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Errors are ubiquitous under the influence of multifarious uncertain factors in real traffic, causing information that used to regulate the mobility of connected automated vehicles (CAVs) to be inconsistent with true information, which provoke concerns on CAVs platoon performance. To date, due to the lack of appropriate model and analytical methodology, our understanding of influence mechanisms of various information errors on CAVs and the resulting anomalous platoon dynamics remains limited. Therefore, this study develops a comprehensive framework to fill these gaps. First, we expound the possible information errors in CAVs, upon which we categorize them into three types: source error, transmission error, and latency error. Second, we formulate a generic bi-layer architecture model with dynamical information flow topology, incorporating the information with errors from both of vehicular and communication layers, so as to describe the longitudinal dynamics of CAVs with information errors. Third, we derive the closed-loop and pseudo string stability conditions of CAVs platoon in the presence of information errors. Final, we perform extensive numerical simulations to exposit the effects of three types of information errors on CAVs platoon dynamics. The results show that information errors may cause deteriorated platoon stability, oscillations, reduced traffic efficiency, wasted road resources, and even collision accidents, which undoubtedly degrade the platoon performance. Overall, this study uncovers how different types of information errors influence the individual behaviors of CAVs and thus the longitudinal dynamics evolution of platoon, laying foundation to establish corresponding anomaly detection and counteracting control methods.

A novel gate-all-around (GAA) nanosheet field-effect transistor (NSFET) with bottom p-i-n isolation is proposed for the first time, which can effectively suppress the parasitic subchannel leakage through introducing a reverse-biased p-i-n subtunnel FET (TFET) channel. By combining the advantages of GAA MOS channel and sub-TFET channel, the proposed NSFET with bottom p-i-n isolation scheme can reduce off leakage current to the same level as NSFET with full bottom dielectric isolation (BDI) scheme, exhibiting superior process compatibility and excellent immunity to process variations at the same time. Performance benchmarking in terms of both static power consumption and power delay product of bottom p-i-n NSFETs compared to full BDI NSFETs and PTS NSFETs has been carried out to assess the device performance for low-power operation.

Lenvatinib is a multiple receptor tyrosine kinases inhibitor (TKI) authorized for first-line treatment of hepatocellular carcinoma (HCC). However, Lenvatinib resistance is common in HCC clinical treatment, highlighting the urgent need to understand mechanisms of resistance. Here, we identified Golgi membrane protein 1 (GOLM1), a type II transmembrane protein originally located in the Golgi apparatus, as a novel regulator of Lenvatinib resistance. We found GOLM1 was overexpressed in Lenvatinib resistant human HCC cell lines, blood and HCC samples. Additionally, GOLM1 overexpression contributes to Lenvatinib resistance and HCC progression in vitro and in vivo. Mechanistically, GOLM1 upregulates CSN5 expression through EGFR-STAT3 pathway. Reversely, CSN5 deubiquitinates and stabilizes GOLM1 protein by inhibiting ubiquitin-proteasome pathway of GOLM1. Furthermore, clinical specimens of HCC showed a positive correlation between the activation of the GOLM1-EGFR-STAT3-CSN5 axis. Finally, GOLM1 knockdown was found to act in synergy with Lenvatinib in subcutaneous and orthotopic mouse model. Overall, these findings identify a mechanism of resistance to Lenvatinib treatment for HCC, highlight an effective predictive biomarker of Lenvatinib response in HCC and show that targeting GOLM1 may improve the clinical benefit of Lenvatinib.

