bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of Students' Skills in Describing Physics Problems: The Effect of STEM-Project-Based Learning
Authors: Nehru Nehru , Kurniawan Wawan , Riantoni Cicyn
Published: December 2023

The difficulty students face in describing problems from posed physics-related questions is an indicator that is rarely studied. This research explores students' abilities in describing electrical circuit problems based on implementing STEM-Project Based Learning (STEM-PBL). This study employed a mixed-methods approach with an explanatory model. The subjects were 35 undergraduate Physics Education students at the University of Jambi enrolled in the Electromagnetism course. Data collection was carried out through tests and interviews. The test instrument used five reasoned multiple-choice questions, while the interview instrument used open-ended questions based on the problems identified from the test results. The study's findings revealed an effect size of 2.1 (medium category) and an N-Gain of 0.5 (medium category). Thus, STEM-PBL influences students' ability to describe problems. Future research should investigate the influence of other variables, such as educational background and learning motivation, on the effectiveness of STEM-PBL in developing students' problem-description skills further.
Measuring Faculty Engagement in Online Formative or Whole-Person Education
Authors: Wortham Stanton , Borowiec Katrina , Kim Deoksoon
Published: December 2023

The COVID-19 pandemic reinforced the importance of supporting students’ comprehensive well-being when teaching online. One promising approach is formative or whole-person education, which emphasizes wholeness, purpose, and community. We created a scale using a
polytomous Item Response Theory modeling approach, measuring the extent to which postsecondary teachers engage in formative education online. To our knowledge, this is the first scale designed to measure this construct. The scale was developed within an exploratory sequential mixed methods study on formative education online that also included semi-structured interviews with 37 faculty members. Results from the qualitative analysis were used to develop initial items. This data-informed process increased the construct validity of the scale. We refined the original item pool through a pilot test using a sample of 308 instructors. This article presents psychometric results for the final, 10-item scale using a sample of 245 instructors. Evaluation of item fit statistics, item trace lines, and the total information curve indicate that the graded response model was appropriate for this scale. The Cronbach’s alpha and marginal reliability coefficients for the final scale were .90 and .91, indicating good reliability. Future research can explore how this scale might be adapted for in-person learning environments and other contexts.
Deep Learning Models for Analyzing Social Construction of Knowledge Online
Authors: Gunawardena Charlotte N. , Chen Yan , Flor Nick , Sanchez Damien
Published: December 2023

Gunawardena et al.’s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a large dataset, this study explores how two neural network architectures—a feed-forward network (Doc2Vec) and a large language model transformer (BERT)—could automatically predict phases of knowledge construction using IAM. The methods interrogated the extent to which the artificial neural networks’ predictions of IAM Phases approximated a human coder’s qualitative analysis. Key results indicate an accuracy of 21.55% for Doc2Vec phases I-V, 43% for fine-tuning a pre-trained large language model (LLM), and 52.79% for prompt-engineering an LLM. Future studies for improving accuracy should consider either training the models with larger datasets or focusing on the design of prompts to improve classification accuracy. Grounded on social constructivism and IAM, this study has implications for designing and supporting online collaborative learning where the goal is social construction of knowledge. Moreover, it has teaching implications for guiding the design of AI tools that provide beneficial feedback for both students and course designers.
Hydrodynamic parameters calculation of viscoplastic oils in the tasks of thermal filling
Authors: Akhmedov Suleiman Abduragimovich , Akhmedova Zukhra Khalipaevna
Published: December 2023

With the discovery of heavy oil deposits, great attention has been paid to the development of oil fields using thermal methods of influencing oil formations. Theoretical studies of reservoir hydrodynamics, as well as temperature fields in multilayer formations, were stimulated with the advent of modern computers and personal computers. Thanks to the mathematical description, hydrodynamic calculations of the displacement of viscoplastic oil by water with abnormal properties became possible. In the case of displacement of high-viscosity and paraffinic oils by cold water in multi-layer formations, paraffin deposition and blockage of weakly permeable formations occur, as a result of the advanced displacement of oil through layers with high permeability. The results of the conducted research show that the creation of a hot water delay at different stages of the development of deposits of high-viscosity paraffin oil improves the development rate, increases the oil recovery coefficient.
El Servicio de Hidrografía Naval: Historia y Desafíos
Authors: Sanz Rodríguez Valentín Alejandro
Published: December 2023

El Servicio de Hidrografía Naval, creado en 1879, es una de las más antiguas instituciones que desarrollan tareas científicas en el país. Su misión es realizar los estudios, trabajos, exploraciones e investigaciones conducentes a promover el máximo de seguridad a la navegación e impulsar la producción de conocimiento científico en virtualmente todas las disciplinas de las ciencias del mar. En este trabajo se presenta un recorrido histórico de su trayectoria, las tareas y proyectos que lleva adelante actualmente y los desafíos futuros que se propone encarar.
A case study – The occurrence of pests in stands of newly introduced energy crops in large-scale pilot experiments in conditions of Central Europe
Authors: Tóth Štefan , Tancik Ján , Šoltysová Božena , Porvaz Pavol
Published: December 2023

