bluuebunny/crossref_metadata_2025 huggingface dataset:
Unpaired Remote Sensing Image Dehazing Using Enhanced Skip Attention-Based Generative Adversarial Networks with Rotation Invariance
Authors: Zheng Yitong , Su Jia , Zhang Shun , Tao Mingliang , Wang Ling
Published: July 2024

Remote sensing image dehazing aims to enhance the visibility of hazy images and improve the quality of remote sensing imagery, which is essential for various applications such as object detection and classification. However, the lack of paired data in remote sensing image dehazing enhances the applications of unpaired image-to-image translation methods. Nonetheless, the considerable parameter size of such methods often leads to prolonged training times and substantial resource consumption. In this work, we propose SPRGAN, a novel approach leveraging Enhanced Perlin Noise-Based Generative Adversarial Networks (GANs) with Rotation Invariance to address these challenges. Firstly, we introduce a Spatial-Spectrum Attention (SSA) mechanism with Skip-Attention (SKIPAT) to enhance the model’s ability to interpret and process spectral information in hazy images. Additionally, we have significantly reduced computational overhead to streamline processing. Secondly, our approach combines Perlin Noise Masks in pre-training to simulate real foggy conditions, thereby accelerating convergence and enhancing performance. Then, we introduce a Rotation Loss (RT Loss) to ensure the model’s ability to dehaze images from different angles uniformly, thus enhancing its robustness and adaptability to diverse scenarios. At last, experimental results demonstrate the effectiveness of SPRGAN in remote sensing image dehazing, achieving better performance compared to state-of-the-art methods.
Realizing Small UAV Targets Recognition via Multi-Dimensional Feature Fusion of High-Resolution Radar
Authors: Jiang Wen , Liu Zhen , Wang Yanping , Lin Yun , Li Yang , Bi Fukun
Published: July 2024

For modern radar systems, small unmanned aerial vehicles (UAVs) belong to a typical types of targets with ‘low, slow, and small’ characteristics. In complex combat environments, the functional requirements of radar systems are not only limited to achieving stable detection and tracking performance but also to effectively complete the recognition of small UAV targets. In this paper, a multi-dimensional feature fusion framework for small UAV target recognition utilizing a small-sized and low-cost high-resolution radar is proposed, which can fully extract and combine the geometric structure features and the micro-motion features of small UAV targets. For the performance analysis, the echo data of different small UAV targets was measured and collected with a millimeter-wave radar, and the dataset consists of high-resolution range profiles (HRRP) and micro-Doppler time–frequency spectrograms was constructed for training and testing. The effectiveness of the proposed method was demonstrated by a series of comparison experiments, and the overall accuracy of the proposed method can reach 98.5%, which demonstrates that the proposed multi-dimensional feature fusion method can achieve better recognition performance than that of classical algorithms and higher robustness than that of single features for small UAV targets.
RETRACTED: Temporal-Difference Graph-Based Optimization for High-Quality Reconstruction of MODIS NDVI Data
Authors: Ji Shengtai , Han Shuxin , Hu Jiaxin , Li Yuguang , Han Jing-Cheng
Published: July 2024

The Normalized Difference Vegetation Index (NDVI) is a crucial remote-sensing metric for assessing land surface vegetation greenness, essential for various studies encompassing phenology, ecology, hydrology, etc. However, effective applications of NDVI data are hindered by data noise due to factors such as cloud contamination, posing challenges for accurate observation. In this study, we proposed a novel approach for employing a Temporal-Difference Graph (TDG) method to reconstruct low-quality pixels in NDVI data. Regarding spatio-temporal NDVI data as a time-varying graph signal, the developed method utilized an optimization algorithm to maximize the spatial smoothness of temporal differences while preserving the spatial NDVI pattern. This approach was further evaluated by reconstructing MODIS/Terra Vegetation Indices 16-Day L3 Global 250 m Grid (MOD13Q1) products over Northwest China. Through quantitative comparison with a previous state-of-the-art method, the Savitzky–Golay (SG) filter method, the obtained results demonstrated the superior performance of the TDG method, and highly accurate results were achieved in both the temporal and spatial domains irrespective of noise types (positively-biased, negatively-biased, or linearly-interpolated noise). In addition, the TDG-based optimization approach shows great robustness to noise intensity within spatio-temporal NDVI data, suggesting promising prospects for its application to similar datasets.
SSH-MAC: Service-Aware and Scheduling-Based Media Access Control Protocol in Underwater Acoustic Sensor Network
Authors: Zhao Hongyu , Chen Huifang , Xie Lei
Published: July 2024

