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Objective: This study investigated the clinical characteristics and pregnancy outcomes of acute pancreatitis during pregnancy (APIP). Methods: A retrospective analysis was conducted on 20 cases of APIP admitted to Hubei Maternal and Child Health Hospital from January 2017 to September 2021. The etiology, clinical manifestations, and perinatal outcomes of APIP were analyzed using descriptive statistical analysis of the collected data. Results: The incidence of APIP in our hospital was 20 (0.02%) cases, all of which occurred in the late stage of pregnancy. Hypertriglyceridemic acute pancreatitis (HTG‐AP) was the primary cause of APIP in 10 (50.0%) patients. A total of 11 (55.0%), seven (35.0%) and two (10.0%) patients had mild acute pancreatitis (MAP), moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP), respectively. Pregnant women with HTG‐AP had significantly elevated serum triglyceride levels, had higher prepregnancy body mass indices, were more prone to developing diabetes and were more likely to progress to SAP. With a multidisciplinary approach and individualized treatment plans, there were no maternal deaths, and fetal death only occurred in one (5.0%) case. Conclusion: HTG‐AP is prone to advancing to more severe states, and it is becoming more common every year. Therefore, blood lipid management during pregnancy should be emphasized. Pregnant women with digestive symptoms or severe hyperlipidaemia should be screened for APIP in a timely manner and receive clinical intervention to improve maternal and fetal outcomes during the perinatal period. Synopsis: Hypertriglyceridemic acute pancreatitis is the primary cause of acute pancreatitis during pregnancy, and blood lipid management during pregnancy should be emphasized. [ABSTRACT FROM AUTHOR]

Background: Immunotherapy combined with molecular targeted therapy is increasingly popular in patients with advanced hepatocellular carcinoma (HCC). However, immune-related adverse events(irAEs) brought on by immunotherapy increase the likelihood of side effects, thus it is important to look into ways to address this issue. Methods: Different metabolite patterns were established by analyzing metabolomics data in liver tissue samples from 10 patients(divided into severe and mild liver injury) before and after immuno-targeted therapy. After establishing a subcutaneous tumor model of HCC, the mice were divided into PBS group, ascorbic acid(AA) group, and anti-PD1 + tyrosine kinase inhibitor (TKI) group, anti-PD1 + TKI + AA group. Liver tissue were stained with hematoxylin-eosin staining(HE) and the content of aspartate transaminase (AST) and alanine transaminase(ALT) in blood were determined. The mechanism was confirmed by western blotting, mass cytometry, and other techniques. Results: Through metabolomics analysis, AA was significantly reduced in the sample of patients with severe liver injury caused by immuno-targeted therapy compared to patients with mild liver injury. The addition of AA in vivo experiments demonstrated a reduction in liver injury in mice. In the liver tissues of the anti-PD1 + TKI + AA group, the protein expressions of SLC7A11,GPX4 and the level of glutathione(GSH) were found to be higher compared to the anti-PD1 + TKI group. Mass cytometry analysis revealed a significant increase in the CD11b+CD44+ PD-L1+ cell population in the AA group when compared to the PBS group. Conclusions: AA could reduce liver injury by preventing hepatocyte SLC7A11/GPX4 ferroptosis and improve the immunotherapy effect of anti-PD1 by boosting CD11b+CD44+PD-L1+cell population in HCC. [ABSTRACT FROM AUTHOR]

This study proposes an efficient method for computing State Vectors in Sequence-to-Sequence (SVSeq2Seq) architecture to improve the performance of sequence data forecasting, which associates each element with other elements instead of relying only on nearby elements. First, the dependency between two elements is adaptively captured by calculating the relative importance between hidden layers. Second, tensor train decomposition is used to address the issue of dimensionality catastrophe. Third, we further select seven instantiated baseline models for data prediction and compare them with our proposed model on six real-world datasets. The results show that the Mean Square Error (MSE) and Mean Absolute Error (MAE) of our SVSeq2Seq model exhibit significant advantages over the other seven baseline models in predicting the three datasets, i.e., weather, electricity, and PEMS, with MSE/MAE values as low as 0.259/0.260, 0.186/0.285 and 0.113/0.222, respectively. Furthermore, the ablation study demonstrates that the SVSeq2Seq model possesses distinct advantages in sequential forecasting tasks. It is observed that replacing SVSeq2Seq with LPRcode and NMTcode resulted in an increase under an MSE of 18.05 and 10.11 times, and an increase under an MAE of 16.54 and 9.8 times, respectively. In comparative experiments with support vector machines (SVM) and random forest (RF), the performance of the SVSeq2Seq model is improved by 56.88 times in the weather dataset and 73.78 times in the electricity dataset under the MSE metric, respectively. The above experimental results demonstrate both the exceptional rationality and versatility of the SVSeq2Seq model for data forecasting. [ABSTRACT FROM AUTHOR]

This article discusses the emerging role of single-cell RNA sequencing (scRNA-seq) in studying cochlear aging, specifically age-related hearing loss (ARHL) or presbycusis. ARHL is a common disorder characterized by progressive hearing loss, particularly at high frequencies, and is associated with various comorbidities and economic costs. The cochlea, the auditory system's main component, is complex and consists of different cell types. Recent scRNA-seq studies have provided insights into cochlear development, noise-induced damage, and the effects of aging on specific cell types. A comprehensive scRNA-seq analysis of cochlear aging in mice has revealed cellular and molecular mechanisms associated with aging, providing a foundation for diagnostic and therapeutic strategies for ARHL. The article also highlights the importance of studying cochlear aging at the spatial level and using non-human primate models to gain a better understanding of cochlear aging in humans. [Extracted from the article]

The popularity of renewable energy distributed generation has increased for environmental and convenient concerns. However, the occurrence of the above situation will cause the communication resources of the microgrid to be rapidly consumed to maintain the frequency stability of the system. In this work, a novel event‐triggered scheme is developed to ameliorate the present communication networks of island microgrid with communication delay. Combining the newly constructed Lyapunov–Krasovskii functional and the convex combinatorial method, the asymptotic stability of a typical microgrid is demonstrated. Moreover, taking dynamic switching system into account, the two‐part proof is completed independently. Then, a positive inter‐execution time lower bound is implemented to guarantee that there is no Zeno behaviour. Finally, the numerical simulation results are compared with other sampling methods in different scenarios. It indicates that the proposed scheme is superior to other types of scheme in frequency response performance and communication burden. [ABSTRACT FROM AUTHOR]

Large macroporous structures of permeable asphalt pavement made high-viscosity asphalt (HVA) more susceptible to aging and failure. However, the standard pressure aging vessel (PAV) test was difficult to accurately emulate the long-term aging behavior of HVA. Hence, 1–5PAV aging levels of two HVAs (i.e. HVA-1 and HVA-2) were emulated by the simple aging test (SAT). Rheological analysis indicated that asphalt oxidation consistently dominated regardless of the long-term aging levels of HVAs. Combined with the fluorescence microscopy observation, HVA-2 with meticulous and uniform granular distribution was more resistant to aging than HVA-1 with coarse and continuously strip-like structures. Stress-strain curve analysis in linear amplitude sweep (LAS) test revealed that the accumulated strain energy (ASE) representing the overall mechanical properties of HVAs first increased and then decreased as the long-term aging level grew. The continuous repeated LAS (RLAS) test further reflected that the yield stress, yield strain and ASE of HVAs gradually decreased as the LAS loading number increased at initial long-term aging states; but as the sustained growth of aging level, the stress-strain curve of HVAs become increasingly chaotic until remarkable strain hardening occurred. Furthermore, RLAS-based self-healing (RLASSH) test was developed by introducing intermittent time into RLAS test. The variation of ratio of ASE decrease can characterize the self-healing performance of HVAs. RLASSH test showed that the self-healing performance of HVAs was unstable at 1–3PAV aging level, and the HVAs with 4 or 5PAV aging levels completely lost their self-healing performance. Overall, with the increase in long-term aging levels, significant differences were observed in the evolution characteristics of morphology, rheology and self-healing performances of different HVAs. This study helps to understand the rheology and self-healing performance evolution pattern of HVA during long-term service. • Performance evolution of various HVAs was totally different as long-term aging deepened. • Asphalt oxidation consistently dominated regardless of long-term aging levels of HVAs. • Stress-strain curve of HVAs become increasingly chaotic until remarkable strain hardening occurred as aging deepened. • Specific long-term thermal aging level was beneficial for HVA self-healing. [ABSTRACT FROM AUTHOR]