The objective of this paper is to document the occurrence of pests recorded in a large-scale pilot field experiment, where a unique set of newly-introduced herbaceous energy crops was tested under conditions of eastern Slovakia. The set consisted of Elymus elongatus, Secale cereanum, Silphium perfoliatum, Galega orientalis, Sida hermaphrodita, Panicum virgatum, Amaranthus spp., Panicum miliaceum, Sorghum sudanense, and Sorghum bicolor. A total of 14 cultivars were tested on 4 sites during 4 crop years (2016 – 2020). At least 17 species of pests were recorded in total, as some of the species may represent the identity of the couple or several relative ones, which was rare only as usually a fower common species. The occurred pests list consists of Anisoplia lata Erichson, Agriotes lineatus L., Capreolus capreolus L., Deroceras agreste L., Oulema gallaeciana Heyden, Lepisma saccharinum L., Lepus europaeus Pallas, Meloe proscarabaeus L., Metcalfa pruinosa Say, Microtus arvalis Pallas, Philaenus spumarius L., Psylliodes chrysocephala L., Rhopalosiphum padi L., stemborers as any insect larva or arthropod boring into plant stem, Sus scrofa L., Aleyrodes proletella L., Tettigonia viridissima L., and Trialeurodes vaporariorum Westwood. Overall, the occurrence of pests was regular and scattered, and damages caused by them were negligible usually, but a total destruction of the crop stand even cultivar-specific was recorded too. Most of the meaningful pests are primarily field hunting animals and only secondarily commonly occurring insect species, which for further observations are desirable in order to capture the tendency of important pests’ overpopulation, confirming respectively. Although even rare finding of the single caterpillar of Xylena exsoleta exsoleta L. was recorded in a buffer zone, within the experiment no newly introduced pest species was recorded.
Confusion and Countermeasures of College Students’ Career Guidance Work Based on Deep Learning Models
Authors: Ji Liya
Published: December 2023

In this paper, we identify teaching signals and employment factors by designing a college student employment guidance work model. The deep learning model is used to identify the given feature vectors, find the word sequence with the highest probability among them, generate the probability of the corresponding acoustic feature vectors, and model the college students’ employment guidance work model to model and calculate them. The teaching signal feature distribution is used to create the description, and the output probability is adjusted to it. The number of college graduates in 2020 will be 6.3 million, an increase of 190,000 compared to last year, and the initial employment rate is 91.07%. The deep learning model can effectively identify college students’ employment confusion, propose effective countermeasures and improve the employment rate.
Study on the Role of Big Data Technology in Promoting the Transformation of Financial Accounting in the Digital Economy Era
Authors: Zhao Jinjiang
Published: December 2023

This paper examines big data technology through the use of big data clustering algorithms and examines the factors that influence the transformation of financial accounting in the digital economy. Separate the clustering center to rectify it, finish accurate clustering of the original data set, and normalize the data. The data center point results are output after dividing the data set, and the final clustering results of the data set are obtained according to the similarity coefficient through the continuous iterative execution process. The results show that the comprehensive scores after the transformation of financial accounting have all risen sharply, and the score of the work content indicator in financial risk avoidance has risen from 4 points before the transformation to 9.5 points. It shows that big data technology can effectively promote the transformation of financial accounting in the digital economy era.
Analyzing the Integration Interpretation of Civics and Family Poetry Culture in University Language Programs Based on Deep Learning Models
Authors: Cai Liping
Published: December 2023

In this paper, firstly, we start from the imagery in the poem, excavate the resources of the ideology and politics in the university language poetry, and put forward the feasible path of the integration of the ideology and politics of the university language course and the poetry culture of the family training. The research on poetry culture in university language is conducted using a deep learning model. Based on the deep learning model, keywords in the poetry text are extracted and extended, taking into account the issue of word splitting and lexical annotation. The sequence coding of word vectors is needed so as to construct a poetry generation model based on RNNPG, and then the research and analysis on the concept of ideology and politics of the poetry culture in the university language are carried out. The results show that in terms of model performance, the RNNPG model is 1.17 overall, and the overall generation effect is more ideal compared to other single discriminator generation models. The acceptance level of sophomores is generally above 0.29, which is better than that of freshmen, and the teaching of ancient poems under the perspective of “curriculum politics” is especially necessary to improve their cultural taste and aesthetic interest. This study is conducive to the personalized development of students and the formation of correct concepts.
Interdisciplinary Talent Cultivation Model for Theatre Performance Based on Big Data Analysis
Authors: Zhang Cong
Published: December 2023

