditional methods, which could promote the optimal design of the MNF devices and the practical application.

Allium fistulosum (Welsh onion) is a perennial onion species that originates in eastern Asia. It is an important cooking ingredient in eastern countries, such as China, Japan, and Korea. In western countries, it is primarily used as a scallion or salad onion. According to the dictionary of Chinese drugs, the seeds of A. fistulosum, a traditional Chinese medicine, are used as tonic and aphrodisiac. The purpose of this study was to evaluate the protective effect of the seeds of A. fistulosum extract (SAFE) against acute myocardial ischemia. Rat and dog acute myocardial ischemia models were used, the model of acute myocardial ischemia in rats were divided into six groups: control group (saline, 10 mL·kg−1), model group (saline, 10 mL·kg−1), SAFE low, medium and high dose groups（50, 150, 300 mg·kg−1）and the positive control group (Xingling granule, 900 mg·kg−1), and the model of acute myocardial ischemia in dogs were also divided into the control group （saline, 2 mL·kg−1）, SAFE low, medium and high dose groups（15, 45, 90 mg·kg−1）and the positive control group (Xingling granule, 300 mg·kg−1). Myocardial ischemia degree was measured by epicardium electrocardiogram, the range of myocardial infarction was determined by quantitative histology （N-BT staining), and serum creatine kinase (CK）and lactate dehydrogenase（LDH) content were detected by biochemical assay. Compared with the control group, the results showed that SAFE could reduce the degree of myocardial ischemia, infarcted area, and elevation of serum CK and LDH levels in rats and dogs after coronary ligation. In conclusion, SAFE can improve acute myocardial ischemia and reduce myocardial infarction in rats and dogs, and which suggests that it can achieve prevention effects of myocardial ischemia.

Real-time perception of rock mass information is of great importance to efficient tunneling and hazard prevention in tunnel boring machines (TBMs). In this study, a TBM–rock mutual feedback perception method based on data mining (DM) is proposed, which takes 10 tunneling parameters related to surrounding rock conditions as input features. For implementation, first, the database of TBM tunneling parameters was established, in which 10,807 tunneling cycles from the Songhua River water conveyance tunnel were accommodated. Then, the spectral clustering (SC) algorithm based on graph theory was introduced to cluster the TBM tunneling data. According to the clustering results and rock mass boreability index, the rock mass conditions were classified into four classes, and the reasonable distribution intervals of the main tunneling parameters corresponding to each class were presented. Meanwhile, based on the deep neural network (DNN), the real-time prediction model regarding different rock conditions was established. Finally, the rationality and adaptability of the proposed method were validated via analyzing the tunneling specific energy, feature importance, and training dataset size. The proposed TBM–rock mutual feedback perception method enables the automatic identification of rock mass conditions and the dynamic adjustment of tunneling parameters during TBM driving. Furthermore, in terms of the prediction performance, the method can predict the rock mass conditions ahead of the tunnel face in real time more accurately than the traditional machine learning prediction methods.

Abstract Background Survival times differ among patients with advanced gastric carcinoma. A precise and universal prognostic evaluation strategy has not yet been established. The current study aimed to construct a prognostic scoring model for mortality risk stratification in patients with advanced gastric carcinoma. Methods Patients with advanced gastric carcinoma from two hospitals (development and validation cohort) were included. Cox proportional hazards regression analysis was conducted to identify independent risk factors for survival. A prognostic nomogram model was developed using R statistics and validated both in bootstrap and external cohort. The concordance index and calibration curves were plotted to determine the discrimination and calibration of the model, respectively. The nomogram score and a simplified scoring system were developed to stratify patients in the two cohorts. Results Development and validation cohort was comprised of 401 and 214 gastric cancer patients, respectively. Mucinous or non-mucinous histology, ECOG score, bone metastasis, ascites, hemoglobin concentration, serum albumin level, lactate dehydrogenase level, carcinoembryonic antigen level, and chemotherapy were finally incorporated into prognostic nomogram. The concordance indices were 0.689 (95% CI: 0.664 ~ 0.714) and 0.673 (95% CI: 0.632 ~ 0.714) for bootstrap and external validation. 100 and 200 were set as the cut-off values of nomogram score, patients in development cohort were stratified into low-, intermediate- and high-risk groups with median overall survival time 15.8 (95% CI: 12.2 ~ 19.5), 8.4 (95% CI: 6.7 ~ 10.2), and 3.9 (95% CI: 2.7 ~ 5.2) months, respectively; the cut-off values also worked well in validation cohort with different survival time in subgroups. A simplified model was also established and showed good consistency with the nomogram scoring model in both of development and validation cohorts. Conclusion The prognostic scoring model and its simplified surrogate can be used as tools for mortality risk stratification in patients with advanced gastric carcinoma.

