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Nowadays, academic research relies not only on sharing with the academic community the scientific results obtained by research groups while studying certain phenomena but also on sharing computer codes developed within the community. In the field of atomistic modeling, these were software packages for classical atomistic modeling, and later for quantum-mechanical modeling; currently, with the fast growth of the field of machine-learning potentials, the packages implement such potentials. In this paper, we present the MLIP-3 package for constructing moment tensor potentials and performing their active training. This package builds on the MLIP-2 package [Novikov et al., "The MLIP package: moment tensor potentials with MPI and active learning," Mach. Learn.: Sci. Technol., 2(2), 025002 (2020)], however, with a number of improvements, including active learning on atomic neighborhoods of a possibly large atomistic simulation. [ABSTRACT FROM AUTHOR]

Background: With the development of computational literacy, there has been a surge in both research and practice application of text‐based and block‐based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major programming modalities, especially in the context of secondary education settings. Objectives: To further compare programming effects between and within text‐based and block‐based modalities, this research conducted a quasi‐experimental research in China's secondary school. Methods: An online programming platform, Code4all, was developed to allow learners to program in text‐based and block‐based modalities. This research collected multimodal data sources, including programming platform data, process data, and performance data. This research further utilized multiple learning analytics approaches (i.e., clustering analysis, click stream analysis, lag‐sequential analysis and statistics) to compare learners' programming features, behavioural patterns and knowledge gains under two modalities. Results and Conclusions: The results indicated that learners in text‐based modality tended to write longer lines of code, encountered more syntactical errors, and took longer to attempt debugging. In contrast, learners in block‐based modality spent more time operating blocks and attempt debugging, achieving better programming knowledge performances compared to their counterparts. Further analysis of five clusters from the two modalities revealed discrepancies in programming behavioural patterns. Implications: Three major pedagogical implications were proposed based on empirical research results. Furthermore, this research contributed to the learning analytics literature by integrating process‐oriented and summative analysis to reveal learners' programming learning quality. Lay Description: What is currently known about the subject matter: Programming has the potential to improve learners' higher‐order thinking skills.Block‐based and text‐based modalities are two major instructional methods.There has been a growing interest to understand how learning occurs in two modes.Most previous work has evaluated two modalities based on learners' knowledge, skills, and attitudes. What this paper adds: Code4all allows learners to programming in text‐based and block‐based modalities.Quasi‐experimental research was conducted to examine block‐based and text‐based programming modalities.Multimodal learning analytics were used to compare programming under two modalities.Learners' programming features, behaviouralbehavioral patterns, and knowledge gains were identified under two modalities. The implications of study findings for practitioners: Instructors should integrate text‐based and block‐based modalities into programming courses.Process‐oriented assessment should be integrated with summative assessment. Adaptive, timely scaffoldings should be provided with the external support (this should be marked like above two points). [ABSTRACT FROM AUTHOR]

This paper considers how a curricular design that integrated computer programming and creative movement shaped students' engagement with computing. We draw on data from a camp for middle schoolers, focusing on an activity in which students used the programming environment NetLogo to re-represent their physical choreography. We analyze the extent to which students noticed incompatibilities (mismatches between possibilities in dance and NetLogo), and how encountering them shaped their coding. Our findings suggest that as students attended to incompatibilities, they experienced struggle, but persisted and engaged in iterative cycles of design. Our work suggests that tensions between arts and programming may promote student engagement. [ABSTRACT FROM AUTHOR]

The corrosion problem of the tank floor of the oil depot tank area becomes more and more serious with the extension of the operation time. At present, how to determine the potential distribution of the storage tank floor and how to judge the cathodic protection effect of the storage tank floor is the bottleneck of technological development. In this paper, by constructing a mathematical model of cathodic protection in the tank area, influence of deep well anode on potential distribution of tank bottom is calculated by boundary element method (BEM) with computer programming, to study the potential distribution of the tank floor under different anode parameters. The results show that the calculated results are in good agreement with the field measured results, which verifies the accuracy and reliability of the calculation. [ABSTRACT FROM AUTHOR]

