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This paper is dedicated to studying the existence of periodic solutions to a new class of forced damped vibration systems by the variational method. The advantage of this kind of system is that the coefficient of its second order term is a symmetric $N \times N$ matrix valued function rather than the identity matrix previously studied. The variational principle of this problem is obtained by using two methods: the direct method of the calculus of variations and the semi-inverse method. New existence conditions of periodic solutions are created through several auxiliary functions so that two existence theorems of periodic solutions of the forced damped vibration systems are obtained by using the least action principle and the saddle point theorem in the critical point theory. Our results improve and extend many previously known results.

Emerging organophosphate flame retardants (eOPFRs) have attracted attention in recent times and are expected to gain extensive usage in the coming years. However, they may have adverse effects on organisms. Due to their novel nature, there are few relevant articles dealing with toxicological studies of the above eOPFRs, especially their information on the perturbation of cellular metabolism, which is, thus far, marginally understood. Our research initially assessed the cytotoxicity of eOPFRs, which include compounds like cresyl diphenyl phosphate (CDP), resorcinol bis(diphenyl phosphate) (RDP), triallyl phosphate (TAP), and pentaerythritol phosphate alcohol (PEPA). This evaluation was conducted using the methyl thiazolyl tetrazolium (MTT) assay. Subsequently, we utilized a gas chromatography/mass spectrometry (GC/MS)-based metabolomic approach to investigate the metabolic disruptions induced by these four eOPFRs in A549 cells. The MTT results showed that, at high concentrations of 1 mM, their cytotoxicity was ranked as CDP > TAP > RDP > PEPA. In addition, metabolic studies at low concentrations of 10 μM showed that the metabolic interference of CDP, TAP, and PEPA focuses on oxidative stress, amino acid metabolism, and energy metabolism, while RDP mainly affects energy metabolism—galactose metabolism and gluconeogenesis. Therefore, from the perspective of cytotoxicity and metabolic analysis, RDP may be a more promising alternative. Our experiments provide important insights into the possible metabolic effects of potential toxic substances and complement the evidence on the human health risks of eOPFRs.

In this paper, we study the variational principle and the existence of periodic solutions for a new class of second-order ordinary p-Laplacian systems. The variational principle is given by making use of two methods. We obtain three existence theorems of periodic solutions to this problem on various sufficient conditions on the potential function F(t,x) or nonlinearity ∇F(t,x). Four examples are presented to illustrate the feasibility and effectiveness of our results.

Introduction: Methamphetamine (METH) abuse by pregnant drug addicts causes toxic effects on fetal neurodevelopment; however, the mechanism underlying such effect of METH is poorly understood.Methods: In the present study, we applied three-dimensional (3D) neurospheres derived from the embryonic rat hippocampal tissue to investigate the effect of METH on neurodevelopment. Through the combination of whole genome transcriptional analyses, the involved cell signalings were identified and investigated.Results: We found that METH treatment for 24 h significantly and concentration-dependently reduced the size of neurospheres. Analyses of genome-wide transcriptomic profiles found that those down-regulated differentially expressed genes (DEGs) upon METH exposure were remarkably enriched in the cell cycle progression. By measuring the cell cycle and the expression of cell cycle-related checkpoint proteins, we found that METH exposure significantly elevated the percentage of G0/G1 phase and decreased the levels of the proteins involved in the G1/S transition, indicating G0/G1 cell cycle arrest. Furthermore, during the early neurodevelopment stage of neurospheres, METH caused aberrant cell differentiation both in the neurons and astrocytes, and attenuated migration ability of neurospheres accompanied by increased oxidative stress and apoptosis.Conclusion: Our findings reveal that METH induces an aberrant cell cycle arrest and neuronal differentiation, impairing the coordination of migration and differentiation of neurospheres.