In the framework of the space-air-ground-ocean integrated network, the underwater acoustic sensor network (UASN) plays a pivotal role. The design of media access control (MAC) protocols is essential for the UASN to ensure efficient and reliable data transmission. From the perspective of differentiated services in the UASN, a service-aware and scheduling-based hybrid MAC protocol, named the SSH-MAC protocol, is proposed in this paper. In the SSH-MAC protocol, the centralized scheduling strategy is adopted by sensor nodes with environmental monitoring service, and the distributed scheduling strategy is adopted by sensor nodes with target detection service. Considering the time-varying data generation rate of sensor nodes, the sink node will switch the scheduling mode of sensor nodes based on the specific control packet and adjust the resource allocation ratio between centralized scheduling and distributed scheduling. Simulation results show that the performance of the SSH-MAC protocol, in terms of utilization, end-to-end delay, packet delivery ratio, energy consumption, and payload efficiency, is good.
Junction Piezotronic Transistor Arrays Based on Patterned ZnO Nanowires for High-Resolution Tactile and Photo Mapping
Authors: Zhang Li , Zhou Runhui , Ma Wenda , Lu Hui , Mo Yepei , Wang Yi , Bao Rongrong , Pan Caofeng
Published: July 2024

Recently, a great deal of interest has been focused on developing sensors that can measure both pressure and light. However, traditional sensors are difficult to integrate into silicon (Si)-based integrated circuits. Therefore, it is particularly important to design a sensor that operates on a new principle. In this paper, junction piezotronic transistor (JPT) arrays based on zinc oxide (ZnO) nanowire are demonstrated. And the JPT arrays show high spatial resolution pressure and light mapping with 195 dpi. Because ZnO nanowires are arranged vertically above the p-type Si channel’s center of the transistor, the width of the heterojunction depletion region is constricted by the positive piezoelectric potential generated by strained ZnO. In addition, photogenerated charge carriers can be created in the Si channel when JPT is stimulated by light, which increases its electrical conductivity. Consequently, the external pressure and light distribution information can be obtained from the variation in the output current of the device. The prepared JPT arrays can be compatible with Si transistors, which make them highly competitive and make it possible to incorporate both pressure and light sensors into large integrated circuits. This work will contribute to many applications, such as intelligent clothing, human–computer interaction, and electronic skin.
Thin-Film Transistor Digital Microfluidics Circuit Design with Capacitance-Based Droplet Sensing
Authors: Jiang Shengzhe , Li Chang , Du Jiping , Wang Dongping , Ma Hanbin , Yu Jun , Nathan Arokia
Published: July 2024

With the continuous expansion of pixel arrays in digital microfluidics (DMF) chips, precise droplet control has emerged as a critical issue requiring detailed consideration. This paper proposes a novel capacitance-based droplet sensing system for thin-film transistor DMF. The proposed circuit features a distinctive inner and outer dual-pixel electrode structure, integrating droplet driving and sensing functionalities. Discharge occurs exclusively at the inner electrode during droplet sensing, effectively addressing droplet perturbation in existing sensing circuits. The circuit employs a novel fan-shaped structure of thin-film transistors. Simulation results show that it can provide a 48 V pixel voltage and demonstrate a sensing voltage difference of over 10 V between deionized water and silicone oil, illustrating its proficiency in droplet driving and accurate sensing. The stability of threshold voltage drift and temperature was also verified for the circuit. The design is tailored for integration into active matrix electrowetting-on-dielectric (AM-EWOD) chips, offering a novel approach to achieve precise closed-loop control of droplets.
Development of a Two-Dimensional Liquid Chromatography Online Deproteinization Method for Determining Paclitaxel-Related Substances in a Paclitaxel Injection (Albumin-Bound)
Authors: Yao Jing , Zhao Xuejia , Jiang Yifei , Zuo Limin , Qiu Xiaodan , Lian Xiaofang , Liu Huiyi , Jia Qingying , Sun Huimin , Shan Guangzhi
Published: July 2024