The first part of this paper examines the issues of interprofessional talent cultivation for theatrical performances and develops a model of interprofessional talent cultivation for theatrical performances based on the competency model. Secondly, to evaluate the effectiveness of the talent cultivation model, a quality evaluation index system is constructed. Then, the index weights are calculated by using the ordinal relationship analysis method in big data analysis, and the object element topology law is introduced to comprehensively evaluate the quality of talent cultivation. Finally, an empirical analysis was conducted to verify the effectiveness of the talent cultivation model and the evaluation system. The results show that the quality of professional teaching has the greatest influence on the cultivation of interdisciplinary talents in theatrical performance, with a weight of 0.3508, and the comprehensive correlation can effectively realize the ranking of the cultivation level of professional talents in theatrical performance. This shows that big data analysis in theater performance inter-specialty talent cultivation can provide effective data support for the development of university disciplines and help universities innovate and reform the theater performance specialty.
The Path of Integrating Curriculum Civics into Advertising Design Teaching in Higher Vocational Colleges and Universities Based on Big Data Analysis
Authors: Tao Yinghong
Published: December 2023

In order to cultivate advertising design applied talents, this paper firstly combs through the status quo of the current teaching system of advertising design and designs the model of advertising design teaching system under the concept of curriculum ideology and political education. Secondly, on the basis of the classical division clustering algorithm, by adding a fuzzy set, fuzzy clustering and fuzzy center of mass and explaining the importance of distance, a weighted fuzzy clustering teaching quality evaluation model based on big data analysis is designed. In the end, the teaching model was employed to evaluate the clustering of teaching quality by accumulating educational data. The percentage of excellent teaching quality in the clustering results is about 0.35, the smallest average percentage is failing and average, which are 0.12 and 0.11, respectively, and the highest average weight is the teacher’s professional knowledge and the student’s learning achievement, which are 0.12 and 0.125, respectively.
An Exploration of the Practical Path of Internet Civic Education in Student Management in Colleges and Universities Based on K-means Clustering
Authors: Sun Hong
Published: December 2023

This paper first analyzes the path of network ideological education to boost student management and constructs a student management platform that integrates network ideological education using big data technology. Secondly, K-means clustering analysis is used to mine students’ campus behaviors, and the DPC algorithm combined with the improved AdaBoost algorithm is used to detect students’ academic anomalies so as to help schools better realize student management. Finally, performance testing and application analysis were conducted to verify the effectiveness of the student management platform that integrates online ideological education. The results show that when the number of concurrent users is 5000, the CPU occupancy rate and response time of this platform are 10.34% and 0.52 s. It is able to analyze and detect abnormalities in students’ campus behaviors and academic situations and encourage universities to analyze students’ situations through visual reports. This shows that the student management platform integrating network ideological education in the era of big data can promote the level of student management in colleges and universities.
Innovation and Practice of Educational Management Path Building in Colleges and Universities in the Context of Big Data
Authors: Zhai Hong
Published: December 2023

In this paper, a digital education management information system (e-MIS) is constructed based on big data, which realizes the comprehensive processing of education administration and school management data. Through the fuzzy comprehensive evaluation model, the e-MIS system was evaluated and optimized. Then, the e-MIS system was practically applied to the fields of teaching effectiveness evaluation, teachers’ work assessment, scholarship evaluation and dormitory management. Finally, the significant impact of the e-MIS system on the enhancement aspects of new student enrollment education was empirically verified. The results show that the average score of freshmen’s school rules and discipline education is 4.35, learning culture education is 4.53, mental health education is 4.41, and life guidance education is 4.31, all of which are in the middle-upper level, as calculated by the e-EMIS evaluation model. This paper is a positive exploration of improving the efficiency of student education and management in local colleges and universities and promoting the overall development of students.
The Influence of Traditional Opera Culture on the Development of Ethnic Vocal Music Art under Deep Learning Modeling
Authors: Hou Juncai
Published: December 2023

In this paper, according to the characteristics and development trend of traditional opera, based on the deep learning model, we use a convolutional neural network to extract the opera features, combined with an SVM classifier to construct a CNN-SVM classification model. For the two classification algorithm models of logistic regression and deep confidence network, combined with two types of feature parameters of timbre and melody, six groups of experiments are designed to extract the time-frequency features of traditional opera. The CNN-SVM classification model is used to categorize the emotion of traditional opera, which aims to divide the musical features by multi-feature selection. Analyze the timbre feature parameter MFCC to investigate the impact of traditional opera timbre on ethnic vocal singing. For the logistic regression model, the coefficient of MFCCs is 0.5588, and the classification accuracy is only 0.5301 when the feature parameters are selected as melodic features, i.e., gene frequency, resonance peak, and band energy, and 0.6228 when the feature parameters are selected as a combination of timbral and melodic features. The diversity of the traditional opera timbres contributes to the development of ethnic vocal art with the trend of inclusiveness.
Construction of a vocal singing style repository based on a deep learning model
Authors: Kang Shaohua
Published: December 2023