The objectives of this study were to investigate the relationship between the in vitro ruminal ammonia nitrogen (NH3‐N) concentration and the Cornell Net Carbohydrate and Protein System (CNCPS) N‐fractions of feeds for cattle and further compare the performance of developing multiple linear regression (MLR) and artificial neural network (ANN) models in estimating the NH3‐N concentration in rumen fermentation. Two data sets were established, of which the training data set containing forty‐five rations for cattle with concentrate/roughage ratios of 50:50, 40:60, 30:70, 20:80 and 10:90 used for developing models and the test data set containing ten other rations with the same concentrate/roughage ratios with the training data set were used for validating of models. The NH3‐N concentrations of feed samples were measured using an in vitro incubation technique. The CNCPS N‐fractions (g), for example PB1 (rapidly degraded true protein), PB2 (neutral detergent soluble nitrogen), PB3 (acid detergent soluble nitrogen) of rations, were calculated based on chemical analysis. Statistical analysis indicated that the NH3‐N concentration (mg) was significantly correlated with the CNCPS N‐fractions (g) PB1, PB2 and PB3 in a multiple linear pattern: NH3‐N = (130.70±33.80) PB1 + (155.83±17.89) PB2 ‐ (85.44±37.69) PB3 + (42.43±1.05), R2 = 0.77, p < 0.0001, n = 45. The results indicated that both MLR and ANN models were suitable for predicting in vitro NH3‐N concentration of rations using CNCPS N‐fractions PB1, PB2, and PB3 as independent variables while the neural network model showed better performance in terms of greater r2, CCC and lower RMSPE between the observed and predicted values. [ABSTRACT FROM AUTHOR]

A surveillance system with more than hundreds of cameras and much fewer monitors strongly relies on manual scheduling and inspections from monitoring personnel. A monitoring method which improves the surveillance performance by analyzing and learning from a large amount of manual operation logs is proposed in this paper. Compared to fixed rules or existing computer-vision methods, the proposed method can more effectively learn from the operators' behaviors and incorporate their intentions into the monitoring strategy. To the best of our knowledge, this method is the first to apply a monitoring-strategy recommendation model containing a global encoder and a local encoder in monitoring systems. The local encoder can adaptively select important items in the operating sequence to capture the main purpose of the operator, while the global encoder is used to summarize the behavior of the entire sequence. Two experiments are conducted on two data sets. Compared with att-RNN and att-GRU, the joint coding model in experiment 1 improves the Recall@20 by 9.4% and 4.6%, respectively, and improves the MRR@20 by 5.49% and 3.86%, respectively. In experiment 2, compared with att-RNN and att-GRU, the joint coding model improves by 11.8% and 6.2% on Recall@20, and improves by 7.02% and 5.16% on MRR@20, respectively. The results illustrate the effectiveness of the our model in monitoring systems. [ABSTRACT FROM AUTHOR]

A growing body of electricity consumers with renewable energy and demand response resources have become active prosumers who can both produce and consume energy. However, the small size of most prosumers forbids their direct participation in electricity markets. This study addresses this issue by proposing a bidding strategy for the prosumer aggregator based on a bi-level model to enable multiple prosumers to participate in day-ahead energy and reserve markets as a single entity. Here, the prosumer aggregator profit and social welfare are maximized in the upper-level and lower-level models, respectively, where the heating, ventilation, and air-conditioning system loads, residential loads, energy outputs associated with photovoltaic power generators, and energy storage systems are included. The Karush–Kuhn–Tucker condition and strong duality equalities are used to transform the proposed bi-level model into a single-level model. The effectiveness and economy of the proposed approach are demonstrated based on the numerical results obtained for a realistic test system. • We develop a bi-level model for prosumers in energy and reserve markets. • The uncertainty of renewables is accommodated by the prosumer aggregator. • The economic value of the proposed stochastic model is quantified. • The flexibility provided by a prosumer aggregator is exploited. [ABSTRACT FROM AUTHOR]

Since reform and opening, our country's sports and cultural industries have grown from nothing. Due to the complexity of the evaluation factors and methods used to determine the competitiveness of the sports cultural industry, this paper establishes a seven-dimensional sports cultural industry competition based on the integration and development of the sports tourism industry and national culture, drawing on the theory and methods used to determine the tourism industry's competitiveness. Based on a fuzzy analysis algorithm, we developed a system for evaluating strength and a model for evaluating the competitiveness of the sports culture industry. According to the results of the evaluation of the competitiveness of the sports culture industry in numerous regions of China, the evaluation method proposed in this paper is superior to the traditional evaluation method and has contributed to the development of China's sports culture industry. [ABSTRACT FROM AUTHOR]

Background. The DNA repair enzyme poly(ADP-ribose) polymerase (PARP) is involved in DNA damage repair and cell death. However, the association between PARP's biological activities and the immune microenvironment in hepatocellular carcinoma (HCC) is unclear. The present study will explore whether combining a PARP inhibitor with anti-PD1 might improve the anti-HCC impact and explain how it works. Method. The PARP inhibitor olaparib was screened out of 867 drugs through Cell Counting Kit 8 (CCK-8) assay. The expression of PARP was verified through the TCGA and TISIDB databases. The impacts exerted by PARP inhibitor olaparib to HCC cells were assessed via wound healing, Transwell, and proliferation assay. In vivo, experiments were performed in a C57BL/6 mouse model to evaluate the function of PARP inhibitor olaparib combination with anti-PD1 in HCC and mice tumors were further detected by immunohistochemically staining. Result. Olaparib was selected as the research object on the basis of drug screening. The results of the TCGA and Human Protein Atlas databases revealed that PARP was significantly upregulated in carcinoma cell cluster of HCC tissues compared to normal tissues. Higher expression of PARP showed a poorer prognosis based on Kaplan-Meier Plotter. qRT-PCR experiments confirmed that olaparib could increase PD-L1 expression through inhibiting miR-513 in HCC cells. In vivo, experiment confirmed that the combination of olaparib and anti-PD1 could enhance the immunotherapy effect of HCC. Conclusion. The present study reveals that inhibition of PARP potentiates immune checkpoint therapy through the miR-513/PD-L1 pathway in HCC and the combination of PARP inhibitor olaparib and anti-PD1 is beneficial to HCC therapy. [ABSTRACT FROM AUTHOR]

• We propose a decentralized distributionally robust optimization model for interconnected smart buildings based on P2P energy sharing. • We implement the energy sharing strategy based on the alternating direction method of multipliers. • We develop an equivalent virtual energy storage model for the energy and reserve co-dispatch of HVAC systems. • We apply the distributionally robust optimization approach to accommodate the uncertainty of renewables. The development of distributed renewable energy sources (RESs), and heating, ventilation, and air conditioning (HVAC) systems are facilitating the drive toward smart building energy operation modes, along with peer-to-peer (P2P) energy sharing and reserve co-optimization between smart buildings. However, while distributionally robust optimization (DRO) methods are ideally suited to such decentralized conditions, the application of DRO methods within P2P environments and the co-optimization of operationally flexible HVAC systems for providing additional energy reserves within smart building clusters remain poorly developed. This paper addresses this issue by proposing a decentralized DRO model for smart building clusters. The P2P energy sharing strategy is implemented in a fully decentralized manner based on an alternating direction method of multipliers algorithm, and a virtual energy storage model of HVAC systems is established for implementing the co-optimization of energy and reserve between buildings. Finally, the DRO approach is applied to accommodate uncertainties in RES outputs and thereby obtain a worst-case expected total cost. The DRO model is solved by its reformulation into a tractable second-order cone program by applying linear decision rules and second-order cone duality. The effectiveness and economy of the proposed approach are demonstrated by its simulated application to a representative building cluster consisting of three smart buildings. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disease with no cure. Huge efforts have been made to develop anti‐AD drugs in the past decades. However, all drug development programs for disease‐modifying therapies have failed. Possible reasons for the high failure rate include incomplete understanding of complex pathophysiology of AD, especially sporadic AD (sAD), and species difference between humans and animal models used in preclinical studies. In this study, sAD is modeled using human induced pluripotent stem cell (hiPSC)‐derived 3D brain organoids. Because the blood–brain barrier (BBB) leakage is a well‐known risk factor for AD, brain organoids are exposed to human serum to mimic the serum exposure consequence of BBB breakdown in AD patient brains. The serum‐exposed brain organoids are able to recapitulate AD‐like pathologies, including increased amyloid beta (Aβ) aggregates and phosphorylated microtubule‐associated tau protein (p‐Tau) level, synaptic loss, and impaired neural network. Serum exposure increases Aβ and p‐Tau levels through inducing beta‐secretase 1 (BACE) and glycogen synthase kinase‐3 alpha / beta (GSK3α/β) levels, respectively. In addition, single‐cell transcriptomic analysis of brain organoids reveals that serum exposure reduced synaptic function in both neurons and astrocytes and induced immune response in astrocytes. The human brain organoid‐based sAD model established in this study can provide a powerful platform for both mechanistic study and therapeutic development in the future. [ABSTRACT FROM AUTHOR]