To determine the paclitaxel-related substances in a paclitaxel injection (albumin-bound), it is necessary to remove human blood albumin from the sample via solid-phase extraction and subsequently perform high-performance liquid chromatography analysis. The pre-processing operation is complicated, the duration of analysis is long, and much human power and material resources are needed in the sample testing process. Thus, the purpose of this study was to develop a quick two-dimensional liquid chromatography method that requires less consumables and possesses high sensitivity. Samples were directly injected into one-dimensional solid-phase extraction columns to remove human blood albumin. Paclitaxel and its related substances in the solid-phase extraction columns were then eluted into two-dimensional analytical columns through valve switching technology. The sample pretreatment step can be omitted in this method, which allows for the analysis of paclitaxel and its related substances to be completed more quickly, within only 15 min, under the developed two-dimensional elution conditions. The established method had good linearity (R2 = 0.9994), limit of detection (0.25 μg·mL−1), limit of quantification (0.5 μg·mL−1), precision (RSD = 0.5%), and accuracy (102.53–107.97%).
Toxicity to the Male Reproductive System after Exposure to Polystyrene Nanoplastics: A Macrogenomic and Metabolomic Analysis
Authors: Zhang Xue , Wu Yueping , Fu Xufeng , He Shulan , Shi Liping , Xu Haiming , Shi Xiaojuan , Yang Yue , Zhu Yongbin , Wang Yanrong , Qiu Hongyan , Li Hongmei , Li Jiangping
Published: July 2024

Nanoplastics (NPs) cause serious contamination of drinking water and potential damage to human health. This study aimed to investigate the effects of NPs with different particle sizes and concentrations on the reproductive function of male mice. In this study, free drinking water exposure was used to expose male BALB/C mice to PS-NPs (20 nm, 200 nm, and 1000 nm) at 0.1 mg/L, 1 mg/L, and 5 mg/L for 4 months. The male reproductive function of the mice was assessed after NPs exposure, and fecal and blood samples were collected for macrogenomics and metabolomics. The results showed that PS-NPs resulted in mice with reduced testicular organ coefficients, decreased sperm quality, altered testicular tissue structure, disturbed sex hormone levels, and abnormal levels of inflammatory factors and oxidative stress. Furthermore, this study found that NP exposure affected the alteration of gut communities and metabolic pathways related to male reproduction, such as Clostridium and glutathione metabolism. Importantly, we found an effect of NP particle size on reproductive function. In the future, more attention should be paid to the smaller particle sizes of NPs.
Deriving a Continuous Point of Departure for Skin Sensitization Risk Assessment Using a Bayesian Network Model
Authors: Tourneix Fleur , Carron Leopold , Jouffe Lionel , Hoffmann Sebastian , Alépée Nathalie
Published: July 2024

Regulations of cosmetic ingredients and products have been the most advanced in embracing new approach methodologies (NAMs). Consequently, the cosmetic industry has assumed a forerunner role in the development and implementation of animal-free next-generation risk assessment (NGRA) that incorporates defined approaches (DAs) to assess the skin sensitization potency of ingredients. A Bayesian network DA predicting four potency categories (SkinSens-BN) was constructed against reference Local Lymph Node Assay data for a total of 297 substances, achieving a predictive performance similar to that of other DAs. With the aim of optimally informing risk assessment with a continuous point of departure (PoD), a weighted sum of the SkinSens-BN probabilities for four potency classes (non-, weak, moderate, and strong/extreme sensitizer) was calculated, using fixed weights based on associated LLNA EC3-values. The approach was promising, e.g., the derived PoDs for substances classified as non-sensitizers did not overlap with any others and 77% of PoDs were similar or more conservative than LLNA EC3. In addition, the predictions were assigned a level of confidence based on the probabilities to inform the evaluation of uncertainty in an NGRA context. In conclusion, the PoD derivation approach can substantially contribute to reliable skin sensitization NGRAs.
ΛCDM Tensions: Localising Missing Physics through Consistency Checks
Authors: Akarsu Özgür , Ó Colgáin Eoin , Sen Anjan A. , Sheikh-Jabbari M. M.
Published: July 2024

