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Abstract Background Previous research has examined the associations of preschoolers’ 24-h movement behaviours, including light and moderate-to-vigorous physical activity (LPA and MVPA), sedentary behaviour (SB), sleep, with physical fitness in isolation, ignoring intrinsically compositional nature of movement data while increasing the risk of collinearity. Thus, this study investigated the associations of preschoolers’ 24-h Movement behaviours composition with physical fitness, estimated changes in physical fitness when time was reallocated between movement behaviours composition, and determined whether associations differ between different genders, using compositional data analysis. Methods In the cross-sectional study, a total of 275 preschoolers (3 ~ 6 y) from China were included. SB, LPA and MVPA times were objectively monitored with an ActiGraph GT9X accelerometer for 7 consecutive days. Sleep duration was obtained using parental reports. Physical fitness parameters, including upper and lower limb strength, static balance, speed-agility, and cardiorespiratory fitness (CRF), were determined with the PREFIT battery. The associations of 24-h movement behaviours composition with each physical fitness parameter were examined employing compositional multivariable linear regression models. The changes following time reallocation among behaviours were estimated employing compositional isotemporal substitution analyses. Results Greater MVPA, but not LPA, was significantly related to better upper and lower limb strength, speed-agility, and CRF. Reallocating time from LPA or SB to MVPA was related to better physical fitness. The associations were non-symmetrical: the estimated detriments to physical fitness from replacing MVPA with LPA or SB were larger than the estimated benefits associated with adding MVPA of the same magnitude. The aforementioned associations with lower limb strength, CRF, and speed-agility were observed in boys, while associations with upper and lower limb strength were noted in girls. Conclusion Our findings reinforce the importance of physical activity (PA) intensity for the development of physical fitness in preschoolers. Replacing LPA or SB time with MVPA may be an appropriate strategy for enhancing preschoolers’ physical fitness.

Abstract Lidamycin (LDM) has been confirmed to have a strong anti-pancreatic cancer effect and can affect the mitochondrial function of pancreatic cancer cells. Mitofusin-2 (Mfn2) is located in the outer membrane of mitochondria, and Mfn2 is currently believed to play a role in cancer inhibition in pancreatic cancer. In order to explore whether the anti-pancreatic cancer effect of LDM is related to Mfn2-mediated mitophagy, Bioinformatics and in vitro cell experiments are used for experimental research. The experimental results demonstrated that Mfn2 is correlated with mitochondrial autophagy in pancreatic cancer. Lidamycin can increase the expression of Mfn2 in pancreatic cancer and affect the process of EMT, affect the level of reactive oxygen species and mitochondrial membrane potential, and increase the expression of mitochondrial autophagy marker proteins BNIP3L and Beclin1. These results demonstrate that Mfn2 affects mitophagy in pancreatic cancer cells by regulating the expression of Mfn2.

Abstract The movement towards electrification is entailing deep changes in power systems. On the demand side, the adoption of electric heating (EH) has grown rapidly in recent years. To eliminate the voltage fluctuations caused by the random switching‐on/‐off behaviors of EHs in some application scenes with special‐power‐line in low voltage distribution networks (LVDNs), a swarm‐intelligence‐based coordinated control approach of EHs for voltage stabilization with zero communication burden while guaranteeing the users’ thermal comforts is researched. A novel bird‐perch‐on‐branch (BPB) ‐based swarm intelligence theory is proposed, which reveals the mapping relation between local observations and global states. On this theoretical basis, a multi‐agent reinforcement learning (MARL) framework is developed for the coordinated dispatch of EHs, where the deep‐Q‐network (DQN) algorithm is adopted to learn and generate the optimal control policy for each EH. The implementation of the proposed MADQN‐BPB approach is described based on the principle of centralized‐training and decentralized‐execution. Comparative control performances of MADQN‐BPB with a commercially available approach, and the global optimal solution are evaluated. Simulation results verify the capability of MADQN‐BPB in voltage stabilization with zero communication burden. Its control performance is close to that of the global optimal solution, and is scalable to the variations of environment.

ABSTRACTThe decline in air quality is thought to be due to rapid land use/land cover (LULC) changes near metropolitan areas that are undergoing rapid urbanisation. Here, we quantify the characteristics and relationship between the aerosol optical depth (AOD) index and LULC changes in Hangzhou, China, since the 21st century using multispectral satellite remote sensing data. The regional study results show that the correlation between the operational AOD observations (MOD04_3K) at 3 km resolution and the in situ AOD measurements available in Hangzhou ranges from 0.48 to 0.80, and their root mean square error (RMSE) < 0.30. During the past two decades, Hangzhou has been in the stage of rapid urbanisation, and the area of construction land has increased significantly, mainly converted from cultivated land and forests. The correlation coefficients between the AOD and the changes of cultivated land, forest land, grassland and construction land in Hangzhou were 0.36, 0.86, 0.61 and 0.63, respectively, indicating a strong correlation except for the cultivated land. Finally, the temporal evolution of the correlation coefficients between the cultivated land and building land are positively correlated with AOD, while from the trend of the correlation curve, grassland, woodland and AOD show negative correlations.

Abstract Pancreatic cancer (PC) is one of the most common malignant tumors of the digestive tract and has a very high mortality rate worldwide. Different PC patients may respond differently to therapy and develop therapeutic resistance due to the complexity and variety of the tumor microenvironment. The Eph/ephrin signaling pathway is extensively involved in tumor-related biological functions. However, the key function of the Eph/ephrin signaling pathway in PC has not been fully elucidated. We first explored a pan-cancer overview of Eph/ephrin signaling pathway genes (EPGs). Then we grouped the PC patients into 3 subgroups based on EPG expression levels. Significantly different prognoses and tumor immune microenvironments between different subtypes further validate Eph/ephrin's important role in the pathophysiology of PC. Additionally, we estimated the IC50 values for several commonly used molecularly targeted drugs used to treat PC in the three clusters, which could help patients receive a more personalized treatment plan. Following a progressive screening of optimal genes, we established a prognostic signature and validated it in internal and external test sets. The receiver operating characteristic (ROC) curves of our model exhibited great predictive performance. Meanwhile, we further validated the results through qRT-PCR and immunohistochemistry. Overall, this research provides fresh clues on the prognosis and therapy of PC as well as the theoretical groundwork for future Eph/ephrin signaling pathway research.

Abstract Recently, the following global-best strategy and discussion mechanism have been prevailing to solve the slow convergence and the low optimization accuracy in the brain storm optimization (BSO) algorithm. However, the traditional BSO algorithm also suffers from the problem that it is easy to fall into local optimum. Therefore, this work innovatively designed the chaotic difference step strategy. This strategy introduced four commonly used chaotic maps and difference step to expand the population search space to improve the situation. Moreover, opposition-based learning thought was innovatively adopted into the BSO algorithm. The thought aims to generate the opposition-based population, increase the search density, and make the algorithm out of the local optimum as soon as possible. In summary, this work proposed a global-best brain storm optimization algorithm based on the chaotic difference step and opposition-based learning (COGBSO). According to the CEC2013 benchmark test suit, 15 typical benchmark functions were selected, and multiple sets of simulation experiments were conducted on MATLAB. The COGBSO algorithm was also compared to recent competitive algorithms based on the complete CEC2018 benchmark test suit. The results demonstrate that the COGBSO outperforms BSO and other improved algorithms in solving complex optimization problems.

