The study explores the importance of market orientation strategy to enhance brand performance and the mediating role of positioning strategies. The researcher used questionnaires to collect data from ...the managers of middle and high fashion apparel manufacturing firms based on the quantitative research approach. The data was collected from 220 managers who were directly involved in the decision-making process. The analysis has revealed a significant impact of market orientation strategy on Pakistan’s fashion brands' performance, with the mediating effect of positioning strategies. The management of firms must give considerable importance to market orientation strategies to enhance overall brand performance. The market orientation strategies’ development is also helpful in building different positioning strategies through which performance gets enhanced. This study contributes valuable literature because it focuses on the fashion apparel industry's context, which is almost most important for everyone in the present era. Firms can focus on tight product quality control, innovative manufacturing processes, trained and experienced personnel, and extensive customer service.
With the rapid development of information technology, a large amount of traffic generated by various Internet applications occupies a large amount of network resources. It poses a huge challenge to ...service quality and has a negative impact on Internet security. In order to utilize network resources effectively and provide effective management and control measures for network administrators, network traffic classification technologies is a hot topic for scientists to identify application layer protocols. Today, there are more and more applications based on TCP/IP. With the emergence of various anti-surveillance applications, traditional port and application-based identification methods are difficult to meet current or future traffic identification requirements. It has become a very challenging problem to require more efficient, accurate, intelligent and real-time Internet traffic identification. The Internet of Things is a new network concept proposed by people who based on Internet prototypes. It enables the end user of the system can carry out communication and exchange of information and data between any project. In recent years, with the continuous advancement of Internet of Things technology, the coverage of the Internet of Things has become very wide, and the number of different types of networks that make up the Internet of Things is also increasing. This paper aims to find the dynamic network traffic classification problem of hybrid fixed in dynamic network and dynamic network in mobile network, and gives a reasonable mapping scheme. The dynamics of network traffic for Internet of Things are reflected fully and will not cause route flapping. The simulation results show that the decision tree classification algorithm in machine learning has higher efficiency, and improves the utilization of network resources.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Fossil energy consumption and environmental protection issues have pushed electric vehicles (EVs) to become one of the alternatives to traditional fossil-fuel vehicles. EV refers to a vehicle that ...uses electric energy as power and is driven by an electric motor. The electric energy of EVs is stored in batteries. When the EV is not traveling, the battery can provide power for other loads. Therefore, with the increase in the number of EVs and the load of the power grid, the EV-to-grid (V2G) mode, which uses EVs to supply power to the power grid, has gradually entered the field of vision of researchers. The physical connection mode, charge and discharge technology, and energy management strategy are the main topics of the current review papers; however, there is a lack of systematic research on V2G modeling, framework, and business models. This paper describes the concepts of the spatio-temporal distribution model and the adjustable capacity of EVs. In addition, common constraints and methods in optimization are introduced. Moreover, this paper introduces the interactive relationship among power grids, load aggregators, and EV users. Furthermore, the business model of V2G is introduced and analyzed from various perspectives. Finally, the future development of V2G is pointed out. This paper’s goal is to provide an overview of the present V2G application scenarios and to identify any challenges that must be overcome.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
We previously found that FoxM1B is overexpressed in human glioblastomas and that forced FoxM1B expression in anaplastic astrocytoma cells leads to the formation of highly angiogenic glioblastoma in ...nude mice. However, the molecular mechanisms by which FoxM1B enhances glioma angiogenesis are currently unknown. In this study, we found that vascular endothelial growth factor (VEGF) is a direct transcriptional target of FoxM1B. FoxM1B overexpression increased VEGF expression, whereas blockade of FoxM1 expression suppressed VEGF expression in glioma cells. Transfection of FoxM1 into glioma cells directly activated the VEGF promoter, and inhibition of FoxM1 expression by FoxM1 siRNA suppressed VEGF promoter activation. We identified two FoxM1-binding sites in the VEGF promoter that specifically bound to the FoxM1 protein. Mutation of these FoxM1-binding sites significantly attenuated VEGF promoter activity. Furthermore, FoxM1 overexpression increased and inhibition of FoxM1 expression suppressed the angiogenic ability of glioma cells. Finally, an immunohistochemical analysis of 59 human glioblastoma specimens also showed a significant correlation between FoxM1 overexpression and elevated VEGF expression. Our findings provide both clinical and mechanistic evidence that FoxM1 contributes to glioma progression by enhancing VEGF gene transcription and thus tumor angiogenesis.
