Search

In this paper, we obtained complete qth-moment convergence of the moving average processes, which is generated by m-WOD moving random variables. The results in this article improve and extend the results of the moving average process. m-WOD random variables include WOD, m-NA, m-NOD and m-END random variables, so the results in the paper also promote the corresponding ones in WOD, m-NA, m-NOD, m-END random variables .

Clinical cancer immunotherapies are usually impeded by tumor immunosuppression driven by tumor associated macrophages (TAMs). Thus, TAMs can be considered as a promising therapeutic target for improved immunotherapy, and TAMs-focused molecular targeting agents have made ideal progress in clinical practice. Even so, most TAMs-targeting agents still cannot cover up their own shortcomings as free drugs. The emergence of multifunctional nanomaterials can expectedly endow these therapeutic cargoes with high solubility, favorable pharmacokinetic distribution, cell-specific delivery, and controlled release. Here, the underlying mechanisms of tumor immunosuppression caused by TAMs are first emphatically elucidated, and then the basic design of TAMs-focused immune-nanomedicines are discussed, mainly including diverse categories of nanomaterials, targeted and stimulus-responsive modifications, and TAM imaging in nanomedicines. A summary of current TAMs-targeting immunotherapeutic mechanisms based on functional nanomedicines for TAMs elimination and/or repolarization is further presented. Lastly, some severe challenges related to functional nanomedicines for TAMs-focused cancer immunotherapy are proposed, and some feasible perspectives on clinical translation of TAMs-associated anticancer immunonanomedicines are provided. It is hoped that, with rapid development of nanomedicine in cancer immunotherapy, TAMs-focused therapeutic strategies may be anticipated to become an emerging immunotherapeutic modality for future clinical cancer treatment.

Clinically, the conventional treatments of cancer are still often accompanied by tumor recurrence, metastasis and other poor prognosis. Nowadays, more attention has been paid to photodynamic therapy (PDT), which is regarded as an adjuvant antineoplastic strategy with superiorities in great spatiotemporal selectivity and minimal invasiveness. In addition to eliminating tumor cells via reactive oxygen species (ROS), more meaningfully, this phototherapy can trigger immunogenic cell death (ICD) that plays a vital role in photodynamic immunotherapy (PDIT). ICD-based PDIT holds some immunotherapeutic potential due to further enhanced antitumor efficacy by utilizing various combined therapies to increase ICD levels. To help the PDIT-related drugs improve pharmacokinetic properties, bioavailability and system toxicity, multifunctional nanocarriers can be reasonably designed for enhanced PDIT. In further consideration of severe hypoxia, low immunity and immune checkpoints in tumor microenvironment (TME), advanced nanotherapeutics-mediated PDIT has been extensively studied for boosting antitumor immunity by oxygen-augment, ICD-boosting, adjuvant stimulation and combined checkpoints blockade. Herein, this review will summarize different categories of nanocarriers consisting of their material type, targeting and stimuli-responsiveness. Moreover, we will focus on the latest progress of various strategies to enhance the antitumor immune effect for PDIT and elucidate their corresponding immune-activation mechanisms. Nevertheless, there are several thorny challenges in PDIT, including limited light penetration, tumor hypoxia, immune escape and the development of novel small-molecule compounds that replace immune checkpoint inhibitors (ICIs) for easy integration into nanosystems. It is hoped that these issues raised will be helpful to the preclinical study of nanotherapeutics-based PDIT, thus accelerating the transformation of PDIT to clinical practice.

Single image dehazing is a challenging task because of the hue and brightness distortion problems due to the atmospheric scattering. These problems limit the perceptual fidelity, as well as information integrity, of a given image. In this paper, we propose an image dehazing method based on the optical neural networks dehazing by simulating optical diffraction. The algorithm is trained from a large number of hazy images and their corresponding clean images. The experimental results demonstrate that the proposed method has reached an advanced level in both PSNR and SSIM dehazing performance indicators, and the amount of calculation is less than most artificial neural networks.

