On Evaluation of the New Edition College English Textbooks Based on Multi-dimensional Perspectives

Relative fi ndings about the evaluation of English textbooks in China are really rare. In this paper, the new edition college Englishtextbooks are analyzed and evaluated through drawing on the evaluation experience of English textbooks of other countries. The conclusion wasdrawn through questionnaires that the multi-dimensional mode, as a mode of learning based on the multi-sensory experience of students, couldprovide students with broader space for free development and exploration. It could guide the compilation and improvement of textbooks.

Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Assessment of public perspectives and barriers towards dengue preventive practices using the Health Belief Model in Puducherry,India:A cross-sectional study

Objective:To assess the perspectives and barriers towards dengue preventive practices among the residents of Puducherry,India.Methods:A cross-sectional survey was conducted in 300 households in Puducherry,using a population-proportionate(7:3)distribution from urban and rural areas by grid sampling.One adult interview per household was conducted and the participants were selected using a KISH grid.A semi-structured questionnaire based on the Health Belief Model(HBM)with additional questions on knowledge assessment was used.Knowledge was assessed based on the correctness of answers and the HBM scores were calculated on a 5-point Likert scale.Participants were categorized based on the median score under each domain.Logistic regression was used for adjusted analysis and models were built to predict the performances in each domain.Results:Four percent of the participants lacked basic knowledge regarding dengue transmission.While 208(69.3%)participants did not consider themselves at risk of contracting dengue within the next year,majority perceived dengue as a disease with low severity.Around 49.3%(148)were skeptical about the benefit of time and money spent on dengue prevention.Inadequate government efforts were stated as the major barrier(47.0%)and frequent reminders(142,47.3%)as the major cue to action.Age above 50 years(aOR 1.78,95%CI 1.04-3.06,P=0.037)and rural locality(aOR 2.68,95%CI 1.52-4.71,P=0.001)were found to be significantly associated with poor knowledge scores.Urban participants had a significantly higher chance to perceive low susceptibility as compared to the rural counterparts(aOR 1.74,95%CI 1.05-2.9,P=0.03).Participants with less than a high school education had low perceived benefits(aOR 2.46,95%CI 1.52-3.96,P<0.001)and low self-efficacy scores(aOR 2.66,95%CI 1.61-4.39,P<0.001).Conclusions:This study identifies key gaps in dengue prevention,including low perceived susceptibility,mild disease perception,limited knowledge of breeding sites,and overreliance on government efforts.Tailoring interventions to community needs,stratified to factors influencing the community perspectives can significantly improve dengue prevention efforts.

Recent advances and perspectives of zinc metal-free anodes for zinc ion batteries

Zinc-ion batteries(ZIBs) are recognized as potential energy storage devices due to their advantages of low cost, high energy density, and environmental friendliness. However, zinc anodes are subject to unavoidable zinc dendrites, passivation, corrosion, and hydrogen evolution reactions during the charging and discharging of batteries, becoming obstacles to the practical application of ZIBs. Appropriate zinc metal-free anodes provide a higher working potential than metallic zinc anodes, effectively solving the problems of zinc dendrites, hydrogen evolution, and side reactions during the operation of metallic zinc anodes. The improvement in the safety and cycle life of batteries creates conditions for further commercialization of ZIBs. Therefore, this work systematically introduces the research progress of zinc metal-free anodes in “rocking chair” ZIBs. Zinc metal-free anodes are mainly discussed in four categories: transition metal oxides,transition metal sulfides, MXene(two dimensional transition metal carbide) composites, and organic compounds, with discussions on their properties and zinc storage mechanisms. Finally, the outlook for the development of zinc metal-free anodes is proposed. This paper is expected to provide a reference for the further promotion of commercial rechargeable ZIBs.

Surgeon Perspectives on Anastomotic Leaks and FluidAI’s StreamTM Platform: Integrating Qualitative Insights for Technological Innovation