In soil-rice systems, microbial reduction of iron (Fe) has been recognized as a crucial biogeochemical process that regulates Fe and chromium (Cr) translocation; however, the underlying processes are unknown. To investigate the impacts of biochar on the biochemical cycling of Fe and Cr and their toxicity to rice, maize straw biochar was applied at 1% (weight/weight) to a paddy soil spiked with 300 mg kg-1Cr under two phosphorus (P) levels (0 or 90 mg kg-1) in a pot experiment. The key microbial groups affecting Fe dissimilatory reduction and their environmental drivers were explored. Biochar inhibited root Cr uptake by 36%, owing to the promoted iron plaque (IP) formation on the rice root surface. Correlation analysis showed that Fe concentration in pore water was strongly linked to the abundances of Geobacter(r= 0.81–0.94, P< 0.05) and Clostridium(r= 0.83–0.95, P< 0.05), indicating that Geobacterand Clostridiumplayed essential roles in Fe reduction. Redundancy analysis showed that labile carbon and pore water P concentrations were the key determinants influencing Fe-reducing bacterial abundances, accounting for 42% and 32% of the variation in community composition, respectively. Besides, biochar increased Fe and P concentrations in root cell walls, which retained more Cr. Overall, Cr stress in rice under biochar treatment was relieved through increasing IP formation and altering subcellular distribution. These mechanistic insights had important implications for reducing Cr uptake by rice.

Alkali activation at high temperatures serves as a significant method for the resource reuse of coal gasification fine slag (CGFS). This experimental approach used CGFS, coal-based solid waste, to prepare multifunctional materials and neither waste acid nor alkali was discharged in the process. Using this method, MCM-41 with hexagonal mesopores and carbon/zeolite composite with NaP-type zeolite structures were prepared hierarchically. It is noteworthy that this synthetic method incorporates Al from CGFS into MCM-41, which enhances the acidic sites of the material. This modification endows MCM-41 with potential application in catalyzing guaiacol. Under the same conditions, CGFS-based MCM-41 demonstrated the capacity to convert guaiacol into cyclohexane. In contrast, commercial MCM-41 exhibited the ability to catalyze the conversion of guaiacol into cyclohexanol and cyclohexane. At the same time, the carbon/zeolite composite retains the Fe in CGFS and can be used for the catalytic oxidative degradation of tetracycline. The carbon/zeolite composite was able to degrade 100 mL of 100 mg‧L−1tetracycline solution by 99.38 % in 120 min at dose of 30 mg, an H2O2concentration of 25 mmol‧L−1and solution pH of 3. This research outlines a promising approach for the innovative concept of "turning waste into treasure."

To investigate the causal effect of protein intake on hypertension and the related mediating pathways.

Adsorption solar thermal energy storage and heat transformation are ecologically benign and energy-efficient technologies. Efficient adsorbents are the key to this technology. In this paper, two metal ions, Mg2+and Ni2+, were introduced into the metal–organic framework MOF-74. The synthesis conditions were adjusted to obtain MOF-74 with a high water adsorption capacity and stability. The results show that MOF-74-MgNi-2 has the maximum water adsorption capacity. At a low moisture pressure P/P0= 0.1, its water adsorption capacity is 0.44 g/g, 0.12 g/g, and 0.10 g/g greater than that of MOF-74-Mg and MOF-74-Ni, respectively. Its saturated water adsorption capacity at P/P0= 0.9 is as high as 0.62 g/g, which is 1.3 times that of MOF-74-Ni and 1.1 times that of MOF-74-Mg, respectively. Its superior water adsorption capacity is explained by the combination of experiment and molecular simulation, which takes into account the pore structure and electrostatic potential energy distribution. Its thermal breakdown temperature is greater than 250 °C. Its water adsorption capacity decreases by only 9.0% in the 10th cycle. Under conventional refrigeration conditions, its refrigeration coefficient and working capacity are 0.75 and 0.43 cm3/cm3, respectively, which are greater than those of the majority of the regularly used adsorbents. In addition, it satisfies the primary technological goals of adsorption-based thermal batteries with a heat storage capacity of up to 1394 kJ/kg. The mixed-metal method is shown to be useful in the design of high-performance MOF-74 for solar thermal energy storage and heat transformation.

