Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Enhancing Emergency ECG Interpretation: A Practical Checklist Developed from a Study Assessing Young Physicians’ Diagnostic Abilities

Effective interpretation of electrocardiograms (ECGs) is a critical skill for healthcare professionals, especially in emergency settings. This study assessed the diagnostic abilities of 200 final-year medical students and young doctors in ECG interpretation. Subsequently, based on the study findings, a practical checklist was developed, and a comprehensive book entitled “Critical ECG in Emergencies” was authored by the researchers. The checklist provides cognitive aids and serves as a systematic guide to enhance ECG interpretation in urgent situations. The study revealed a need for improved confidence in interpreting critical ECGs among the participants. The checklist offers promise for reducing diagnostic errors and improving patient outcomes. Further research is required to evaluate its impact on daily practice and patient care, while the book provides valuable resources for healthcare professionals in emergency medicine.

Directly predicting N_(2) electroreduction reaction free energy using interpretable machine learning with non-DFT calculated features

Electrocatalytic nitrogen reduction to ammonia has garnered significant attention with the blooming of single-atom catalysts(SACs),showcasing their potential for sustainable and energy-efficient ammonia production.However,cost-effectively designing and screening efficient electrocatalysts remains a challenge.In this study,we have successfully established interpretable machine learning(ML)models to evaluate the catalytic activity of SACs by directly and accurately predicting reaction Gibbs free energy.Our models were trained using non-density functional theory(DFT)calculated features from a dataset comprising 90 graphene-supported SACs.Our results underscore the superior prediction accuracy of the gradient boosting regression(GBR)model for bothΔg(N_(2)→NNH)andΔG(NH_(2)→NH_(3)),boasting coefficient of determination(R^(2))score of 0.972 and 0.984,along with root mean square error(RMSE)of 0.051 and 0.085 eV,respectively.Moreover,feature importance analysis elucidates that the high accuracy of GBR model stems from its adept capture of characteristics pertinent to the active center and coordination environment,unveilling the significance of elementary descriptors,with the colvalent radius playing a dominant role.Additionally,Shapley additive explanations(SHAP)analysis provides global and local interpretation of the working mechanism of the GBR model.Our analysis identifies that a pyrrole-type coordination(flag=0),d-orbitals with a moderate occupation(N_(d)=5),and a moderate difference in covalent radius(r_(TM-ave)near 140 pm)are conducive to achieving high activity.Furthermore,we extend the prediction of activity to more catalysts without additional DFT calculations,validating the reliability of our feature engineering,model training,and design strategy.These findings not only highlight new opportunity for accelerating catalyst design using non-DFT calculated features,but also shed light on the working mechanism of"black box"ML model.Moreover,the model provides valuable guidance for catalytic material design in multiple proton-electron coupling reactions,particularly in driving sustainable CO_(2),O_(2),and N_(2) conversion.

Study on the Integration of Professional Ethics in Medical Interpretation Course Based on Situational Simulation Teaching Method and Virtual Reality Technology

Based on the theory of situational simulation,the article explores the approach to building the medical interpretation course from three aspects,which are the objective,design,and teaching model.The course aims to cultivate high-quality medical interpreting talents and enhance students’practical interpretation skills,as well as to integrate professional ethics into teaching.Thus,it is necessary for lecturers to change their teaching philosophy,apply information technology,and improve teaching design.Through rich medical interpretation course,lecturers can promote the integration of professional ethics in medical interpretation.

Intelligent geochemical interpretation of mass chromatograms:Based on convolution neural network

