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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]

In order to address the issues of high viscosity and excessive fume exhaust associated with high-viscosity modified asphalt (HVMA), the objective of this study was to develop an eco-friendly HVMA by incorporating fume suppressants and viscosity-retarding agents (VRAs). To begin with, desulfurization rubber powder (DRP) was utilized as a modifier, and fume suppressants, including activated carbon, a chemical reaction fume suppressant, and a composite fume suppressant combining activated carbon and chemical reaction fume suppressant were added to the HVMA separately. The fume suppression effect and odor level were observed to determine the optimal fume suppressant composition for this study. Based on these observations, an area integration method was proposed, utilizing rotational viscosity testing and temperature sweeping experiments, evaluating the viscosity-retarding effect and mixing temperature when different amounts of Sasobit VRA, Evotherm3G VRA, and a composite VRA of Sasobit and Evotherm3G were added to the HVMA. This approach aimed to identify the eco-friendly HVMA with the most effective fume suppression and viscosity-retarding abilities. Furthermore, the morphology and rheological properties of the eco-friendly HVMA were examined through fluorescence microscopy, zero shear viscosity test, multiple stress creep recovery analysis, liner amplitude sweep test, and frequency sweep test. The results demonstrated that the HVMA formulation consisting of 15% DRP and 1% composite fume suppressant exhibited a satisfactory fume suppression effect and odor level. Based on this, the HVMA formulation containing 0.6% Evotherm3G and 3% Sasobit VRAs displayed the best viscosity-retarding effect while reducing the mixing temperature. Moreover, when compared to common HVMA, the eco-friendly HVMA exhibited excellent high-temperature resistance, successfully accomplishing the dual objectives of ecological friendliness and superior performance. [ABSTRACT FROM AUTHOR]

The overall rigidity of the cement concrete pavement is high, but there are defects such as easy cracking and insufficient anti-slip performance. The epoxy resin ultra-thin wearing course overlay can effectively solve these issues. However, there is still a lack of knowledge about the long-term performance of epoxy resin ultra-thin wearing course overlay on cement concrete pavement. Therefore, this article analyzed the interlayer adhesion and durability of epoxy resin ultra-thin wearing course overlay through the Hamburg rutting test and a series of shear tests under damp heat, thermal oxygen aging, and ultraviolet (UV) aging conditions. Shear test results indicated that the shear performance of epoxy resin overlay grew with the increase in epoxy resin content and was severely affected by high temperature, and the optimal content was set as 3.4 kg/m2. The Hamburg rutting test results showed that the epoxy resin overlay exhibited satisfactory high-temperature performance and water resistance. For the damp heat effect, it was revealed that damp heat led to more significant shear strength loss compared with the overlay specimens without damp heat. The water immersion caused the shear strength decline due to the water damage to the overlay interface. As for the thermal oxygen aging effect, it was reflected that the short-term thermal oxygen aging had a minor impact on the shear performance of the epoxy resin overlay. However, with the increase in thermal oxygen aging duration, the shear strength of the epoxy resin overlay significantly decreased due to the aging of epoxy resin binders. Regarding the UV aging impact, it was also found that the shear performance of the epoxy resin overlay rapidly decreased as the UV aging duration grew whether at 20 °C or 60 °C. Moreover, UV aging led to a more significant impact on the shear performance of the epoxy resin overlay than thermal oxygen aging. [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]

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]

Based on the petrological characteristics and elemental geochemical analysis of core samples from the Pingtai area in the northern structural belt of the Qaidam Basin, this study shows that the clay mineral assemblage of Lulehe Formation sandstone is dominated by high contents of smectite, chlorite and illite, and does not contain illite–smectite mixed layers or kaolinite. The chlorite and illite in the Xiaganchaigou Formation decreased gradually and the smectite disappeared. In addition, illite–smectite mixed layers began to appear and kaolinite was not present. These results indicate that the diagenetic environment of the Pingtai area in the early Eocene was dominated by alkaline media poor in K+ and rich in Mg2+, Na+ and Ca2+. In the late Eocene, K+ content in the diagenetic medium increased significantly, and smectite began to transform into illite. From the early Eocene to the late Eocene, the overall climate and environmental characteristics showed a transition from cold and dry to a cold climate that alternated between dry and wet. The content changes of common oxides, such as CaO, MgO, K2O, Na2O, SiO2, Al2O3, Fe2O3 and TiO2, showed obvious correlation. Based on the content and ratio change tendencies of Sr, Ba, Cu, Zn, U, Th, Ce and other trace elements, combined with the variation characteristics of rare earth element contents, it is suggested that the Lulehe Formation was dominated by a dry and cold freshwater sedimentary environment, and that paleoclimatic conditions were relatively cold and arid during this sedimentary period. However, the climate in the sedimentary period of the Xiaganchaigou Formation was dominated by a cold environment alternating between dry and wet, which also reflected the finding that the global climate was mainly cold and dry in the early Eocene and gradually became warm and humid in the late Eocene. [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]