We present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao‐Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in predicting condensate and precipitation amounts and maintains low global‐average bias (≤4%) for 1 year of continuous simulation when replacing the Fortran scheme. The stability and success of this emulator stems from key design decisions. By separating the emulation of condensation and precipitation processes, we can better enforce physical priors such as mass conservation and locality of condensation, and the vertical dependence of precipitation falling downward, using specific network architectures. An activity classifier for condensation imitates the discrete‐continuous nature of the Fortran microphysics outputs (i.e., tendencies are identically zero where the scheme is inactive, and condensate is zero where clouds are fully evaporated). A temperature‐scaled conditional loss function ensures accurate condensate adjustments for a high dynamic range of cloud types (e.g., cold, low‐condensate cirrus clouds or warm, condensate‐rich clouds). Despite excellent overall performance, the emulator exhibits some deficiencies in the uppermost model levels, leading to biases in the stratosphere. The emulator also has short episodic skill dropouts in isolated grid columns and is computationally slower than the original Fortran scheme. Nonetheless, our challenges and strategies should be applicable to the emulation of other microphysical schemes. More broadly, our work demonstrates that with suitable physically motivated architectural choices, ML techniques can accurately emulate complex human‐designed parameterizations of fast physical processes central to weather and climate models. Plain Language Summary: In this study, we create computer code that uses machine learning to mimic a weather model's algorithm for handling how clouds form and rain falls. When used in the weather model to replace this algorithm, our machine learning code is highly accurate in simulations for a whole year. We achieve this by making smart code design choices. We split the code into two parts: one for cloud formation and one for rain and snow. This allows us to better build important aspects of these processes into the machine learning approach. For instance, clouds form where it is moist and evaporate when it gets dry, and rain and snow fall downward. Our code learns cloud behavior based on temperature to ensure it works both for cold, thin clouds high up in the sky and warm, thick clouds closer to the ground. Our work shows a path for suitably designed machine learning code to eventually replace important parts of weather and climate models, but also that this path still requires careful human design respecting known physical principles. Key Points: We build an emulator to replace the Zhao‐Carr Fortran microphysics scheme in FV3GFSThe integrated emulator sustains high skill throughout a 1‐year simulationTailoring the ML architecture to the structure of the underlying scheme greatly improves the online behavior of the emulator [ABSTRACT FROM AUTHOR]

The purpose of this article is to present grassroots concepts and ideas about "the algorithm" in the religious context. The power and causality of algorithms are based on lines of computer code, making a society influenced by "black boxes" or "enigmatic technologies" (as they are incomprehensible to most people). On the other hand, the power of algorithms lies in the meanings that we attribute to them. The extent of the power, agency, and control that algorithms have over us depends on how much power, agency, and control we are willing to give to algorithms and artificial intelligence, which involves building the idea of their omnipotence. The key question is about the meanings and the ideas about algorithms that are circulating in society. This paper is focused on the analysis of "vernacular/folk" theories on algorithms, reconstructed based on posts made by the users of Polish Catholic forums. The qualitative analysis of online discourse makes it possible to point out several themes, i.e., according to the linguistic concept, "algorithm" is the source domain used in explanations of religious issues (God as the creator of the algorithm, the soul as the algorithm); algorithms and the effects of their work are combined with the individualization and personalization of religion; algorithms are perceived as ideological machines. [ABSTRACT FROM AUTHOR]

Summary: Software complexity is the very essence of computer programming. As the complexity increases, the potential risks and defects of software systems will increase. This makes the software correctness analysis and the software quality improvement more difficult. In this paper, we present a quantitative metric to describe the complexity of a hierarchical software and a Complexity‐oriented Software Architecture Refactoring (CoSSR) approach to reduce the complexity. The main idea is to identify and then reassemble subcomponents into one hierarchical component, which achieves minimum complexity in terms of the solution algorithm. Moreover, our algorithm can be improved by introducing partition constraint, heuristic search strategy, and spectral clustering. We implement the proposed method as an automated refactoring tool and demonstrate our algorithm through a case study of battery management system (BMS). The results show that our approach is more efficient and effective to reduce the complexity of hierarchical software system. [ABSTRACT FROM AUTHOR]