Due to the excellent shear deformation resistance of high-viscosity polymer-modified bitumen (HVPMB), the traditional methods based on time sweep and linear amplitude sweep (LAS) had problems with insufficient damage accumulation and inability to disrupt the integrity of HVPMB, making it difficult to accurately evaluate its fatigue and healing characteristics. To solve this problem, this study developed an effective evaluation proposal called continuous multiple LAS (MLAS) test and MLAS-based healing (MLASH) test. One base bitumen and three HVPMBs were selected for related experiments. MLAS test results confirmed that the percentage of strain energy attenuation (PSEA) can be used to evaluate the fatigue damage degree of HVPMBs. The lower the PSEA , the lesser damage. Combined with the fluorescence microscope and direct photography observation, the fatigue hairline cracks during MLAS test gradually expanded from the sample periphery to center until completely destroyed. Further, the MLASH test was developed to evaluate the healing performance of HVPMB by introducing intermittent duration into MLAS test. The variation of PSEA after tenth LAS loading (i.e. Δ PSEA) was proposed to evaluate the healing performance of HVPMB. The larger the Δ PSEA , the better the healing performance of HVPMB. All HVPMBs showed satisfactory healing performance once there was sufficient healing intermittent time (e.g. 180 s), and the healing performance was negatively correlated with the damage degree. Notably, the polymer structures had a dual effect on the healing performance of HVPMB, that is, they promoted the elastic healing recovery of HVPMB at lower temperature, while hindering the flow healing recovery at higher temperatures. Moreover, different temperatures caused a shift in the ranking of healing performance of various HVPMBs, thus the healing result at only single temperature cannot comprehensively represent the healing performance of HVPMB. Overall, the newly developed evaluation proposal can help to select HVPMB with excellent fatigue resistance and healing properties and provide a certain basis for accurately predicting HVPMB pavement life. [Display omitted] ● An effective evaluation proposal based on MLAS was developed. ● Percentage of strain energy attenuation (PSEA) can evaluate the fatigue degree of HVPMB. ● Variation of PSEA after tenth LAS loading can evaluate the healing performance of HVPMB. ● Polymer structures had a dual effect on the healing performance of HVPMB. ● Healing result at only single temperature cannot comprehensively represented the healing performance of HVPMB. [ABSTRACT FROM AUTHOR]

High-viscosity asphalt (HVA) provides excellent cracking and rutting resistance for ecological permeable pavement. However, HVA suffers from severe aging due to higher construction temperatures and rich porous structures, which limited its applications for urban sustainability. Currently there is still a lack of knowledge about the thermal aging effects and mechanisms of HVA. In this study, the effects of thermal aging on the morphological structures, rheological and fatigue properties of two HVAs (i.e. HVA-1 and HVA-2) at five aging levels via Simple Aging Test (SAT) are systematically investigated. HVA-1, characterized by loosen and coarse reticulated structures, undergoes significant structural changes during aging, whereas HVA-2, characterized by dense and fine reticulated structures, experiences fewer alterations. The changes in the modulus master curves of HVAs become more gradual after aging, indicating the reduced temperature sensitivity. Multiple stress creep recovery results reflect that two types of HVAs exhibit totally different dominance of oxidation or polymer degradation depending on aging level. Liner amplitude sweep (LAS) results based on damage mechanics analysis reveal that aging leads to an increase in the accumulated strain energy observed in stress-strain curves for both HVAs. As aging progresses, the proportion of elastic energy decreases due to polymer degradation, resulting in a reduction in fatigue life. Especially, the fatigue life of aged HVAs significantly decreases after SAT40. LAS results based on fracture mechanics analysis show that the crack length increases with aging due to polymer degradation and asphalt phase hardening. Aging effect on crack length was limited at initial stage but becomes more significant as crack extends. As aging deepens, the crack initial stage of HVAs tends to lengthen while the crack extension stage tends to shorten. Moreover, the crack growth process of HVAs follows a two-stage behavior of crack initiation and propagation under certain aging levels from the relationship between energy release rate and crack propagation rate. Overall, the thermal aging kinetics of various HVAs differ significantly in the structures, rheological and fatigue properties as aging deepens. HVA-2 with loosen and coarse structures exhibits greater aging resistance and lower temperature sensitivity than HVA-1 with dense and fine structures. • Different HVAs exhibits totally various dominance of oxidation or polymer degradation depending on aging level. • Fatigue life of aged HVAs significantly decreases after SAT40. • Aging effects become more significant as crack extends. • Crack growth process of HVAs follows a two-stage behavior of crack initiation and propagation. • Thermal aging kinetics of various HVAs differ significantly. [ABSTRACT FROM AUTHOR]

This study is performed to elucidate the role of long non-coding RNA myocardial infarction associated transcript (lncRNA MIAT) in vulnerable plaque formation in rats with atherosclerosis (AS) through the regulation of the PI3K/Akt signaling pathway. The mice model of AS was established, and the successful modeled AS mice were treated with overexpressed MIAT and silenced MIAT. The levels of blood lipids, atherosclerotic plaques (AP) formation, the lipid content, collagen content, apoptosis of aortic cells, angiogenesis as well as the expression of inflammatory factors, such as tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) were determined through a series of experiments. MIAT was found to be upregulated in AS. Additionally, MIAT up-regulated the levels of blood lipids, promoted AP formation, increased the lipid content and decreased the collagen content of AP, promoted the apoptosis of aortic cells in AS mice by activating the PI3K/Akt signaling pathway. Meanwhile, MIAT was determined to promote angiogenesis as well as the expression of inflammatory factors (IL-1β, IL-6, and TNF-α) in AS mice through the activation of the PI3K/Akt signaling pathway. Furthermore, MIAT activated the PI3K/Akt signaling pathway to participate in AS progression. Our study suggests that upregulation of MIAT can aggravate AS injury in AS mice via the activation of the PI3K/Akt signaling pathway, which could provide a novel target for the treatment of AS. [ABSTRACT FROM AUTHOR]