AbstractContext Qingyi granules can be used to effectively treat patients with severe acute pancreatitis (SAP).Objective To elucidate the role of gut microbiota-mediated metabolism in the therapeutic effects of Qingyi granules.Materials and methods Sprague–Dawley rats were grouped into the sham operation, SAP model, Qingyi granule intervention (Q, 1.8 g/kg) and emodin intervention (E, 50 mg/kg) groups and observed for 24 h. H&E staining and ELISA were used for histopathological analysis and serum enzyme and cytokine assays. 16S rDNA sequencing and UHPLC-HRMS were used for gut microbiota analysis and untargeted metabolomics.Results In SAP rats, Qingyi granules decreased the pancreatic pathological score (Q, 7.4 ± 1.14; SAP, 11.6 ± 1.14, p

In view of issues affecting manual on-demand sowing of spinach, such as high working intensity, low seeding efficiency, and high cost, a mechanized precision seeding device for spinach seeds is proposed, based on a spoon-wheel including a combined cell with two intersecting surfaces. The key structure was designed, and motion analysis was conducted employing SolidWorks software (2022). Additionally, the seeding process was simulated using EDEM simulation software (2022). The number of spoons, the radius of the spoons, and the speed of the seed wheel were chosen as the influencing factors, while the qualified index, reseeding index, and missing index were utilized as the evaluation indexes. A response surface method test based on the Box–Behnken design was carried out, and the test results were analyzed to obtain the optimal parameter combination for the seed-metering device. The field test results showed that when the rotation speed was 18 rpm, the radius of each seed spoon was 2.5 mm, and the number of seed spoons was 50, the average qualified index was 90.89%, the reseeding index was 8.22%, and the missed seeding index was 0.89%. The test results satisfy the technical production requirements for spinach seed sowing.

Abstract Packet switching revolutionized the Internet by allowing the efficient use of network resources for data transmission. In a previous work, we introduced packet switching in quantum networks as a path to the Quantum Internet and presented a proof-of-concept for its application to quantum key distribution (QKD). In this paper, we outline a three-step approach for key rate optimization in a packet-switched network. Our simulated results show that practical key rates may be achieved in a sixteen-user network with no optical storage capacity. Under certain network conditions, we may improve the key rate by using an ultra-low-loss fiber delay line to store packets during network delays. We also find that implementing cut-off storage times in a strategy analogous to real-time selection in free-space QKD can significantly enhance performance. Our work demonstrates that packet switching is imminently suitable as a platform for QKD, an important step towards developing large-scale and integrated quantum networks.

The aroma characteristics of crude walnut oil (CWO) and soft-refined walnut oil (RWO) were analyzed using gas chromatography-ion mobility spectrometry (GC-IMS) and headspace gas chromatography-mass spectrometry (HS-SPME-GC-MS). CWO was obtained from walnut samples of seven varieties in Yunnan using aqueous enzymatic extraction (AEE), while RWO was produced by deacidifying and dehydrating CWO. Comprehensive analyses using both GC-IMS and HS-SPME-GC-MS were performed to discern the volatile compounds in CWO and RWO. Chemometric techniques including hierarchical clustering analysis (HCA), principal component analysis (PCA), stepwise linear discriminant analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were employed for the characterization and classification of the oils. The results indicated that GC-IMS served as an excellent complementary technique to GC-MS for aroma characterization. Additionally, PLS-DA was found to be effective for categorizing walnut oil based on HS-GC-IMS. Through GC-MS and OPLS-DA, a clear distinction between CWO and RWO samples was established. The outcomes indicated that both CWO and RWO contained distinct volatile compounds, and the refining process impacted the composition of volatile compounds in the oils. This research sheds light on the volatile substances in walnut oils and their changes during the refining process, enhancing insights into moderate processing of walnut oil.

The intelligent control of precision planting can detect and regulate the operation quality of the planter in real time, which plays an important role in improving the operation quality of the planter and the yield of the corn. In this paper, the control system of a corn precision planter is designed to realize the operating quality monitoring and electric driving of the seed-metering device. The planting quality is calculated by the time interval between the neighboring falling seeds, instead of the plant spacing, to improve the operational efficiency of the system. At the same time, the forward speed of the planter is obtained by radar, which is used to accurately match the speed of the seed-metering device with the forward speed of the planter. The velocity error of the radar is analyzed, and the relevant relationship of the radar output frequency and forward speed is established. Comparative test results of this system and the JPS-12 test bench show that the detection performance of the system is reliable, and the maximum detection error of the quality parameters is less than 2.88%. Field experiments were carried out to verify the operational performance of the control system. Two speed sensors, radar and GPS, were chosen to study the effect of speed measuring on the performance of the control system. We found that speed measuring has a significant effect on planting performance. The qualified parameters of radar were significantly higher than those of GPS, at a forward speed of 6–12 km/h. The qualification feeding index (QFI) of radar was 0.51%, 0.67%, and 2.05% higher than that of GPS at speeds of 6, 8, 10, and 12 km/h. The precision index (PREC) of radar was 17.60%, 5.44%, 16.81%, and 17.30% lower than that of GPS. Therefore, the control system based on the radar speed measurement developed in this paper can significantly improve the operating quality of the planter.

The quantitative evaluation and prediction of ecosystem service value (ESV) in the Lhasa River Basin can provide a basis for ecological environment assessment and land-use optimization and adjustment in the future. Previous studies on the ESV in the Lhasa River Basin have focused mainly on static assessment and evolution analysis based on historical data, and have not considered future development trends. Moreover, most of the current driving factors selected in land use and ESV prediction studies are homogeneous, and do not reflect the geographical and cultural characteristics of the study area well. With the Lhasa River Basin as the research focus, 20 driving factors were selected according to the characteristics of the plateau alpine area, and the land-use changes under three developmental orientations, namely, natural evolution, ecological protection, and agricultural development, were predicted for the year 2030 with the FLUS-Markov model. Based on these predictions, the values of ecosystem services were calculated, and their spatiotemporal dynamic characteristics were analyzed. The results show that the model has high accuracy in simulating land-use change in the Lhasa River Basin, with a kappa coefficient of 0.989 and an overall accuracy of 99.33%, indicating a high applicability. The types of land use in the Lhasa River basin are dominated by the existence of grassland, unused land, and forest, with a combined proportion of 94.3%. The change trends of each land-use type in the basin under the three scenarios differ significantly, with grassland, cropland, and building land showing the most significant changes. The area of cropland increased only in the agricultural development scenario; the areas of forest and grassland increased only in the ecological protection scenario; and the expansion of building land was most effectively controlled in the ecological protection scenario. The ESV increased in all three scenarios, and the spatial distribution of the ESV per unit area in the middle and lower reaches was greater than that in the upper reaches. The ESV was the greatest in the ecological protection scenario, with grasslands, forests, and water bodies contributing more to the ESV of the basin. This study provides decision-making references for the effective utilization of land resources, ecological environmental protection planning, and urban construction in the Lhasa River Basin in the future.