This present paper is inspired by one of the questions posed by Okeke (Results Math 78(96):1-30, 2023, see Remark 2.10b). In particular, we aim to develop a robust computer code based on the theoretical results obtained in Okeke (2023), which determines the polynomial solutions of the following functional equation, 0.1 ∑ i = 1 n γ i F (a i x + b i y) = ∑ j = 1 m (α j x + β j y) f (c j x + d j y) , for all x , y ∈ R , γ i , α j , β j ∈ R , and a i , b i , c j , d j ∈ Q , and their special forms. The primary motivation for writing such a computer code is that solving even simple equations belonging to class (0.1) needs long and tiresome calculations. Therefore, one of the advantages of such a computer code is that it allows us to solve complicated problems quickly, easily, and efficiently. Additionally, the computer code will significantly improve the level of accuracy in calculations. Along with that, there is also the factor of speed. We point out that the computer code will operate with symbolic calculations provided by the programming language Python, which means that it does not contain any numerical or approximate methods, and it yields the exact solutions of the equations considered. [ABSTRACT FROM AUTHOR]

The road between a hypothesis about a disease or condition and its cure or palliation is never simply linear. There are many tantalizing tangents to be chased and many seemingly obvious truths with countless exceptions; this is usually a feature, not a bug, as they say in computer programming. In the tangents and exceptions are clues and alternative roads to science and medicine that can provide cures and palliative measures, sometimes for diseases or conditions other than the one being studied. The narrative that follows uses the author's scientific experience in childhood nervous system cancer to illustrate the importance of a robust, bidirectional interaction between the laboratory bench and the clinic bedside in the quest for solutions to problems of health, longevity, and quality of life. [ABSTRACT FROM AUTHOR]

Background/Aims: Traditional manual methods of extracting anesthetic and physiological data from the electronic health record rely upon visual transcription by a human analyst that can be labor‐intensive and prone to error. Technical complexity, relative inexperience in computer coding, and decreased access to data warehouses can deter investigators from obtaining valuable electronic health record data for research studies, especially in under‐resourced settings. We therefore aimed to develop, pilot, and demonstrate the effectiveness and utility of a pragmatic data extraction methodology. Methods: Expired sevoflurane concentration data from the electronic health record transcribed by eye was compared to an intermediate preprocessing method in which the entire anesthetic flowsheet narrative report was selected, copy‐pasted, and processed using only Microsoft Word and Excel software to generate a comma‐delimited (.csv) file. A step‐by‐step presentation of this method is presented. Concordance rates, Pearson correlation coefficients, and scatterplots with lines of best fit were used to compare the two methods of data extraction. Results: A total of 1132 datapoints across eight subjects were analyzed, accounting for 18.9 h of anesthesia time. There was a high concordance rate of data extracted using the two methods (median concordance rate 100% range [96%, 100%]). The median time required to complete manual data extraction was significantly longer compared to the time required using the intermediate method (240 IQR [199, 482.5] seconds vs 92.5 IQR [69, 99] seconds, p =.01) and was linearly associated with the number of datapoints (rmanual =.97, p <.0001), whereas time required to complete data extraction using the intermediate approach was independent of the number of datapoints (rintermediate = −.02, p =.99). Conclusions: We describe a pragmatic data extraction methodology that does not require additional software or coding skills intended to enhance the ease, speed, and accuracy of data collection that could assist in clinician investigator‐initiated research and quality/process improvement projects. [ABSTRACT FROM AUTHOR]