Based on petrography and geochemistry, formation phases of carbonate cements and their sedimentary–diagenetic environments in Jurassic clastic rocks from the Lenghu V tectonic belt are determined. The results demonstrate that studied successions are mainly dark gray or black mudstone with interbedded thin gray siltstone and a few greywacke layers. Sandstones are lithic and feldspathic lithic greywacke with high kaolinite content. Calcite and ferrocalcite are the main carbonate cements. The carbon isotope values(δ13C) of the carbonate cements range from − 15.6 to 9.2‰ (average − 3.2‰) with a bimodal distribution. One peak is 4‰, which includes samples from the upper Xiaomeigou Formation (Fm) and the other one is − 12‰, which mainly represents the lower section. The oxygen isotope values(δ18O) have a wide range from − 18.5 to − 8.3‰ (average − 13.31‰). Combined with microscopic observations, two phases of carbonate cements are distinguished according to their isotopic characteristics. The earlier carbonate cements are mainly calcite and ferrocalcite, and they were precipitated in eodiagenesis stage. The carbon source of calcite was inorganic, and ferrocalcite was mixed with carbon from methanogenesis. This mixture led to a positive bias in the δ13C curve, which artificially inflated the paleosalinity. The later carbonate cements, formed in mesodiagenesis stage, were ferrocalcite. Decarboxylation of organic matters led to lower δ13C values. The major and trace elements data show that Sr, Ba, Fe and Mn have weak correlation with Al, Ti. So, they are effective to interpret the sedimentary environment. The Sr/Ba ratio < 1 indicates fresh water environment, Sr/Ca, Sr/Cu and Fe/Mn ratios suggest humid climate, and V/(V + Ni) ratio shows suboxic–anoxic environment. The carbon and oxygen isotopes, together with elemental geochemistry, show that the climate during the Early Jurassic was warm and wet and the studied successions were deposited in fresh water. The variations in elemental ratio curves indicate that climate became wetter and warmer later in the Early Jurassic. [ABSTRACT FROM AUTHOR]

Active deicing and snow melting technologies, such as conductive asphalt concrete and heating cable, have got extensively concerned, however they are not applicable to the existing roads. Therefore, the conductive ultrathin bonded wearing course (CUBWC) is proposed, which mainly consists of the conductive functional layer (CFL) and gravel wearing course. The CFL is prepared by blending the graphite, carbon fibre (CF) and epoxy resin adhesive. To get the optimal electrical characteristics of CUBWC, the effects of CF length, CF content and graphite content on the resistivity of CFL were measured. The temperature sensitivity test and the temperature cycling test were further conducted to evaluate the temperature sensitive property and stability of CUBWC. Finally, the optimal contents of the graphite (25% by mass) and CF (4% by mass) were determined by considering the effective electrical conductivity and temperature stability of CUBWC. [ABSTRACT FROM AUTHOR]

• The high fatigue damage dramatically reduces the low temperature healing potential of asphalt mixtures. • The internal crack distribution characteristics of different mixtures are different under the same fatigue degree. • The longer the intermittent time, the less the effect on fatigue healing of asphalt mixture. The primary objective of this study is to advance the understanding of the low temperature self-healing character of asphalt mixtures under different damage degrees, thus to determine the effective strategy of asphalt pavement maintenance. Firstly, three kinds of asphalt mixtures are selected to conduct the indirect tensile (IDT) fatigue test to a certain fatigue damage degree at low temperatures, and then the resilient modulus (Mr) at different rest time is measured to quantify the healing potential. Next, the fatigue loading with different intermittent time (0 s, 1 s and 3 s) is applied to determine the impact of intermittent time on healing potential. The results indicate that the descending order of healing potential of asphalt mixtures is: SMA-11 > AC-8 > AC-11 at 5 °C and −5°C. The loading intermittent time has an obvious effect on the fatigue damage state of asphalt mixtures, while the longer the intermittent time, the less the effect on fatigue damage healing. Besides, the fatigue damage state has great influence on its healing potential of asphalt mixture. Under the low damage conditions, the initial healing rate is greater than the long term healing rate. However, the low temperature (−5°C) dramatically reduces the healing rate of asphalt mixtures, and causes their long-term healing rate to stabilize gradually to a very low level. Especially under the high fatigue damage conditions, the healing potential of asphalt mixtures will almost disappear at −5°C. Furthermore, together with meso-scale Computed Tomography (CT) scanning technique, it is found that the internal crack distribution characteristics of different graded asphalt mixtures are different even under the same damage degree, which may explain the differences in the healing potential of asphalt mixtures. The use of a fast two-dimensional (2D) scanning technology further confirms that the crack zones inside the asphalt mixture are gradually shrinking after a period of high temperature healing. Finally, the Grey relational analysis reveals that the healing time has the most significant influence on the healing potential of asphalt mixtures. The gradation type and temperature have the similar influence level on the healing potential. The correlation degree between the fatigue damage degree and healing potential is the smallest compared with the other three factors. [ABSTRACT FROM AUTHOR]

Provenance analyses provide valuable insights into both the complex interaction between orogenic belts and surrounding sedimentary basins and the role of plate collision in the basin-mountain coupling process. This paper investigates the provenance of the Cenozoic sediments filling the Qaidam Basin (Qinghai Tibetan Plateau, China) by combining petrology, major elements, trace elements, rare earth elements (REEs), and Zircon U Pb dating analysis to provide new insight about the collision of the Indian and Asian plates. The petrographic analysis indicates that the studied sediments are poorly sorted and made of angular to subrounded clasts, suggesting deposition relatively near to the source area. The Chemical Index of Alteration (CIA) of the samples in the study area, which ranges from 68.88 to 74.08, indicates that the study area experienced moderate weathering from the early Eocene to the early Miocene. In addition, Zr/Sc versus Th/Sc shows that most samples did not experience recycling. K 2 O/Na 2 O, SiO 2 , Th, Sc, Zr, La and Co contents indicate that the Cenozoic sediments filling the Qaidam Basin derived mainly from an active continental margin and a continental island arc setting. U Pb dating of detrital zircons denotes that the studied sediments were derived from rocks with five major sets of ages (200–350 Ma, 350–500 Ma, 500–1000 Ma, 1000–1500 Ma, and >1500 Ma), with the two first sets being more common. Based on the regional geology, therefore, these ages indicate that the main provenance source was shifted southwards from the Mesozoic crystalline basement (south Qilian Mountains) in the early-middle Eocene, to the Saishiteng Mountains in the middle-late Eocene, and to Lvliang and Qilian Mountains during the late Eocene-early Miocene. Zircon dating also indicates that the main source area was displaced eastward through time. Finally, it is concluded that the tectonic deformation progressed from west to east in the northern margin of the Qaidam Basin, reflecting a far-field response to the onset of the India-Asia collision. • The sediments mainly derive from source terranes that used to be active continental margin and continental island arc. • Detrital zircon evidence indicates that the Qilian Mountains, instead of the East Kunlun, were the dominant detrital source. • The tectonic deformation during the early Eocene reflected a far-field response to the onset of India-Asia collision. [ABSTRACT FROM AUTHOR]

• We propose a Tensor Ring decomposition framework for context-aware recommendation. • Our framework can achieve a better balance between performance and computational. • We analyze the advantages of formulating recommendation as Tensor Ring. • Experiments show the superiority of the proposed framework. As a powerful tool for processing high-dimensional data, tensor decomposition has been widely used in context-aware recommendation. Most of the current tensor decomposition-based recommendation models use CP decomposition or Tucker decomposition. In practical recommendation applications, fewer parameters limit the performance of CP decomposition, and the high-order tensor kernel makes the computational complexity of Tucker decomposition exponential. In order to improve the performance of recommendation while maintaining high computational efficiency, we propose a bias Tensor Ring decomposition framework for context-aware recommendation, which employs Tensor Ring decomposition to extract user-item-context latent factors. Comparing to current tensor decomposition-based recommendation models, our framework achieves a better balance between recommendation performance and computational complexity by Tensor Ring decomposition. This is a highly scalable recommendation framework that can easily further integrate additional information such as social trust and implicit feedback, thus used for more complex recommendation tasks. To the best of our knowledge, this work is the first to formulate context-aware recommendation as Tensor Ring decomposition process. Our in-depth analyses confirm that Tensor Ring decomposition has certain advantages over CP decomposition and Tucker decomposition. Multiple experiments on three real datasets also show that the proposed framework helps to improve the recommendation performance. [ABSTRACT FROM AUTHOR]