The uplift of the Tibetan Plateau (TP) during the late Cenozoic is thought to be one of the crucial factors controlling the Asian climate. However, the complex interaction between tectonics and climate change remains unclear. The carbon and oxygen isotopes and elementary geochemistry of rocks from the early Eocene Lulehe Formation to the Miocene Youshashan Formation in the northern margin of Qaidam Basin, shows important variations in the Rb/Sr, MgO/CaO, Sr/Cu, and V/Cr ratios, together with CMI and CIA, which are interpreted as reflecting relevant regional climate and environmental changes. Combining the above mentioned parameters, we reconstructed the evolution of the sedimentary environment in the Qaidam Basin. The climate is roughly divided into four stages: (1) warm and humid; (2) cold and dry; (3) alternations of cold and dry with warm and humid; and (4) cold and arid. At the same time, there are also minor short-term changes of dry, wet, cold, and warm in each stage. The early Eocene to Miocene climate changes in the Qaidam Basin were mainly affected by global climate changes, the uplift of the Qinghai Tibet Plateau, and the long-lasting plate collision, but there was no continuous drought due to the uplift of the Qinghai Tibet Plateau. From the early Eocene to the late Miocene, the climate of the Qaidam Basin became warm and humid. [ABSTRACT FROM AUTHOR]

The growth of energy consumption has led to the depletion of fossil energy and the increasing greenhouse effect. In this case, low carbonization has become an important trend in the world's energy development, in which clean energy occupies an important position. The uncertainties brought by the large-scale integration of wind power, photovoltaic and other renewable energy sources into the grid pose a serious challenge to system dispatch. The participation of demand response (DR) resources can flexibly cooperate with renewable energy, optimizing system dispatch and promoting renewable energy consumption. Thus, we propose a flexible DR scheduling strategy based on multiple response modes in this paper. We first present a DR resource operation model based on multivariate response modes. Then, the uncertainties are considered and dealt with by scenario generation and reduction technology. Finally, a day-head dispatch strategy considering flexible DR operation and wind power uncertainties is established. The simulation results show that the proposed strategy promotes wind power consumption and reduces system operation costs. [ABSTRACT FROM AUTHOR]

Featured Application: The method proposed in this paper can be applied to the dispatch of power system with the large-scale integration of wind power, under the background of proposing of virtual synchronous generator technology. With the large-scale integration of renewable energy sources (e.g., wind power), the system inertial response and primary frequency regulation are affected. The virtual synchronous generator technology, which makes it possible for wind power units to adjust the frequency, provides a new way of approaching this problem. In this paper, we set up the related constraints that fit the optimal dispatch framework with a primary reserve representing the primary frequency response between the conventional synchronous generator and the wind power units, and the technical parameters of the virtual synchronous generator. Meanwhile, we use the robust day-ahead optimization dispatch model considering the wind power integrated primary frequency control in the real-time operation with the scenario of the wind power output showing the uncertainty of wind power. Based on the model, we identify the key set using an iterative method and obtain the maximum power loss. Through the proposed model, we could provide the day-ahead unit output and real-time primary reserve, thus ensuring the reliable operation of the system. Finally, the effectiveness of the proposed method is verified by a computational experiment. [ABSTRACT FROM AUTHOR]

The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. In this study, first we establish a travel pattern model based on the Monte Carlo simulation (MCS). Then, with the traveling data of EVs, we build a bi-level planning model of charging stations. For the upper model, with an aim to maximize the travel success ratio, we consider the influence of the placement of charging stations on the user’s travel route. We adopt a hybrid method based on queuing theory and the greedy algorithm to determine the capacity of charging stations, and we utilize the total social cost and satisfaction index as two indicators to evaluate the optimal solutions obtained from the upper model. Additionally, the impact of the increase of EV ownership and slow charger coverage in the public parking lot on the fast charging demands and travel pattern of EV users are also studied. The example verifies the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

In modern power systems with more renewable energy sources connected, the consideration of both security and economy becomes the key to research on power system optimal dispatch, especially when more participants from the source and load sides join in the interaction response activities. In this paper, we propose a two-stage dispatch model that contains a day-ahead multi-objective optimization scheduling sub-model that combines a hyper-box and hyper-ellipse space theory-based system security index in the first stage, and an intraday adjustment scheduling sub-model that considers active demand response (DR) behavior in the second stage. This model is able to quantitatively analyze the relationship between the security and economy of the system dispatch process, as well as the impacts of the interaction response behavior on the wind power consumption and the system's daily operating cost. The model can be applied to the evaluation of the response mechanism design for interactive resources in regional power systems. [ABSTRACT FROM AUTHOR]