Analog computing is often considered to be an outdated technology only to be found and cared for in museums but not as the basis of modern cutting edge computing. Nothing could be further from reality. Together with quantum computers, analog computers complement today's stored program digital computers, acting as co-processors for certain types of computationally intensive tasks. They are highly energy efficient and exhibit a degree of parallelism that by far surpasses classic digital computers. In contrast to quantum computers, analog computers do not require exotic technologies, no intricate cooling systems, no elaborate shielding systems, etc. In addition to this there already exists a plethora of proven programs for analog computers to solve a wide variety of problems. This paper describes the necessity of analog computing for the twenty-first century, gives a short introduction to the structure and programming of analog computers, before discussing future application areas. Analog computing will drastically alter the way we think about computing in the years to come as it will become an integral part of every high performance computer. It will be an indispensable technology for future AI systems, it will revolutionize many medical applications, it might even replace or at least complement, certain types of quantum computers, etc. [ABSTRACT FROM AUTHOR]

Learning in the computer laboratory is an important component when students learn computer programming. In this article, we analyse empirical data on novice students working in pairs in the laboratory. Using an approach inspired by phenomenography and variation theory, we specifically focus on how students' learning of theory and their learning of practice interact. We found that theory-oriented and practice-oriented actions play different, but complimentary and closely intertwined roles in students' learning. In particular, we discuss that students' frequent switches between practice-oriented and theory-oriented actions create a variation that is helpful for learning. This variation adds to the variation the teacher creates. Finally, we discuss how and why frequent switches are important for the successful learning process and we suggest a couple of ways to make it more likely that students make such switches when working with assignments at the computer. [ABSTRACT FROM AUTHOR]

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub. Author summary: Bioengineering holds fantastic perspectives and is poised to change how we produce foods, materials, and medicines. However, rapid progress is limited by a lack of mechanistic knowledge in even the simplest model organisms, such as bacteria and yeast. Thus, to compensate, we often have to construct and study a large number of engineered cells and select the cells with the greatest potential for the given objective function. The targeted construction of engineered cells is often described as an iterative process of design, build, test, and learn (the DBTL cycle). Literate programming is a paradigm that encourages the combination of text and computer code with the potential to describe all workflows covered by the DBTL cycle. The purpose of the present work is to give a first estimate of the extent to which we can accelerate the individual steps in the DBTL cycle by using end-to-end literate programming workflows. To achieve this, we established an open-source platform called teemi, and used it to optimize production of a key precursor to medicinal alkaloids in yeast. We expect that teemi will enable higher DBTL throughput with fewer errors, better integration of IT tools with laboratory resources, and more effective knowledge capture. [ABSTRACT FROM AUTHOR]

As computer programming becomes more central to the workforce, the need for better models of how it is effectively learned has become more apparent. The current study addressed this gap by recording electrophysiological brain responses as 62 Python programmers with varying skill levels read lines of code with manipulations of form (syntax) and meaning (semantics). At the group level, results showed that manipulations of form resulted in P600 effects, with syntactically invalid code generating more positive deflections in the 500–800 ms range than syntactically valid code. Meaning manipulations resulted in N400 effects, with semantically implausible code generating more negative deflections in the 300–500 ms range than semantically plausible code. Greater Python expertise within the group was associated with greater sensitivity to violations in form. These results support the notion that skilled programming, like skilled natural language learning, is associated with the incorporation of rule-based knowledge into online comprehension processes. Conversely, programmers at all skill levels showed neural sensitivity to meaning manipulations, suggesting that reliance on pre-existing semantic relationships facilitates code comprehension across skill levels. [ABSTRACT FROM AUTHOR]

The key to decoding a coded video in such a manner that the decoded video is as clear as possible is to remove noise contained in the original video, which also improves coding efficiency. Many researchers studying imaging have investigated this noiseremoval problem; as a result, it is now said that random noise can be reduced to the limit at which only shot noise, a type of noise resulting from the random arrival of photons, remains. Although noise is generally an undesirable phenomenon, research that exploits it to achieve various effects is attracting attention. Seishi Takamura, visiting senior distinguished researcher at NTT Computer and Data Science Laboratories, developed a technology that uses fluctuations (noise) in the brightness of light to estimate brightness beyond the upper limit of digital values. We asked him about this technology and his stance as a researcher: "question everything," "don't be content," "never say no," and "let it lie". [ABSTRACT FROM AUTHOR]