Self-healing has great potential to extend the service life of asphalt pavement, and this capability has been regarded as an important strategy when designing a sustainable infrastructure. This review presents a comprehensive summary of the state-of-the-art investigations concerning the self-healing mechanism, model, characterization and enhancement, ranging from asphalt to asphalt pavement. Firstly, the self-healing phenomenon as a general concept in asphalt materials is analyzed including its definition and the differences among self-healing and some viscoelastic responses. Additionally, the development of self-healing in asphalt pavement design is introduced. Next, four kinds of possible self-healing mechanism and corresponding models are presented. It is pointed out that the continuum thermodynamic model, considering the whole process from damage initiation to healing recovery, can be a promising study field. Further, a set of self-healing multiscale characterization methods from microscale to macroscale as well as computational simulation scale, are summed up. Thereinto, the computational simulation shows great potential in simulating the self-healing behavior of asphalt materials from mechanical and molecular level. Moreover, the factors influencing self-healing capability are discussed, but the action mechanisms of some factors remain unclear and need to be investigated. Finally, two extrinsic self-healing technologies, induction heating and capsule healing, are recommended as preventive maintenance applications in asphalt pavement. In future, more effective energy-based healing systems or novel material-based healing systems are expected to be developed towards designing sustainable long-life asphalt pavement. [ABSTRACT FROM AUTHOR]

The molecular dynamics (MD) simulation was used in this study to explain the microscopic process of asphalt self-healing and investigate the influence of temperature on the self-healing capability of asphalt binders. Asphalt average molecular structure models of four types of neat asphalt binders were constructed firstly and a three-dimensional (3D) micro-crack model was further introduced to simulate the asphalt healing process. Based on the simulation results, the density analysis, relative concentration analysis, and mean square displacement analysis (MSD) were performed to investigate the temperature sensitive self-healing character of asphalt binders. Differential scanning calorimeter (DSC) test was adopted to get the phase transition (PT) temperature range of asphalt binders. The DSR-based fatigue-healing-fatigue test at different temperatures was also carried out to observe the self-healing capability of asphalt binders from the macroscopic view. According to the numerical and experimental results, it can be found that the molecular diffusion rate and diffusion range were more distinct especially within the PT temperature range, which indicated that the self-healing capability of asphalt was strong in PT temperature. Moreover, the results showed that there existed an optimal temperature range for asphalt healing, considering too high temperature may lead to permanent deformation, the optimal healing temperature range determined in this paper was 40.3–48.7 °C. [ABSTRACT FROM AUTHOR]

Waste cooking oil residues (WCORs)-based bio-asphalt is a potential substitute for petroleum asphalt. However, asphalt binders with a high WCOR content indicates a low rheological property, leading to a limited WCOR mixed content (usually no more than 10 wt% of asphalt binder). This study aims to prepare an eco-friendly bio-asphalt with a high WCOR content. Based on the formula uniform design method, the optimum blending proportion of the bio-asphalt was determined as 33.3% WCOR, 31.8% hard asphalt particles (HAP), 30.3% hydrocarbon resin (HR 1 ), 4.6% recycled low density polyethylene (R-LDPE), and external 4% linear SBS polymer (L-SBS). Rheological test results indicated that the optimized bio-asphalt (OBA) presented similar high-temperature performance to SBS modified asphalt (SBS-MA), and much better low-temperature performance than both of SBS-MA and PEN 70 base asphalt (PEN 70). Fourier transform infrared spectroscopy (FTIR) test proved that OBA had some special chemical composition such as the acids and esters originated from the addition of WCOR. On the basis of mixture performance tests, it confirmed that OBA mixture possessed similar rutting resistance and moisture susceptibility to SBS-MA mixture, and showed more satisfying low-temperature capability than both of SBS-MA mixture and PEN 70 mixture. Additionally, OBA mixture showed prominent fatigue performance since it had the highest fatigue life and stable fatigue sensitivity at different strain levels. All above evaluations imply the feasibility of using high content of WCOR in road construction applications since OBA containing 33.3% WCOR shows excellent binder and mixture performance. [ABSTRACT FROM AUTHOR]

The integration of local power generation units into integrated energy service providers (IESPs) can enable IESPs to realize optimal resource allocation and provide multiple energy services. We propose a bi-level model for IESPs participating in joint electricity and carbon peer-to-peer (P2P) markets. To reduce carbon emissions, we set up carbon capture equipment in IESPs to collect carbon dioxide for the synthesis of methane and methanol. Furthermore, we propose a P2P transaction mechanism based on carbon emission flow and build a bi-level model to achieve the collaborative optimization of IESPs and distribution system operators. Additionally, we utilize the alternating direction method of multipliers (ADMM) algorithm to protect the privacy of users in the P2P transaction process. Simulation results of a distribution network with multiple IESPs demonstrate that the proposed model reduces the overall carbon emissions, allocates part of the carbon emission responsibilities to loads, and reduces the carbon emission costs of P2P transaction participants. [ABSTRACT FROM AUTHOR]

In order to distinguish the wetting healing stage and the molecular diffusion healing stage during the self-healing process of asphalt binders, the fluorescence microscope (FM) together with the image processing technique was employed. The healing index was put forward based on the variation of crack area. On the basis of the established capillary diffusion theory, the Two-Stage Model was built to fit the healing curves characterizing the healing index variation with healing time. It is found that the established method is quite suitable to identify the wetting and the diffusion stages. The wetting healing occurs firstly, during which the asphalt molecules spontaneously wet the both faces of crack. Although the strength recovery is not distinct at this stage, SBS modified asphalt shows greater wetting healing strength than the other neat asphalt binders. Once the wetting process is nearly finished, the molecular diffusion healing ratio accelerates significantly, and the descending order of the molecular diffusion rate is: SBS > PEN 100 > PEN 70 > PEN 50 > PEN 20. The test results also show that the disappearance of visible crack does not indicate that the strength has been fully recovered. Here, the tensile strength test is developed to identify the strength recovery rate after the crack is fully closed, which implies that the strength regeneration is a long process. [ABSTRACT FROM AUTHOR]

An ultrasensitive photoelectrochemical (PEC) immunosensor for the detection of carcinoembryonic antigen (CEA) was constructed using CdS@Cu 2 O co-sensitized porous ZnO nanosheets as photoactive materials and multiwalled carbon nanotubes (MWCNTs) as electrons sink. Porous ZnO was assembled on the MWCNTs modified indium tin oxides electrode to immobilize capture antibodies. With a sandwich immunoassay format, CEA and signal antibodies labeled CdS@Cu 2 O were introduced in sequence via specific immunoreaction, and the ultrahigh sensitivity of this immunoassay results from the following three aspects. First, the co-sensitization of Cu 2 O and CdS extends the absorption range of ZnO from ultraviolet region to visible light region, which can adequately utilize the light energy. Second, the effective matching of energy levels between the ZnO, CdS and Cu 2 O accelerates the separation and transfer of photogenerated electron-hole pairs and improves the PEC performance, significantly. Finally, the introduced MWCNTs evidently expedite the interfacial electron transfer from ZnO to electrode, further resulting in noticeably increased photocurrent. On the basis of multiple signal amplification strategy, a largely increased linear detection range from 1.0 pg mL −1 to 80 ng mL −1 with a low detection limit (0.4 pg mL −1 ) are obtained. Meanwhile, the prepared materials with attractive properties provide a promising platform for PEC detection. [ABSTRACT FROM AUTHOR]

The accidents of many share-control engineering application, including the aircraft carrier-landing process, are directly related to human error. In order to identify human error and assess the reliability of Human system interaction (HSI) in carrier landing, a control theoretic based simulation method is proposed. The simulator combines the pilot control with the cognition model that exploits the human error mechanism to describe the dynamic characteristics of carrier-landing. And the Performance shaping factors (PSFs) are also taken into consideration to represent the likelihood of human error. Moreover, the mission reliability is proposed as an appropriate metric of HSI. By quantitative simulation, the human error produced in HSI could be presented and demonstrated dynamically. The performance of the proposed method is tested through a case study. [ABSTRACT FROM AUTHOR]