Gas chromatography-mass spectrometry(GC-MS)is an extremely important analytical technique that is widely used in organic geochemistry.It is the only approach to capture biomarker features of organic matter and provides the key evidence for oil-source correlation and thermal maturity determination.However,the conventional way of processing and interpreting the mass chromatogram is both timeconsuming and labor-intensive,which increases the research cost and restrains extensive applications of this method.To overcome this limitation,a correlation model is developed based on the convolution neural network(CNN)to link the mass chromatogram and biomarker features of samples from the Triassic Yanchang Formation,Ordos Basin,China.In this way,the mass chromatogram can be automatically interpreted.This research first performs dimensionality reduction for 15 biomarker parameters via the factor analysis and then quantifies the biomarker features using two indexes(i.e.MI and PMI)that represent the organic matter thermal maturity and parent material type,respectively.Subsequently,training,interpretation,and validation are performed multiple times using different CNN models to optimize the model structure and hyper-parameter setting,with the mass chromatogram used as the input and the obtained MI and PMI values for supervision(label).The optimized model presents high accuracy in automatically interpreting the mass chromatogram,with R2values typically above 0.85 and0.80 for the thermal maturity and parent material interpretation results,respectively.The significance of this research is twofold:(i)developing an efficient technique for geochemical research;(ii)more importantly,demonstrating the potential of artificial intelligence in organic geochemistry and providing vital references for future related studies.

An improved deep dilated convolutional neural network for seismic facies interpretation

With the successful application and breakthrough of deep learning technology in image segmentation,there has been continuous development in the field of seismic facies interpretation using convolutional neural networks.These intelligent and automated methods significantly reduce manual labor,particularly in the laborious task of manually labeling seismic facies.However,the extensive demand for training data imposes limitations on their wider application.To overcome this challenge,we adopt the UNet architecture as the foundational network structure for seismic facies classification,which has demonstrated effective segmentation results even with small-sample training data.Additionally,we integrate spatial pyramid pooling and dilated convolution modules into the network architecture to enhance the perception of spatial information across a broader range.The seismic facies classification test on the public data from the F3 block verifies the superior performance of our proposed improved network structure in delineating seismic facies boundaries.Comparative analysis against the traditional UNet model reveals that our method achieves more accurate predictive classification results,as evidenced by various evaluation metrics for image segmentation.Obviously,the classification accuracy reaches an impressive 96%.Furthermore,the results of seismic facies classification in the seismic slice dimension provide further confirmation of the superior performance of our proposed method,which accurately defines the range of different seismic facies.This approach holds significant potential for analyzing geological patterns and extracting valuable depositional information.

Angular unconformity in Pennsylvanian strata from 3-D seismic interpretation,Goldsmith Field,West Texas

The Pennsylvanian unconformity,which is a detrital surface,separates the beds of the Permian-aged strata from the Lower Paleozoic in the Central Basin Platform.Seismic data interpretation indicates that the unconformity is an angular unconformity,overlying multiple normal faults,and accompanied with a thrust fault which maximizes the region's structural complexity.Additionally,the Pennsylvanian angular unconformity creates pinch-outs between the beds above and below.We computed the spectral decomposition and reflector convergence attributes and analyzed them to characterize the angular unconformity and faults.The spectral decomposition attribute divides the broadband seismic data into different spectral bands to resolve thin beds and show thickness variations.In contrast,the reflector convergence attribute highlights the location and direction of the pinch-outs as they dip south at angles between 2° and 6°.After reviewing findings from RGB blending of the spectrally decomposed frequencies along the Pennsylvanian unconformity,we observed channel-like features and multiple linear bands in addition to the faults and pinch-outs.It can be inferred that the identified linear bands could be the result of different lithologies associated with the tilting of the beds,and the faults may possibly influence hydrocarbon migration or act as a flow barrier to entrap hydrocarbon accumulation.The identification of this angular unconformity and the associated features in the study area are vital for the following reasons:1)the unconformity surface represents a natural stratigraphic boundary;2)the stratigraphic pinch-outs act as fluid flow connectivity boundaries;3)the areal extent of compartmentalized reservoirs'boundaries created by the angular unconformity are better defined;and 4)fault displacements are better understood when planning well locations as faults can be flow barriers,or permeability conduits,depending on facies heterogeneity and/or seal effectiveness of a fault,which can affect hydrocarbon production.The methodology utilized in this study is a further step in the characterization of reservoirs and can be used to expand our knowledge and obtain more information about the Goldsmith Field.