Internal combustion engines consuming fossil fuels produce roughly one-quarter of the world’s anthropogenically generated power. In automobiles, over 50% of the fuel’s energy is dissipated as waste heat. Exhaust heat and jacket water heat are good candidates for waste heat recovery applications. To recover reusable energy from exhaust gases and coolant, water-steam-assist technology has been proposed and established based on an in-cylinder steam-assisted cycle. In this paper, typical water-based waste heat recovery technologies are reviewed and analysed, including the Rankine, Kalina and trilateral cycles. Relevant studies on water-steam-assist implementation are reviewed, and a novel thermodynamic cycle named the in-cylinder steam-assisted cycle is proposed based on their common features. The main characteristics of this cycle are compared with those of previous techniques in terms of principles, parameters, merits and demerits, and development trends. The analysis shows that water-steam-assist technology has the potential to increase engine efficiency considerably. This work helps elaborate the utilization of this waste heat recovery technology in automobiles and provides a comprehensive overview of its mechanisms.

Abstract Background To evaluate whether the addition of taxanes to platinum and fluoropyrimidines in adjuvant chemotherapy would result in longer survival than platinum plus fluoropyrimidines in gastric cancer patients who received D2 gastrectomy. Methods Data of patients with gastric adenocarcinoma who received D2 gastrectomy and adjuvant chemotherapy with platinum plus fluoropyrimidines or taxanes, platinum plus fluoropyrimidines was retrospectively collected and analyzed. 1:1 Propensity score matching analysis was used to balance baseline characteristics between two groups. Survival curves were estimated using Kaplan-Meier method, and the differences were compared using the log-rank test. Results Four hundred twenty-five patients in the platinum plus fluoropyrimidines group and 177 patients in the taxanes, platinum plus fluoropyrimidines group were included into analysis. No statistical differences in disease-free survival and overall survival were observed between two groups. After propensity score matching, 172 couples of patients were matched, the baseline characteristics were balanced. The median disease-free survival were 15.8 months (95% CI, 9.3~22.4) in the platinum plus fluoropyrimidines group and 22.6 months (95% CI, 15.9~29.4) in the taxanes, platinum plus fluoropyrimidines group (HR = 0.63; 95% CI, 0.48~0.85; P = 0.002). The median overall survival was 25.4 months for patients in the platinum plus fluoropyrimidines group (95% CI, 19.4~31.3) and 33.8 months (95% CI, 23.5~44.2) for those in the taxanes, platinum plus fluoropyrimidines group (HR = 0.68; 95% CI, 0.53-0.87; log-rank test, P = 0.002). Conclusions For gastric adenocarcinoma patients, the adjuvant triplet combination of taxanes, platinum, and fluoropyrimidines regimen after D2 gastrectomy was superior to platinum plus fluoropyrimidines regimen in disease-free survival as well as overall survival. Trial registration This project has been registered in the Chinese Clinical Trial Registry ( ChiCTR1800019978 ).

Herein, a combined multipoint picking scheme was proposed, and the sizes of the end of the bud picker were selectively designed. Firstly, the end of the bud picker was abstracted as a fixed-size picking box, and it was assumed that the tea buds in the picking box have a certain probability of being picked. Then, the picking box coverage and the greedy algorithm were designed to make as few numbers of picking box set as possible to cover all buds to reduce the numbers of picking. Furthermore, the Graham algorithm and the minimum bounding box were applied to fine-tune the footholds of each picking box in the optimal coverage picking box set, so that the buds were concentrated in the middle of the picking boxes as much as possible. Moreover, the geometric center of each picking box was taken as a picking point, and the ant colony algorithm was used to optimize the picking path of the end of the bud picker. Finally, by analyzing the influence of several parameters on the picking performance of the end of the bud picker, the optimal sizes of the picking box were calculated successfully under different conditions. The experimental results showed that the average picking numbers of the combined multipoint picking scheme were reduced by 31.44%, the shortest picking path was decreased by 11.10%, and the average consumed time was reduced by 50.92% compared to the single-point picking scheme. We believe that the proposed scheme can provide key technical support for the subsequent design of intelligent bud-picking robots.

Gasoline–water mixed injections are of great interest because of their advantages for reduced manufacturing costs and improved atomization, with the potential to alleviate engine detonation and reduce emissions. In this work, based on the principle of impinging flow, a real-time gasoline–water mixture preparation system for internal combustion engines was designed and the preparation system performance was compared with the standard swirl mixing technique. An image processing method was established to quantify the uniformity of the prepared mixture. Based on the flash-boiling spray flash-boiling spray experiment, the spray characteristics of different gasoline–water mixtures were analyzed under different injection temperatures (30–160 °C) and pressures (5–15 MPa). The experiments showed that the impinging pressure was the main factor affecting the emulsification performance of the real-time gasoline–water mixture, and that the proposed real-time mixing system could produce a stable gasoline–water emulsion. For temperatures in the 30–160 °C range, the flash-boiling spray flash-boiling spray experiments showed that the spray penetration distance first decreases and then increases with the injection temperature, while the spray angle shows an opposite trend. The turning point corresponded to the flash-boiling point of each gasoline–water mixture.