Herein, a photoelectrochemical (PEC) immunoassay is constructed for squamous cell carcinoma antigen (SCCA) detection using zinc oxide nanoflower-bismuth sulfide (Bi 2 S 3 ) composites as photoactive materials and reduced graphene oxide (rGO) as signal labels. Horseradish peroxidase is used to block sites against nonspecific binding, and then participated in luminol-based chemiluminescence (CL) system. The induced CL emission is acted as an inner light source to excite photoactive materials, simplifying the instrument. A novel signal amplification strategy is stem from rGO because of the rGO acts as an energy acceptor, while luminol serves as a donor to rGO, triggering the CL resonance energy transfer phenomenon between luminol and rGO. Thus, the efficient CL emission to photoactive materials decreases. Furthermore, the signal amplification caused by rGO labeled signal antibodies is related to photogenerated electron–hole pairs: perfect matching of energy levels between rGO and Bi 2 S 3 makes rGO a sink to capture photogenerated electrons from Bi 2 S 3 ; the increased steric hindrance hinders the electron donor to the surface of Bi 2 S 3 for reaction with the photogenerated holes. On the basis of the novel signal amplification strategy, the proposed immunosensor exhibits excellent analytical performance for PEC detection of SCCA, ranging from 0.8 pg mL −1 to 80 ng mL −1 with a low detection limit of 0.21 pg mL −1 . Meanwhile, the designed signal amplification strategy provides a general format for future development of PEC assays. [ABSTRACT FROM AUTHOR]

Combining multibranched hybridization chain reaction (mHCR), the photoelectrochemical (PEC) immunosensor was fabricated with a microfluidic paper-based analytical devices using different sizes of CdTe quantum dots (QDs) sensitized flower-like 3D ZnO superstructures as photoactive materials. Firstly, 4-aminothiophenol (PATP) functioned ZnO was anchored on gold-paper working electrode. With the aid of PATP, large-sized CdTe-COOH QDs (QDs1) were conjugated onto the ZnO surface because of the formation of a strong bond (Zn-S) between the thiol of PATP molecule and the ZnO, and the remaining amino group formed an amide bond with carboxylic acid group capping CdTe. Then the small-sized CdTe-NH 2 QDs (QDs2) were modified on the QDs1 by forming amide bond, which leaded to a very strong photocurrent response because of the formation of cosensitized structure. The designed mHCR produced long products with multiple branched arms, which could attached multiple PdAu nanoparticles and catalyze the oxidation of hydroquinone (HQ) using H 2 O 2 as anoxidant. Double strands DNA with multiple branched arms (mdsDNA) was formed by mHCR. In the presence of carcinoembryonic antigen (CEA), PdAu-mdsDNA conjugates-labeled CEA antibody was captured. The concentrations of CEA were measured through the decrease in photocurrent intensity resulting from the increase in steric hindrance of the immunocomplex and the polymeric oxidation product of HQ. In addition, the oxidation product of HQ deposited on the as-obtained electrode, which could efficiently inhibit the photoinduced electron transfer. Under optimal conditions, the PEC immunosensor exhibited excellent analytical performance: the detection range of CEA was from 0.001 to 90 ng mL −1 with low detection limit of 0.33 pg mL −1 . The as-obtained immunosensor exhibited excellent precision, prominent specificity, acceptable stability and reproducibility, and could be used for the detection of CEA in real samples. The proposed assay opens a promising platform of clinical immunoassay for other biomolecules. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the association of peroxisome proliferator-activated receptor-δ (PPAR-δ) and additional SNP-SNP interaction with essential hypertension (EH) in Chinese Han population. A total of 1248 subjects (625 males, 623 females), including 620 EH patients and 628 normotension subjects, were included in the study. The mean age was 51.2 ± 15.1 years old. Logistic regression model was used to examine the association between four SNP and EH; odds ratio (OR) and 95 % confident interval (95 %CI) were calculated. Generalized multifactor dimensionality reduction (GMDR) was employed to analyze SNP-SNP interaction. EH risk was significantly lower in carriers of C allele of the rs2016520 polymorphism than those with TT (TC + CC versus TT, adjusted OR (95 %CI) = 0.61 (0.49-0.78)). In addition, we also found a significant association between rs9794 and EH; EH risk was also significantly lower in carriers of G allele of the rs9794 polymorphism than those with CC (CG + GG versus CC, adjusted OR (95 %CI) = 0.65 (0.53-0.83)). We also found a potential SNP-SNP interaction between rs2016520 and rs9794; subjects with TC or CC of rs2016520 and CG or GG of rs9794 genotype have the lowest EH risk, compared to subjects with TT of rs2016520 and CC of rs9794 genotype; OR (95 %CI) was 0.32 (0.23-0.62) after covariate adjustment. Our results support an important association between rs2016520 and rs9794 minor allele of PPAR-δ and decreased risk of EH and additional interaction between rs2016520 and rs9794. [ABSTRACT FROM AUTHOR]

Branched zinc oxide nanorods (BZR) arrays, an array with high charge carries collection efficiency and specific surface area, are grown on the reduced graphene oxide-paper working electrode for the first time to construct a paper-based electrochemical (EC) immunosensor. Typically, the BZR are fabricated via a simple hydrothermal process, which can provide abundant sites for antibodies loading. By combining the large surface area of porous zinc oxide (PZS) and good biocompatibility of gold nanoparticles (AuNPs), PZS–AuNPs (PZS@Au) nanocomposites are designed to label horseradish peroxide (HRP) and antigens. After a competitive reaction between antigens and PZS@Au nanocomposites labeled antigens, the signal labels are introduced into the immunosensor, in which, HRP participate in biocatalytic precipitation process. The produced precipitate reduces the electrode surface area and hinders the electron transfer. With the increase of concentration of antigens, the signal labels introduced into the sensor decrease, thus, a signal-on immunoassay for α-fetoprotein detection is constructed. The proposed paper-based EC immunosensor combines enzymatic biocatalytic precipitation reaction and competitive immunoassay mode for the first time, and possesses a wide linear range from 0.2 pg mL −1 to 500 ng mL −1 with a detection limit of 0.08 pg mL −1 . In addition, the proposed method is simple, sensitive and specific and can be a promising platform for other protein detection. [ABSTRACT FROM AUTHOR]

Copper sulfide (CuS), an excellent photoactive material, is introduced into a paper-based photoelectrochemical (PEC) immunosensor for the first time using an in situ electron donor producing approach. ZnO nanoflakes (ZNF) with a large surface area are first electrodeposited onto a gold-paper electrode, and then functionalized with CuS via a simple hydrothermal and ion exchange method. The recombination process of electron–hole pairs in CuS is prevented since the energy levels between ZnO and CuS are matched well, resulting in a high PEC performance. The glucose oxidase (GOx) and signal antibodies co-labeled nanoporous gold (NPG) is then introduced into the immunosensor via sandwich immunoreactions. On the basis of the catalytic chemistry of GOx to produce in situ H2O2 for electron donation, an enhanced photocurrent was achieved. By coupling the brilliant properties of CuS/ZNF, a modified gold-paper electrode with amplified electron donor production through NPG, a sensitive PEC immunosensor for carcinoembryonic antigen (CEA) analysis is proposed. The immunosensor displayed a linear response to CEA in the range from 2 pg mL−1 to 100 ng mL−1 with a relatively low detection limit of 0.7 pg mL−1. The proposed immunosensor exhibited good performance, which has a promising prospect in clinical diagnosis. [ABSTRACT FROM AUTHOR]

An ultrasensitive enzyme-free electrochemical immunosensor is constructed using a gold nanorods (AuNRs) modified paper electrode as the sensor platform and porous zinc oxide spheres (PZS)–silver nanoparticles (AgNPs) nanocomposites as signal labels. Significantly enhanced sensitivity for prostate specific antigen (PSA) comes from a dual signal amplification strategy. First, interconnected AuNRs layers, which can improve the electronic transmission rate, are grown on the surface of cellulose fibers on a paper sample zone to capture primary antibodies. Second, PZS, a porous material with large surface area, is synthesized to provide sites for AgNPs loading, which improves the catalytic capacity of the AgNPs towards H2O2 reduction. Under optimized conditions, the proposed immunosensor for PSA exhibits a wide linear detection range from 0.004 to 60 ng mL−1 with a detection limit of 1.5 pg mL−1. Moreover, the immunosensor shows excellent selectivity, high stability, and acceptable fabrication reproducibility. This strategy appears to be a simple method, which provides a promising platform for the detection of other proteins. [ABSTRACT FROM AUTHOR]

