Study on "Borrowing Scenery under the Guidance of Emotion" in Chinese Landscape Architecture

One of the main theories of "borrowing scenery" which was "borrowing scenery under the guidance of emotion" was expounded from two aspects.And the second aspect was emphasized,that is,integrating social beauty into natural beauty so as to produce artistic beauty of landscape,and layer beauty was the main content manifested in Chinese landscape garden.

Chinese Borrowings in English

There are eight types of English word formation, which are widely used nowadays in English. Among them, Borrowings, as one of widely used types of English word formation, has drawn people's attention because many English words are borrowed from other languages, such as German, Latin. This article aims to demonstrate Chinese Borrowings in English from two aspects.

Geliable Lexical Borrowings in China English on the Internet

Lexical borrowing in China English is an important part of English localization.This paper,on the basis of the study of vogue lexical English expressions on the Internet,tries to describe and explain the characteristics of lexical borrowings in China English on the Internet.

STUDY ON THE INTERRELATION BETWEEN THE FOREIGN ELEMENTS AND THE NATIVE ELEMENT IN ENGLISH——English Borrowings from Chinese

This dissertaion will focus on the words English borrowed from Chinese to discuss the influence of Chinese culture on English. In the history of word borrowing, it is not until in the 18 th and 19th century that there was a flood of Chinese loanwords into English. Most of the words are nouns about custom,culture, and goods with Chinese characteristic. The Chinese loanwords set foot into English by the means of transliteration, Among all Chinese dialects Mandarin, Cantonese and Amoy contributed most to English. Other languages such as Japanese bridged the borrowing process,too.

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Resource management with borrowing from reservation for cognitive networks

Resource reservation is an effective measure to ensure end-to-end quality of service （QoS）, however, the burstyness of the traffic makes the reservation idle some time, and forms a waste of re- sources. Based on the analysis of active queue management （AQM） of DiffServ network, we propose a resource management scheme, which allows borrowing resources from unused reservation, accord- ing to the characteristics and advantages of cognitive networks. First, some nodes reserve certain proportion capacity for some special services （for instance, some services pay additional money） to guarantee the priority of these applications. Then resources are assigned according to the different parameters of services. If the available resource can not meet the requirements of new services, real- time ones are admitted with higher priority and allow borrowing the unused reservation from other nodes appropriately. Simulations show that, the proposed scheme has good performance at network resource utilization, the admission rate of new aDolications and OoS of users.

A novel spectrum borrowing scheme in integrated 3G/WLAN networks

In the heterogeneous wireless networks of the next generation, a large number of different radio access technologies will be integrated into a common network. This paper considers optimizing the utilization of spectrum resource in heterogeneous environment consisting two different networks： wireless local area network （WLAN） and time division-synchronous code division multiple access （TD-SCDMA） network. An optimal joint spectrum borrowing scheme maximizing overall network revenue is proposed with quality of service （QoS） constraints over both the WLAN and the TD-SCDMA cellular networks. Simulation results illustrate that system revenue earned in the proposed joint spectrum borrowing scheme is significantly larger than the case when individual networks are optimized independently.

An Analysis of Lexical Borrowing From Languages： ＂Konglish＂

This paper analyzes English loan words in Korean language. English words and phrases are largely absorbed into Korean either out of filling lexical gap or at the whim of fashion. These words have been borrowed and adapted orthographically and become a part of Korean language. Some loan words have the same meaning or phonological features as their corresponding words, but some do not. The only real solution to the ＂false friends＂ is to be aware of them, to look out for them, and to learn them. Teachers of English need to raise learners＇ awareness of the existence of English-origin words in fheir mother tongues

The Public Savings’ Relation With Borrowing Requirement and Financial Balances After Global Crisis in Turkey

In this study, we aim to determine public savings’ structural location in the analysis of effect levels that are related to public borrowing requirement to cope with the deviation of financial balances, especially after 2009 global crisis in Turkey. Public savings as a financial option take up an important place in the scope of expressed government budget balances related to public borrowing requirements which are increasingly located together with budget deficits. This fact especially is pertaining to investments and capital’s transfers that are subject to the public decision making process towards economic growth in the future in developing countries like Turkey. Therefore, increasing public savings’ limits appear on these countries as an inevitable financial phenomenon concerning the desired investments. Turkey, as a developing country, has faced two financial phenomenons that increase borrowing requirement terms that lead to intend financial balances that have generally deviated after 2009 financial crisis. Firstly, it’s increasing foreign debt burden and the public savings’ levels that have not been enough to cover all the proportion of foreign debt payments since 2009. Secondly, the effect level of global crisis on the exchange rates directly causes the deviation of national currency values as a meaningful important negative impact on budget balances that are aimed at together with the macroeconomic financial balances.

Source Text Borrowing in Summary of Integrated Writing

Integrated writing tasks,requiring writers to summarize source content and integrate their ideas or experience with those in the source text,are widely used in standardized tests of English proficiency.Integrated writing adds an element not found in traditional independent writing:the use of source text material.Recently,concern has been raised that over-reliance on source texts in integrated writing may lead to plagiarism as well as inaccurate assessment which calls for further investigation.Research on L2 students’writing using sources has broadened its focus from transgressive citing practices to stages of skill development in this complicated literacy,the successive challenges students face,and how instruction might be of benefit.Previous literature mainly focused on source use in academic writing and seldom considered summary writing in standardized tests,while summary strategy is particularly important in standardized tests,in which summary accounts for a significant part of the assessment criteria.Given that a series of previous literature have indicated that source text use,source texts,and prompts are associated with the quality of summary writing,this article reviews the source text borrowing in the summary of integrated writing to further explore the relationship between some variables and the quality of summary writing and therefore finds some research gaps in this field.