In this paper, we first use the short-time Fourier transform method to extract statistical features in the frequency domain of vocal music. The extracted features are fused using D − S -evidence theory. The fused vocal features are inputted into the improved deep learning network to construct a vocal singing style classification model. Secondly, the requirements of vocal music resources according to the classification of song styles are constructed for the vocal singing resource library system. Finally, the vocal music resource library system undergoes testing in all directions to ensure it meets both functional and performance requirements. The results show that under the respective optimal threads of the vocal music resource library, the number of DM7 network reads and writes remains between 200 and 300 kb, and the random read performance of HBase reaches 8340 TPS, indicating that the resource library provides users with a fast and convenient way to retrieve multidimensional resources. This paper provides a long-term reference for the preservation and use of vocal singing resources.
Innovative Development of College Students’ Civic Education Based on Multiple Data Chain Networks
Authors: Liu Qilin , Zhang Ye
Published: December 2023

This paper logically explores the overall form of ideological and political education system construction in colleges and universities, constructs the logical rationale of system cognition and development, and explores the operation process of system dynamic balance. The ideological and political education system is constructed through the comprehensive planning of multiple data chains, and the demand for teaching tasks and communication delays is solved through optimized planning. Maximizing the utilization of teaching resources is achieved by optimizing the deployment of teaching resources. Finally, the Civics teaching mode of multi-data chain integrated planning was evaluated and tested through experiments. The results show that the three dimensions of the pre-test of the experimental group are 4.29, 4.21 and 4.41, respectively, which are improved to 5.60, 5.83 and 4.99, with a significant improvement effect. This paper effectively explores the development of Civics teaching, realizes all-round education, and achieves the fundamental purpose of cultivating morality.
Research on the Integration Path of College Vocal Music Teaching and Traditional Music Culture Based on Deep Learning
Authors: Wang Jing
Published: December 2023

In this paper, we first start from extracting music features and analyze the extraction methods for time-domain, frequency-domain, and cepstrum-domain features of music. Next, the logistic regression model is used to recognize music and deal with two-class and multi-class classification problems. To extract music and text features, a CNN-SVM-based classification model is proposed using a deep learning teaching practice structure. Finally, feature selection experiments are carried out on the extracted raw feature set using various feature selection algorithms to optimize the feature set and reduce classifier computation. The results show that the average number of feature items selected using the improved correlation coefficient method is 64, and the number of feature items is mostly distributed between 58 and 72. The data verifies that the improved correlation coefficient method proposed can effectively extract the features of traditional music, improve the accuracy of traditional music classification, and thus promote the development of the fusion of traditional music culture and vocal music teaching in colleges and universities.
Predicting scoring trends in basketball games based on multivariate time series analysis
Authors: Zheng Lei , Ma Liang , Jia Zhiqiang
Published: December 2023

In this paper, we first study the evaluation framework of Granger causality between time series. Then, the multivariate time series prediction model is constructed based on transfer entropy and graph attention network. The multivariate time series prediction model architecture has causal branches with transfer entropy, and the prediction module is executed using graph attention network. Finally, the accuracy of basketball game score prediction is analyzed, as well as comparing the accuracy of the multivariate time series prediction model with other models. The number of offensive rounds in basketball games can be predicted with a high accuracy of 67.94% using the multivariate time series prediction model. For the prediction of the scoring trend of player rotation, the ABHJI combination rotating on the court is the most efficient in scoring, and the average value of scoring is as high as 85.463. The average accuracy of the TSP reaches 72.2%, and the model has high feasibility and is suitable for scoring prediction in basketball games.
Modern Clothing Design and Clothing Culture Communication Strategy Based on the Classical Network Model
Authors: He Liudan
Published: December 2023

At present, with the strengthening of China’s economic and cultural strength, “Chinese culture” is widely sought after. Therefore, incorporating cultural elements into clothing design can promote the spread of Chinese clothing culture. This paper proposes a classical network model based on the Internet’s background. A modal communication model of the culturalization process is built on this basis to combine the Internet and the network model. The survey and analysis of the effects of clothing culture on comfort and aesthetics of clothing design are being conducted. Consumers have a positive and active attitude towards clothing culture, with 3625 out of 7563 sample comments supporting the communication of clothing culture in the communication effect. The comfort of clothing is a top priority for 139 people when it comes to clothing design. Therefore, the aspect of comfort should be emphasized in clothing design, and the dissemination of clothing culture should be strengthened at the same time.
A Study on the Psychological State of Ideal View of College Students based on Multivariate Data Analysis
Authors: Wang Changhe
Published: December 2023