The emergence of online teaching has brought new opportunities to computer coding education. In this paper, we examine how the move online is generating a new kind of dynamic within computer programming classes on an online EdTech platform in South Korea. As the platform seeks to solve some old problems within large-scale programming classes, such as machine dependency and labor-intensive operation, its online classes face unique challenges arising from temporal and spatial separation. The new environment requires that class participants coordinate their actions and relationships with other members, which means technical adjustments and human adaptations. Instructors, students, and managers form a distinctive three-party relationship as they respond to the tricky problems of online teaching, such as the time delay between audio and video transmission. The automation of evaluation labor by the platform also influences the human relationship as well as educational efficiency. Our study suggests that the most challenging task in online EdTech experiments would not be to move classes online completely, but to rearrange roles, identities, and relationships within the class. [ABSTRACT FROM AUTHOR]

This paper presents a new method of reducing the inrush current and improving the starting performance of a line-start permanent-magnet synchronous motor (LSPMSM). The novelty of the proposed method relies on the selection of the time instant of the connection of the stator winding to the grid, for which the smallest values of the amplitudes of inrush currents are obtained. To confirm the effectiveness of the developed method of limiting the inrush current, simulations and experimental studies were carried out. The algorithm and dedicated computer code developed by the authors for the analysis of transient coupled phenomena in the LSPMSM were used to study the impact of the time instant of connection of the winding to the grid on the motor start-up process. The algorithm was based on a field model of coupled electromagnetic and thermal phenomena in the studied motor. To verify the developed model of the phenomena and the proposed method, experimental research was carried out on a purpose-built computerised test stand. Good concordance between the results of the experiments and simulations confirmed the high reliability of the proposed model, as well as the effectiveness of the developed approach in limiting the inrush current and improving the starting performance of LSPMSMs. [ABSTRACT FROM AUTHOR]

In this manuscript, we describe a coding club we created and implemented during the COVID-19 pandemic. We were purposeful in creating the club to: (a) focus on design and problem solving as the basis for learning computer coding and (b) include elements to improve the engagement of girls. We ran multiple iterations of a Girls Design with Code Club that involved over 100 girls from 22 countries. We reviewed various sources of data to evaluate how our design and implementation of the coding clubs impacted the girls who participated. In an effort to share our learnings with other researchers and program providers, we share evidence of choices that we believe had positive impacts and others that we can improve in future iterations. [ABSTRACT FROM AUTHOR]

Alan Turing's "Computing Machinery and Intelligence," published in 1950, is one of the founding texts in the field of artificial intelligence (AI), although the term was not coined until 1958, 4 years after his death. From the treatment of human intelligence as computational and the brain as mechanical to the comparison of animals to machines to the disregard for the materiality of computers to programming as a stand-in for procreation to fiction-inspired science, many of the core tenets that have shaped the field of AI have their origins in Turing's paper. A close analysis of the paper exposes some of the problematic logic underlying these tenets that are now proving damaging for both society and the planet. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present an easier and more efficient method for the determination of the geometry of a bevelled gear tooth. Based on a method that provides an easier way for the rack generation of involute helical gears, the mathematical model of a beveloid gear is studied. The mathematical procedure for developing two-dimensional cross-sections has been extended to three-dimensional gear models. A computer programme is developed to obtain generating and generated surfaces. The proposed algorithm is compared with the previous studies for verification and validation. The results demonstrate that the coordinates obtained from the given method are nearly the same on the start and end points of the main gear parts, such as the involute and root fillets regions. Also, between the limits, the values can be considered acceptable. A coordinate deviation of the gear profile has been observed in the mathematical model, because of the profile shift. Modifications have been developed in the equations to eliminate these cases. The main advantage of the proposed method is to obtain mathematical models without carrying out some of the calculation steps used in previous studies. Eventually, this feature will provide an easier and faster method to develop computer-aided models of the beveloid gear types. [ABSTRACT FROM AUTHOR]

