A Probe Into the Mixed Teaching Reform of Python Language Programming

This paper first analyzes the significance of applying mixed teaching to the“Python Language Programming”course,briefly describes the current state of teaching in“Python Language Programming,”and discusses strategies for reforming mixed teaching approaches.The goal is to provide a reference for the innovative development of teaching the“Python Language Programming”course.

Glia-to-neuron reprogramming to the rescue?

Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.

Neurocircuit regeneration by extracellular matrix reprogramming

The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.

Evaluating large language models as patient education tools for inflammatory bowel disease:A comparative study

BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patient information needs.However,LLM use to deliver accurate and comprehensible IBD-related medical information has yet to be thoroughly investigated.AIM To assess the utility of three LLMs(ChatGPT-4.0,Claude-3-Opus,and Gemini-1.5-Pro)as a reference point for patients with IBD.METHODS In this comparative study,two gastroenterology experts generated 15 IBD-related questions that reflected common patient concerns.These questions were used to evaluate the performance of the three LLMs.The answers provided by each model were independently assessed by three IBD-related medical experts using a Likert scale focusing on accuracy,comprehensibility,and correlation.Simultaneously,three patients were invited to evaluate the comprehensibility of their answers.Finally,a readability assessment was performed.RESULTS Overall,each of the LLMs achieved satisfactory levels of accuracy,comprehensibility,and completeness when answering IBD-related questions,although their performance varies.All of the investigated models demonstrated strengths in providing basic disease information such as IBD definition as well as its common symptoms and diagnostic methods.Nevertheless,when dealing with more complex medical advice,such as medication side effects,dietary adjustments,and complication risks,the quality of answers was inconsistent between the LLMs.Notably,Claude-3-Opus generated answers with better readability than the other two models.CONCLUSION LLMs have the potential as educational tools for patients with IBD;however,there are discrepancies between the models.Further optimization and the development of specialized models are necessary to ensure the accuracy and safety of the information provided.

Spatial Data Process Using Python Script and Visual Programming Language in ArcGIS

Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geographic Information System） software in GIS sector. However, those table data contain much unnecessary information that do not need for a certain project. Using the raw data can increase processing times and reduce performance of geoprocessing tools. This study shows steps of how the raw data are being processed using ArcGIS ModelBuilder and Python script.

Shrek:a dynamic object-oriented programming language

From a perspective of theoretical study, there are some faults in the models of the existing object-oriented programming languages. For example, C# does not support metaclasses, the primitive types of Java and C# are not objects, etc. So, this paper designs a programming language, Shrek, which integrates many language features and constructions in a compact and consistent model. The Shrek language is a class-based purely object-oriented language. It has a dynamical strong type system, and adopts a single-inheritance mechanism with Mixin as its complement. It has a consistent class instantiation and inheritance structure, and the ability of intercessive structural computational reflection, which enables it to support safe metaclass programming. It also supports multi-thread programming and automatic garbage collection, and enforces its expressive power by adopting a native method mechanism. The prototype system of the Shrek language is implemented and anticipated design goals are achieved.

OFF LINE INTERPRETER OF AGENT ORIENTED PROGRAMMING LANGUAGE AOPLID

AOPLID is a novel agent oriented programming language whose theoretical framework is the existed situation calculus theory and agent model based on intention driven manner. An AOPLID program is represented in set manner. In this paper, an off line AOPLID interpreter in Prolog is implemented, based on the off line AOPLID program semantics. At the same time, the set of rules is given which transforms an AOPLID program represented by sets into Prolog clauses so that it can be interpreted by the off line interpreter. Finally, the sound codes of the off line interpreter are listed.

Concurrent Constraint Programming:A Language and Its Execution Model

To overcome inefficiency in traditional logic programming, a declarative programming language COPS is designed based on the notion of concurrent constraint programming (CCP). The improvement is achieved by the adoption of constraint-based heuristic strategy and the introduction of deterministic components in the framework of CCP. Syntax specification and an operational semantic description are presented.