Abstract Background Cancer cells have an imbalance in oxidation-reduction (redox) homeostasis. Understanding the precise mechanisms and the impact of the altered redox microenvironment on the immunologic reaction to tumors is limited. Methods We isolated exosomes from ovarian cancer cells through ultracentrifuge and characterized by Western-blots and Nanoparticle Tracking Analysis. 2D, 3D-coculture tumor model, and 3D live cell imaging were used to study the interactions between tumor cells, macrophages and CD3 T cells in vitro. The role of exosomal miR-155-5p in tumor growth was evaluated in xenograft nude mice models and immune-competent mice models. Flow cytometry and flow sorting were used to determine the expression levels of miR-155-5p and PD-L1 in ascites and splenic macrophages, and the percentages of CD3 T cells subpopulations. Results The elevation of reactive oxygen species (ROS) greatly downregulated exosomal miR-155-5p expression in tumor cells. Neutralization of ROS with N-acetyl-L-cysteine (NAC) increased the levels of miR-155-5p in tumor exosomes that were taken up by macrophages, leading to reduction of macrophage migration and tumor spheroid infiltration. We further found that programmed death ligand 1 (PD-L1) is a functional target of miR-155-5p. Co-culture of macrophages pre-treated with NAC-derived tumor exosomes or exosomal miR-155-5p with T-lymphocytes leading to an increased percentage of CD8+ T-lymphocyte and a decreased CD3+ T cell apoptosis through PD-L1 downregulation. Tumor growth in nude mice was delayed by treatment with NAC-derived tumor exosomes. Delivery of tumor exo-miR-155-5p in immune-intact mice suppressed ovarian cancer progression and macrophage infiltration, and activated CD8+ T cell function. It is of note that exo-miR-155-5p inhibited tumor growth more potently than the PD-L1 antibody, suggesting that in addition to PD-L1, other pathways may also be targeted by this approach. Conclusions Our findings demonstrate a novel mechanism, ROS-induced down-regulation of miR-155-5p, by which tumors modulate the microenvironment that favors tumor growth. Understanding of the negative impact of ROS on the tumor immune response will improve current therapeutic strategies. Targeting miR-155-5p can be an alternative approach to prevent formation of an immunosuppressive TME through downregulation of PD-L1 and other immunosuppressive factors. Graphical Abstract

CO2-based enhanced geothermal systems (CO2-EGS) are greatly attractive in geothermal energy production due to their high flow rates and the additional benefit of CO2 geological storage. In this work, a CO2-EGS model is built based on the available geological data in the Gonghe Basin, Northwest China. In our model, the wellbore flow is considered and coupled with a geothermal reservoir to better simulate the complex CO2 flow and heat production behavior. Based on the fractured geothermal reservoir at depths between 2900 m and 3300 m, the long-term (30-year) heat production performance is predicted using CO2 as the working fluid with fixed wellhead pressure. The results indicate that the proposed CO2-EGS will obtain an ascending heat extraction rate in the first 9 years, followed by a slight decrease in the following 21 years. Due to the significant natural convection of CO2 (e.g., low viscosity and density) in the geothermal reservoir, the mass production rate of the CO2-EGS will reach 150 kg/s. The heat extraction rates will be greater than 32 MW throughout the 30-year production period, showing a significant production performance. However, the Joule–Thomson effect in the wellbore will result in a drastic decrease in production temperature (e.g., a 62.6 °C decrease in the production well). This means that the pre-optimization analyses and physical material treatments are required during geothermal production using CO2 as the working fluid.

Exogenous melatonin (MT) is widely used in fruit preservation, and can increase the storage time and delay the quality deterioration. Firstly, it was found that 150 μM MT was the optimal concentration to treat ‘Xinli No.7’ under storage at 4 °C for 60 days. MT could significantly improve oxidase activity and inhibit the reduction of physiological indexes, including pulp hardness, weight loss, titratable acid and soluble solid content. MT could also reduce ethylene release and limit the reduction of fruit aroma. The average content of fruit aroma substance increased by 43.53%. A relevant RNA-Seq database was built to further explore the regulation mechanism of MT. A total of 2,761 differentially expressed genes (DEGs) were identified. DEGs were enriched in 64 functional groups and 191 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. DEGs were mainly enriched in alpha-linolenic acid metabolism, fatty acid metabolism and plant hormone signal transduction pathway. The gene pycom09g05270 belonging to long chain acyl-CoA synthetase family and participating in fatty acid metabolism pathway was identified, and its expression level was consistent with fragments per kilobase per million mapped reads (FPKM) values, implying that pycom09g05270 might play a vital role in maintaining quality during the storage process.