Combined SINS/GPS navigation systems have been widely used. However, when the traditional combined SINS/GPS navigation system travels between tall buildings, in the shade of trees, or through tunnels, the GPS encounters frequent signal blocking, which leads to the interruption of GPS signals, and as a result, the combined SINS/GPS-based navigation method degenerates into a pure inertial guidance system, which will lead to the accumulation of navigation errors. In this paper, an adaptive Kalman filtering algorithm based on polynomial fitting and a Taylor expansion is proposed. Through the navigation information output from the inertial guidance system, the polynomial interpolation method is used to construct the velocity equation and position equation of the carrier, and then the Taylor expansion is used to construct the virtual measurement at the moment of the GPS signal interruption, which can make up for the impact of the lack of measurement information on the combined SINS/GPS navigation system when the GPS signal is interrupted. The results of computer simulation experiments and road measurement tests based on the loosely combined SINS/GPS navigation system show that when the carrier faces a GPS signal interruption situation, compared with a combined SINS/GPS navigation algorithm that does not take any rescue measures, our proposed combined SINS/GPS navigation algorithm possesses a higher accuracy in the attitude angle estimation, a higher accuracy in the velocity estimation, and a higher accuracy in the positional localization, and the system possesses higher stability.

Government subsidies play a crucial role in optimizing industrial structures, eliminating outdated production capacities, and facilitating industrial transformation and upgrading in traditional industries. This paper is based on data collected from 112 sources, including 26 listed companies in China's steel industry and 30 companies in the photovoltaic sector, during the period from 2019 to 2020. Utilizing the three-stage undesirable output SBM model, we examine the impact of government subsidies on input-output slack and production efficiency. We find that the production efficiency of steel enterprises and photovoltaic enterprises is seriously polarized after considering the undesirable output, and the production efficiency of relatively small enterprises is high for the steel industry. In an unstable economic environment, it is advisable for the government to provide pre-subsidies to steel enterprises to assist them in adjusting resource allocation and effectively responding to unforeseen events. Regardless of the economic conditions, photovoltaic enterprises rely more on post-subsidies to mitigate personnel and technology investment slack. Overall, this study sheds light on the effectiveness of government subsidies in driving efficiency improvements in traditional and emerging industries.

Fear refers to an adaptive response in the face of danger, and the formed fear memory acts as a warning when the individual faces a dangerous situation again, which is of great significance to the survival of humans and animals. Excessive fear response caused by abnormal fear memory can lead to neuropsychiatric disorders. Fear memory has been studied for a long time, which is of a certain guiding effect on the treatment of fear-related disorders. With continuous technological innovations, the study of fear has gradually shifted from the level of brain regions to deeper neural (micro) circuits between brain regions and even within single brain regions, as well as molecular mechanisms. This article briefly outlines the basic knowledge of fear memory and reviews the neurobiological mechanisms of fear extinction and relapse, which aims to provide new insights for future basic research on fear emotions and new ideas for treating trauma and fear-related disorders.

Because the conventional Temperature Drift Error (TDE) estimation model for Capacitive MEMS Gyros (CMGs) has inadequate Temperature Correlated Quantities (TCQs) and inaccurate parameter identification to improve their bias stability, its novel model based on thermal stress deformation analysis is presented. Firstly, the TDE of the CMG is traced precisely by analyzing its structural deformation under thermal stress, and more key decisive TCQs are explored, including ambient temperature variation ∆T and its square ∆T2, as well its square root ∆T1/2; then, a novel TDE estimation model is established. Secondly, a Radial Basis Function Neural Network (RBFNN) is applied to identify its parameter accurately, which eliminates local optimums of the conventional model based on a Back-Propagation Neural Network (BPNN) to improve bias stability. By analyzing heat conduction between CMGs and the thermal chamber with heat flux analysis, proper temperature control intervals and reasonable temperature control periods are obtained to form a TDE precise test method to avoid time-consuming and expensive experiments. The novel model is implemented with an adequate TCQ and RBFNN, and the Mean Square Deviation (MSD) is introduced to evaluate its performance. Finally, the conventional model and novel model are compared with bias stability. Compared with the conventional model, the novel one improves CMG’s bias stability by 15% evenly. It estimates TDE more precisely to decouple Si-based materials’ temperature dependence effectively, and CMG’s environmental adaptability is enhanced to widen its application under complex conditions.

Abstract It is a critical part of increasing renewable energy accommodation by using virtual power plant (VPP) to attain carbon neutrality. However, VPP applications primarily consider VPP's participation in power market transactions as a whole and rarely consider the transaction interaction between internal resources. VPP's internal resources complement each other organically, and blockchain technology for distributed transactions has incorporated points. In this article, the authors undertake a study and examine the P2P scenario of VPP internal transactions in light of the issues experienced by DERs transactions. Next, the authors analyse the consensus mechanism, smart contract, inter‐blockchain technology, and game theory, and how to apply them in the P2P scenarios of VPP internal transactions. Further, the authors design the function of the DER transaction system, which lays the foundation for the realisation of the system in the future. Finally, the authors conclude that the potential of blockchain technology in P2P transactions between internal entities of the VPP is significant and warrants further investigation.

Abstract Background Neuroendocrine tumors (NETs) arise from neuroendocrine cells and are extremely rare in the biliary tract. Currently, there are no guidelines for the diagnosis and treatment of biliary NETs. We presented a case with NETs G1 of the hilar bile duct and the challenges for her treatment. Case presentation A 24-year-old woman was presented to our department with painless jaundice and pruritus, and the preoperative diagnosis was Bismuth type II hilar cholangiocarcinoma. She underwent Roux-en-Y hepaticojejunostomy with excision of the extrahepatic biliary tree and radical lymphadenectomy. Unexpectedly, postoperative pathological and immunohistochemical examination indicated a perihilar bile duct NETs G1 with the microscopic invasion of the resected right hepatic duct. Then the patient received 3 cycles of adjuvant chemotherapy (Gemcitabine and tegafur-gimeracil-oteracil potassium capsule). At present, this patient has been following up for 24 months without recurrence or disease progression. Conclusion We know little of biliary NETs because of its rarity. There are currently no guidelines for the diagnosis and treatment of biliary NETs. We reported a case of perihilar bile duct NETs G1 with R1 resection, as far as we know this is the first report. More information about biliary NETs should be registered.

BackgroundStomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stress can promote cancer by increasing mutagenicity, genomic instability, cell survival, proliferation, and stress resistance pathways. As a direct and indirect result of oncogenic mutations, cancer depends on cellular metabolic reprogramming. However, their roles in STAD remain unclear.Method743 STAD samples from GEO and TCGA platforms were selected. Oxidative stress and metabolism-related genes (OMRGs) were acquired from the GeneCard Database. A pan-cancer analysis of 22 OMRGs was first performed. We categorized STAD samples by OMRG mRNA levels. Additionally, we explored the link between oxidative metabolism scores and prognosis, immune checkpoints, immune cell infiltration, and sensitivity to targeted drugs. A series of bioinformatics technologies were employed to further construct the OMRG-based prognostic model and clinical-associated nomogram.ResultsWe identified 22 OMRGs that could evaluate the prognoses of patients with STAD. Pan-cancer analysis concluded and highlighted the crucial part of OMRGs in the appearance and development of STAD. Subsequently, 743 STAD samples were categorized into three clusters with the enrichment scores being C2 (upregulated) > C3 (normal) > C1 (downregulated). Patients in C2 had the lowest OS rate, while C1 had the opposite. Oxidative metabolic score significantly correlates with immune cells and immune checkpoints. Drug sensitivity results reveal that a more tailored treatment can be designed based on OMRG. The OMRG-based molecular signature and clinical nomogram have good accuracy for predicting the adverse events of patients with STAD. Both transcriptional and translational levels of ANXA5, APOD, and SLC25A15 exhibited significantly higher in STAD samples.ConclusionThe OMRG clusters and risk model accurately predicted prognosis and personalized medicine. Based on this model, high-risk patients might be identified in the early stage so that they can receive specialized care and preventative measures, and choose targeted drug beneficiaries to deliver individualized medical services. Our results showed oxidative metabolism in STAD and led to a new route for improving PPPM for STAD.