The expression of matrix metalloproteinase-2 (MMP-2) has been linked with tumor invasion, angiogenesis, and metastasis. However, the molecular basis for MMP-2 overexpression in tumor cells remains ...unclear. In this study, by using K-1735 melanoma system, we demonstrated that highly metastatic C4, M2, and X21 tumor cells express elevated MMP-2 mRNA and enzymatic activity, whereas poorly metastatic C10, C19, and C23 tumor cells express much lower levels. Moreover, a concomitant elevated Stat3 activity has been detected in these metastatic tumor cells that overexpress MMP-2. Transfection of constitutively activated Stat3 into poorly metastatic C23 tumor cells directly activated the MMP-2 promoter, whereas the expression of a dominant-negative Stat3 in highly metastatic C4 tumor cells inhibited the MMP-2 promoter. A high-affinity Stat3-binding element was identified in the MMP-2 promoter and Stat3 protein bound directly to the MMP-2 promoter. Blockade of activated Stat3 through expression of a dominant-negative Stat3 significantly suppressed MMP-2 expression in the metastatic tumor cells. Therefore, overexpression of MMP-2 in the metastatic melanoma cells can be attributed to elevated Stat3 activity, and Stat3 upregulates the transcription of MMP-2 through direct interaction with the MMP-2 promoter. Furthermore, blockade of activated Stat3 in highly metastatic C4 cells significantly suppressed the invasiveness of the tumor cells, inhibited tumor growth, and prevented metastasis in nude mice. Collectively, these studies suggest that Stat3 signaling directly regulates MMP-2 expression, tumor invasion, and metastasis, and that Stat3 activation might be a crucial event in the development of metastasis.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The photocatalytic reduction of soluble
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from radioactive wastewater is becoming an effective method to reduce radioactive pollution, while available catalysts are considerable limitation. ...Herein, the ZnS@g-C
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(ZSGCN) heterojunctions complexes were compounded as catalysts to reduce
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. The results from TEM, XRD, XPS, EIS, DRS and PL showed that the ZnS nanoparticles combined with graphite carbon nitride (GCN), which is the construction of heterojunctions broadened the absorption range of sunlight. The ZSGCN-5 presented the optimal photocatalytic reduction activity to
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, which was 4.34 times than that of pristine GCN. The ZSGCN-5 heterojunction becomes a promising photocatalyst for radioactive environment remediation.
The further liberalization of China's electricity market encourages demand-side entities to participate in electricity market transactions. Electric vehicles (EVs) are developing rapidly and have ...high regulating potential, and are the main force for demand-side participation in the auxiliary service market. Aiming at the problems of dispatching accuracy and economy in EV participation in auxiliary service market, this paper analyzes the bidding strategy and dispatching scheme of EV-storage participation in auxiliary service market, and proposes EV-storage optimal allocation strategy with the goal of economic optimum. In the process of optimal allocation, based on the market rules of third-party subject participation in auxiliary services, the bidding strategy of EV-storage coordinated EV participation in auxiliary services market considering daily load scale changes is designed, while the conditional value at risk (CVaR) method is used to determine the short-term coordinated energy storage capacity and efficiency storage capacity considering the uncertainty of EV response situation; then, based on the annual EV load scale change, the benefit calculation function is constructed by considering various factors such as auxiliary service market revenue, spread revenue, investment cost and market opportunity cost of EV-storage participation in the auxiliary market. Finally, taking EV aggregation participation in the valley-filling ancillary service market as an example, it is verified that the strategy proposed in this paper can effectively improve the responsiveness of EV participation in the ancillary service market and increase the revenue of electric vehicle aggregator (EVA).