Regulation of the two-photon excited fluorescence (TPEF) emission intensity and wavelength of metal–organic framework (MOF) crystals with similar constitutions presents a significant challenge. In this study, two MOFs, Zn–BTPPA and Cd3–BTPPA, were constructed using tetrakis(1,1′-biphenyl-4-carboxylic acid)-1,4-benzenediamine (H4BTPPA) as the organic ligand and mononuclear Zn and trinuclear Cd3inorganic nodes, respectively. The incorporation of H4BTPPA within the MOF structures enables effective TPEF emission in both Zn–BTPPA and Cd3–BTPPA. The TPEF results show that Zn–BTPPA and Cd3–BTPPA exhibited strong emissions at 523 and 463 nm, respectively, when excited with a 780 nm laser. Moreover, Zn–BTPPA and Cd3–BTPPA exhibited much higher two-photon absorption cross sections, approximately 4.9 and 5.2 times higher than that of the reported dinuclear MOF, Cd2–BTPPA, with a similar composition, respectively. With different inorganic nodes, the stacking of chromophores, π···π interactions, and ligand geometry were found to correlate with the enhanced TPEF in Cd3–BTPPA and the blue-shifted TPEF in Zn–BTPPA. This work serves as an inspiration for designing efficient TPEF MOF materials based on the structure–property relationship.

Acinetobacter baumannii, a commonly multidrug-resistant Gram-negative bacterium responsible for large numbers of bloodstream and lung infections worldwide, is increasingly difficult to treat and constitutes a growing threat to human health. Structurally novel antibacterial chemical matter that can evade existing resistance mechanisms is essential for addressing this critical medical need. Herein, we describe our efforts to inhibit the essential A. baumanniilipooligosaccharide (LOS) ATP-binding cassette (ABC) transporter MsbA. An unexpected impurity from a phenotypic screening was optimized as a series of dimeric compounds, culminating with 1(cerastecin D), which exhibited antibacterial activity in the presence of human serum and a pharmacokinetic profile sufficient to achieve efficacy against A. baumanniiin murine septicemia and lung infection models.

State estimation (SE) plays a crucial role in the monitoring of smart grids. However, as an important cyber-physical system (CPS), smart grid is currently facing various anomalies that pose a serious threat to the accuracy of the state estimation process. This paper proposes a new framework named Grid2Vec (Grid To Vector) for detecting abnormal types in the power system based on graph representation learning. The proposed method involves constructing a statement sequence using a random walk of nodes on the power system graph and training a classification neural network by optimizing the node vector. The trained network can then accurately determine the type of anomaly present in the power system. The proposed Grid2Vec model is scalable to large-scale graph networks and can improve learning efficiency through parallel walking. The effectiveness of the proposed model was verified through numerical experiments conducted on real power systems. The results indicate that the Grid2Vec model exhibits high precision and efficiency in detecting several fault types amongst diverse noise and assault scenarios. It achieves an average detection accuracy of 100.00%, 99.97%, 99.49%, and 99.21%. The level of precision demonstrated is notably superior to the relative error attained by current methodologies.

Precipitation plays a crucial role in the water cycle of Northwest China. Obtaining accurate precipitation data is crucial for regional water resource management, hydrological forecasting, flood control and drought relief. Currently, the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated. In this study, precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products (the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5), Global Precipitation Climatology Centre (GPCC), Climatic Research Unit gridded Time Series Version 4.07 (CRU TS v4.07, hereafter CRU), and Tropical Rainfall Measuring Mission (TRMM)) based on the following statistical indicators: correlation coefficient, root mean square error (RMSE), relative bias (RB), mean absolute error (MAE), probability of detection (POD), false alarm ratio (FAR), and equitable threat score (ETS). The results showed that precipitation in Northwest China was generally high in the east and low in the west, and exhibited an increasing trend from 1979 to 2020. Compared with the station observations, ERA5 showed a larger spatial distribution difference than the other products. The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity. The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations. The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation. At the monthly scale, GPCC performed well but underestimated precipitation in the Tarim Basin (RB= −4.11%), while ERA5 and TRMM exhibited poor accuracy in high-altitude regions. ERA5 had a large bias (RB≥120.00%) in winter months and a strong dispersion (RMSE≥35.00 mm) in summer months. TRMM showed a relatively low correlation with station observations in winter months (correlation coefficients ≤0.70). The capture performance analysis showed that ERA5, GPCC, and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased. ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased. GPCC had the lowest FAR values. TRMM was statistically ineffective for predicting the occurrence of daily precipitation events. The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.