NewBee: Context-Free Grammar (CFG) of a New Programming Language for Novice Programmers

Learning programming and using programming languages are the essential aspects of computer science education.Students use programming languages to write their programs.These computer programs(students or practitioners written)make computers artificially intelligent and perform the tasks needed by the users.Without these programs,the computer may be visioned as a pointless machine.As the premise of writing programs is situated with specific programming languages,enormous efforts have been made to develop and create programming languages.However,each program-ming language is domain-specific and has its nuances,syntax and seman-tics,with specific pros and cons.These language-specific details,including syntax and semantics,are significant hurdles for novice programmers.Also,the instructors of introductory programming courses find these language specificities as the biggest hurdle in students learning,where more focus is on syntax than logic development and actual implementation of the program.Considering the conceptual difficulty of programming languages and novice students’struggles with the language syntax,this paper describes the design and development of a Context-Free Grammar(CFG)of a programming language for the novice,newcomers and students who do not have computer science as their major.Due to its syntax proximity to daily conversations,this paper hypothesizes that this language will be easy to use and understand by novice programmers.This paper systematically designed the language by identifying themes from various existing programming languages(e.g.,C,Python).Additionally,this paper surveyed computer science experts from industry and academia,where experts self-reported their satisfaction with the newly designed language.The results indicate that 93%of the experts reported satisfaction with the NewBee for novice,newcomer and non-Computer Sci-ence(CS)major students.

《Grammars for Programming Languages》简介

加利福尼亚大学J. Craig cleaveland和Robert C. Uzgalis合著的“Grammars forProgramming Languages”(程序设计语言的文法)一书系美国ELSEVIER NORTH-HO-LLAND, INC.1977年出版的一套程序设计语言丛书之一。 自从1956年Noam

Analysis of an event study using the Fama–French five‑factor model:teaching approaches including spreadsheets and the R programming language

The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts.However,only a limited number of free tools are available for this purpose.Given this lack of tools,the present study provides two approaches to facilitate the implementa-tion of an event study.The first approach consists of a set of MS Excel files based on the Fama–French five-factor model,which allows the application of the event study methodology in a semi-automatic manner.The second approach is an open-source R-programmed tool through which results can be obtained in the context of an event study without the need for programming knowledge.This tool widens the calculus possibilities provided by the first approach and offers the option to apply not only the Fama–French five-factor model but also other models that are common in the finan-cial literature.It is a user-friendly tool that enables reproducibility of the analysis and ensures that the calculations are free of manipulation errors.Both approaches are freely available and ready-to-use.

An Exploratory Practice of Integration of Industry and Education in High-level Programming Language Course in the Background of New Engineering

This paper analyzes some problems of the current teaching situation in the course High-level Programming Language,such as the lagging content of the course compared with technology development,the emphasis on theory rather than on practice,the low enthusiasm of students for learning,and the weak practical ability of students.In response to the needs of enterprises for talents under the background of New Engineering,especially the cultivation of students’adaptability and practical abilities towards future industries to improve students’knowledge and problemsolving abilities to keep up with the modern technology,this paper proposes the ways and methods to reform and explore the teaching content and teaching methods by integrating industry and education,assisting teaching according to industrial demands,and lowering technology barriers of new technology.The practical effect is evaluated through a survey in class and the follow-up questionnaire after class,and the results show that the effect of the practice is effective.

Linguistic Economy Applied to Programming Language Identifiers

Though many different readability metrics have been created, there still is no universal agreement defining readability of software source code. The lack of a clear agreement of source code readability has ramifications in many areas of the software development life-cycle, not least of which being software maintainability. We propose a measurement based on Linguistic Economy to bridge the gap between mathematical and behavioral aspects. Linguistic Economy describes efficiencies of speech and is generally applied to natural languages. In our study, we create a large corpus of words that are likely to be found in a programmer’s vocabulary, and a corpus of existing identifiers found in a collection of open-source projects. We perform a usage analysis to create a database from both of these corpora. Linguistic Economy suggests that words requiring less effort to speak are used more often than words requiring more effort. This concept is applied to measure how difficult program identifiers are to understand by extracting them from the program source and comparing their usage to the database. Through this process, we can identify source code that programmers find difficult to review. We validate our work using data from a survey where programmers identified unpleasant to review source files. The results indicate that source files identified as unpleasant to review source code have more linguistically complicated identifiers than pleasant programs.