The penetration of renewables on the demand side has recently attracted a large amount of attention. Its dual identity has an important impact on the competition between power producers and market dispatching. This study analyzed the participation of prosumers in the Nash–Cournot model for power market clearing. On this basis, we considered the uncertainty of renewable energy production, under which we used the distributionally robust optimization (DRO) model to produce a market equilibrium. Moreover, the Column-and-Constraint Generation algorithm was employed to solve the model. As a result, the impact of prosumers penetration and their production uncertainty on market equilibria was quantified and analyzed. Numerical simulations on an IEEE-30 bus system investigated the impact of the uncertainty of renewable energy output, the penetration level of wind power, and the demand level on the market equilibria. Test results demonstrate that the social welfare obtained from the proposed DRO model is 6.89% higher than that obtained from traditional robust optimization models. [ABSTRACT FROM AUTHOR]

In this work, multiplexed photoelectrochemical (PEC) immunoassays are introduced into an indium tin oxide (ITO) device. Firstly, the ITO device is fabricated using a simple acid etch treatment method. Secondly, AuPd alloy nanoparticles are electro-deposited on ITO working electrodes as electron sink to construct the immunosensor platform. After that, ZnO nanotubes (ZNTs) arrays are synthesized via chemical etching of ZnO nanorods that are grown on AuPd surface by electrochemical deposition method. Subsequently, CdS is electro-deposited on ZNTs arrays and used as photoactive material. Then, CuO nanoseeds are labeled with signal antibodies and firstly used as PEC signal amplification label. The introduction of CuO brings signal amplification because of the conduction band (CB) of both CuO and ZnO are lower than that of CdS, CuO will compete the photo-induced electrons in CB of CdS with ZnO, leading to the decrease of the photocurrent intensity. Using cancer antigen 125, prostate specific antigen and α-fetoprotein as model analytes, the proposed immunoassay exhibits excellent precision and sensitivity. Meanwhile, this work provides a promising, addressable and simple strategy for the multi-detection of tumor markers. [ABSTRACT FROM AUTHOR]

An enzyme-free electrochemical immunoassay is introduced into microfluidic paper-based analytical devices for the first time using novel three dimensional flower-like Au nanoparticles modified paper working electrode (FLAuNPs-PWE) as sensor platform and gold (Au)-silver (Ag) bimetallic nanoparticles (Au-Ag BMNPs) as tracer. FLAuNPs with large surface area serve as an effective matrix for primary antibodies. Au-Ag BMNPs with good biological activity, such as mimicking natural peroxidases, are used for binding of signal antibodies (Ab 2 ). Then the Ab 2 labeled BMNPs is linked to the FLAuNPs-PWE via sandwich immunoreactions. Enhanced sensitivity is achieved by efficient catalysis of the Au-Ag BMNPs toward hydrogen peroxide. Under the optimized experimental conditions, the proposed paper-based electrochemical immunosensor exhibits excellent analytical performance for enzyme-free detection of carcinoembryonic antigen, ranging from 0.001-50 ng mL −1 with a low detection limit of 0.3 pg mL −1 . The immunosensor shows good precision, acceptable stability and reproducibility. The proposed method provides a new promising platform for the design of the highly sensitive detection method, showing great promise for clinical application. [ABSTRACT FROM AUTHOR]

[Display omitted] • Decay pattern of self-healing temperature susceptibility of bitumens at various ageing states is examined. • Self-healing rate parabola evolution with temperature of bitumen is related to the frequent phase transition. • Superposition impacts of temperature and ageing on phase structures elicit the healing transition phenomena. • All-weather ageing causes more serious impact on self-healing temperature susceptibility than long-term ageing. • RA bitumen undergoes smaller ageing impact on self-healing temperature susceptibility than pure bitumen. Understanding the evolution law of the self-healing ability of bitumen under actual service environment is conductive to optimizing the design of self-healing bituminous pavement, while the changing temperatures and variety of ageing states complicate this issue. In this study, the decay pattern of self-healing temperature susceptibility of pure bitumen and rock-asphalt (RA) modified bitumen at the simulated ageing states of thermal oxidation and all-weather is analyzed by the dynamic shear rheometer based fatigue-healing-fatigue experiment. Through the thin layer chromatography, differential scanning calorimeter and rheological characterizations, the chemical composition, colloidal stability and macro phase transition (PT) behavior of bitumens with various ageing levels are examined. Results show that the self-healing rate parabola evolution with temperature of bitumen has to do with its frequent PT behaviors. The shift of self-healing curves and the appearance of healing inert temperature zone are the results of the growth of heavy components and decays of colloidal structure and phase structure caused by ageing. Notably, the superposition impacts of temperature and ageing on bitumen phase structures elicit the healing transition phenomena in the viscoelastic zone and viscous flow zone. Moreover, the multi-scale analysis reveals that the decay of self-healing temperature susceptibility with ageing is consistent with the deterioration tendency of the macro PT property, chemical composition and colloidal stability. Especially, all-weather ageing causes more serious impact on the self-healing temperature susceptibility of bitumens than thermal oxidative long-term ageing. RA bitumen with greater ageing resistance undergoes smaller ageing impact on self-healing temperature susceptibility than pure bitumen. [ABSTRACT FROM AUTHOR]

Simple Summary: Impaired invasion of extravillous trophoblasts (EVTs) results in inadequate remodelling of arteries and poor placentation, leading to preeclampsia (PE). Transmembrane BAX Inhibitor-1 Motif-containing 4 (TMBIM4) was found to promote the migration and invasion of human osteosarcoma U2-OS and breast cancer MCF7 cell lines. However, the effect of TMBIM4 on trophoblast biological behaviour and its relevance to PE pathophysiology remain unclear. In this study, we confirmed that TMBIM4 was highly expressed in cytotrophoblasts, syncytiotrophoblasts, and EVTs of the human placenta during early pregnancy. Moreover, TMBIM4 was found to be significantly decreased in PE placenta. Thereafter, lipopolysaccharide (LPS) treatment reduced the expression of TMBIM4 and induced NLR family pyrin domain-containing 3 (NLRP3) inflammasome activity in a first-trimester human trophoblast cell line, the HTR-8/SVneo cell line. Knockout (KO) of TMBIM4 in the HTR-8/SVneo cell line impaired cell viability, migration, and invasion, which was more severe in the LPS/ATP-treated TMBIM4-KO cell line. TMBIM4 deficiency enhanced NLRP3 inflammasome activity and promoted subsequent pyroptosis. Inhibiting the NLRP3 inflammasome with MCC950 in HTR-8/SVneo cells alleviated LPS/ATP-induced pyroptosis and damaged cell function in the TMBIM4-KO cell line. Overall, this study discovered a new PE-associated protein, TMBIM4, and its biological significance in trophoblast pyroptosis mediated by the NLRP3 inflammasome. Impaired invasion of EVTs results in inadequate remodelling of arteries and poor placentation, leading to PE. TMBIM4 was found to promote the migration and invasion of human osteosarcoma U2-OS and breast cancer MCF7 cell lines. However, the effect of TMBIM4 on trophoblast biological behaviour and its relevance to PE pathophysiology remain unclear. In this study, we confirmed that TMBIM4 was highly expressed in cytotrophoblasts, syncytiotrophoblasts, and EVTs of the human placenta during early pregnancy. By comparing the expression levels of TMBIM4 in the placenta of women with normal-term pregnancy and PE, TMBIM4 was found to be significantly decreased in PE. Thereafter, we determined the expression of TMBIM4 in the LPS-treated first-trimester human trophoblast cell line HTR-8/SVneo (mimicking a PE-like cell model), and determined the effect of TMBIM4 on trophoblast function and its underlying mechanism. LPS treatment reduced the expression of TMBIM4 and induced NLRP3 inflammasome activity in HTR-8/SVneo cells. KO of TMBIM4 in the HTR-8/SVneo cell line impaired cell viability, migration, and invasion, which was more severe in the LPS/ATP-treated TMBIM4-KO cell line. Moreover, TMBIM4 deficiency enhanced NLRP3 inflammasome activity and promoted subsequent pyroptosis, with or without LPS/ATP treatment. The negative relationship between TMBIM4 expression and NLRP3 inflammatory activity was verified in PE placentas. Inhibiting the NLRP3 inflammasome with MCC950 in HTR-8/SVneo cells alleviated LPS/ATP-induced pyroptosis and damaged cell function in the TMBIM4-KO cell line. Overall, this study revealed a new PE-associated protein, TMBIM4, and its biological significance in trophoblast pyroptosis mediated by the NLRP3 inflammasome. TMBIM4 may serve as a potential target for the treatment of placental inflammation-associated PE. [ABSTRACT FROM AUTHOR]