Low-temperature stress limits global tea planting areas and production efficiency. Light is another essential ecological factor that acts in conjunction with temperature in the plant life cycle. However, it is unclear whether the differential light environment affects the low temperature adaptability of tea plant (Camellia sect. Thea). In this study, tea plant materials in three groups of light intensity treatments showed differentiated characteristics for low-temperature adaptability. Strong light (ST, 240 μmol·m−2·s−1) caused the degradation of chlorophyll and a decrease in peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), and polyphenol oxidase (PPO) activities, as well as an increase in soluble sugar, soluble protein, malondialdehyde (MDA), and relative conductivity in tea leaves. In contrast, antioxidant enzyme activities, chlorophyll content, and relative conductivity were highest in weak light (WT, 15 μmol·m−2·s−1). Damage was observed in both ST and WT materials relative to moderate light intensity (MT, 160 μmol·m−2·s−1) in a frost resistance test. Chlorophyll degradation in strong light was a behavior that prevented photodamage, and the maximum photosynthetic quantum yield of PS II (Fv/Fm) decreased with increasing light intensity. This suggests that the browning that occurs on the leaf surface of ST materials through frost may have been stressed by the previous increase in reactive oxygen species (ROS). Frost intolerance of WT materials is mainly related to delayed tissue development and tenderness holding. Interestingly, transcriptome sequencing revealed that stronger light favors starch biosynthesis, while cellulose biosynthesis is enhanced in weaker light. It showed that light intensity mediated the form of carbon fixation in tea plant, and this was associated with low-temperature adaptability.

Abstract Background The risk of stroke in individuals with very low low-density lipoprotein cholesterol (LDL-C) concentrations remains high. We sought to prioritize predictive risk factors for stroke in Chinese participants with LDL-C concentrations

Ambient atmospheric aerosol particles comprised of various inorganic and organic substances ubiquitously undergo phase transition, such as efflorescence, amorphization, and especially liquid-liquid phase separation (LLPS). Resultant changes of physicochemical properties in aerosols then deeply affect the climate system. However, finely detecting these processes occurring in single aerosol particles, especially under the acidic condition of real atmospheric environment, remains a challenge. In this work, we investigated the pH-dependent phase separation in single levitated microdroplets using a self-developed laser tweezers Raman spectroscopy (LTRS) system. The dynamic process of LLPS in laser-trapped droplets over the course of humidity cycles was detected with the time-resolved cavity-enhanced Raman spectra. These measurements provide the first comprehensive account of the pH-dependent LLPS in single levitated aerosol microdroplets and bring possible implications on phase separation in actual atmospheric particles.

In this study, chitosan(CS), nano-silicon aerogels(nSA) and tea polyphenols(TP) were used as film-forming materials and processed with ultrasonication to form films using the tape-casting method. The effects of ultrasonication time, temperature and frequency on the properties of CS/nSA/TP film were explored via material property testing. The results of response surface showed that the maximum tensile strength of the film was 4.036 MPa at ultrasonication time(57.97 min), temperature(37.26 °C) and frequency(30 kHz). The maximum elongation at break of the film was 279.42 % at ultrasonication time(60.88 min), temperature(39.93 °C) and frequency(30 kHz). Due to cavitation and super-mixing effects, ultrasonication may make the surface of the film smoother and easier to degrade. After ultrasonication, TPs were protected by the 3D network structure composed of CS and nSA. Ultrasonication improved the antioxidant and antibacterial properties of the film. These results show that ultrasonication is an effective method to improve the properties of films.

Abstract Background Polygonum cuspidatum Sieb. et Zucc. is a well-known medicinal plant whose pharmacological effects derive mainly from its stilbenes, anthraquinones, and flavonoids. These compounds accumulate differentially in the root, stem, and leaf; however, the molecular basis of such tissue-specific accumulation remains poorly understood. Because tissue-specific accumulation of compounds is usually associated with tissue-specific expression of the related biosynthetic enzyme genes and regulators, we aimed to clarify and compare the transcripts expressed in different tissues of P. cuspidatum in this study. Results High-throughput RNA sequencing was performed using three different tissues (the leaf, stem, and root) of P. cuspidatum. In total, 80,981 unigenes were obtained, of which 40,729 were annotated, and 21,235 differentially expressed genes were identified. Fifty-four candidate synthetase genes and 12 transcription factors associated with stilbene, flavonoid, and anthraquinone biosynthetic pathways were identified, and their expression levels in the three different tissues were analyzed. Phylogenetic analysis of polyketide synthase gene families revealed two novel CHS genes in P. cuspidatum. Most phenylpropanoid pathway genes were predominantly expressed in the root and stem, while methylerythritol 4-phosphate and isochorismate pathways for anthraquinone biosynthesis were dominant in the leaf. The expression patterns of synthase genes were almost in accordance with metabolite profiling in different tissues of P. cuspidatum as measured by high-performance liquid chromatography or ultraviolet spectrophotometry. All predicted transcription factors associated with regulation of the phenylpropanoid pathway were expressed at lower levels in the stem than in the leaf and root, but no consistent trend in their expression was observed between the leaf and the root. Conclusions The molecular knowledge of key genes involved in the biosynthesis of P. cuspidatum stilbenes, flavonoids, and anthraquinones is poor. This study offers some novel insights into the biosynthetic regulation of bioactive compounds in different P. cuspidatum tissues and provides valuable resources for the potential metabolic engineering of this important medicinal plant.