Abstract Background The therapeutic value of targeted therapies in patients with lung cancer is reduced when tumours acquire secondary resistance after an initial period of successful treatment. However, the molecular events behind the resistance to targeted therapies in lung cancer remain largely unknown. Aims To discover the important role and mechanism of lncRNA BC in promoting tumor metastasis and influencing clinical prognosis of LUAD. Materials & Methods: Microarrays were used to screen a comprehensive set of lncRNAs with differential expression profiles in lung cancer cells. The functional role and mechanism of lncRNA were further investigated by gain‐ and loss‐of‐function assays. RNA pull‐down, protein assays, and mass spectrometry were used to identify proteins that interacted with lncRNA. TaqMan PCR was used to measure lncRNA in lung adenocarcinoma and adjacent nontumor tissues from 428 patients. The clinical significance of lncRNA identified was statistically confirmed in this cohort of patients. Results In this study, we show that the long non‐coding RNA BC009639 (BC) is involved in acquired resistance to EGFR‐targeted therapies. Among the 235 long non‐coding RNAs that were differentially expressed in lung cancer cell lines, with different metastatic potentials, BC promoted growth, invasion, metastasis, and resistance to EGFR‐tyrosine kinase inhibitors (EGFR‐TKIs), both in vitro and in vivo. BC was highly expressed in 428 patients with lung adenocarcinoma (LUAD) and high BC expression correlated with reduced efficacy of EGFR‐TKI therapy. To uncover the molecular mechanism of BC‐mediated EGFR‐TKI resistance in lung cancer, we screened and identified nucleolin and hnRNPK that interact with BC. BC formed the splicing complex with nucleolin and hnRNPK to facilitate the production of a non‐protein‐coding inositol monophosphatase domain containing 1 (IMPAD1) splice variant, instead of the protein‐coding variant. The BC‐mediated alternative splicing (AS) of IMPAD1 resulted in the induction of the epithelial–mesenchymal transition and resistance to EGFR‐TKI in lung cancer. High BC expression correlated with clinical progress and poor survival among 402 patients with LUAD. Disscussion Through alternative splicing, BC boosted the non‐coding IMPAD1‐203 transcript variant while suppressing the IMPAD1‐201 variant. In order to control the processing of pre‐mRNA, BC not only attracted RNA binding proteins (NCL, IGF2BP1) or splicing factors (hnRNPK), but also controlled the formation of the splicing‐regulator complex by creating RNA‐RNA‐duplexes. Conclusion Our results reveal an important role for BC in mediating resistance to EGFR‐targeted therapy in LUAD through IMPAD1 AS and in implication for the targeted therapy resistance.

Although cognitive flexibility has always been considered essential to empathy, the relevant findings have been inconsistent. Inconsistent results may be because cognitive flexibility is a multi-level structure, while empathy is also a multilayer structure, and there are differences in how researchers define and measure cognitive flexibility. Therefore, the study explores the relationship between cognitive flexibility and empathy from a multi-dimensional perspective. This study involved 105 China students aged between 18 and 22 (M age = 20.26, SD = 2.00) who completed the Cognitive Flexibility Scale (cognitive flexibility trait, cognitive flexibility at the individual level), perspective-switching flexibility task (perspective-switching flexibility, cognitive flexibility at the cognitive level), the Interpersonal Reactivity Index scale (IRI, traits empathy), Multi-dimensional Empathy Test (state empathy), 2-back task (inhibitory control), and Stroop task (working memory). After controlling for additional variables, the results showed that: (1) Cognitive flexibility traits negatively predicted trait cognitive (IRI-PT) and affective empathy (IRI-EC). (2) The Other/Self perspective-switching flexibility negatively predicted the affective component of state empathy. (3) Cognitive flexibility traits and Other/Self perspective-switching flexibility negatively predicted empathy even after controlling for one of these. The study’s results suggested that cognitive flexibility negatively predicts empathy and is a protective factor for reducing the cost of empathy and promoting emotion regulation.

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in gynecology. Traditional Chinese medicine (TCM) is widely used for the treatment of PCOS in China. The Bu Shen Hua Zhuo formula (BSHZF), a TCM decoction, has shown great therapeutic efficacy in clinical practice. However, the mechanism underlying the BSHZF function in PCOS remains unclear. This study aimed to identify the potential mechanisms of action of BSHZF in the treatment of PCOS. PCOS-model rats treated with letrozole were administered different doses of BSHZF, metformin, and 1% carboxymethylcellulose. Serum sex hormones, fasting blood glucose, and fasting insulin levels were measured, and the morphology of the ovaries was observed in each group, including the normal group. The structure and abundance of the gut microbiota in rats were measured using 16S ribosomal RNA gene sequencing. Toll-like receptor 4 (TLR4) and phospho-NF-κB p65 levels in the ovarian tissue of the rats were detected using Western blotting. Furthermore, the levels of lipopolysaccharide (LPS) and inflammatory cytokines TNF-α, IL-6, and IL-8 in the serum of rats were detected by ELISA. The results showed that BSHZF administration was associated with a decrease in body weight, fasting blood glucose, fasting insulin, and testosterone and changes in ovarian morphology in PCOS-model rats. Moreover, BSHZF was associated with an increase in the α-diversity of gut microbiota, decrease in the relative abundance of Firmicutes, and increase in Lactobacillus and short chain fatty acid–producing bacteria (Allobaculum, Bacteroides, Ruminococcaceae_UCG-014). Furthermore, BSHZF may promote carbohydrate and protein metabolism. In addition, BSHZF was associated with a decrease in the serum level of LPS and TLR4 expression, thereby inhibiting the activation of the NF-κB signaling–mediated inflammatory response in ovarian tissue. Therefore, the beneficial effects of BSHZF on PCOS pathogenesis are associated with its ability to normalize gut microbiota function and inhibit PCOS-related inflammation.