Heavy metal pollution has become an increasingly prominent problem. Consequently, adsorbents with high heavy metal removal efficiency using a convenient synthesis method have to be developed urgently. The magnesium carbonate hydroxide microsheets modified activated carbon fiber (MCH@ACF) was prepared by a facile in situ hydrothermal method. The results of the characteristic of MCH@ACF indicated that a large amount of magnesium carbonate hydroxide porous microsheets is densely arranged on the surface of ACF. The Mn2+, Cu2+, Pb2+, and Cr2O72−ions adsorption kinetics of the MCH@ACF could be fitted with the pseudo-second-order model, and the results indicate the fast adsorption rate. The Mn2+, Cu2+, and Pb2+ions adsorption on the MCH@ACF follow the Langmuir model, while the Cr2O72−adsorption on the MCH@ACF follows the Freundlich model. The theoretical adsorption capacity of the Mn2+, Cu2+, Pb2+, and Cr2O72−ions on the MCH@ACF is 558.6 mg/g, 1591.7 mg/g, 1802.8 mg/g, and 125.7 mg/g, respectively. The heavy metal ions removal performance of MCH@ACF under different pH conditions has been studied. Furthermore, the adsorption mechanism could be ascribed to the binding of heavy metal ions with carbonate or hydroxyl group. The results indicated that the MCH@ACF can be used as the potential suitable candidate for heavy metal removal.

C32H30ClCoN5O8S, monoclinic, P21/c(no. 14), a= 14.5008(9) Å, b= 13.6648(9) Å, c= 17.9741(12) Å, β= 113.086(2)°, V= 3276.4(4) Å3, Z= 4, Rgt(F) = 0.0620, wRref(F2) = 0.1696, T= 293(2) K.

Object parts serve as crucial intermediate representations in various downstream tasks, but part-level representation learning still has not received as much attention as other vision tasks. Previous research has established that Vision Transformer can learn instance-level attention without labels, extracting high-quality instance-level representations for boosting downstream tasks. In this paper, we achieve unsupervised part-specific attention learning using a novel paradigm and further employ the part representations to improve part discovery performance. Specifically, paired images are generated from the same image with different geometric transformations, and multiple part representations are extracted from these paired images using a novel module, named PartFormer. These part representations from the paired images are then exchanged to improve geometric transformation invariance. Subsequently, the part representations are aligned with the feature map extracted by a feature map encoder, achieving high similarity with the pixel representations of the corresponding part regions and low similarity in irrelevant regions. Finally, the geometric and semantic constraints are applied to the part representations through the intermediate results in alignment for part-specific attention learning, encouraging the PartFormer to focus locally and the part representations to explicitly include the information of the corresponding parts. Moreover, the aligned part representations can further serve as a series of reliable detectors in the testing phase, predicting pixel masks for part discovery. Extensive experiments are carried out on four widely used datasets, and our results demonstrate that the proposed method achieves competitive performance and robustness due to its part-specific attention.

Long-chain free fatty acids (FFAs) are associated with risk of incident diabetes. However, a comprehensive assessment of the associations in normoglycemic populations is lacking.