The average thickness of Paleogene sandstones reaches about 3000–4000 m at the northern margin of the Qaidam Basin. However, the provenance and sedimentary environment of these sandstones are uncertain; thus, more comprehensive research is needed. Integrated research is conducted on the provenance and weathering process based on petrographic characteristics, clay minerals, and geochemical compositions of sandstones in the center of the northern Qaidam Basin. The results of lithofacies analysis show that the Paleogene sandstones were mainly derived from an active continental magmatic arc, subduction accretion, or a fold-thrust belt. The average illite content in the Paleogene clay minerals is more than 50%, followed by chlorite and smectite, which reflect climatic and environmental characteristics that were arid to semi-arid, whereas the characteristics of carbon–oxygen isotopes reveal a mainly freshwater sedimentary environment. The corrected chemical index of alteration (CIAcorr) is between 56.3 and 75.7, with an average value of 66.5. These results indicate that the provenance of the Paleogene sandstones in the center of the northern Qaidam Basin mainly formed under cold and dry climatic conditions and experienced limited chemical weathering with a small amount that underwent intermediate chemical weathering under warm and humid conditions. [ABSTRACT FROM AUTHOR]

We performed mineralogical and geochemical analyses of core samples from the Lenghuqi area in the northern marginal tectonic belt of the Qaidam Basin. The clay mineralogy of the Xiaganchaigou Formation sandstone is dominated by I + I/S + C types and characterized by high illite, a higher mixed-layer illite/smectite and chlorite, lesser smectite, and an absence of kaolinite. The clay minerals reflect that the Oligocene sedimentary basin formed in an arid-semi-arid climate with weak leaching and chemical weathering, and that diagenesis occurred in a K+- and Mg2+-rich alkaline environment. Measured major oxide concentrations show clear correlations. The lower Xiaganchaigou Formation is representative of a dry and cold freshwater sedimentary environment, whereas the upper Xiaganchaigou Formation is warmer and more humid. Trace element and rare earth element variations indicate that the paleoclimate conditions of the lower Xiaganchaigou Formation sedimentary period were relatively cold and dry, while the upper Xiaganchaigou Formation formed under warmer and more humid climate conditions. These findings reflect a global climate of a cold and dry period from the late Eocene to early Oligocene, and a short warming period in the late Oligocene. [ABSTRACT FROM AUTHOR]

Power dispatching systems currently receive massive, complicated, and irregular monitoring alarms during their operation, which prevents the controllers from making accurate judgments on the alarm events that occur within a short period of time. In view of the current situation with the low efficiency of monitoring alarm information, this paper proposes a method based on natural language processing (NLP) and a hybrid model that combines long short-term memory (LSTM) and convolutional neural network (CNN) for the identification of grid monitoring alarm events. Firstly, the characteristics of the alarm information text were analyzed and induced and then preprocessed. Then, the monitoring alarm information was vectorized based on the Word2vec model. Finally, a monitoring alarm event identification model based on a combination of LSTM and CNN was established for the characteristics of the alarm information. The feasibility and effectiveness of the method in this paper were verified by comparison with multiple identification models. [ABSTRACT FROM AUTHOR]

Alarm messages for grid monitoring are an important way to supervise the operation of power grids. Since the use of alarm messages is increasing exponentially due to the continuous expansion of the scale of power grids, a processing method for alarm messages based on statistics is proposed in this study. Entropy theory in information theory is introduced into the calculation of information value in power-grid alarming. By means of multiple entropy definitions, an evaluation index system for information value is constructed. Based on the analytic hierarchy process (AHP), various alarm-message entropies are used as indices to comprehensively assess the information value and level of each alarm message. Finally, an example is given to illustrate the effectiveness and practicality of the proposed method. This study provides a new idea for the intelligent classification of alarm messages. [ABSTRACT FROM AUTHOR]

This paper develops a nonlinear analytical algorithm for predicting the probabilistic mass flow of radial district heating networks based on the principle of heat transfer and basic pipe network theory. The use of a nonlinear mass flow model provides more accurate probabilistic operation information for district heating networks with stochastic heat demands than existing probabilistic power flow analytical algorithms based on a linear mass flow model. Moreover, the computation is efficient because our approach does not require repeated nonlinear mass flow calculations. Test results on a 23-node district heating network case indicate that the proposed approach provides an accurate and efficient estimation of probabilistic operation conditions. [ABSTRACT FROM AUTHOR]

Wind energy is a commonly utilized renewable energy source, due to its merits of extensive distribution and rich reserves. However, as wind speed fluctuates violently and uncertainly at all times, wind power integration may affect the security and stability of power system. In this study, we propose an ensemble model for probabilistic wind speed forecasting. It consists of wavelet threshold denoising (WTD), recurrent neural network (RNN) and adaptive neuro fuzzy inference system (ANFIS). Firstly, WTD smooths the wind speed series in order to better capture its variation trend. Secondly, RNNs with different architectures are trained on the denoising datasets, operating as sub-models for point wind speed forecasting. Thirdly, ANFIS is innovatively established as the top layer of the entire ensemble model to compute the final point prediction result, in order to take full advantages of a limited number of deep-learning-based sub-models. Lastly, variances are obtained from sub-models and then prediction intervals of probabilistic forecasting can be calculated, where the variances inventively consist of modeling and forecasting uncertainties. The proposed ensemble model is established and verified on less than one-hour-ahead ultra-short-term wind speed forecasting. We compare it with other soft computing models. The results indicate the feasibility and superiority of the proposed model in both point and probabilistic wind speed forecasting. [ABSTRACT FROM AUTHOR]