Clinically, the primary cause of chemotherapy failure belongs to the occurrence of cancer multidrug resistance (MDR), which directly leads to the recurrence and metastasis of cancer along with high mortality. More and more attention has been paid to multifunctional nanoplatform-based dual-therapeutic combination to eliminate resistant cancers. In addition to helping both cargoes improve hydrophobicity and pharmacokinetic properties, increase bioavailability, release on demand and enhance therapeutic efficacy with low toxic effects, these smart co-delivery nanocarriers can even overcome drug resistance. Here, this review will not only present different types of co-delivery nanocarriers, but also summarize targeted and stimuli-responsive combination nanomedicines. Furthermore, we will focus on the recent progress in the co-delivery of dual-drug using such intelligent nanocarriers for surmounting cancer MDR. Whereas it remains to be seriously considered that there are some knotty issues in the fight against MDR of cancers via using co-delivery nanoplatforms, including limited intratumoral retention, the possible changes of combinatorial ratio under complex biological environments, drug release sequence from the nanocarriers, and subsequent free-drug resistance after detachment from the nanocarriers. It is hoped that, with the advantage of continuously developing nanomaterials, two personalized therapeutic agents in combination can be better exploited to achieve the goal of cooperatively combating cancer MDR, thus advancing the time to clinical transformation.

Diffractive deep neural networks (D2NNs) have demonstrated their importance in performing various all-optical machine learning tasks such as classification and segmentation. However, current D2NNs can only detect spatial domain intensity information. They cannot solve problems that rely on frequency information, such as laser linewidth compression. We propose a new D2NN architecture that fully exploits frequency domain information. We demonstrate that only frequency domain D2NN (OF-D3NN) can be trained using deep learning algorithms and be successfully integrated into a free-space optical communications system (FSO) for information recovery.

Trajectory planning is of great value and yet challenging for multirotor unmanned aerial vehicle (UAV) applications in a complex urban environment, mainly due to the complexities of handling cluttered obstacles. The problem further complicates itself in the context of autonomous multi-UAV trajectory planning considering conflict avoidance for future city applications. To tackle this problem, this paper introduces the multi-UAV cooperative trajectory planning (MCTP) problem, and proposes a bilevel model for the problem. The upper level is modeled as an extended multiple traveling salesman problem, aiming at generating trajectories based on heuristic framework for multi-UAV task allocation and scheduling and meanwhile considering UAV kinodynamic properties. The lower level is modeled as a holding time assignment problem to avoid possible spatiotemporal trajectory conflicts, where conflict time difference is analyzed based on the proposed state-time graph method. Numerical studies are conducted in both a 1 km2 virtual city and 12 km2 real city with a set of tasks and obstacles settings. The results show that the proposed model is capable of planning trajectories for multi-UAV from the system-level perspective based on the proposed method.

Let {Xni,un≤i≤vn,n≥1} be an arrays of rowwise pairwise negatively quadrant dependent (NQD) random variables. In this paper, some novel sufficient conditions of LP-convergence for {Xni,un≤i≤vn,n≥1} ...

The accessibility of transit stops (ATS) is a critical index for the evaluation of transit service, focusing on the first/last mile portions of transit trips. It is significantly affected by feeder modes, such as walking and cycling. Comparison of the application of different modes has been addressed in previous research, thus there is mostly only one feeder mode considered in this case study. This study has proposed a model for ATS with multiple feeder modes (ATSMFM), capable of integrating multiple feeder modes and considering the heterogeneity of travellers from the perspective of city managers. It is a bi-level model, combining cumulative and utility-based approaches. The final form of ATSMFM is developed referring to the cumulative approach, while the determination of the catchment area is utility-based. A numerical experiment has been conducted to demonstrate the necessity and applicability of ATSMFM. The results show that the ATS with a single feeder mode, such as cycling or walking, underestimates the catchment area of nearly one-third or two-thirds of travellers. As for ATSMFM, this proposed approach can automatically select the feeder mode from alternatives according to traveller attributes, thus removing the limitation of a single feeder mode, and is suitable for calculating ATS in the complex environment with multiple feeder modes. Besides, the ATSMFM model can support city managers with different emphases in transit planning via flexibly setting the threshold.