Impaired intestinal barrier function and gut microbiota dysbiosis are believed to be related to exacerbation of acute pancreatitis (AP). As a bacterial cell wall peptidoglycan component, diaminopimelic acid (DAP) is a specific ligand of NOD1 that regulates the NOD1/RIP2/NF-kB signaling pathway. Here, we investigated the role of DAP in the crosstalk between the gut microbiota and pancreas during the occurrence of AP. Upregulation of NOD1/RIP2/NF-kB and elevated serum DAP levels were found in severe AP (SAP) model rats. The accumulation of DAP in SAP patients corroborated its ability to serve as an indicator of disease severity. Subsequently, SAP rats were treated with oral administration of the traditional Chinese medicine Qingyi Keli (QYKL) as well as neomycin, which can widely eliminate DAP-containing bacteria. Both QYKL and neomycin intervention ameliorated intestinal and pancreatic damage and systemic inflammation in SAP rats. Through 16S rDNA sequencing, we found that QYKL could rehabilitate the gut microbiota structure and selectively inhibit the overgrowth of enteric bacteria, such as Helicobacter and Lactobacillus, in SAP rats without affecting some protective strains, including Romboutsia and Allobaculum. Interestingly, we demonstrated that the decrease in serum DAP was accompanied by suppression of the NOD1/RIP2/NF-kB signaling pathway in both the intestine and pancreas of the two intervention groups. Taken together, these results suggested that the gut microbiota-DAP-NOD1/RIP2 signaling pathway might play a critical role in the progression of AP and that SAP could be alleviated via intervention in the signaling pathway. Our work provides new potential early warning indicators of SAP and targets for intervention.

Abstract Background The prediction of drug-target interaction from chemical and biological data can advance our search for potential drug, contributing to a therapeutic strategy for pancreatic adenocarcinoma (PAAD). We aim to identify hub genes of PAAD and search for potential drugs from distinct databases. The docking simulation is adopted to validate our findings from computable perspective. Methods Differently expressed genes (DEGs) of PAAD were performed based on TCGA. With two Cytoscape plugins of CentiScaPe and MCODE, hub genes were analyzed and visualized by STRING analysis of Protein–protein Interaction (PPI). The hub genes were further selected with significant prognostic values. In addition, we examined the correlation between hub genes and immune infiltration in PAAD. Subsequently, we searched for the hub gene-targeted drugs in Connectivity map (Cmap) and cBioportal, which provided a large body of candidate drugs. The hub gene, which was covered in the above two databases, was estimated in Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Herbal Ingredients’ Targets (HIT) database, which collected natural herbs and related ingredients. After obtaining molecular structures, the potential ingredient from TCMSP was applied for a docking simulation. We finalized a network connectivity of ingredient and its targets. Results A total of 2616 DEGs of PAAD were identified, then we further determined and visualized 24 hub genes by a connectivity analysis of PPI. Based on prognostic value, we identified 5 hub genes including AURKA (p = 0.0059), CCNA2 (p = 0.0047), CXCL10 (p = 0.0044), ADAM10 (p = 0.00043), and BUB1 (p = 0.0033). We then estimated tumor immune correlation of these 5 hub genes, because the immune effector process was one major result of GO analysis. Subsequently, we continued to search for candidate drugs from Cmap and cBioportal database. BUB1, not covered in the above two databases, was estimated in TCMSP and HIT databases. Our results revealed that genistein was a potential drug of BUB1. Next, we generated two docking modes to validate drug-target interaction based on their 3D structures. We eventually constructed a network connectivity of BUB1 and its targets. Conclusions All 5 hub genes that predicted poor prognosis had their potential drugs, especially our findings showed that genistein was predicted to target BUB1 based on TCMSP and docking simulation. This study provided a reasonable approach to extensively retrieve and initially validate putative therapeutic agents for PAAD. In future, these drug-target results should be investigated with solid data from practical experiments.

With the advantages of large piezoelectric constant, wide frequency response range and good flexibility, Poly(vinylidine fluoride) (PVDF) is receiving heightened attention as a promising alternative to traditional piezoelectric materials. This paper focuses on investigating the magnetoelectric effect of a three-layer composite consisting of a core layer of PVDF and two layers of silver-plated electrodes under the action of AC and DC magnetic fields. The resonance frequency of the measurement system is firstly determined to obtain the maximum magnetoelectric response. Then, the existence of magnetoelectric effect in the laminated sample is further verified, which is realized through the coupling of the piezoelectric effect and the Ampere forces caused by the eddy current under the DC bias magnetic field. The experimental results show that the magnetoelectric voltage has an excellent linear response to both AC and DC magnetic fields. The magnetoelectric voltage coefficient is obtained as 299.97 mV/cm·Oe at the resonance frequency under the DC magnetic field of 1000 Oe amplitude. Besides, the theoretical model of the magnetoelectric energy conversion is established, which matches well with the experimental results. Consequently, both AC and DC magnetic field sensing can be realized by observing the magnetoelectric voltage. Without requiring a magnetostrictive phase and power supply, the three-layer composite with a considerable magnetoelectric effect is promising for the application of online monitoring sensors used in the smart grid.

Haze has a significant impact on photovoltaic (PV) power generation. When the fine particulate matter reaches a certain concentration, it becomes the main factor affecting solar irradiance and seriously reduces PV power generation, but few quantitative studies on the effect caused by haze to PV power generation. This study proposes the use of the improved method of the degree of grey slope incidence to analyze the weight factors of the effects of haze on irradiance. The exponential-linear model is used to describe the impact of haze on the amount of irradiance. Furthermore, the PV system model is used to focus on the quantitative loss of PV power under the influence of haze. By modeling and analyzing the data samples of PV power generation in Hangzhou, China, it can be concluded that the losses caused by haze on PV power generation in 2017 and 2018 were 5.25 ± 1.19% and 6 ± 1.16% of the original PV power generation, respectively. We extended this analysis to other cities to analyze the PV data in Tianjin, China. From December 2018 to December 2019, the loss of PV power generation caused by haze in Tianjin was 8.77 ± 0.9%. The quantitative analysis of haze on PV power can provide an effective basis for the economic evaluation of new PV systems and also plays an important role in the prediction and scheduling of PV power generation.

The integration of Design for Manufacture and Assembly (DfMA) into the design process of industrialized construction has the potential to reduce errors and changes occurring after the design has been finalized, ultimately improving overall productivity. Based on DfMA, the designers would need to consider whether their designs meet the architectural and performance requirements, as well as the manufacturing and assembly requirements from assembly and manufacturing technicians. However, some limitations present challenges for DfMA-oriented prefabricated design, such as lack of information interoperability, lack of conflict detection and management, and inefficient data processing and requirement checking. Thus, this research presents a novel BIM and ontology-based framework for DfMA of prefabricated and modular components. Various types of algorithms, plugins, and programming are also integrated to support the operation of the framework. The primary functions of this framework include: (1) collection of various stakeholder requirements in a standardized data format; (2) conflict detection and resolution between the design, manufacturing, and assembly requirements; and (3) automated compliance checking of whether the designed BIM models meet DfMA requirements. This research applies the framework on a prefabricated hotel project as a case study to validate the feasibility of the framework. Based on the results of a user experience survey, the developed framework shows promise for improving the DfMA process and stakeholder communication. Although a few limitations were encountered, such as the low computer operating speed and the limited ontology, the framework has been validated and shows great potential in advancing prefabricated component design applications