Polyelectrolyte-doped microcapsules (PDM) was fabricated by coaxial electrospray of a mixture of glycerol and water containing 10 mg/mL cationic polyelectrolyte poly(allylamine hydrochloride) (PAH) fed as the core phase solution, and a N,N-dimethylacetylamide solution of 10 wt% polyurethane fed as the shell phase solution. Multi-enzyme system involving Candida Antarctica lipase B (CALB), glucose oxidase (GOD), and horseradish peroxidase (HRP) for cascade reaction was assembled in the PDM at three different places, namely, surface, shell, and lumen. Placing of enzyme inside aqueous lumen of the PDM was realized by in situ encapsulation through adding the enzyme in the core-phase solution for coaxial electrospray. By ion-pairing of enzyme with cationic surfactant CTAB, an organic soluble enzyme-CTAB complex was prepared, so that in situ embedding of enzyme in the shell of the PDM was realized by adding it into the shell phase solution. Surface attachment of enzymes was achieved by layer-by-layer (LbL) technology, which is based on the ion-exchange interactions between oppositely charged enzymes and PAH that was doped in PDM. The enzyme-decorated microcapsule was then studied as a micro-bioreactor, in which 1-Oxododecyla-α-glucopyranoside was converted by CALB to glucose, which was oxidised by GOD to gluconolactone in a second step. The hydrogen peroxide produced was then used by HRP to oxidize ABTS to form coloured radical cation ABTS•+ for activity analysis. The successful fabrication of the PDM and precise localization of enzymes in the PDM by different strategies were fully characterized. By varying the immobilization strategy, totally six PDM bioreactors with three enzymes precisely positional assembled in different strategies were constructed and their activities for the cascade reaction were investigated and compared. The PDM micro-bioreactor prepared by novel electrospray technologies provide a smart platform for positional assembly of multi-enzyme cascade reaction in a precise and well-controlled manner.

The rapid expansion of information content on the internet and the mobile internet has resulted in violations of laws and regulations and bad information,which affects the content security of the internet space.Traditional text content security recognition methods based on matching of sensitive words ignore context semantics,resulting in high false positive rate and low accuracy.Based on the analysis of traditional text content security recognition methods,a fusion recognition model using deep learning and a model fusion algorithm process were proposed.Text content security recognition system based on the fusion recognition model using deep learning and experimental verification was introducted deeply.Results show that the proposed model can effectively solve the problem of high false positive rate caused by the lack of semantic understanding of traditional recognition methods,and improve the accuracy of the bad information detection.

Ochratoxin A (OTA) is a mycotoxin found in a variety of foods and herbal medicines, and several governmental bodies around the world have set maximum allowable levels of OTA in different foods and herbal medicines. This study aims to evaluate the health risk of OTA in Astragali Radix (AR) in China, and to evaluate the effects of different limit levels on the risk control of OTA in AR. The concentrations of OTA in 187 samples of AR were investigated, and 61 (32.6%) samples were positive. The mean, 50th and 95th percentile values of OTA in positive samples were 56.2, 5.1 and 304.5 μg/kg, respectively. A margin of exposure (MOE) approach was applied to assess the risk. Considering other food sources, long-term consumers have a relatively high risk of OTA exposure due to the ingestion of AR. Theoretical limit levels of OTA in AR were evaluated from two dimensions by weighing the costs and the benefits. The results indicated that the limit levels that might be applied to the management of OTA contamination in AR in China could be screened out through risk-based evaluation of limit levels.