This article describes the standardization trends in the International Organization for Standardization/International Electrotechnical Commission Joint Technical Committee 1 (ISO/IEC JTC 1)/Subcommittee 29 (SC 29), and International Telecommunication Union - Telecommunication Standardization Sector (ITU-T) Study Group 16 (SG16) as well as ISO/IEC JTC 1/SC 27 and ITU-T SG17. Both SC 29 and SG16 deal with multimedia coding and transmission and are shaping the future of entertainment and business communication. Both SC 27 and SG17 work on standardization related to information security and communication security and are helping to strengthen the reliability and privacy protection of the rapidly evolving digital society. [ABSTRACT FROM AUTHOR]

Likelihood-free methods are an essential tool for performing inference for implicit models which can be simulated from, but for which the corresponding likelihood is intractable. However, common likelihood-free methods do not scale well to a large number of model parameters. A promising approach to high-dimensional likelihood-free inference involves estimating low-dimensional marginal posteriors by conditioning only on summary statistics believed to be informative for the low-dimensional component, and then combining the low-dimensional approximations in some way. In this article, we demonstrate that such low-dimensional approximations can be surprisingly poor in practice for seemingly intuitive summary statistic choices. We describe an idealized low-dimensional summary statistic that is, in principle, suitable for marginal estimation. However, a direct approximation of the idealized choice is difficult in practice. We thus suggest an alternative approach to marginal estimation which is easier to implement and automate. Given an initial choice of low-dimensional summary statistic that might only be informative about a marginal posterior location, the new method improves performance by first crudely localizing the posterior approximation using all the summary statistics to ensure global identifiability, followed by a second step that hones in on an accurate low-dimensional approximation using the low-dimensional summary statistic. We show that the posterior this approach targets can be represented as a logarithmic pool of posterior distributions based on the low-dimensional and full summary statistics, respectively. The good performance of our method is illustrated in low to moderate dimensional examples. Computer code to implement the methods for the examples of this article is available at . [ABSTRACT FROM AUTHOR]

The increasing prevalence of exploratory factor analysis (EFA) applications in scholarly literature reflects its popularity and the convenience of computer‐assisted analysis. With advancements in computer hardware and software, the complexity and variations of EFA analysis have also grown. Despite the availability of sophisticated computer programming, the appropriate utilization of EFA necessitates users to make informed judgments. Additionally, users are responsible for searching and identifying suitable statistical software to accommodate their data and analysis requirements. This review aims to enhance understanding of the EFA technique and summarize the analysis options available for EFA in R packages. A total of 50 packages were examined in this study. Specifically, the review focuses on (1) diagnostic functions, (2) factor extraction, (3) factor retention, (4) factor rotation, and (5) complex data and technique features provided by these packages. The review summarizes the available function options in R packages by outlining these five crucial steps in conducting an EFA analysis. This synthesis offers an overview of the similarities and distinctive features of each package, serving as a valuable resource for users in selecting a suitable EFA technique. It is important to note that there is no definitive approach to conducting an exploratory factor analysis. Users need to deliberately select and combine appropriate techniques to achieve optimal results. This article is categorized under:Statistical and Graphical Methods of Data Analysis > Dimension ReductionSoftware for Computational Statistics > Software/Statistical Software [ABSTRACT FROM AUTHOR]

The inverse degree index, also called inverse index, first attracted attention through numerous conjectures generated by the computer programme Graffiti. Since then its relationship with other graph invariants has been studied by several authors. In this paper we obtain new inequalities involving the inverse degree index, and we characterize graphs which are extremal with respect to them. In particular, we obtain several inequalities relating the inverse degree index with the first and second Zagreb indices, the general first and second Zagreb indices, the Forgotten index, the general sum-connectivity index, the Sombor index and the misbalance indeg index, and several parameters of the molecular graph as the number of vertices, the number of edges, the minimum degree and the maximum degree. Also, we compute the inverse degree index for some classes of chemical graphs. Furthermore, some applications are given to the study of the physicochemical properties of three classes of compounds: polyaromatic hydrocarbons, polychlorobiphenyls, and octane isomers. [ABSTRACT FROM AUTHOR]