ΛCDM tensions are by definition model-dependent; one sees anomalies through the prism of ΛCDM. Thus, progress towards tension resolution necessitates checking the consistency of the ΛCDM model to localise missing physics either in redshift or scale. Since the universe is dynamical and redshift is a proxy for time, it is imperative to first perform consistency checks involving redshift, then consistency checks involving scale as the next steps to settle the “systematics versus new physics” debate and foster informed model building. We present a review of the hierarchy of assumptions underlying the ΛCDM cosmological model and comment on whether relaxing them can address the tensions. We focus on the lowest lying fruit of identifying missing physics through the identification of redshift-dependent ΛCDM model fitting parameters. We highlight the recent progress made on S8:=σ8Ωm/0.3 tension and elucidate how similar progress can be made on H0 tension. Our discussions indicate that H0 tension, equivalently a redshift-dependent H0, and a redshift-dependent S8 imply a problem with the background ΛCDM cosmology.
Graviton Physics: A Concise Tutorial on the Quantum Field Theory of Gravitons, Graviton Noise, and Gravitational Decoherence
Authors: Hsiang Jen-Tsung , Cho Hing-Tong , Hu Bei-Lok
Published: July 2024

The detection of gravitational waves in 2015 ushered in a new era of gravitational wave (GW) astronomy capable of probing the strong field dynamics of black holes and neutron stars. It has opened up an exciting new window for laboratory and space tests of Einstein’s theory of classical general relativity (GR). In recent years, two interesting proposals have aimed to reveal the quantum nature of perturbative gravity: (1) theoretical predictions on how graviton noise from the early universe, after the vacuum of the gravitational field was strongly squeezed by inflationary expansion; (2) experimental proposals using the quantum entanglement between two masses, each in a superposition (gravitational cat, or gravcat) state. The first proposal focuses on the stochastic properties of quantum fields (QFs), and the second invokes a key concept of quantum information (QI). An equally basic and interesting idea is to ask whether (and how) gravity might be responsible for a quantum system becoming classical in appearance, known as gravitational decoherence. Decoherence due to gravity is of special interest because gravity is universal, meaning, gravitational interaction is present for all massive objects. This is an important issue in macroscopic quantum phenomena (MQP), underlining many proposals in alternative quantum theories (AQTs). To fully appreciate or conduct research in these exciting developments requires a working knowledge of classical GR, QF theory, and QI, plus some familiarity with stochastic processes (SPs), namely, noise in quantum fields and decohering environments. Traditionally a new researcher may be conversant in one or two of these four subjects: GR, QFT, QI, and SP, depending on his/her background. This tutorial attempts to provide the necessary connective tissues between them, helping an engaged reader from any one of these four subjects to leapfrog to the frontier of these interdisciplinary research topics. In the present version, we shall address the three topics listed in the title, excluding gravitational entanglement, because, despite the high attention some recent experimental proposals have received, its nature and implications in relation to quantum gravity still contain many controversial elements.
Computational Optimisation of Urban Design Models: A Systematic Literature Review
Authors: Tay JingZhi , Ortner Frederick Peter , Wortmann Thomas , Aydin Elif Esra
Published: July 2024

The densification of urban spaces globally has contributed to a need for design tools supporting the planning of more sustainable, efficient, and liveable cities. Urban Design Optimisation (UDO) responds to this challenge by providing a means to explore many design solutions for a district, evaluate multiple objectives, and make informed selections from many Pareto-efficient solutions. UDO distinguishes itself from other forms of design optimisation by addressing the challenges of incorporating a wide range of planning goals, managing the complex interactions among various urban datasets, and considering the social–technical aspects of urban planning involving multiple stakeholders. Previous reviews focusing on specific topics within UDO do not sufficiently address these challenges. This PRISMA systematic literature review provides an overview of research on topics related to UDO from 2012 to 2022, with articles analysed across seven descriptive categories. This paper presents a discussion on the state-of-the-art and identified gaps present in each of the seven categories. Finally, this paper argues that additional research to improve the socio-technical understanding and usability of UDO would require: (i) methods of optimisation across multiple models, (ii) interfaces that address a multiplicity of stakeholders, (iii) exploration of frameworks for scenario building and backcasting, and (iv) advancing AI applications for UDO, including generalizable surrogates and user preference learning.
Substantiation of the Monitoring Network of Talik Zones in Urbanized Permafrost Areas Based on GPR Profiling Data (Anadyr, Chukotka)
Authors: Tregubov Oleg D. , Uyagansky Konstantin K.
Published: July 2024