Purpose: This article investigates the critical importance of integrating surgeons’ direct input into the development of innovative technologies that address gaps in surgical care, including those aimed at reducing anastomotic leaks (AL), a major complication in gastrointestinal surgery. While traditional quantitative research methods are prevalent, they often overlook the invaluable insights of the surgeons who manage these complications firsthand. Subjects and Methods: This study employs a qualitative approach, utilizing semi-structured interviews with 40 surgeons from various specialties, including general, bariatric, colorectal, trauma, hepato-biliary, and thoracic surgery. The interviews were designed to probe the needs of surgeons, challenges currently faced, and gaps in clinical practice, research, and technology for detection and/or management of AL. The data were analyzed using thematic analysis, which revealed significant gaps in current technologies for early detection and prevention of leaks. Results: Surgeons expressed strong interest in FluidAI’s Stream™ Platform, a non-invasive medical device designed to monitor postoperative drainage fluid in real-time, providing continuous data on AL risk. The ability of this platform to offer early prediction through pH and electrical conductivity analysis was particularly appealing to participants, who emphasized the importance of timely interventions in improving patient outcomes. The study’s findings highlight not only the clinical challenges but also the emotional toll that AL takes on surgeons, underlining the need for innovations that are both data-driven and humanistic. Conclusion: By centering surgeons’ perspectives, this research advocates for a human-centered approach to technological advancement, ensuring that new tools are both clinically effective and aligned with the real-world needs of surgical practitioners.

Mistreatment during Childbirth: Impact on Maternal Outcomes and Importance of Provider Perspectives

Background: Dying in childbirth is one of the most common causes of death for women. While maternal mortality rates, defined as deaths per 100,000 live births, have been steadily dropping in most countries worldwide, maternal mortality rates have doubled in the United States in the last twenty years. This commentary examines the various contributing factors to this trend. Methods: A literature review was performed using the keywords: maternal mortality, United States, disrespectful maternity care, obstetric violence, provider perspectives, and disparities. Maternal mortality statistics were obtained from the World Health Organization website. Results: Medical factors associated with maternal mortality include increased maternal age and cardiovascular conditions. Social factors include barriers to healthcare access, delays in receiving medical care, reduction in reproductive health services in some states, and non-obstetrical deaths such as accidents, domestic violence, and suicide. Racial inequities and disparities of care are reflected in higher maternal mortality rates for minorities and people of color. Disrespectful maternity care or obstetric violence has been reported worldwide as a factor in delay of lifesaving obstetrical care and reluctance by a pregnant person to access the healthcare system. About one in five US women has reported experiencing mistreatment, varying from verbal abuse to lack of privacy, from coerced procedures to neglect during childbirth. Conclusion: This commentary highlights the importance of inclusion of providers in research on respectful maternity care. Provider burnout, moral distress, limited time, and burden of clinical responsibilities are known challenges to respectful and comprehensive medical care. The association of disrespectful care with poor maternal outcomes needs to be studied. Exploring root causes of disrespectful childbirth care can empower nurses, midwives, and physicians to improve their environment and find solutions to reduce a potential cause of maternal mortality.

Current perspectives of viral hepatitis

Viral hepatitis represents a major danger to public health,and is a globally leading cause of death.The five liver-specific viruses:Hepatitis A virus,hepatitis B virus,hepatitis C virus,hepatitis D virus,and hepatitis E virus,each have their own unique epidemiology,structural biology,transmission,endemic patterns,risk of liver complications,and response to antiviral therapies.There remain few options for treatment,in spite of the increasing prevalence of viral-hepatitiscaused liver disease.Furthermore,chronic viral hepatitis is a leading worldwide cause of both liver-related morbidity and mortality,even though effective treatments are available that could reduce or prevent most patients’complications.In 2016,the World Health Organization released its plan to eliminate viral hepatitis as a public health threat by the year 2030,along with a discussion of current gaps and prospects for both regional and global eradication of viral hepatitis.Today,treatment is sufficiently able to prevent the disease from reaching advanced phases.However,future therapies must be extremely safe,and should ideally limit the period of treatment necessary.A better understanding of pathogenesis will prove beneficial in the development of potential treatment strategies targeting infections by viral hepatitis.This review aims to summarize the current state of knowledge on each type of viral hepatitis,together with major innovations.

Multidimensional Perspectives on the Teaching and Practice of Typography Design

With the deepening of the curriculum teaching reform in colleges and universities,the teaching reform of art design professional courses is imperative.The study found that the current art design professional font design course teaching there are more solidified teaching methods,students operating ability is relatively homogenised,the teaching content to the"westernised"based,resulting in poor adaptability of students and other prominent problems.This paper starts from the"three effects"of"effect","efficiency"and"effectiveness",and adopts a multi-dimensional and emotional thinking perspective to carry out the curriculum of typeface design.This paper starts from the"three effects"of"effect","efficiency"and"effectiveness",and adopts a multi-dimensional and emotional perspective of thinking to carry out the teaching and practice of typeface design in order to strengthen the visual information of Chinese culture,and at the same time,to explore the creative potential of the students,so as to improve the students'innovation and creativity.