A Semiotic Analysis of Programming Languages

The paper presents an analysis of computer programming languages based on the semiotics of Charles S. Peirce. The author describes how such languages could evolve in order to achieve some of the expressive characteristics of natural languages. This description evinces otherwise unnoticed differences between natural languages and programming languages, showing that Peircean semiotics is an efficient analysis tool. This suggests further research on the technical features needed to implement an easier way to program computers.

Current Trends in Online Programming Languages Learning Tools: A Systematic Literature Review

Students face difficulties in programming languages learning (PLL) which encourages many scholars to investigate the factors behind that. Although there a number of positive and negative factors found to be effective in PLL procedure, utilising online tools in PLL were recognized as a positive recommended means. This motivates many researchers to provide solutions and proposals which result in a number of choices and options. However, categorising those efforts and showing what has been done, would provide a better and clear image for future studies. Therefore, this paper aims to conduct a systematic literature review to show what studies have been done and then categorise them based on the type of online tools and the aims of the research. The study follows Kitchenham and Charters guidelines for writing SLR (Systematic Literature Review). The search result reached 1390 publications between 2013-09/2018. After the filtration which has been done through selected criteria, 160 publications were found to be adequate to answer the review questions. The main results of this systematic review are categorizing the aims of the studies in online PLL tools, classifying the tools and finding the current trends of the online PLL tools.

Sustainable Learning of Computer Programming Languages Using Mind Mapping

In the current era of information technology,students need to learn modern programming languages efficiently.The art of teaching/learning program-ming requires many logical and conceptual skills.So it’s a challenging task for the instructors/learners to teach/learn these programming languages effectively and efficiently.Mind mapping is a useful visual tool for establishing ideas and connecting them to solve problems.This research proposed an effective way to teach programming languages through visual tools.This experimental study uses a mind mapping tool to teach two programming environments:Text-based Programming and Blocks-based Programming.We performed the experiments with one hundred and sixty undergraduate students of two public sector universities in the Asia Pacific region.Four different instructional approaches,including block-based language(BBL),text-based languages(TBL),mind map with text-based language(MMTBL)and mind mapping with block-based(MMBBL)are used for this purpose.The results show that instructional approaches using a mind mapping tool to help students solve given tasks in their critical thinking are more effective than other instructional techniques.

Unified Mogramming with Var-Oriented Modeling and Exertion-Oriented Programming Languages

The Service ORiented Computing EnviRonment (SORCER) targets service abstractions for transdisciplinary complexity with support for heterogeneous service-oriented (SO) computing. SORCER's models are expressed in a top-down Var-oriented Modeling Language (VML) unified with programs in a bottoms-up Exertion-Oriented Language (EOL). In this paper the introduction to mogramming (modeling and programing), which uses both languages, is described. First, the emphasis is on modeling with service variables that allow for computational fidelity within VML. Then, seven types of service providers, both local and distributed, are described to form collaborative federations described in EOL. Finally, the unified hybrid of SO modeling and SO programming is presented. Fourteen simple mogramming examples illustrate the syntax and usage of both VML and EOL.

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

High-Level Portable Programming Language for Optimized Memory Use of Network Processors

Network processors (NPs) are widely used for programmable and high-performance networks;however, the programs for NPs are less portable, the number of NP program developers is small, and the development cost is high. To solve these problems, this paper proposes an open, high-level, and portable programming language called “Phonepl”, which is independent from vendor-specific proprietary hardware and software but can be translated into an NP program with high performance especially in the memory use. A common NP hardware feature is that a whole packet is stored in DRAM, but the header is cached in SRAM. Phonepl has a hardware-independent abstraction of this feature so that it allows programmers mostly unconscious of this hardware feature. To implement the abstraction, four representations of packet data type that cover all the packet operations (including substring, concatenation, input, and output) are introduced. Phonepl have been implemented on Octeon NPs used in plug-ins for a network-virtualization environment called the VNode Infrastructure, and several packet-handling programs were evaluated. As for the evaluation result, the conversion throughput is close to the wire rate, i.e., 10 Gbps, and no packet loss (by cache miss) occurs when the packet size is 256 bytes or larger.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.