In order to meet the sowing demand of the hybrid rice plug seedling, a horizontal rotary precision seed metering device was proposed. The key structure parameters were designed, the kinematics analysis of the seed-filling process was carried out, and the main influencing factors of the seeding performance evaluation index were determined. Taking motor speed, the eccentric distance of the disk, and seed layer thickness as test factors, and the taking qualification rate, repetition rate, and miss-seeding rate as seeding performance test indexes, the quadratic regression orthogonal rotation combination test was carried out, and the relationship between the test factors and evaluation indexes was approached by a quadratic polynomial. On the basis of discussing the influence of the test factors on the performance index, the regression surrogate mathematical model between the main performance index and the influencing factors was established. The value of the evaluation index of correlation degree p between the model variables was less than 0.01. Based on the regression surrogate mathematical model, the response surface of the qualified rate of the seeding performance evaluation index was established, and the test data were analyzed by multiple regression analysis. The rapid prediction of qualified rates under the influence of test factors was realized, and the optimum test parameters were obtained as follows: motor speed 165 r/min, an eccentric distance of disk 22 mm, seed layer thickness 28 mm, qualification rate 98.55%, miss-seeding rate 1.45%, and repetition rate 0%. According to the best combination of test parameters, the performance evaluation index test of the prototype was carried out, and the qualification rate, miss-seeding rate, and repetition rate were 98.34%, 1.66%, and 0%. The experimental results were in good agreement with the theoretical analysis, indicating that the horizontal rotary precision seed metering device can meet the agronomic requirements of hybrid rice. The research results could provide some reference for the design of a precision seeding device for industrialized plug seedlings.

The application of agricultural robot in hilly and mountain areas faces several problems, such as bad walking performance, easy tilt, and low safety. The auto-adaptive leveling hydraulic suspension for the agricultural robot can help to eliminate some sort of problems. The design of such system is the main aim of the article. The hydraulic system with load-sensing system and its controlling model were established and then the load-sensing system was modeled and simulated in Advanced Modeling Environment for SIMulation. The optimal proportional–integral–derivative parameters were determined by the optimized algorithm. The simulation results illustrated that the inlet and outlet pressure difference of throttle and the flow rate through throttle are 42 bar and 29.65 L/min, respectively, all the time when the load pressure varies from 0 bar to 100 bar. The load-sensing system has good power follow-up and high control accuracy. And then the experimental bench of auto-adaptive leveling hydraulic suspension was researched and developed to verify the leveling performance. The experimental results demonstrate that auto-adaptive leveling hydraulic suspension can keep frame leveling dynamically on upslope, downslope, side slope, and continuous undulating road surface. The maximum errors of the pitch angle and the tilt angle are −0.93° and 0.97°. The feasibility of the designed hydraulic suspension was verified. The research methods in this article can provide theoretical basis for the design of other auto-adaptive leveling systems in hilly and mountain areas.

Large-scale quantum networks with thousands of nodes require scalable network protocols and physical hardware to realize. In this paper, we introduce packet switching as a paradigm for quantum data transmission in both future and near-term quantum networks. We propose a classical-quantum data frame structure and explore methods of frame generation and processing. Further, we present conceptual designs for a quantum reconfigurable optical add-drop multiplexer to realize the proposed transmission scheme. Packet switching allows for a universal design for a next-generation Internet where classical and quantum data share the same network protocols and infrastructure. In this quantum networking paradigm, entanglement distribution, as with quantum key distribution, is an application built on top of the quantum network rather than as a network designed especially for those purposes. For analysis of the network model, we simulate the feasibility of quantum packet switching for some preliminary models of quantum key and entanglement distribution. Finally, we discuss how our model can be integrated with other network models toward a realization of the quantum Internet.

The traditional fuzzy comprehensive evaluation (FCE) based on Analytic Hierarchy Process (AHP) has the problem of the applicability of the dimensionless method and the subjectivity of the weighting method, which lead to the inaccurate and unreasonable of evaluation results. An optimization weight (OW) and FCE (OW-FCE) model based on modified differential evolution (MDE) algorithm is proposed. For the navigation system, aiming at the problem that the conversion index of traditional dimensionless method are inaccurate, the linear extremum method and the nonlinear exponential function method are utilized to derive a hybrid dimensionless method of navigation system (NSHD method). When multi-expert weights are adopted to solve the subjectivity of weights, there is uncertainty in each weight, and the weights and OW need to be consistent, which become a difficult problem to solve OW. The optimization model of combination coefficients for OW is established, and the optimal coefficients are solved by MDE. The optimal coefficients and multi-expert weights are used to calculate OW. Taking three sets of Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) integrated navigation systems as an example, the simulation and evaluation have been carried out. The results show that the proposed model is feasible and effective, which can distinguish the system differences and provide technical support for decision makers.

Research on precision seeders operated in the dry field shows that an electric driving system used for a seed meter can significantly improve the planting uniformity. The measuring method for forward speed greatly affects the control accuracy of the electric driving system. However, the performance of an electric drive system for precision seeders operating in wet fields, such as paddy, is still unclear. The operating conditions of dry and wet fields are quite different, and it is necessary to study the effects of an electric driving system and corresponding speed measuring methods on a wet-field operating seeder. In this paper, field experiments were carried out by using a wet direct planter of rice under three driving methods for seed meter, including classic mechanical driving system (MDS), electric driving system with speed acquiring from an encoder (EDSE), and electric driving system with speed acquiring from the global positioning system (EDSG), at forward speeds of 4.62, 5.81, and 7.23 km·h−1. The seeding uniformity (seeding rates, coefficient of variations) and the slippage (slippage rate, broken strips) were investigated. Results showed that the EDSG exhibited more qualified operation performance compared with the MDS and the EDSE. For both the MDS and EDSE, the seeding rates significantly decreased and deviated from the desired value as the forward speed increased. The negative slippages of MDS and EDSE were 3.47–31.72% and 2.13–7.7%, respectively, and they significantly increased when the forward speeds increased from 4.62 to 7.23 km·h−1. Analysis of the seeding uniformity and slippage presented that the EDSG exhibited a more qualified operation and is recommended for the wet direct seeder of rice.

Abstract Background The goat is an important farm animal. Reproduction is an important process of goat farming. The ovary is the most important reproductive organ for goats. In recent years, an increasing number of long non-coding RNAs (lncRNAs) have been implicated in the regulation of mammal reproduction. However, there are few studies on the function of lncRNAs in reproduction, particularly lncRNAs in the ovary. Results The sequencing of goat ovaries generated 1,122,014,112 clean reads, and 4926 lncRNAs and 1454 TUCPs (transcripts of uncertain coding potential) were identified for further analysis by using the coding potential analysis software, CNCI, CPC and Pfam-sca. There were 115 /22 differential lncRNAs /TUCPs transcripts between the ovaries of the luteal phase and the follicular phase. We predicted the related genes of lncRNA /TUCP based on co-expression and co-localization methods. In total, 2584 /904 genes were predicted by co-expression, and 326/73 genes were predicted by co-localization. The functions of these genes were further analyzed with GO and KEGG analysis. The results showed that lncRNAs /TUCPs, which are highly expressed in goat ovaries in the luteal phase, are mainly associated with the synthesis of progesterone, and we filtered the lncRNAs /TUCPs, such as XR_001918177.1 and TUCP_001362, which may regulate the synthesis of progesterone; lncRNAs /TUCPs, which are highly expressed in goat ovaries in the follicular phase, are mainly associated with oogenesis and the maturation of oocytes, and we filtered the lncRNAs /TUCPs that may regulate the oogenesis and maturation of oocyte, such as XR_001917388.1 and TUCP_000849. Conclusion The present study provided the genome expression profile of lncRNAs /TUCPs in goat ovaries at different estrus periods and filtered the potential lncRNAs /TUCPs associated with goat reproduction. These results are helpful to further study the molecular mechanisms of goat reproduction.