In this paper, several research topics are presented that provide productive avenues of exploration for students in an undergraduate cryptography course. The topics are intended for a variety of skill levels and interests. In some cases, a student might be inspired to try to solve the proposed problem or write computer code. Other topics might motivate them to learn new mathematics or algorithms, or research a historical event or person. In all cases, a short description of the topic is given along with several references that can be used as a starting point for student research. The author also describes some challenges and recommendations when teaching a course where a project is a main component. [ABSTRACT FROM AUTHOR]

In this paper, a novel methodology is presented for the construction of ab initio effective rotation–vibration spectroscopic models from potential energy and dipole moment surfaces. Non-empirical effective Hamiltonians are obtained via the block-diagonalization of selected variationally computed eigenvector matrices. For the first time, the derivation of an effective dipole moment is carried out in a systematic way. This general approach can be implemented quite easily in most of the variational computer codes and turns out to be a clear alternative to the rather involved Van Vleck perturbation method. Symmetry is exploited at all stages to translate first-principles calculations into a set of spectroscopic parameters to be further refined on experiment. We demonstrate on H2CO, PH3, CH4, C2H4, and SF6 that the proposed effective model can provide crucial information to spectroscopists within a very short time compared to empirical spectroscopic models. This approach brings a new insight into high-resolution spectrum analysis of polyatomic molecules and will be also of great help in the modeling of hot atmospheres where completeness is important. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the effects of the integration of goal-based scenario (GBS) approach into a block-based coding instruction. Scratch platform was used to find out the effects of GBSs on programming skills of students, who did not have any programming experience. GBSs were used during practice and the development in students' weekly products was examined. This study was designed on the basis of mixed methodology. The quasi-experimental part includes experimental and control groups. The groups received the same lecture by the same lecturer, but in the laboratory sessions the practicing approach was designed separately. The experimental group received GBS integrated tasks. The scenario flow of each week occurred through an existing character. The students completed 10 products during one semester. The scores of students' weekly products, observation notes of the researchers, pre and post-test scores, and interview data were analyzed and used in a complimentary manner. The analyses showed that GBS integration significantly affected the knowledge and skill improvement in block-based programming. The knowncontributions of block-based tools were also observed, but the realistic nature of GBSs contributed the programming instruction in the affective dimension. They served as tools for motivation, scaffolding, and monitoring. [ABSTRACT FROM AUTHOR]

Part-fill and part-cut subgrade is widely distributed in mountainous highway engineering, and their resilient modulus and settlement exhibit significant transversal non-uniformity, which has an important effect on the performance of cement concrete pavement structure. A numerical model, focusing on a two-slab system on part-fill and part-cut subgrade, was developed by the finite element computer programme taking into account non-uniform settlement (a large range of partial contact) simultaneously with non-uniform modulus. Cement concrete pavement structure responses, including the load stress, vertical displacement and joint load transfer capacity were comprehensively investigated considering the two part-fill and part-cut subgrade characteristics. The results indicate that the non-uniform settlement has a higher impact on the concrete pavement structure than that of the non-uniform modulus in more cases. When the resilient modulus of the fill part is close to that of the cut part, the additional stress (relative stress increment) caused by the combination of the two factors is approximately the sum of the additional stress caused by the two factors individually. [ABSTRACT FROM AUTHOR]

In-service teachers' professional development regarding technology adoption in education is often focused on only one specific technology. To maximize the utilization of technologies, teachers need to be able to leverage different technologies seamlessly. Technological Pedagogical Content Knowledge (TPACK) is one of the most important frameworks depicting teachers' competences for effectively teaching with technology. The TPACK Support-Stimulate-Seek model (3S-TPACK) was used to design training programs with learning activities using robots, IoT-based sensors, actuators, tablets, and computer programming tools. The results show that the training programs designed by adapting the 3S-TPACK model not only can improve the teachers' learning outcomes but also can support positive attitudes toward adopting robots and IoT technologies in the teaching and learning process. [ABSTRACT FROM AUTHOR]