With the obvious improvement of various telecom business demands,the outbound call industry,which is the main channel for marketing,resolution and notification of telephone services under the traditional mode,is facing more and more pain points,including market,personnel,training,customer sentiment,cost,accurate data and people flow in all aspects.In order to realize the cost reduction and efficiency increase,inject wisdom and improve capability of telecom services,the main needs of the existing network outbound call system were combined with the application of artificial intelligence and big data technology in the field of outbound calls,aim to build intelligent and high efficiency.A discussion of the feasibility of the program was given based on the network construction involved in the efficiency of the ＆quot;smart outbound system＆quot;.

Background: Hierarchical medical system (HMS) is a good policy to promote the fairness of medical services for residents. Given the importance of HMS, it is necessary to know the implementation effect of the policy. Therefore, we aimed to analyze the efficiency of medical service resources in China under the background of hierarchical medical policy. Methods: Based on the panel data of China's medical resources in 2015-2019, we used DEA model to calculate the technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of medical resources from both lateral and longitudinal aspects. We used Malmquist index to evaluate the change trend of efficiency, and further we compared the efficiency differences of regions and medical institutions. Results: In lateral evaluation results, TE was relatively stable, while total factor productivity (TFP) was on the rise. In longitudinal evaluation results, TE and TFP showed a downward trend. Conclusion: The government should consider the differences in development between regions and make health plans by regions. Medical institutions should strive to break down the constraints and make use of their advantages, which is conducive to improving efficiency.

Multienergy load forecasting (MELF) is the premise of regional integrated energy systems (RIES) production planning and energy dispatch. The key of MELF is the consideration of multienergy coupling and the improvement of prediction accuracy. Therefore, a MELF method considering the multienergy coupling of variation characteristic curves (MELF_MECVCC) for RIES is proposed. The novelty of MELF_MECVCC lies in the following three aspects. 1) For the trend stripping and volatility extraction of multienergy load time series, the extreme-point symmetric mode decomposition-sample entropy (ESMD-SE) method is introduced to decompose and reconstruct the variation characteristic curves of multienergy, including trend curve and fluctuation curve. 2) The multienergy coupling of the variation characteristic curves is considered to reflect the variation characteristics of the multienergy loads. 3) Different methods are applied according to different variation characteristics; i.e., the combined method based on multitask learning and long short-term memory network (MTL-LSTM) is applied to predict the trend curve with strong correlation and the least square support vector regression (LSSVR) method is applied to predict the fluctuation curve with strong volatility and high complexity. Based on the actual data set of the University of Texas in Austin, the MELF_MECVCC model is simulated and verified, which shows that the model reduces the mean absolute percentage error (MAPE) and the root mean square error (RMSE) and fits better with the original load and has higher prediction accuracy, compared with current advanced algorithms.

Networking and intelligentization are the future development directions of interactive service systems.Internet popularization and rich social channels have realistic needs for intelligent interactive services.High-quality and low-cost intelligent interactive solutions have become the main issues that need to be addressed in various industries.Relying on artificial intelligence technology,intelligent means such as intent recognition,semantic understanding,dialogue and judgment were introduced,the integration of scene design and knowledge fragmentation processing technology has brought new means and opportunities for the realization of interactive service intelligence.The problems faced by the existing interactive system were analyzed.On this basis,the key functional elements and system architecture of the intelligent interactive system were designed.

Text classification is very important to text data mining and value exploration.The traditional text classification system has problems of weak feature extraction ability and low classification accuracy.Compared with the traditional text classification technology,deep learning technology has many advantages such as high accuracy and effective feature extraction.Therefore,it is necessary to apply deep learning technology to the text classification system to solve the problems of the traditional text classification system.The traditional text classification system was analyzed,and the architecture and key technologies of text classification system based on deep learning were proposed.Finally,several classification models were verified and compared,including the traditional classification model,TextCNN and CNN+LSTM.

As the most important contact point for customers in the internet industry,customer service orders have become the main issues that need to be addressed and urgently solved in various industries.The intelligent sequencing of work orders provides a feasible application for solving this problem.The rapid development of artificial intelligence technology and big data technology has given new directions and opportunities to solve such problems.The background of the intelligent sequencing of customer service orders was analyzed firstly.On the basis of this,the main methods and implementations of intelligent sequencing of customer service orderswere analyzed,and the application of intelligent sequencing of customer service orders based on multi-factor vectorization was expounded.