Effective classification of flies is beneficial to prevent the spread of disease and protect agricultural production. It is important to prevent the invasion of fly species. Aiming at the problem of similar morphology and difficulty in the classification of fly species in the natural environment, this paper proposes a fine-grained classification method for fly species in the complex natural environment based on deep convolutional neural network. Firstly, the specific position of the fly in the image is located by the gradient-weighted class activation graph method, and the object region of the fly is obtained. Then, the local region containing the most abundant information in the image is extracted. When extracting features from the local region, the attention module and cross-layer bilinear pooling are combined. The feature information of different convolutional layers is integrated. Finally, the global and local feature information is integrated for classification. We experimentally compared the proposed method with other state-of-the-art methods on the established dataset. Experimental results show that the accuracy of the proposed method on the three datasets is 84.34%, 89.53% and 93.26%, respectively. Compared with other state-of-the-art methods, this method has a good classification effect on fly species.

BackgroundSecondary Acute Myeloid Leukemia (S-AML) patients generally have a poor prognosis, and the chromosomal karyotype of S-AML have been rarely reported in the published literature. We aimed to explore the chromosomal karyotype and its clinical significance in patients with S-AML.MethodsClinical characteristics and chromosome karyotypes of 26 patients with S-AML were retrospectively analyzed. The overall survival (OS) was measured from the time of the patients’ transition to AML (which means the time of S-AML diagnosis) .ResultsAmong the 26 S-AML patients, there were 13 males and 13 females, with a median age of 63 years old (range, 20-77 years old). All of them were secondary to a variety of hematologic malignancies or solid tumors, and most of them were secondary to myelodysplastic syndrome (MDS). About 62% of the S-AML patients showed chromosome abnormalities. The level of serum lactate dehydrogenase (LDH) in S-AML patients with abnormal chromosome karyotype was higher than those with normal chromosome karyotype. Apart from the differences in treatment regimens, S-AML patients with chromosomal karyotype abnormalities had shorter OS (P

Additional file 1:. Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2009 checklist.

Additional file 4:. The Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) assessment tool.

Additional file 3:. Specific calculations of our systematic reviews and meta-analysis.

Additional file 2:. Search strategy.

Kelvin wake is an important detection target of ocean visible spectral remote sensing. In the case of slow ship speed and low atmospheric transmissivity, the wake signal is weak and the SNR (Signal-Noise Ratio) is low. Therefore, the image obtained by the visible spectral remote sensing imaging system is often “unclear”. In order to solve the problems above, this paper carries out the modeling of Kelvin wake imaging mechanism of visible spectral remote sensing. The Kelvin wake reflection distribution characteristics of rough sea surface are simulated based on the hydrodynamic model of Kelvin wake and the probability density distribution of rough sea surface, and a method to quantify the reflectance resolution for Kelvin wake imaging of rough sea surface is proposed. The changes in reflectance resolution caused by different wind speeds, ship parameters, source angle, receiver angle are also analyzed. Then the imaging link model of TDI-CCD (Time Delay and Integration Charge Coupled Devices) imaging system was established. The imaging results of a Kelvin wake reflected on the rough sea surface are simulated, and the impact of the changes of main imaging parameters (optical system F number, quantization bits, integration stages) on the imaging results of a Kelvin wake at different reflectance resolutions are analyzed. The research has clarified the mechanism of the visible spectral remote sensing system to clearly imaging the Kelvin wake, which can provide guidance on parameters design and attitude planning for the ocean visible spectral remote sensing system, and improve the ability of the imaging system to detect weak wake signals.

In this paper, we assume that the sequence $\{Y_{n},-\infty< n

We address the problem of globally asymptotic stability for a class of stochastic nonlinear systems with time-varying delays. By the backstepping method and Lyapunov theory, we design a linear output feedback controller recursively based on the observable linearization for a class of stochastic nonlinear systems with time-varying delays to guarantee that the closed-loop system is globally asymptotically stable in probability. In particular, we extend the deterministic nonlinear system to stochastic nonlinear systems with time-varying delays. Finally, an example and its simulations are given to illustrate the theoretical results.