Background: Inhibitor of DNA Binding 2 (ID2) plays a crucial role in tumor cell proliferation, invasion, metastasis, and stemness. Aberrant ID2 expression is associated with poor prognosis in various cancers. However, the specific function of ID2 in thyroid cancer remain unclear. Method: The TCGA database were utilized to explore the clinical relevance of ID2 in cancer. GO, KEGG, and TIMER were employed to predict the potential roles of ID2 in cancer. Functional analysis, including CCK-8, colony formation, transwell, wound healing, and sphere formation experiments, were conducted to determine the biological functions of ID2 in human cancers. Western blot (WB), RT-qPCR, and immunohistochemical (IHC) analyses were used to investigate the relationship between ID2 and downstream targets. Results: Our study revealed significant overexpression of ID2 in various malignant tumor cells. Knocking ID2 significantly inhibited cancer cell proliferation and invasion, while overexpressing ID2 enhanced these capabilities. Additionally, ID2 mediates resistance of cancer cells to protein kinase B (or Akt) inhibitions. Further WB and IHC experiments indicated that ID2 promotes the phosphorylation activation of phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway, thereby upregulating the expression of downstream proliferation, epithelial-mesenchymal transition (EMT), and stemness-related markers. Conclusion: We found that ID2 significantly promotes thyroid cancer cell proliferation, migration, EMT, and stemness through the PI3K/Akt pathway. Moreover, ID2 plays a crucial role in regulating cancer immune responses. It may serve as a potential biomarker for enhancing the efficacy of chemotherapy, targeted therapy, and immunotherapy against cancer.

Despite the excellent performance of Nb3O7(OH) in dye-sensitized solar cells and catalysis, its charge separation, transport, and structural properties remain poorly understood. Herein, the Nb3O7(OH) nanorods were prepared, and their structural characteristics, optoelectronic properties, and carrier mobility were also analyzed and investigated through a series of complex characterizations. Theoretical prediction suggested that the exciton binding energy of Nb3O7(OH) could be as high as 100.49 meV. The temperature-dependent photoluminescence (PL) of Nb3O7(OH) nanorods revealed two activation energies, and a higher proportion of long-lived components observed in the photoluminescence decay indicated effective electron trapping. That is, two energy states were present, hindering photogenerated charge recombination and promoting photocatalytic action. Current–voltage characteristics of the Nb3O7(OH) nanorod film were analyzed, revealing an ultrahigh carrier mobility of ∼310 cm2/V·s, ensuring fast and efficient electron transfer. Furthermore, Nb3O7(OH) nanorods were employed to reduce CO2, resulting in the effective production of CO and CH4. Overall, considering the presence of hydroxyl pairs on the surface of Nb3O7(OH), which facilitate the formation of the frustrated Lewis acid–base pairs and the activation of CO2, together with its effective electron trapping and charge transport, give Nb3O7(OH) nanorods a promising potential for CO2reduction.

Pixian broad bean paste (PBP) is a popular fermentation condiment known in home and abroad. Aroma is a significant index for evaluating PBP quality during fermentation process. Hence, in this study, electronic nose (E-nose) system combined machine learning methods were applied for PBP quality characterization. The machine learning methods including partial least squares discriminant analysis (PLS-DA), partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and artificial neural networks (ANN) were introduced for qualitatively discriminating fermentation time and quantitatively analyzing the contents of key aromas of PBP samples. The PLS-DA result indicated that it is feasible to identify the fermentation stages of PBP samples by E-nose and a classification accuracy of 99% could be achieved. As for the quantitative prediction modelling, ANN exhibited preferable performance than PLSR, SVM and RF for analyzing the contents of phenethyl alcohol (R2= 0.846, RMSE = 10.270), isoamyl alcohol (R2= 0.940, RMSE = 6.857), 3-methylthiopropanol (R2= 0.910, RMSE = 2.205), benzaldehyde (R2= 0.824, RMSE = 4.172), furfural (R2= 0.902, RMSE = 2.066), 4-ethyl guaiacol (R2= 0.877, RMSE = 11.249) and 4-ethylphenol (R2= 0.913, RMSE = 12.754).