The construction of an ideal view is crucial for the personal growth of college students. The way they perceive the dialectical relationship between individuals and society and how they strive to realize the value of life is determined by it. This study focuses on college students as the survey subject and designs a questionnaire around their ideal beliefs. Analyzing the current pattern of ideal belief construction among college students is the goal. The current reality, factors that influence the construction of ideal views, and existing problems are analyzed in detail using statistical data from the questionnaire. It also proposes feasible methods to encourage the creation of ideal views among college students. Optimizing college education content, cultivating a creative spirit, and reforming family education are some of the strategies that are included in these strategies.
Research on new energy grid-connected load monitoring method based on the network analysis method
Authors: Wang Qing , Li Guimin , Chen Zhiru , Jing Zhen
Published: December 2023

The steady-state characteristic parameters of the loads are used to identify new energy grid-connected loads using an event-based network analysis method in this paper. The analysis of interdependence among elements is done by studying the element layer and special structure of the network analysis method. Using the principle of limit relative ranking vector calculation, the supermatrix and weighting matrix of the ANP element layer are constructed, and the basic steps of ANP model weights are determined. The ANP-based load monitoring algorithm is evaluated by combining the load identification accuracy with the F-value. The results show that event detection algorithms are generally more than 70% accurate. 17 out of 18 times of identifying load events of computers can be correctly identified with an accuracy rate of 89.37%, 9 out of 10 times of identifying fluorescent lamps with an accuracy rate of 89.98%, and 14 out of 15 times of identifying microwave ovens with an accuracy rate of 92.75%. The new energy grid-connected load can also be detected by combining the harmonic content rate. The harmonic content rates when the desktop computer was turned on were 93.04%, 86.67%, 60.16%, 61.76%, and 23.46%, respectively. This study helps to improve the accuracy of new energy grid-connected load monitoring.
ReliefF-RF model application in communication security risk detection of distribution network
Authors: Zhang Jing , Ma Yong , Lu Yu , Wang Jun
Published: December 2023

The construction of an intelligent power grid system has promoted innovation and development in the power grid industry, but the distribution network covers a wide range and has more access data, and the network attack risk is the focus of attention. In this regard, the stochastic forest model is introduced to build the distribution network risk detection model based on the software-defined network. The first is to study the power grid system based on a software-defined network, realize the analysis and extraction of the characteristics of abnormal power grid engineering data, and realize the diagnosis of risk data through a random forest model. At the same time, considering the long modeling time of the random forest model and the low classification accuracy in unbalanced samples, the feature selection model is introduced to optimize the random forest model, and the sampling weight function is set to improve the insufficient sampling accuracy of random forest model in small samples. The model classification effect is evaluated during the model performance test. The proposed model is the most accurate of the three data sets. In the three data classification tests of Satimage, Senbased, and Cleveland, the accuracy of MICRO Average is respectively 0.886, 0.986 and 0.856. At the same time, the proposed model is superior to other models in terms of training time and variance stability test. When the data set is 18000, the model accuracy is 0.968, which is better than the other two models. The research content has important reference value for maintaining communication security and improving system stability in distribution networks.
Distributed Power Grid Connected Panoramic Perception Technology Based on Digital Twin Model
Authors: Li Guimin , Wang Qing , Chen Zhiru , Jing Zhen , Zhang Zhi
Published: December 2023

To address the issue that large-scale distributed Proton-exchange membrane fuel cell grid-connected operation status is difficult to effectively monitor, this study carried out clustering screening of Proton-exchange membrane fuel cell grid connected status variables. The digital twin model of the Proton-exchange membrane fuel cell group grid connection is established by using key important variables, and the digital model accurately reflects the real-time operation status of the Proton-exchange membrane fuel cell. Then, it predicts the operation status of the Proton-exchange membrane fuel cell. The experiment showcases that the optimal accuracy of fuzzy C-means clustering algorithm, K-means clustering algorithm and fuzzy C-means clustering algorithm in view of the objective function for clustering screening of grid-connected state quantity of Proton-exchange membrane fuel cell is 0.74, 0.65 and 0.59 respectively; The optimal recall rates are 0.84, 0.76, and 0.68, respectively; The optimal F-measure values are 0.78, 0.70, and 0.64, respectively. Among the three clustering analysis algorithms, the fuzzy C-means clustering algorithm, in view of the objective function, has the shortest running time and the least memory consumption. The monitoring results are basically consistent with the actual situation, indicating that this design method can complete the task of monitoring the operating status of distributed power grid-connected equipment. This study’s proposed method is more accurate than conventional methods and is better suited for monitoring the grid connection status of distributed power systems.
The Relationship between Structural Upgrading and Economic Growth of Sports Industry Based on AD-AS Modeling
Authors: Wang Baixiang
Published: December 2023