The stability issue is investigated for a class of stochastic neural networks with time delays in the leakage terms. Different from the previous literature, we are concerned with the almost sure stability. By using the LaSalle invariant principle of stochastic delay differential equations, Itô’s formula, and stochastic analysis theory, some novel sufficient conditions are derived to guarantee the almost sure stability of the equilibrium point. In particular, the weak infinitesimal operator of Lyapunov functions in this paper is not required to be negative, which is necessary in the study of the traditional moment stability. Finally, two numerical examples and their simulations are provided to show the effectiveness of the theoretical results and demonstrate that time delays in the leakage terms do contribute to the stability of stochastic neural networks.

The presence of bike-sharing has a significant influence on the ease of trips by bike, which is one critical aspect of bicycling accessibility (BAcc). The existing measurements of BAcc rarely consider the factor of ownership of bikes, which means that no distinction is made between private-bikes and shared bikes. To measure BAcc more fully, this paper proposes a method to evaluate the influences of bike-sharing on BAcc and to perform the method on a real-world case study in Beijing. It is found that bike-sharing has a boosting effect on BAcc, and the increased rate of BAcc is significantly affected by bicycling frequency and shared-bike availability. A case study in Beijing utilizing geo-location data collected from two major bike-sharing companies (OFO and Mo-bike) illustrates the significance of the impact of bike-sharing on BAcc and the necessity to include bike-sharing in the measurement of BAcc. Besides, the case study shows BAcc around the transit station is better than that over the whole area. Given that bicycling feeds transit, this research lays the foundation for analyzing the combination of bike-sharing and transit from the perspective of accessibility and can further support transportation planning.

Purpose C-terminal binding protein 1 (CtBP1) is a transcriptional co-repressor that is overexpressed in many cancers. CtBP1 transcriptionally represses a broad array of tumor suppressors, which promotes cancer cell proliferation, migration, invasion, and resistance to apoptosis. Recent studies have demonstrated that CtBP1 is a potential target for cancer therapy. This study was designed to screen for compounds that potentially target CtBP1. Methods Using a structure-based virtual screening for CtBP1 inhibitors, we found protocatechuic aldehyde (PA), a natural compound found in the root of a traditional Chinese herb, Salvia miltiorrhiza, that directly binds to CtBP1. Microscale thermophoresis assay was performed to determine whether PA and CtBP1 directly bind to each other. Further, clustered regularly interspaced short palindromic repeats associated Cas9 nuclease-mediated CtBP1 knockout in breast cancer cells was used to validate the CtBP1 targeting specificity of PA. Results Functional studies showed that PA repressed the proliferation and migration of breast cancer cells. Furthermore, PA elevated the expression of the downstream targets of CtBP1, p21 and E-cadherin, and decreased CtBP1 binding affinity for the promoter regions of p21 and E-cadherin in breast cancer cells. However, PA did not affect the expression of p21 and E-cadherin in the CtBP1 knockout breast cancer cells. In addition, the CtBP1 knockout breast cancer cells showed resistance to PA-induced repression of proliferation and migration. Conclusion Our findings demonstrated that PA directly bound to CtBP1 and inhibited the growth and migration of breast cancer cells through CtBP1 inhibition. Structural modifications of PA are further required to enhance its binding affinity and selectivity for CtBP1.

The disassembly of waste products is an important part of remanufacturing activities. The difficulty of disassembly has an important impact on the remanufacturing cost, the parts quality and the remanufacturing cycle. It assumes that the original equipment manufacturer (OEM) considers disassembly during new product design stage. Accordingly, it will generate invested costs associated with disassembly level and reduce remanufacturing cost. It sets up a two-stage programming model with constraint to maximize OEM's profit and obtains the optimal disassembly level and optimal pricing strategies by using Kuhn-Tucker condition. It carries out the sensitivity analysis of the decision variables and the objective function by means of analytical methods and numerical examples.