At the present stage, China’s energy development has the following characteristics: continuous development of new energy technology, continuous expansion of comprehensive energy system scale, and ...wide application of multi-energy coupling technology. Under the new situation, the accurate prediction of power load is the key to alleviate the problem that the planning and dispatching of the current power system is more complex and more demanding than the traditional power system. Therefore, firstly, this paper designs the calculation method of the power load demand of the grid under the multi-energy coupling mode, aiming at the important role of the grid in the power dispatching in the comprehensive energy system. This load calculation method for regional power grid operating load forecasting is proposed for the first time, which takes the total regional load demand and multi-energy coupling into consideration. Then, according to the participants and typical models in the multi-energy coupling mode, the key factors affecting the load in the multi-energy coupling mode are analyzed. At this stage, we fully consider the supply side resources and the demand side resources, innovatively extract the energy system structure characteristics under the condition of multi-energy coupling technology, and design a key factor index system for this mode. Finally, a least squares support vector machine optimized by the minimal redundancy maximal relevance model and the adaptive fireworks algorithm (mRMR-AFWA-LSSVM) is proposed, to carry out load forecasting for multi-energy coupling scenarios. Aiming at the complexity energy system analysis and prediction accuracy improvement of multi-energy coupling scenarios, this method applies minimal redundancy maximal relevance model to the selection of key factors in scenario analysis. It is also the first time that adaptive fireworks algorithm is applied to the optimization of adaptive fireworks algorithm, and the results show that the model optimization effect is good. In the case of A region quarterly load forecasting in southwest China, the average absolute percentage error of a least squares support vector machine optimized by the minimal redundancy maximal relevance model and the adaptive fireworks algorithm (mRMR-AFWA-LSSVM) is 2.08%, which means that this model has a high forecasting accuracy.
In view of the randomness in the selection of kernel parameters in the traditional kernel independent component analysis (KICA) algorithm, this paper proposes a CPSO-KICA algorithm based on Chaotic ...Particle Swarm Optimization (CPSO) and KICA. In CPSO-KICA, the maximum entropy of the extracted independent component is first adopted as the fitness function of the PSO algorithm to determine the optimal kernel parameters, then the chaotic algorithm (CO) is used to avoid the local optimum existing in the traditional PSO algorithm. Finally, this proposed algorithm is compared with Weighted KICA (WKICA) and PSO-KICA with Tennessee Eastman Process (TEP) as the benchmark. Simulation results show that the proposed algorithm can determine the optimal kernel parameters and perform better in terms of false alarm rates (FAR), detection latency (DL) and fault detection rates (FDR).
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The rapid development of renewable energy power has improved global energy and environmental problems. However, with the high volatility of renewable energy, it is an important challenge to guarantee ...the consumption of renewable energy and the reliable operation of high percentage renewable energy power systems. To solve this problem, this paper proposes a tracking absorption strategy for renewable energy based on the interaction between the supply side and the demand side, which adjusts the charging process of electric vehicles (EVs) through electric vehicle aggregator (EVA) to realize the tracking absorption of renewable energy abandoned electricity. In view of this process, we analyze the interaction among power grid, EVA and renewable energy generation (REG) as well as their market characteristics. The master-slave game model of EVA and REG was constructed considering the charging behavior characteristics of EVs and the output characteristics of REGs. Then the model solving strategy based on soft actor-critic (SAC) algorithm is proposed, and the REG pricing strategy and EVA scheduling strategy are calculated to optimize the mutual benefits. The case analysis shows that, under the same scale of electric vehicles, the proposed method can promote about 93.89% of the power abandonment consumption of wind power system, 96.00% of the photovoltaic system, and 97.41% of the wind-solar system. This strategy reduces the electricity purchase cost of EVA, promotes the interaction among renewable energy, vehicles and power grid, and improves the utilization efficiency of renewable energy.
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