This paper determines the structural upgrading measurement indexes of the sports industry by analyzing the metrics from three perspectives: industrial structure advancement, rationalization, and coordination. With reference to the AD-AS model in economics, it introduces the positive exchange factor to improve the comprehensive supply model, utilizes the pressure factor and the negative exchange factor to improve the comprehensive supply-demand model, and obtains the improved SAD-SAS model. Based on the equilibrium relationship between aggregate supply and aggregate demand, five hypotheses regarding influence are proposed. The results show that the output growth rate fluctuation coefficient of the sports industry is 0.25-0.45, and the time, robust, and spatial elasticity economic growth volume shows a stable incremental curve with the incremental increase of time, which illustrates that the structural upgrading of the sports industry and the economic growth is a positive effect significant relationship.
Mixed-use and Street Network Attributes of Vibrant Urban Settings
Authors: Kashef Mohamad
Published: December 2023

This study examines two crucial interlinked physical planning and design aspects with potential impact on pedestrian flow in urban settings. Mixed land uses and gridded/interconnected streets are invariably characterised in the urban design literature as the essence of vibrant cities and lively street environments. The study develops a critical approach that investigates some of the most popular algorithms utilised in assessing mixed-use characteristics and their impact on pedestrian movement. “Entropy,” “LUM,” and “dissimilarity” indices are critically evaluated in terms of their reliability in predicting pedestrian travel patterns. The study also examines street network measurement indices and spatial analysis tools that enhance urban vitality and aid in the design and development of active street environments. It bridges the gap between disparate approaches aiming at understanding and prescribing the built environment attributes that enhance urban vitality. The theoretical quest of this study provides a robust foundation for future case study research on the built environment.
Transitioning to Decentralized Renewable Energy in Latvia: A Comprehensive Payback Analysis
Authors: Gicevskis K. , Linkevics O. , Karlsons K.
Published: December 2023

It is believed that the transition to renewable decentralized energy supply solutions (e.g., solar panels, storage of electricity in batteries) will help promote the decarbonization of the energy system. At the same time, it is expected to happen only when society is convinced of the environmental benefits and when there are enough economic incentives for it. This study analyses the economic feasibility of transitioning to decentralized renewable energy solutions, including solar panels and electricity storage, in Latvia. Our research explores potential savings of these solutions under various scenarios based on different factors, such as national NETO billing system, financial support scheme, electricity pricing, distribution network tariffs, energy storage options, as well as the impact of the battery energy storage system (BESS) discharging strategy. The results show that the potential savings can vary depending on these factors that are changing over time. Nevertheless, the rise in small-scale power generation at households shows that there is an increasingly rapid transition from centralized electricity supply to a decentralized supply system, which might indicate that society supports energy transition.
Selective Patterned Growth of ZnO Nanoneedle Arrays
Authors: Mihailova I. , Krasovska M. , Sledevskis E. , Gerbreders V. , Mizers V. , Bulanovs A. , Ogurcovs A.
Published: December 2023

Nanostructured coatings are widely used to improve the sensitivity of various types of sensors by increasing the active surface area compared to smooth films. However, for certain applications (in some cases), it may be necessary to achieve selectivity in the coating process to ensure that nanostructures only form in specific areas leaving interelectrode spaces free of nanostructures. This article discusses several methods for creating intricate ZnO nanostructured patterns, including area selective application of Zn acetate seeds followed by hydrothermal growth, selective thermal decomposition of zinc acetate via laser irradiation followed by hydrothermal growth, and the electrochemical deposition method. These methods enable ZnO nanostructures to grow onto designated surface areas with customised, patterned shapes, and they are rapid, cost-effective, and environmentally benign.

The article examines the process of producing a nanostructured coating with a complex shape and discusses several factors that can impact the quality of the final product. These include the influence of the thermocapillary flows and the “coffee stain” effect on the deposition of a seed layer of zinc oxide from an ethanol solution of zinc acetate. Additionally, the study found that using a protective screen during the growth of nanostructures can reduce the occurrence of unintended parasitic structures in areas lacking a seed layer. Overall, the article presents various techniques and strategies to improve the quality of nanostructured coatings.

We have proven that the use of laser radiation to create a seed layer does not impact the final morphology of the resulting nanostructures. However, when combined with computer-controlled technology, this approach allows for the creation of intricate patterns made up of micrometre-sized lines which cannot be achieved by using other methods.