Online International Peer Interaction:An Exploration of Impacts on Comprehensive Competencies,Global Perspectives,and Cross-Cultural Communication Skills

With the increasing trend of globalization and the rapid advancement of information technology,online learning platforms such as Zoom are becoming increasingly influential in the field of education.The focus of this study was the online international peer interaction based on the Zoom platform,detailing how such interaction programs are conducted and exploring in depth the specific impacts of this interaction mode on students’comprehensive competencies,global perspectives,and cross-cultural communication skills.This research not only provides new practical references for online learning and international education but also offers new research perspectives and directions for educators and researchers.

Intelligent 6G Wireless Network with Multi-Dimensional Information Perception

Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.

Past, Present and Future Perspectives of Rice Production in Tanzania

Cultivated rice (Oryza sativa L. and Oryza. glaberrima) is one of the most important food crops in the world. World rice production has increased three times since the green revolution. However, climate change and global warming effects as well as ever increasing world population will require the world to produce more rice without increasing area under rice production in order to meet those demands. The best option to overcome these challenges includes adoption of climate-smart technologies and sustainable solutions to rice production. Rice was probably introduced in Tanzania over 1000 years ago by Asian traders during trade contacts between Asia and East Africa Coast through Indian Ocean. Rice cultivation had been restricted to coastal area until 19th century when it started spreading to interior areas of Tanzania. During colonial period (1880s-1960s), the emphasis was to produce cash crops as raw materials for industrialized world. After independence production of rice increased significantly. Currently, rice is the second most important food crop in Tanzania after maize and Tanzania is the leading producer of rice in East African countries. It ranks 4th and 22nd in Africa and World respectively in terms of rice production. In this paper, the rice history, ecosystems, challenges and future perspective for sustaining rice production in Tanzania is reviewed.

Envelope Method and More General New Global Structures of Solutions for Multi-dimensional Conservation Law

For the two-dimensional(2D)scalar conservation law,when the initial data contain two different constant states and the initial discontinuous curve is a general curve,then complex structures of wave interactions will be generated.In this paper,by proposing and investigating the plus envelope,the minus envelope,and the mixed envelope of 2D non-selfsimilar rarefaction wave surfaces,we obtain and the prove the new structures and classifications of interactions between the 2D non-selfsimilar shock wave and the rarefaction wave.For the cases of the plus envelope and the minus envelope,we get and prove the necessary and sufficient criterion to judge these two envelopes and correspondingly get more general new structures of 2D solutions.

Research and Practice on the Multi-dimensional Course Goal Achievement Evaluation of Software Engineering

According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.

An Ordinal Multi-Dimensional Classification(OMDC)for Predictive Maintenance

Predictive Maintenance is a type of condition-based maintenance that assesses the equipment's states and estimates its failure probability and when maintenance should be performed.Although machine learning techniques have been frequently implemented in this area,the existing studies disregard to the nat-ural order between the target attribute values of the historical sensor data.Thus,these methods cause losing the inherent order of the data that positively affects the prediction performances.To deal with this problem,a novel approach,named Ordinal Multi-dimensional Classification(OMDC),is proposed for estimating the conditions of a hydraulic system's four components by taking into the natural order of class values.To demonstrate the prediction ability of the proposed approach,eleven different multi-dimensional classification algorithms(traditional Binary Relevance(BR),Classifier Chain(CC),Bayesian Classifier Chain(BCC),Monte Carlo Classifier Chain(MCC),Probabilistic Classifier Chain(PCC),Clas-sifier Dependency Network(CDN),Classifier Trellis(CT),Classifier Dependency Trellis(CDT),Label Powerset(LP),Pruned Sets(PS),and Random k-Labelsets(RAKEL))were implemented using the Ordinal Class Classifier(OCC)algorithm.Besides,seven different classification algorithms(Multilayer Perceptron(MLP),Support Vector Machine(SVM),k-Nearest Neighbour(kNN),Decision Tree(C4.5),Bagging,Random Forest(RF),and Adaptive Boosting(AdaBoost))were chosen as base learners for the OCC algorithm.The experimental results present that the proposed OMDC approach using binary relevance multi-dimensional classification methods predicts the conditions of a hydraulic system's multiple components with high accuracy.Also,it is clearly seen from the results that the OMDC models that utilize ensemble-based classification algorithms give more reliable prediction performances with an average Hamming score of 0.853 than the others that use traditional algorithms as base learners.