Abstract: Combining microfluidic paper-based analytical device (μ-PAD) and the molecular imprinting technique, a visible light photoelectrochemical (PEC) sensing platform for the detection of pentachlorophenol (PCP) was established on gold nanoparticles (AuNPs) decorated paper working electrode using polypyrrole-functionalized ZnO nanoparticles. Ascorbic acid (AA) was exploited as an efficient and nontoxic electron donor for scavenging photogenerated holes under mild solution medium and facilitating the generation of stable photocurrent. The microfluidic molecular imprinted polymer-based PEC analytical origami device is developed for the detection of PCP in the linear range from 0.01ngmL−1 to 100ngmL−1 with a low detection limit of 4pgmL−1. This disposable microfluidic PEC origami device would provide a new platform for sensitive, specific, and multiplex assay in public health, environmental monitoring, and the developing world. [Copyright &y& Elsevier]

Highlights: [•] The addition of sodium carboxymethyl cellulose improved the properties of membrane. [•] The addition of Co2+ to alginate gel improved activity of the enzyme. [•] Co2+ can improve the mechanical strength of microcapsules. [•] Co2+ replaced the Ca2+ in the traditional alginate gel. [ABSTRACT FROM AUTHOR]

Highlights: [•] Aptamer biosensor for MCF-7 cells based on ultrasensitive electrochemical detection. [•] Porous GO/Au composites and porous PtFe alloy were used as effective sensing platform and signal amplification labels. [•] PEG not only as an excellent reductant, it can also make Au nanoparticles uniformly distributed in the GO/Au composites. [ABSTRACT FROM AUTHOR]

In this work, microfluidic paper-based analytical device (μ-PAD) was applied in a photoelectrochemical (PEC) method and thus a truly low-cost, simple, portable, and disposable microfluidic PEC origami device (μ-PECOD) was demonstrated. The molecular imprinting technique was introduced into microfluidic paper-based analytical devices (μ-PADs) through electropolymerization of molecular imprinted polyaniline (MPANI) in a novel Au nanoparticle (AuNP)-modified paper working electrode (Au-PWE). This is fabricated through the growth of an AuNP layer on the surfaces of cellulose fibers in the PWE. Under visible light irradiation, MPANI can generate the photoelectric transition from the highest occupied molecular orbital (HOMO) to the lowest unoccupied molecular orbital (LUMO), delivering the excited electrons to the AuNPs, and then to the carbon working electrode. Simultaneously, it is believed that a positively charged hole of MPANI that took part in the oxidation process was consumed by ascorbic acid (AA) to promote the amplifying photocurrent response. On the basis of this novel MPANI-Au-PWE and the principle of origami, a microfluidic molecular imprinted polymer (MIP)-based photoelectrochemical analytical origami device (μ-MPECOD), comprised of an auxiliary tab and a sample tab, is developed for the detection of heptachlor in the linear range from 0.03 nmol L−1 to 10.0 nmol L−1 with a low detection limit of 8.0 pmol L−1. The selectivity, reproducibility, and stability of this μ-MPECOD are investigated. This μ-MPECOD would provide a new platform for high-throughput, sensitive, specific, and multiplex assay in public health, environmental monitoring, and the developing world. [ABSTRACT FROM AUTHOR]

This paper systematically investigated the roles of aging and bio-oil regeneration on the self-healing evolution behavior of pure asphalt and terminal blend (TB) rubberized asphalt within wide temperature range, which was expected to promote the applications of self-healing asphalt pavement, meanwhile to accelerate the sustainable disposal of local bio-oil and rubber wastes. The self-healing, flow and elastic recovery (ER) abilities of asphalts within wide temperature range and their relationship were traced through the dynamic shear rheometer based fatigue-healing-fatigue, frequency sweep and creep recovery tests. Results revealed that different effects of temperature on ER and flow abilities of aged or rejuvenated asphalts resulted in the complexity of self-healing evolution behavior. The proposed ER-flow self-healing theory clarified that the ER ability of aged asphalts led the self-healing process in viscoelastic region, and the flow ability dominated as temperature rose into viscous flow region; however, the flow ability of regenerated asphalts dominated the self-healing at all measured temperatures. The aging growth percentage and regeneration recovery percentage (%RR) based on four self-healing characteristic temperatures were proposed to quantify the influences of aging and regeneration on self-healing evolution behavior of asphalts. The climate aging imparted severer impact on the self-healing evolution behavior of pure asphalt than long-term aging, whereas caused less impact on that of TB asphalt. The aging impact on the self-healing evolution behavior of TB asphalt was smaller than that of pure asphalt. Inversely, the %RR of rejuvenated asphalts increased as the growth of bio-oil content, and reached the maximum when adding 4%wt. waste cooking oil residues. The bio-oil elicited the greater regeneration improvement of self-healing performance than petroleum-based rejuvenator. Overall, the bio-oil regeneration recovery of the self-healing evolution performance of aged asphalts was limited. [Display omitted] • The elastic recovery(ER)-flow self-healing theory was proposed and clarified. • ER of aged asphalts led self-healing in viscoelastic region, while flow dominated in viscous flow region. • Flow ability of regenerated asphalts dominated self-healing at all measured temperatures. • Regeneration recovery percentage based on four self-healing characteristic temperatures was proposed. • Bio-oil regeneration recovery of aged asphalts in self-healing evolution performance was limited. [ABSTRACT FROM AUTHOR]

Highlights: [•] Ultrasensitive electrochemical immunoassay for detecting CEA was developed. [•] 3D-AuNPs/GN was employed as the carrier of primary antibodies. [•] Multienzyme functionalized nanoporous silver was used as signal enhancer. [Copyright &y& Elsevier]

High penetration of renewable energy in the power grid causes serious frequency deviations. Large-scale integrations of electric vehicles (EVs) in the power grid provide considerable vehicle-to-grid potential for frequency regulation. Existing frequency regulation strategies with aggregated EVs realize accurate power control that relies on complete information interaction between the EV aggregator and individual EVs. However, the data collection for all EV parameters is not applicable due to privacy protection and the limited communication environment. Considering the limited data collection from grid-connected EVs, this paper provides a novel frequency regulation strategy and tends to address the uncertain influence from EV users' charging requirements, the EV aggregator's power regulation, and the frequency regulation performance. Firstly, considering the influence of the limited data collection by EVs on the users' requirement of traveling and regulation preference, a probabilistic evaluation model for the available regulation capacity of the EV aggregator and the probabilistic control method for EVs are developed. Then, a frequency regulation strategy with error correction control and progressive regulation recovery is developed to simultaneously guarantee the system frequency regulation performance and the regulation requirements of EV users. Finally, case studies are carried out to validate the effectiveness of frequency regulation strategy for decreasing the uncertain influence from the limited data collection, ensuring the EV users' requirements, and improving the system frequency stability. [ABSTRACT FROM AUTHOR]

Abstract: The core transcriptional regulatory circuitries are important for controlling stem cell self-renewal and differentiation. Nuclear receptors provide an ideal model to regulate gene expression in both ligand-dependent and ligand-independent manners. Recent studies of regulatory events by nuclear receptors in neural stem cells, embryonic stem cells, and induced pluripotent stem cells (iPSCs) provided unique insights into mechanisms of stem cell regulation and provided invaluable resources for regenerative medicine. Nuclear receptors have been shown to be key players in stem cell self-renewal, pluripotency, and reprogramming. We summarize recent progress of studies on nuclear receptors in stem cell field as well as the potential therapeutic implications of these nuclear receptors and their cognate ligands. These studies not only uncover molecular mechanisms of stem cell regulation, but also provide unique opportunities for drug discovery. [ABSTRACT FROM AUTHOR]