Log interpretation of carbonate rocks based on petrophysical facies constraints

The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability.In view of the sedimentation,diagenesis,testing,and production characteristics of carbonate reservoirs in the study area,combined with the current trends and advances in well log interpretation techniques for carbonate reservoirs,a log interpretation technology route of“geological information constraint+deep learning”was developed.The principal component analysis(PCA)was employed to establish lithology identification criteria with an accuracy of 91%.The Bayesian stepwise discriminant method was used to construct a sedimentary microfacies identification method with an accuracy of 90.5%.Based on production data,the main lithologies and sedimentary microfacies of effective reservoirs were determined,and 10 petrophysical facies with effective reservoir characteristics were identified.Constrained by petrophysical facies,the mean interpretation error of porosity compared to core analysis results is 2.7%,and the ratio of interpreted permeability to core analysis is within one order of magnitude,averaging 3.6.The research results demonstrate that deep learning algorithms can uncover the correlation in carbonate reservoir well logging data.Integrating geological and production data and selecting appropriate machine learning algorithms can significantly improve the accuracy of well log interpretation for carbonate reservoirs.

Simultaneous Interpreting Output Assessment of Earnings Conference Call: Case Analysis of Tencent 2022 Q3 Result Announcement

Quality in simultaneous interpreting is a frequently discussed concept. In the enterprise setting, earnings conference call remains a rarely explored field. This thesis offers a descriptive study on assessing interpreting quality from perspectives of fidelity, fluency, and appropriacy. As the corpus, Tencent 2022 Third Quarter Result Announcement provides an ideal transcript to the author to conduct its analysis. Interpreting is frequently done without bearing in mind the multitude of factors that can affect the quality of interpreting. Drawing a conclusion that the interpreter does make a lot of omissions, pauses and hesitations posing a negative effect on the fidelity, fluency and accuracy of the interpreting, the present author suggests that more preparation should be done for improving performance, such as terminologies, company background information, a reasonable speech rate, good image and acoustic quality, and so on.

Application of Secondary Logging Interpretation—Taking Yan 9 Reservoir in X Area as an Example

Logging data and its interpretation results are one of the most important basic data for understanding reservoirs and oilfield development. Standardized and unified logging interpretation results play a decisive role in fine reservoir description and reservoir development. Aiming at the problem of the conflict between the development effect and the initial interpretation result of Yan 9 reservoir in Hujianshan area of Ordos Basin, by combining the current well production performance, logging, oil test, production test and other data, on the basis of making full use of core, coring, logging, thin section analysis and high pressure mercury injection data, the four characteristics of reservoir are analyzed, a more scientific and reasonable calculation model of reservoir logging parameters is established, and the reserves are recalculated after the second interpretation standard of logging is determined. The research improves the accuracy of logging interpretation and provides an effective basis for subsequent production development and potential horizons.

Effects and Causes of VR-Supported Interpreting Learning Environment on the Interpretation Classroom Anxiety of Student Interpreter

Interpreting activity is considered a high-anxiety activity due to its immediacy, multitasking, complexity of cognitive processing, and uncertainty of cognitive processing. Research has shown that interpreting anxiety, as the biggest emotional obstacle in the interpreting process, is the main emotional factor that leads to individual differences in interpreting. Students often claim to have fear or anxiety behaviors in interpreting exams, interpreting competitions, and interpreting classes. However, the research on interpreting teaching attaches importance to the cultivation of language knowledge, cultural knowledge, and interpreting skills, and does not pay enough attention to emotional factors such as motivation and anxiety in interpreting learning, which makes it difficult for the cultivated interpreters to meet the requirements of professional practice. In recent years, virtual reality technology (VR) has been gradually applied in the field of foreign language and interpreting teaching for creating a real, interactive and experiential language learning environment. Situated Learning Theory stresses that the fundamental mechanism for learning to take place is for individuals to participate in the real context in which knowledge is generated, and to realize the construction of knowledge through the interaction with the community of practice and the environment. Virtual reality technology can satisfy the needs of language learners for real contexts by providing learners with immersive, imaginative and interactive scenario simulations, and has a certain positive effect on alleviating learning anxiety. Therefore, relying on the virtual simulation course “United Nations Kubuqi International Desert Ecological Science and Technology Innovation International Volunteer Language Service Practical Training System”, this paper adopts a combination of quantitative and qualitative analyses to investigate the interpretation anxiety level of the interpreter trainees and the factors affecting them in the VR situation to help them discover effective responses to interpreter anxiety.