Meropenem (MER) is widely used to treat complicated and serious infections. Therapeutic drug monitoring (TDM) provides a valid clinical tool to avoid suboptimal concentrations and dose–related adverse reactions. However, TDM seems to face challenges since the limited stability of MER in plasma makes transport difficult between clinics and laboratories. Dried plasma spot (DPS) sampling is an attractive but underutilized method for TDM that has the desired features of easy collection, storage, and transport, and overcomes known hematocrit (HCT) issues in dried blood spot (DBS) analysis. This study was designed to investigate a DPS–based liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for quantification of MER. The method was developed and validated for DPS and wet plasma samples. Calibration curves were linear (R2 > 0.995) over the concentration range of 0.5–50 µg/mL. Overall accuracy and precision did not exceed 15% and no significant matrix effect was observed. MER has been more stable in DPS than in wet plasma samples. A comparison of DPS and wet plasma concentrations was assessed in 32 patients treated with MER. The results showed that there was no significant difference between the two methods. So the DPS method developed in this study is appropriate and practical for the monitor of MER in the daily clinical laboratory practice.

The big data resources possessed by telecom operators are usually distributed in many different systems,such as DPI、OIDD、CRM.Moreover,the formulation,interpretation and rules of the big data are not always the same in different systems.Therefore,it is difficult to identify and utilize the same object’s multi-type data in different sys-tems.Big data analysis’ sample size and dimension are limited,with the decreasing of analysis results’ reality and accuracy.The methods,architectures and implementation examples of big data’s heterogeneous association were pre-sented.The data fusion in user-dimension from different systems could optimize the data sample space of applications,such as user portrait.Thus,the value of carrier’s big data density was greatly improved.

Editor's Note: this Article has been retracted; the Retraction Note is available at https://doi.org/10.1038/s41598-021-88178-8 .

Device-to-Device（D2D）communication is an important technology in 5G network.It helps to improve the transmission efficiency of data dissemination services.However,due to the extra signaling overhead caused by D2D communications,currently most of enhanced-multicast solutions cannot solve the contradiction between high-efficient data transmission and low-efficient signaling procedure,so as to reduce the overall performance gain.An intra-cluster D2D information sharing algorithm based on matrix analysis which includes centralized and distributed modes was proposed.The proposed algorithm could significantly reduce D2D retransmission times in clusters by adaptively selecting the optimal transmitters and data packets for D2D multicast retransmission,achieving the aim of reducing signaling overhead and transmission delay.

We investigate the statistical properties of maximum entropy density estimation, both for the complete data case and the incomplete data case. We show that under certain assumptions, the generalization error can be bounded in terms of the complexity of the underlying feature functions. This allows us to establish the universal consistency of maximum entropy density estimation.

A cloud call center architecture was presented and the call center platform cloud technology and business model were studied. The cloud call center application prospect and business trends were also described. A reference of call center platform cloud and technology development was provided for the operator.

In this paper, the ring-opening reaction of 2,5-dioctyldithieno[2,3-b:3',2'-d]thiophene with aryllithium in THF at low temperature to generate 2'-arylthio-3,3'-bithiophene-2-carbaldehydes is studied. Nine examples are explored and all the products are characterized by 1H NMR, 13C NMR and HRMS. The relative relationship between the structures of aryl groups and the efficiency of ring-opening reactions are discussed.

Open-source VoIP technologies can be employed to setup VoIP platforms by deploying open-source software on x86 servers, which have many advantages such as low cost, flexibility and openness. The usage of open-source VoIP technologies in NGN service platform deployment helps to reduce carrier's investment, shorten service deployment cycle and improve the duplicability of service platform. In the paper, the architecture of NGN service platform deployed by open-source VoIP technologies is proposed based on comprehensive survey and detailed analysis. A typical example is also provided to evaluate the feasibility and advantages of the proposed NGN service platform deployment method.