Data inversion of multi-dimensional magnetic resonance in porous media

Since its inception in the 1970s,multi-dimensional magnetic resonance(MR)has emerged as a powerful tool for non-invasive investigations of structures and molecular interactions.MR spectroscopy beyond one dimension allows the study of the correlation,exchange processes,and separation of overlapping spectral information.The multi-dimensional concept has been re-implemented over the last two decades to explore molecular motion and spin dynamics in porous media.Apart from Fourier transform,methods have been developed for processing the multi-dimensional time-domain data,identifying the fluid components,and estimating pore surface permeability via joint relaxation and diffusion spectra.Through the resolution of spectroscopic signals with spatial encoding gradients,multi-dimensional MR imaging has been widely used to investigate the microscopic environment of living tissues and distinguish diseases.Signals in each voxel are usually expressed as multi-exponential decay,representing microstructures or environments along multiple pore scales.The separation of contributions from different environments is a common ill-posed problem,which can be resolved numerically.Moreover,the inversion methods and experimental parameters determine the resolution of multi-dimensional spectra.This paper reviews the algorithms that have been proposed to process multidimensional MR datasets in different scenarios.Detailed information at the microscopic level,such as tissue components,fluid types and food structures in multi-disciplinary sciences,could be revealed through multi-dimensional MR.

Instruction of the Multi-dimensional Developing Perspective on Translation in Translation Competence Development

The overlook of the cultivation of learners’perspective on translation is one of the essential reasons that we fail to enhance learners’translation competence effectively and efficiently.The perspective on translation mirrors not only the interpretation of the essence,value,and function of translation,but the interpretation of culture and intercultural communication,which offers inspiration and implication on translation in the current context.This study analyzes the significance of the multi-dimensional developing perspective on translation and elaborates on the HBARP model to integrate the perspective on translation throughout the learning and teaching process to inspire learners to interpret translation essence and features,to highlight the intercultural communicative significance in the current context with a historical vision.

Multi-dimension and multi-modal rolling mill vibration prediction model based on multi-level network fusion

Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.

Research on Early Warning of Banking Crises from the Perspective of Credit Structures

The relationship between credit expansion and banking crises is complex and cannot be fully explained by total credit alone.A systematic analysis of the relationship between the amount and structure of total credit and banking crises is important for an objective prediction of the influence of potential financial risks.This paper,drawing on data from 15 selected countries,delves into the power of credit indicators in the early warning of banking crises from the perspectives of industrial structure,sector structure,and term structure of credit.Various machine learning methods were used,including Logistic Regression,Random Forest,Decision Tree,Support Vector Machine(SVM),Bagging,and Boosting models.The empirical findings indicate that credit expansion plays a crucial role in triggering banking crises.However,total credit is better suited for the early warning of short-term banking crises,whereas credit structure is more useful for the early warning of long-term banking crises.Moreover,in an early warning system,identifying key early warning indicators is more meaningful than merely increasing the number of indicators.Machine learning can somewhat enhance the early warning power,but it may not always be robust.Therefore,more attention should be paid to potential systemic banking crises resulting from an imbalance in credit structure while regulating the total credit threshold.

Moral Perspective as Depicted in the Archetypes on Divine-Human Perspective of Dianshizhai Pictorial

This article examines the archetypes related to the divine-human perspective in the Dianshizhai Pictorial and uses the basic theory of“Myth-Archetype Criticism”to analyze the concepts of moral perspective and the view of cause and effect reflected in the text.It summarizes the interactive modes and various archetypes of cause and effect in three contexts:gods to humans,humans to gods,and humans to humans,explores the social reality and the relevant views of moral perspective and causality reflected in the illustrated magazine,and reveals the archetype foundation of the narrative of moral perspective retribution in Dianshizhai Pictorial in the three dimensions of psychology,literature,and society.

Study on the detection methods of S&T frontier from the multi-dimensional perspective

The development of network and information technology has brought changes to the information environment.The sources of information are becoming more diverse,and intelligence acquisition will be more complicated.The intelligence reflected by different dimensions of scientific and technologi-cal(S&T)data will have their own focuses.It has become inevitable to carry out the multi-dimen-sional research of S&T frontier,which is also a current research hotspot.This paper uses quantita-tive and qualitative research methods to conduct research and analysis of S&T frontier detection from three dimensions including S&T research projects,S&T papers and patents,and proposes related re-search methods and development tools.This work analyzes the S&T frontiers in the field of artificial intelligence and draws conclusions based on the analysis results of real and effective S&T data in three dimensions.