The performance of energy recovery turbine (ERT) directly determines the cost and energy consumption of reverse osmosis desalination. In order to study the performance and loss mechanisms of ERT under different conditions, the external characteristics and the losses of different components were quantitatively analyzed. The loss mechanisms of each component in the turbine were revealed through the comparative analysis of the internal flow field. The results show that the efficiency is 2.2% higher than that at the design speed when turbine runs at n = 22000 r/min. The impeller losses account for more than 67% of the total losses. The impeller loss is mainly observed at the leading edge. The vortex on the pressure side of the leading edge is caused by the impact effect, while the vortex on the suction side of the leading edge is caused by the flow separation. With the increase in the rotating speed, the loss caused by flow separation in impeller decreases obviously. The volute loss is mainly observed near the tongue, which is caused by the flow separation at the tongue. The design of the tongue is very important to the performance of the volute. The turbulent kinetic energy (TKE) and loss decrease with the increase in the rotating speed. The loss in the draft tube is mainly observed at the inlet core. With the increase in the rotating speed, the turbulence pulsation and the radial pressure fluctuation amplitude reduce. Therefore, the turbine can be operated at the design or slightly higher than the design rotating speed under the condition that both the hydraulic condition and the intensity are satisfied, which are conducive to the efficient utilization of energy.

The rise of China was closely associated with the strategic opportunity offered by a wave of globalization dating from the 1970s. As China grew, western growth was not restored. Soon after the collapse of the Soviet Union and the arrival of the unipolar moment, the world confronted a succession of crises that western countries struggled to handle. In this world in which China's continuing rise was already perceived as a strategic challenge, the COVID-19 pandemic was met with further examples of liberal capitalist governance failure. Notwithstanding attempts to preserve western hegemony and a western liberal world order, the COVID-19 pandemic will accelerate and intensify existing trends towards a global reset, a shift in the centre of economic gravity to Asia, the arrival of a multipolar world and new global development paths.

Owing to the fact that the conventional Temperature Drift Error (TDE) precise estimation model for a MEMS accelerometer has incomplete Temperature-Correlated Quantities (TCQ) and inaccurate parameter identification to reduce its accuracy and real time, a novel TDE precise estimation model using microstructure thermal analysis is studied. First, TDE is traced precisely by analyzing the MEMS accelerometer’s structural thermal deformation to obtain complete TCQ, ambient temperature T and its square T2, ambient temperature variation ∆T and its square ∆T2, which builds a novel TDE precise estimation model. Second, a Back Propagation Neural Network (BPNN) based on Particle Swarm Optimization plus Genetic Algorithm (PSO-GA-BPNN) is introduced in its accurate parameter identification to avoid the local optimums of the conventional model based on BPNN and enhance its accuracy and real time. Then, the TDE test method is formed by analyzing heat conduction process between MEMS accelerometers and a thermal chamber, and a temperature experiment is designed. The novel model is implemented with TCQ and PSO-GA-BPNN, and its performance is evaluated by Mean Square Error (MSE). At last, the conventional and novel models are compared. Compared with the conventional model, the novel one’s accuracy is improved by 16.01% and its iterations are reduced by 99.86% at maximum. This illustrates that the novel model estimates the TDE of a MEMS accelerometer more precisely to decouple temperature dependence of Si-based material effectively, which enhances its environmental adaptability and expands its application in diverse complex conditions.

An industrial furnace, such as a blast furnace, molten salt furnace and a basic oxygen furnace, is a popular reactor, where the distribution of liquid, flow pattern of the fluid and the velocity of the fluid determine the energy distribution and chemical reaction in the reactor. Taking a furnace as the research object, this paper studies the effects of different inlet velocities, liquid densities and viscosity on bubble and velocity distribution. A three-dimensional mathematical model of the furnace is set up by a numerical simulation, and the volume-of-fluid (VOF) method is used to study the behavior of bubbles. The accuracy of the simulation parameters selected in the simulation calculation is verified by comparing the simulation with the experimental results. The findings show that an excessive or too small an inlet velocity will lead to an uneven distribution of chlorine in the furnace, therefore, an inlet velocity of about 30 m/s is more appropriate. In addition, changing the liquid density has little effect on the bubble and velocity distribution while choosing the appropriate liquid viscosity can ensure the proper gas holdup and fluidity of chlorine in the furnace.

Background The functional significance of ADAMs family members in the immune infiltration of pancreatic adenocarcinoma (PAAD) awaits elucidation. Methods ADAMs family members with significant expression were identified among differentially expressed genes of PAAD based on The Cancer Genome Atlas (TCGA) database followed by a verification based on the Oncomine database. The correlation of ADAMs in PAAD was estimated with the Spearman’s rho value. The pathway enrichment of ADAMs was performed by STRING and GSEALite, respectively. The protein–protein interaction and Gene Ontology analyses of ADAMs and their similar genes were exanimated in STRING and visualized by Cytoscape. Subsequently, the Box-Whisker plot was used to show a correlation between ADAMs and different tumor grade 1/2/3/4 with Student’s t-test. TIMER was applied to estimate a correlation of ADAMs expressions with immune infiltrates and immune checkpoint blockade (ICB) immunotherapy-related molecules. Furthermore, the effect of copy number variation (CNV) of ADAMs genes was assessed on the immune infiltration levels. Result ADAM8/9/10/12/15/19/28/TS2/TS12 were over-expressed in PAAD. Most of the nine ADAMs had a significant correlation. ADAM8/12/15/19 expression was remarkably increased in the comparison between grade 1 and grade 2/3 of PAAD. ADAM8/9/10/12/19/28/TS2/TS12 had a positive correlation with almost five immune infiltrates. ADAM12/19/TS2/TS12 dramatically related with ICB immunotherapy-related molecules. CNV of ADAMs genes potentially influenced the immune infiltration levels. Conclusion Knowledge of the expression level of the ADAMs family could provide a reasonable strategy for improved immunotherapies to PAAD.

The strain responses of asphalt pavement layer under vehicular loading are different from those under falling weight deflectometer (FWD) loading, due to the discrepancies between the two types of loadings. This research aims to evaluate and compare the asphalt layer responses under vehicular loading and FWD loadings. Two full-scale asphalt pavement structures, namely, flexible pavement and semirigid pavement, were constructed and instrumented with strain gauges. The strain responses of asphalt layers under vehicular and FWD loadings were measured and analyzed. Except for field measurements, the finite element (FE) models of the experimental pavements were established to simulate the pavement responses under a wide range of loading conditions. Field strain measurements indicate that the asphalt layer strain under vehicular loading increases with the rising temperature roughly in an exponential mode, while it decreases with the rising vehicular speed approximately linearly. The strain pulses in the asphalt layer generated by FWD loading are different from those induced by vehicular loading. The asphalt layer strains generated by FWD loading are close to those induced by low vehicular speed (35 km/h). The results from the FE model imply that the asphalt layer strains under FWD loading and vehicular loading are distributed similarly in the depth profile. For flexible pavement, the position of critical strain shifts gradually from the bottom of the asphalt layer to the mid-depth of the layer, as the temperature increases. For semirigid pavement, the position of critical strain is always located at the intermediate depth of the asphalt layer, regardless of temperatures.