Inthisarticle,wediscussthecompletemomentconvergencefor arrays of B-valued random variables. We obtain some new resultswhichimprovethecorrespondingonesofSungandVolodin[17]. 1. IntroductionLet {Ω,F,P} be a probability space, and let B be a separable real Banachspace with norm ||·||. A random element is defined to be an F-measurablemapping of Ω into B equipped with the Borel σ-algebra (that is, the σ-algebragenerated by the open sets determined by ||·||). The expected value of a B-valued random element X is defined to be the Bochner integral and denotedby EX.Let {X nk ,k ≥ 1,n ≥ 1} be an array of random elements in a real Banachspace. An array of rowwise random elements {X nk ,k ≥ 1,n ≥ 1} is said to bestochastically dominated by a random variable X (write {X nk } ≺ X) if thereexists a constant C > 0 such thatsup n≥1,k≥1 P(||X nk || > x) ≤ CP(|X| > x), ∀x > 0.Now we recall the following concepts of convergence which were introducedby Hsu and Robbins [6] and Chow [4], respectively.Definition 1.1. A sequence of random variables {X

The authors study the complete moment convergence for weighted sums of arrays of Banach space valued random elements. The results in this paper improve the corresponding theorems of Qiu et al. (Lith Math J 52(3):316–325, 2012).

In recent years, bicycle-sharing systems (BSSs) have been getting more and more popular in many cities all over the world, particularly in developing countries. However, a significant operating problem was the imbalance that occurred in the distribution of bicycles, especially in large-scale BSSs during peak hours. This problem could significantly reduce the level of service and number of potential users. To improve the level of service of BSSs, the necessity of redistribution was analyzed, and an operational redistribution model (ORM) that could deal with large-scale redistribution was developed. The objective of the ORM was to minimize the generalized operation costs of BSSs, which were the penalty cost of unserved user demand and the cost of redistribution of bicycles. The overall system performance was analyzed under several scenarios. The results demonstrated that an ORM could effectively improve the level of service of a BSS and could provide a detailed work plan for each redistribution truck to implement. For redistribution in a large-scale BSS, the partition of subzones was important to achieve a high level of service with relatively low generalized costs. In addition, an optimal number of subzones could be found through the scenario-based optimization process.

The efficacy of anaplastic lymphoma kinase (ALK) positive non-small-cell lung cancer (NSCLC) treatment with small molecule inhibitors is greatly challenged by acquired resistance. A recent study reported the newest generation inhibitor resistant mutation L1198F led to the resensitization to crizotinib, which is the first Food and Drug Administration (FDA) approved drug for the treatment of ALK-positive NSCLC. It is of great importance to understand how this extremely rare event occurred for the purpose of overcoming the acquired resistance of such inhibitors. In this study, we exploited molecular dynamics (MD) simulation to dissect the molecular mechanisms. Our MD results revealed that L1198F mutation of ALK resulted in the conformational change at the inhibitor site and altered the binding affinity of ALK to crizotinib and lorlatinib. L1198F mutation also affected the autoactivation of ALK as supported by the identification of His1124 and Tyr1278 as critical amino acids involved in ATP binding and phosphorylation. Our findings are valuable for designing more specific and potent inhibitors for the treatment of ALK-positive NSCLC and other types of cancer.

Multimodal urban transportation systems exhibit complex inter actions between components, including users, multimodal transportation facilities, supply side agencies, and operators. Although these interactions are obvious, rigorous quantitative methods for optimizing control variables across modes of transportation on real-world networks are deficient. A social welfare maximization model was established for joint optimization of bus fare, rail transit fare, and congestion tolls for private cars. The authors determined the optimality conditions and the second-order partial derivatives for this optimization problem. Because of the complexity of the multimodal urban transportation system, the objective function of social welfare has no closed form and is extremely expensive to evaluate. The authors therefore proposed a simulation-based framework for evaluation of the objective function and optimization of three decision variables across multiple travel modes. Several metamodels (i.e., mathematical functions that approximate the true shape of an unknown, nonlinear, and complex objective function) were adopted to approximate the highly nonlinear input–output mappings in the urban system. This is the first study to develop a simulation-based method for joint optimization of transit and road network operations. The case study applied the simulation-based optimization framework to the Sino–Singapore ecocity in Tianjin, China, by using VISSUM as the urban systems simulator. An “ecocity” is defined by the authors as “a thriving city that is socially harmonious, environmentally friendly, resource-efficient, and a model for sustainable development.” Results show that metamodels can accurately approximate the real objective function and produce good suboptimal and near-optimal solutions. The optimal combination of transit fares and congestion tolls significantly outperform those under two baseline scenarios. The optimal solutions also suggest that extreme transit fares (too high or too low) or congestion tolls are contrary to welfare-maximizing objectives. The proposed method can be applied for joint optimization of other multimodal planning and operational strategies, such as investment and operational decisions across various modes of transportation.