The article also demonstrates an electrochemical technique for obtaining zinc oxide nano-structures that can selectively coat metal electrodes without requiring a seed layer.
Non-Enzymatic Co3O4 Nanostructure-Based Electrochemical Sensor for H2O2 Detection
Authors: Mizers V. , Gerbreders V. , Krasovska M. , Sledevskis E. , Mihailova I. , Ogurcovs A. , Bulanovs A. , Gerbreders A.
Published: December 2023

This article describes the synthesis of nanostructured cobalt oxide on iron wires and its application for the detection of hydrogen peroxide as working electrode for non-enzymatic electrochemical sensor. Cobalt oxide was obtained by the hydrothermal synthesis method using chloride and acetate anions. The resulting nanostructured coating obtained from the chloride precursor is a uniform homogeneous porous network of long nanofibers assembled into regular honeyсomb-like formations. In the case of an acetate precursor, instead of nanofibers, petal-like nanostructures assembled into honeycomb agglomerates are observed. The structure, surface, and composition of the obtained samples were studied using field-emission scanning electron microscopy along with energy-dispersive spectroscopy and X-ray diffractometry.

The resultant nanostructured specimens were utilized to detect H2O2 electrochemically through cyclic voltammetry, differential pulse voltammetry, and i-t measurements. A comparative research has demonstrated that the nanostructures produced from the chloride precursor exhibit greater sensitivity to H2O2 and have a more appropriate morphology for designing a nanostructured sensor. A substantial linear correlation between the peak current and H2O2 concentration within the 20 to 1300 μM range was established. The Co3O4 electrode obtained exhibits a sensitivity of 505.11 μA·mM−1, and the electroactive surface area is calculated to be 4.684 cm2. Assuming a signal-to-noise ratio of 3, the calculated limit of detection is 1.05 μM. According to the interference study, the prevalent interfering agents, such as ascorbic acid, uric acid, NaCl, and glucose, do not influence the electrochemical reaction. The obtained results confirm that this sensor is suitable for working with complex analytes.The actual sample assessment demonstrated a recovery rate exceeding 95 %.
Gas Distribution System of Latvia and its Transitional Challenges
Authors: Jansons L. , Bode I. , Koposovs A. , Zeltins N. , Lapuke S.
Published: December 2023

The future of the European Union’s (EU) gas sector and gas distribution systems in particular is under review as a necessity to move away from conventional natural gas is strictly outlined in its strategical energy framework. The main questions of future gas sector layout are largely related to gas decarbonization paths – whether they will include simultaneous transportation, distribution and storage of methane-based and non-methane based renewable gases or not. In general, this question is left for different Member States to decide, because as alternatives to it there are two options – decommissioning of all gas distribution and partially gas transportation and storage systems on the one hand and total replacement of existing gas transportation system with brand new hydrogen transportation and distribution system on the other. The first option leaves only liquified renewable gases (including, hydrogen) that are transported via truck and the second – pipeline transportation and distribution only for hydrogen, limiting methane-based renewable gases to road transportation solutions only.

The Latvian gas distribution system is also facing imminent transformation in foreseeable future; thus, at the moment its sustainability priority is the maintenance of the existing system in a safe and secure manner by improving it in accordance with technical necessities and immediate customer requests. The current research shows two sides of gas distribution system priorities in Latvia – its maintenance and development trends prior to fundamental transformations of gaseous fuel transition and general transitional challenges laying ahead.
Investigation of additive manufactured micro-lattice structures for defence applications
Authors: Shaik Ameer Malik , Reddy Bobbili Veera Siva , Sastry C. Chandrasekhara , Krishnaiah J. , Ramakrishna B.
Published: December 2023

This study investigates the blast mitigation capabilities of A286 steel micro-lattice structures produced through additive manufacturing. The research explores the effects of different manufacturing conditions, such as stress relief and heat treatment, on the mechanical properties and blast resistance of honeycomb and gyroid lattice structures in correlation with armour steel structures. Comprehensive evaluations, including surface morphology, corrosion resistance, and compressive residual stress analysis, reveal notable findings for micro-lattice structures. Micro-lattice structures demonstrated 57.23% higher corrosion resistance compared to conventional materials, presently available in the form of rolled homogeneous armour, medium hardness armour, and high-nitrogen steel. Additionally, honeycomb lattice structures exhibit compressive residual stresses of up to 581.90 MPa, providing significant advantages in blast mitigation potential. These results underscore the significance of lattice geometry, material microstructure, and residual stress in enhancing blast resistance. The research offers valuable insights into optimizing additive manufactured structures as an alternative modular solution for defence applications.
Carbon Pricing in Finland: Balancing policy goals
Authors: Paukku Eelis
Published: December 2023

This study discusses the role and development of carbon pricing via taxation by using Finland as a case example of several issues with carbon taxation. Carbon taxation and carbon pricing face some major problems, mainly competitiveness and social issues. Although Finland was one of the first countries to adopt carbon-based energy taxation, these problems shaped the tax system in a way that could even be described as “avoiding carbon pricing”. This study provides new insights on how to develop carbon taxation and how to overcome major problems related to commonly known problems with carbon pricing.
Dosimetric comparison of postoperative interstitial high-dose-rate brachytherapy and modern external beam radiotherapy modalities in tongue and floor of the mouth tumours in terms of doses to critical organs
Authors: Ferenczi Örs , Major Tibor , Fröhlich Georgina , Béla Dalma , Tódor Szabolcs , Polgár Csaba , Akiyama Hironori , Bukovszky Botond , Takácsi-Nagy Zoltán
Published: December 2023

Background

The aim of the study was to dosimetrically compare interstitial high-dose-rate (HDR) brachytherapy (BT) and modern external beam radiotherapy modalities, as volumetric modulated arc therapy (VMAT) and stereotactic radiotherapy with Cyberknife (CK) of tumours of the tongue and floor of the mouth in terms of dose to the critical organs.