At present, lignin fiber widely used in asphalt mixture is derived from logs, and its large-scale production will consume a lot of forest resources. Bamboo is a good substitute for lignin fiber because of its rapid growth characteristic and good physical and mechanical properties. To evaluate the freeze–thaw cycle durability of bamboo fiber asphalt mixture, using AC-13, AC-16, SMA-13 and SMA-16 gradation schemes, the freeze–thaw resistance of bamboo fiber asphalt mixture was studied by splitting test under different freeze–thaw cycles. Non-fiber asphalt mixture and lignin fiber asphalt mixture were used as control group. Based on the reliability and damage theory, the freeze–thaw damage evolution model was established, the freeze–thaw damage characteristics of bamboo asphalt mixtures were analyzed, and a method for estimating the freeze–thaw damage residual life of bamboo fiber asphalt mixture was proposed. The results show that bamboo fiber and lignin fiber have basically the same improvement effect on the freeze–thaw cycle durability of asphalt mixture. The freeze–thaw cycle durability of stone mastic asphalt (SMA) gradation mixture is better than that of asphalt concrete (AC) gradation mixture. The freeze–thaw damage evolution model can better reflect the freeze–thaw damage characteristics and damage evolution law of bamboo fiber asphalt mixture. The actual freeze–thaw time corresponding to the splitting strength damage degree of bamboo fiber asphalt mixture up to 25% can be taken as its anti-freeze–thaw life.

The effects of the interaction between polygenes and the parent–child relationship on junior high school students' aggressive behaviors were explored through the frameworks of gene‐endophenotype‐behavior and neurophysiological basis. A total of 892 junior high school students participated in this study. They were asked to complete self‐reported questionnaires, and saliva samples were collected. Results showed that 5‐HTTLPR, MAOA‐uVNTR, COMT (rs4680), and Taq1 (rs1800497) of the DRD2 gene affected students' aggressive behaviors in an accumulative way. The polygenic risk score explained 3.4% of boys' aggression and 1.1% of girls' aggression. The interactions between polygenic risk score and parent–child conflict significantly affected the aggressive behaviors of male students, but did not show any significant effect on those of female students. The interactional effect of polygenic risk score and parent–child conflict on junior high school students' aggressive behaviors was completely mediated by frustration. However, the interaction effect of polygenic risk score and parent–child affinity on aggression was not affected by frustration. This study helps us better understand junior high school students' aggressive behaviors and promotes the prevention and correction of adolescents' problem behaviors.

Organophosphorus poisoning is a critical condition that can cause central nervous system depression, respiratory failure, and death early on. As its clinical manifestations closely resemble those of carbamate pesticide poisoning, the aim of this case study is to present a case of misdiagnosis, initially identifying carbofuran poisoning as organophosphate in a patient suspect of a heatstroke. We also present a case of intentional self-poisoning with organophosphate dichlorvos to underline the likelihood of pesticide poisoning in patients exhibiting acute cholinergic symptoms when the ingested substance is not known. In such cases, empirical treatment with atropine and oxime can be started pending timely differential diagnosis to adjust treatment as necessary.

Ionogels have great potential for the development of tissue-like, soft, and stretchable ionotronics. However, conventional isotropic ionogels suffer from poor mechanical properties, low efficient force transmission, and tardy mechanoelectric response, hindering their practical utility. Here, we propose a simple one-step method to fabricate bioinspired anisotropic nanocomposite ionogels based on a combination of strain-induced phase separation and mechanomodulation of ionic conduction in the presence of attapulgite nanorods. These ionogels show high stretchability (747.1% strain), tensile strength (6.42 MPa), Young’s modulus (83.49 MPa), and toughness (18.08 MJ/m3). Importantly, the liquid crystalline domain alignment-induced microphase separation and ionic conductivity enhancement during stretching endow these ionogels with an unusual mechanoelectric response and dual-programmable shape-memory properties. Moreover, the anisotropic structure, good elasticity, and unique resistance–strain responsiveness give the ionogel-based strain sensors high sensitivity, rapid response time, excellent fatigue resistance, and unique waveform-discernible strain sensing, which can be applied to real-time monitoring of human motions. The findings offer a promising way to develop bioinspired anisotropic ionogels to modulate the microstructure and properties for practical applications in advanced ionotronics.

C35H29CuN7O11S2, triclinic, P1‾$P\overline{1}$ (no. 2), a= 12.2643(9) Å, b= 13.3486(9) Å, c= 13.5247(11) Å, α= 69.595(7)°, β= 71.363(7)°, γ= 67.275(7)°, V= 1869.8(3) Å3, Z= 2, Rgt(F) = 0.0570, wRref(F2) = 0.1781, T= 293(2) K.