Due to the significant spatial variation of the performance of Moderate Resolution Imaging Spectrometer (MODIS) aerosol optical depth (AOD) retrievals, validation is very important for applications of MODIS AOD products at regional scales. This study presents a comparative analysis of Collection 6.1 MODIS AOD retrievals and ground measurements from five local sites and one Aerosol Robotic Network (AERONET) site in the Yangtze River Delta (YRD) region, which significantly complements the previous validation that utilized limited AERONET measurements. Generally, MODIS AOD retrievals showed a reasonable agreement with collocated ground measurements (R2 > 0.7), with 66% of Dark Target (DT) 10 km retrievals, 56% of Deep Blue (DB) 10 km retrievals, and 69% of DT 3 km retrievals falling within the expected error (EE = ±(0.05 + 0.2 × AOD)). Nevertheless, it was found that the DT AOD retrievals tended to be overestimated over urbanized and lakeside sites, while the DB AOD retrievals tended to be underestimated over all ground sites except for lakeside sites. Such patterns appeared to be linked with the systematic biases of the single-scattering albedo estimation in the AOD retrieval algorithms. Another significant finding of this study is that the uncertainties of the MODIS AOD retrievals were highly correlated with the land cover proportions of urbanized features and water (LCP_UW) in the surrounding region, especially for the DT products. An empirical correction method based on these correlations could substantially reduce the uncertainties of DT AOD products over high LCP_UW areas. The results not only highlight the significant impacts of both urban and water areas on the MODIS AOD retrieval algorithms but also create new possibilities to correct such impacts once the universal correlations between LCP_UW and the uncertainty measures are established.

Abstract This paper presents a demand dispatch strategy of aggregated electric water heaters (EWHs) for a load aggregation system at demand side, based on the theory of cyber-physical system. The objective is to solve the problem of water heater load control when the cyber-physical load aggregation system participates in demand dispatch of the power grid. First, an implementation framework of the demand dispatch strategy is designed between the cyber space and the physical space, including state awareness, real-time analysis, scientific decision-making and precise execution. Second, a multilevel incentive model, an EWH appliance model and a thermostat setpoint control rule are introduced. Next, based on the models and the rule, the state awareness logic, real-time analysis logic, scientific decision-making logic and precise execution logic of the strategy are designed to implement demand dispatch of aggregated EWHs. Finally, simulation results confirm the effectiveness, the advantage and excellent scalability of the proposed strategy.

Non-intrusive load identification is important to load monitoring and smart power utilization. In order to effectively identify load status and obtain detailed power data, this paper explained a load identification algorithm based on load decomposition and frequency domain filtering. It realized load decomposition through solving an underdetermined problem of a single current signal under non-intrusive collection mode and then further achieved load identification. The underdetermined problem was optimized into a 1-D underdetermined problem. The solving model was constructed as separating the collecting current into two channels. According to the sparseness of the current frequency domain signal, the optimal solution was obtained by a two-step iterative shrinkage threshold algorithm. Therefore, each operation load can be decomposed independently. The frequency-domain filter group was conducted to filter the decomposition current, and load identification was realized based on the decision of the frequency component after filtering. The algorithm simplified the identification complexity, with a fast convergence rate and high identification accuracy. The performance was validated by the actually measured data. The load decomposition and identification was effective, which could accurately determine the load status, and obtain the current waveform of the independent load.

With the rapid development of smart grid and energy Internet, the electric power communication network (EPCN) has more and more data traffic. Under the premise of safety and reliability, this paper studies the survivability technology for dispatching service of EPCN to improve the resource utilization rate of EPCN and increase the network capacity. We design the equipotential preconfigured cycle (p-Cycle) algorithms based on the failure independent path-protecting p-Cycle (FIPP p-Cycle). To guarantee the optimality of the result, we first build a mixed integer linear program model, namely, equipotential path-limited mixed integer linear program of the FIPP p-Cycle. Then, we develop a time-efficient heuristic algorithm, namely, the heuristic algorithm for configuring p-Cycle. As an example, we simulate with EPCN topology from the Jiangsu Province of China, considering end-to-end limited-path protection, reliability of demand, and predefined communication topology given by the electrical grid and the presence of a central dispatching center. Compared with the traditional survivability technology, the two proposed algorithms give better performance.

Internet of Energy is promoting the deep integration between power grid and communication technologies, while the production, operation and service mode of the power grid are undergoing great evolutions. The expanded services need to be carried by efficient electric power communication network (EPCN). Aiming at releasing the bottleneck problem of link capacity in EPCN, we propose a pre-cross-connected trail (p-Trail)-based protection algorithm with load balance (TPLB) in this paper. First, we introduce the current statue and developing trend of EPCN and analyze traffic flow characteristics of various electric communication services. Then the protecting principles and implementing steps of the proposed TPLB algorithm are described in detail, in which an efficient load balancing algorithm is designed to groom the traffic flow. Finally, the validity and efficiency of TPLB is verified and analyzed in a real EPCN topology from a city of Jiangsu Province, China. It is demonstrated from the simulation results that compared with the existing algorithms, the proposed TPLB can further decrease the network redundancy and blocking probability, and improve the utilization of wavelength resources.

In order to understand the effect of sand type on the rheological properties of self-compacting mortar, four varieties of sand, namely, quartz sand (QS), river sand (RS), and two kinds of manufactured sand, marked as MS-A and MS-B, were studied. As part of this study, the sands’ particle shape parameters, such as their length:width ratio and roundness, were determined. Mortars containing the four varieties of sand were tested using the slump flow test and the V-funnel test in oven-dried (OD) and saturated surface-dried (SSD) conditions in order to identify the water absorption, shape-related differences, and specific gravity in their rheological performance. The changing trends of the slump flows and the V-funnel times of the different mortars in OD and SSD were similar. By eliminating the influence of water absorption on mortar rheology, shape–weight parameters, such as the ratio between the length:width ratio and specific gravity (LWS) and the product of roundness and specific gravity (ROS), were defined in order to quantify the compound effects of sand type on mortar rheology. The regression analysis showed an excellent linear correlation between slump flow and both LWS and ROS, and a very good linear correlation was also demonstrated between the V-funnel time and both LWS and ROS. Based on the particle shape–weight parameters, the rheological properties of mortars can be predicted. Based on the mortar rheological threshold theory, the self-compacting mortar (SCM) zone can be drawn. The predicted SCM zone overlaps considerably with the experimental SCM zone for MS-A.

Congestion control is one of the key research topics in relation to the routing algorithms of wireless sensor networks (WSNs). In this paper, we propose a congestion-aware routing algorithm (CARA) for unlimited-lifetime wireless sensor networks by integrating the geographic distance and traffic load of sensor nodes. The algorithm takes alleviating congestion as the primary purpose and considers the traffic of the node itself and local network traffic. According to the geographic distance between nodes, CARA defines four decision parameters (node load factor, forward rate, cache remaining rate, and forward average cache remaining rate), selecting the best node as the next-hop through the multi-attribute decision-making method. Compared with the two existing algorithms for congestion control, our simulation results suggest that the CARA algorithm alleviates network congestion and meets reasonable network delay and energy consumption requirements.