A Study of Borrowing,Imitation and Creation in English-Chinese Translation:A Case Study of Translating“The Root Cause of Poverty”

Based on the translated version of“The Root Cause of Poverty”by Rutger Bregman on the Ted speech online platform,this research analyzes the application of direct borrowing,imitative translation and creative translation in English-Chinese translation.First,we believe the direct borrowing of a ready-made version is most ideal as it reveals the common ground both languages share when translating a source text.Next,it is preferable to imitate an already existing expression as similarity is reader-friendly.However,it is sometimes necessary to adopt creative translation to preserve differences to ensure that the meaning of the original language is accurately transmitted.

Discussion on E-books and Library Borrowing Service

With the vigorous development of network information technology,e-book borrowing service came into being and showed a vigorous development trend.Therefore,in order to strengthen the service function,the library needs to gradually improve the e-book borrowing service,so as to provide readers with high-quality service content,so that the library can give full play to its function of disseminating scientific and cultural knowledge.Therefore,in this article research,we first discuss the main reading methods of e-books,then investigate the current reading situation of e-books and traditional paper books in the library,and then put forward corresponding development strategies to effectively promote the rapid development of the library and strengthen the level of e-book borrowing service.

“Em”:Pragmatics Borrowing in Chinese Wechat Conversations:among Female University Students in China

The term“pragmatics borrowing”refers to a conscious use of foreign pragmatic marker within or between utterances.Distinctive pragmatics functions of using the“cross-linguistic”pragmatic markers in online conversations have become a research focus.In a sample of Wechat communication among university students,the English pragmatics marker“em”and its variations occurred frequently.By analyzing its spelling variations,placement,pragmatic meanings and functions,the study indicates that,besides using it as a hesitator,chat participants consciously use this foreign pragmatic marker as a buffer for later utterance,which is usually an apology or a request,to soften the intonation and give the addressee an impression of politeness.

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault.This can be due to subsurface(geo)engineering activities such as fluid injections and geologic disposal of nuclear waste.Such activities are expected to rise in the future making it necessary to assess their short-and long-term safety.Here,a new machine learning(ML)approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed.The focus is on fault behavior near the injection borehole.To capture the temporal dependencies in the data,long short-term memory(LSTM)networks are utilized.To prevent error accumulation within the forecast window,four critical measures to train a robust LSTM model for predicting fault response are highlighted:(i)setting an appropriate value of LSTM lag,(ii)calibrating the LSTM cell dimension,(iii)learning rate reduction during weight optimization,and(iv)not adopting an independent injection cycle as a validation set.Several numerical experiments were conducted,which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection.The model also captured the decay in pressure and displacement during the injection shut-in period.Further,the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated,which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

Physics Guided Deep Learning-Based Model for Short-Term Origin–Destination Demand Prediction in Urban Rail Transit Systems Under Pandemic

Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,including real-time availability,sparsity,and high-dimensionality issues,and the impact of the pandemic.Consequently,this study proposes a unified framework called the physics-guided adaptive graph spatial–temporal attention network(PAG-STAN)for metro OD demand prediction under pandemic conditions.Specifically,PAG-STAN introduces a real-time OD estimation module to estimate real-time complete OD demand matrices.Subsequently,a novel dynamic OD demand matrix compression module is proposed to generate dense real-time OD demand matrices.Thereafter,PAG-STAN leverages various heterogeneous data to learn the evolutionary trend of future OD ridership during the pandemic.Finally,a masked physics-guided loss function(MPG-loss function)incorporates the physical quantity information between the OD demand and inbound flow into the loss function to enhance model interpretability.PAG-STAN demonstrated favorable performance on two real-world metro OD demand datasets under the pandemic and conventional scenarios,highlighting its robustness and sensitivity for metro OD demand prediction.A series of ablation studies were conducted to verify the indispensability of each module in PAG-STAN.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

Short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function

BACKGROUND Hepatectomy is the first choice for treating liver cancer.However,inflammatory factors,released in response to pain stimulation,may suppress perioperative immune function and affect the prognosis of patients undergoing hepatectomies.AIM To determine the short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function.METHODS Clinical data from patients with liver cancer admitted to Suzhou Ninth People’s Hospital from January 2020 to December 2023 were retrospectively analyzed.Thirty-five patients underwent laparoscopic hepatectomy for liver cancer(liver cancer resection group)and 35 patients underwent medical image-guided microwave ablation(liver cancer ablation group).The short-term efficacy,complications,liver function,and immune function indices before and after treatment were compared between the two groups.RESULTS One month after treatment,19 patients experienced complete remission(CR),8 patients experienced partial remission(PR),6 patients experienced stable disease(SD),and 2 patients experienced disease progression(PD)in the liver cancer resection group.In the liver cancer ablation group,21 patients experienced CR,9 patients experienced PR,3 patients experienced SD,and 2 patients experienced PD.No significant differences in efficacy and complications were detected between the liver cancer ablation and liver cancer resection groups(P>0.05).After treatment,total bilirubin(41.24±7.35 vs 49.18±8.64μmol/L,P<0.001),alanine aminotransferase(30.85±6.23 vs 42.32±7.56 U/L,P<0.001),CD4+(43.95±5.72 vs 35.27±5.56,P<0.001),CD8+(20.38±3.91 vs 22.75±4.62,P<0.001),and CD4+/CD8+(2.16±0.39 vs 1.55±0.32,P<0.001)were significantly different between the liver cancer ablation and liver cancer resection groups.CONCLUSION The short-term efficacy and safety of microwave ablation and laparoscopic surgery for the treatment of liver cancer are similar,but liver function recovers quickly after microwave ablation,and microwave ablation may enhance immune function.

Transformer-based correction scheme for short-term bus load prediction in holidays

To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.