Diverse strategies have been proposed and implemented to relieve increasingly serious urban transportation problems. How to evaluate and optimize combined strategies to increase sustainability and improve efficiency of multimodal transportation systems is still a great challenge. This paper proposes a simulation-based systematic framework for sustainable transportation systems evaluation and optimization. Simulation-based optimization (SBO) is incorporated to seek an optimal combination of transportation planning and operations strategies, e.g. congestion pricing for private cars, bus and rail fares, to minimize generalized costs of multimodal traveling in a heuristic way. Applications in a small network of Tianjin Eco-city with multimodal travelers demonstrate the feasibility and applicability of the SBO approach in sustainable transportation systems evaluation and optimization. The objective is to reduce multimodal travel costs subject to a minimum mode share of green transportation. The SBO process also validates that the efficiency of each strategy may be influenced by the strengths of other strategies.

Osteoarthritis (OA), one of the most common joint disorders, is one of the leading causes of disability among the elderly. Proinflammatory cytokines, such as interleukin (IL)-1β, which is synthesized locally by synovial cells and chondrocytes, have been shown to play a critical role in sustaining cartilage damage in arthritis by creating an imbalance between cartilage degradation and the repair process. Alpha-lipoic acid (α-LA), which is synthesized in animal and plant tissues, has demonstrated its protective effects in a variety of diseases. However, whether or not LA has a protective effect in OA is still unknown. In this study, we found that α-LA inhibits the IL-1β-induced increase in matrix metallopeptidase 3 (MMP-3) and matrix metallopeptidase 13 (MMP-13) expression and activity. Our data also demonstrate that interferon regulatory factor 1 (IRF-1) participates in the induction of MMP-3 and MMP-13. However, α-LA treatment did not change IRF-1 levels. Importantly, we found that α-LA increases SUMOylation of IRF-1, which attenuates IRF-1's transcriptional activity. Finally, we found that α-LA treatment leads to an increase in SUMO-1, but not in SUMO-2 or SUMO-3. Taken together, this study shows that α-LA exerts anti-inflammatory effects in an IL-1β-stimulated chondrocyte model, thereby suggesting a potential protective effect of α-LA in OA.

The authors first present a Rosenthal inequality for sequence of extended negatively dependent (END) random variables. By means of the Rosenthal inequality, the authors obtain some complete moment convergence and mean convergence results for arrays of rowwise END random variables. The results in this paper extend and improve the corresponding theorems by Hu and Taylor (1997).

In order to promote low-carbon transport, “The 12th five-year Transport Development Planning” released by the Ministry of Transport (MoT) of P. R. China in 2011, indicates that MoT will provide significant funds to support 30 cities to build “The Transit Metropolis” before 2015. In order to support the “Transit Metropolis” project, the authors led great efforts on collecting statistic and economic data, geography and population data, transportation infrastructure and operation data, transit passenger degree of satisfaction data, etc. Based on all the ground information, this paper assessed the status of urban public transit in China, and analyzed the factors that affect the public transit development. It is found that the relationship between the transit mode share and the gross domestic product (GDP) per capita follows a “flash” shape and can be divided into three phases. With the growth of GDP, the trend of the transit mode share typically goes “up-down-up” due to the different stages of economy level, car ownership and investment on transit system. Based on the analysis and discussion, some suggestions are provided to develop a hierarchical multi-modal transit system with smooth transfers and good coverage to mitigate traffic congestion and improve the sustainability of urban transportation system in China.