Preliminary report of coseismic surface rupture(part)of Türkiye's M_(W)7.8 earthquake by remote sensing interpretation

Both M_(W) 7.8 and M_(W) 7.5 earthquakes occurred in southeastern Türkiye on February 6,2023,resulting in numerous buildings collapsing and serious casualties.Understanding the distribution of coseismic surface ruptures and secondary disasters surrounding the epicentral area is important for post-earthquake emergency and disaster assessments.High-resolution Maxar and GF-2 satellite data were used after the events to extract the location of the rupture surrounding the first epicentral area.The results show that the length of the interpreted surface rupture zone(part of)is approximately 75 km,with a coseismic sinistral dislocation of 2-3 m near the epicenter;however,this reduced to zero at the tip of the southwest section of the East Anatolia Fault Zone.Moreover,dense soil liquefaction pits were triggered along the rupture trace.These events are in the western region of the Eurasian Seismic Belt and result from the subduction and collision of the Arabian and African Plates toward the Eurasian Plate.The western region of the Chinese mainland and its adjacent areas are in the eastern section of the Eurasian Seismic Belt,where seismic activity is controlled by the collision of the Indian and Eurasian Plates.Both China and Türkiye have independent tectonic histories.

Problems of Music Interpretation and Its Expression: On the Example of the Violin

Music is essentially a sonic phenomenon, an intangible art that we experience through our auditory organs. It is written as a physical note on paper. It is the result of harmony and composition of music that expresses the meaning of music created from the author’s mind, thinking, skills, and feelings, or composition or work. If a composition is not interpreted by a musician and set to music, it is nothing more than a notation and notation written down on paper. The main process of conveying the composition to the listeners through the musician’s interpretation of the music is somewhat overlooked. Therefore, in this research, the musician’s thinking and editing method, and how to express it through interpretation, were the doctoral dissertation and articles of researchers such as have been studied in comparison.

Problems and Countermeasures in the Training of Master of Translation and Interpreting Talents in the Context of Technological Empowerment

This paper aims to explore the problems and countermeasures in the training of Master of Translation and Interpreting(MTI)talents in the context of technological empowerment.Through methods such as questionnaires and literature review,the study analyzes the problems in the training of MTI talents under technological empowerment and,by examining the feasibility and applicability of technologies,proposes countermeasures to these problems.The research finds that there are still problems in four areas:training concept,teaching content,research in the current training of MTI talents,and mutual empowerment of technology and education.Four countermeasures are suggested to address these problems,including utilizing technology to promote personalized training and optimize teaching content.This study provides valuable references for future educators to leverage technology in the training of MTI talents.

Compass for Interpretation:Note-taking

This paper starts with the exploration of the features of interpretation and its connection with memory, and draw the conclusion that note-taking is the "compass for interpretation". Then, the author tries to summarize several principles with a hope to give interpreters some inspirations.

Study of real-time LWD data visual interpretation and geo-steering technology

LWD（logging while drilling） data has been used to explore complex subtle reservoirs by realtime visual interpretation and geo-steering.The method comprises of computer communication,well log data processing,formation recognition,reservoir modeling and model updating in real time.We studied the key technologies related to real-time LWD data visual interpretation and geo-steering and developed computer software with Chinese intellectual property rights covering the following important aspects： 1） real-time computer communication of well site LWD data;2） visualization of geological model and borehole information;3） real-time interpretation of LWD data;4） real-time geological model updating and geo-steering technology.We use field application examples to demonstrate the feasibility and validity of the proposed technologies.