Patients and methods

In National Institute of Oncology, Budapest, between March 2013 and August 2022 twenty patients (11 male/9 female) with stage T1–3N0M0 tongue (n = 14) and floor of mouth (n = 6) tumours received postoperative radiotherapy because of close/positive surgical margin and/or lymphovascular and/or perineural invasion. High-dose-rate interstitial brachytherapy applying flexible plastic catheters with a total dose of 15 × 3 Gy was used for treatment. In addition to BT plans VMAT and stereotactic CK plans were also made in all cases, using the same fractionation scheme and dose prescription. As for the organs at risk, the doses to the mandible, the ipsilateral and the contralateral salivary glands were compared.

Results

The mean volume of the planning target volume (PTV) was 12.5 cm3, 26.5 cm3 and 17.5 cm3 in BT, VMAT and CK techniques, respectively, due to different safety margin protocols. The dose to the mandible was the most favourable with BT, as for the salivary glands (parotid and submandibular) the CK technique resulted in the lowest dose. The highest dose to the critical organs was observed with the VMAT technique. The mean values of D2cm3 and D0.1cm3 for the critical organs were as follows for BT, VMAT and CK plans: 47.4% and 73.9%, 92.2% and 101.8%, 68.4% and 92.3% for the mandible, 4.8% and 6.7%, 7.3% and 13.8%, 2.3% and 5.1% for the ipsilateral parotid gland, 3.5% and 4.9%, 6.8% and 10.9%, 1.5% and 3.3% for the contralateral parotid gland, 7.3% and 9.4%, 9.0% and 14.3%, 3.6% and 5.6% for the contralateral submandibular gland.

Conclusions

The present results confirm that BT, despite being an invasive technique, is dosimetrically clearly beneficial in the treatment of oral cavity tumours and is a modality worth considering when applying radiotherapy, not only as definitive treatment, but also postoperatively. The use of the CK in the head and neck region requires further investigation.
Phase angle as a prognostic indicator of surgical outcomes in patients with gastrointestinal cancer
Authors: Gulin Jana , Ipavic Ester , Mastnak Denis Mlakar , Brecelj Erik , Edhemovic Ibrahim , Kozjek Nada Rotovnik
Published: December 2023

Background

In patients with gastrointestinal cancer with planned elective surgery, malnutrition increases the risk of adverse outcomes in the postoperative period. The phase angle, measured by the bioelectrical impedance analysis is an indicator of the metabolic and functional status of the patient. It may be an important prognostic indicator for the clinical outcome of post-surgical treatment in patients with gastrointestinal cancer.

Patients and methods

In this prospective study, 70 patients with gastrointestinal cancer had their phase angles measured by the bioelectrical impedance analysis before the surgery. During the first month after the surgery, we documented the postoperative complications from the patient's records and classified them according to the Clavien Dindo classification of surgical complications. The time of hospitalization was also recorded. The data was statistically analysed in SPSS.

Results

We found a statistically significant difference (p = 0.036) in the average value of phase angles between the group of patients who had postoperative complications (phase angle 5.09°) and the group without postoperative complications (5.64°). We noted a correlating trend of decreasing phase angle values and increasing hospitalization time (Pe R = −0,40, p = 0,001). The phase angle cut-off value (5.5°) was calculated using the ROC curve method, predicting a higher risk of the postoperative complications (p = 0,037) in patients with lower phase angle.

Conclusions

Lower phase angle values before surgery were associated with more complications during the first month after surgery and longer hospitalization time. We found that a phase angle below than 5.5° could serve as a marker that predicts a greater risk of postoperative complications.
On the Impact of Climate Change Policies on the Clean Technology Innovation: Evidence from Patent Data Analysis
Authors: Balcilar Mehmet , Agan Busra
Published: December 2023

This study investigates the role of environmental policies and regulations in mitigating climate change by promoting clean innovations and discouraging dirty ones. Utilizing nonparametric copula and quantile estimation techniques, along with carefully constructed innovation variables based on patents from 2000 to 2021 across 34 countries, the research examines the effects of policy interventions and external events on energy-related innovations. Findings reveal that climate policy interventions effectively promote clean innovation, particularly at higher levels, and discourage dirty innovations. Therefore, climate change policies and regulations are crucial in achieving net-zero carbon emission targets.