On the Verbal and Non-Verbal Features in Chinese-English Interpretation

This paper investigates the verbal and non - verbal features of interpretation from Chinese into English . On the one hand the language of interpretation belongs to the category of oral language, So It determines the path an interpreter should follow while interpreting . On the other hand it is suggested that the non - verbal approach plays an important role in interpretation. Therefore an interpreter can not be a qualified interpreter unless he is, in addition to language techniques, skilled in the application of paralanguage.

lp norm inverse spectral decomposition and its multi-sparsity fusion interpretation

Spectral decomposition has been widely used in the detection and identifi cation of underground anomalous features(such as faults,river channels,and karst caves).However,the conventional spectral decomposition method is restrained by the window function,and hence,it mostly has low time–frequency focusing and resolution,thereby hampering the fi ne interpretation of seismic targets.To solve this problem,we investigated the sparse inverse spectral decomposition constrained by the lp norm(0<p≤1).Using a numerical model,we demonstrated the higher time–frequency resolution of this method and its capability for improving the seismic interpretation for thin layers.Moreover,given the actual underground geology that can be often complex,we further propose a p-norm constrained inverse spectral attribute interpretation method based on multiresolution time–frequency feature fusion.By comprehensively analyzing the time–frequency spectrum results constrained by the diff erent p-norms,we can obtain more refined interpretation results than those obtained by the traditional strategy,which incorporates a single norm constraint.Finally,the proposed strategy was applied to the processing and interpretation of actual three-dimensional seismic data for a study area covering about 230 km^(2) in western China.The results reveal that the surface water system in this area is characterized by stepwise convergence from a higher position in the north(a buried hill)toward the south and by the development of faults.We thus demonstrated that the proposed method has huge application potential in seismic interpretation.

Optimized Non-hyperbolic Stack Imaging Based on Interpretation Model

In complex media, especially for seismic prospecting in deep layers in East China and in the mountainous area in West China, due to the complex geological condition, the common-mid-point （CMP） gather of deep reflection event is neither hyperbolic, nor any simple function. If traditional normal move-out （NMO） and stack imaging technology are still used, it is difficult to get a clear stack image. Based on previous techniques on non-hyperbolic stack, it is thought in this paper that no matter how complex the geological condition is, in order to get an optimized stack image, the stack should be non time move-out stack, and any stacking method limited to some kind of curve will be restricted to application conditions. In order to overcome the above-mentioned limit, a new method called optimized non-hyperbolic stack imaging based on interpretation model is presented in this paper. Based on CMP/CRP （Common-Reflection-Point） gather after NMO or pre-stack migration, this method uses the interpretation model of reflectors as constraint, and takes comparability as a distinguishing criterion, and finally forms a residual move-out correction for the gather of constrained model. Numerical simulation indicates that this method could overcome the non hyperbolic problem and get fine stack image.

Crustal structure of northeastern Tibetan plateau and Ordos block:Waveform interpretation of the Maqen-Jingbian seismic refraction profile

The Maqen-Jingbian wide-angle seismic reflection and refraction experiment was carried out in 1998, which aims at determining detailed structure in the crust and top of the upper mantle and understanding structural relation between the northeastern Tibetan plateau and the Ordos block. The 1-D crustal models inferred by waveform inversion show strong variations in crustal structure, which can be classified into four different types： ① an Ordos platform with the Proterozoic crust and two high-velocity layers in the northeast section, ② a transitional crust between the northeastern Tibetan plateau and the Ordos block across the Haiyuan earthquake zone, ③ the Qilian orogenic zone in the central part, and ④ the Qinling orogenic zone in the southwestern section. The Moho depth increases from -42 km to -62 km from the NE part to the SW part of the profile. The crystalline crust consists of the upper crust and lower crust in northeastern Tibetan plateau. There is an obviously low P-wave velocity layer dipping northeastward, which is 12-13 km thick, at the bottom of the upper crust in Qinling orogenic zone and Haiyuan earthquake zone. The lower crust is characterized by alternating high and low P-wave velocity layers. Beneath Ordos block, i.e., the NE part of the profile, the crust shows quite a smooth increase in P-wave ve- locity down to the Moho at a depth of about 42 km.