Modern climatic changes have an impact on the bearing capacity of permafrost soils at the base of the foundations of buildings and structures in the urbanized territories of the Arctic and Subarctic. The activation of cryogenic processes leads to the destruction of infrastructure and to social, economic, and environmental consequences for the population. Based on the results for the geothermy of frozen and thawing soil, and on the georadar profiling of the city of Anadyr, it was concluded that the main risks of permafrost degradation are associated with the spread of hydrogenic melting zones. Maps of the soil temperature in imaginary cross-sections with depths of 3, 5, and 10 m were compiled, along with maps of the capacity of thawing soils, the permafrost aquifer, and the dangerous spread zones for exogenous cryogenic processes. The total area of talik zones with a depth of 6 m or more in the urban area was 2.34 km2, or 67% of the built-up area. The system of permafrost monitoring in the territory of Anadyr was substantiated, and is based on monitoring the boundaries of talik zones. It consists of an automated network of observations of the ground temperature in 35 wells at the boundary and in the center of 20 zones of the dangerous development of exogenous cryogenic processes, as well as 12 control GPR profiles at the intersection of linear hydrogenic taliks.
Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies
Authors: Rocha Luiz Gustavo do Nascimento , Guimarães Paul Anderson Souza , Carvalho Maria Gabriela Reis , Ruiz Jeronimo Conceição
Published: July 2024

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program’s strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.
Prognostic Utility of the Flow Cytometry and Clonality Analysis Results for Feline Lymphomas
Authors: Kapoor Sheena , Sen Sushmita , Tsang Josephine , Yap Qi-Jing , Park Stanley , Cromarty Jerry , Swartzfager Deanna , Choy Kevin , Lim Sungwon , Koo Jamin , Holcomb Ilona
Published: July 2024

Feline lymphoma, a prevalent cancer in cats, exhibits varied prognoses influenced by anatomical site and cellular characteristics. In this study, we investigated the utility of flow cytometry and clonality analysis via PCR for antigen receptor rearrangement (PARR) with respect to characterizing the disease and predicting prognosis. For this purpose, we received fine needle aspirates and/or blood from 438 feline patients, which were subjected to flow cytometry analysis and PARR. We used a subset of the results from patients with confirmed B- or T-cell lymphomas for comparison to cytological or histological evaluation (n = 53). Using them as a training set, we identified the optimal set of flow cytometry parameters, namely forward scatter thresholds, for cell size categorization by correlating with cytology-defined sizes. Concordance with cytological sizing among this training set was 82%. Furthermore, 90% concordance was observed when the proposed cell sizing was tested on an independent test set (n = 24), underscoring the reliability of the proposed approach. Additionally, lymphoma subtypes defined by flow cytometry and PARR demonstrated significant survival differences, validating the prognostic utility of these methods. The proposed methodology achieves high concordance with cytological evaluations and provides an additional tool for the characterization and management of feline lymphoproliferative diseases.
Anti-Rollover Trajectory Planning Method for Heavy Vehicles in Human–Machine Cooperative Driving
Authors: Wu Haixiao , Wu Zhongming , Lu Junfeng , Sun Li
Published: July 2024

The existing trajectory planning research mainly considers the safety of the obstacle avoidance process rather than the anti-rollover requirements of heavy vehicles. When there are driving risks such as rollover and collision, how to coordinate the game relationship between the two is the key technical problem to realizing the anti-rollover trajectory planning under the condition of driving risk triggering. Given the above problems, this paper studies the non-cooperative game model construction method of the obstacle avoidance process that integrates the vehicle driving risk in a complex traffic environment. Then it obtains the obstacle avoidance area that satisfies both the collision and rollover profit requirements based on the Nash equilibrium. A Kmeans-SMOTE risk clustering fusion is proposed in this paper, in which more sampling points are supplemented by the SMOTE oversampling method, and then the ideal obstacle avoidance area is obtained through clustering algorithm fusion to determine the optimal feasible area for obstacle avoidance trajectory planning. On this basis, to solve the convergence problems of the existing multi-objective particle swarm optimization algorithm and analyze the influence of weight parameters and the diversity of the optimization process, this paper proposes an anti-rollover trajectory planning method based on the improved cosine variable weight factor MOPSO algorithm. The simulation results show that the trajectory obtained based on the method proposed in this paper can effectively improve the anti-rollover performance of the controlled vehicle while avoiding obstacles.
The Influence of Psychological Factors on Consumer Purchase Intention for Electric Vehicles: Case Study from China: Integrating the Necessary Condition Analysis Methodology from the Perspective of Self-Determination Theory
Authors: Zhao Haipeng , Furuoka Fumitaka , Rasiah Rajah
Published: July 2024

This paper examines the impact of psychological factors on consumer purchase intention for electric vehicles (EVs) through the lens of Self-Determination Theory (SDT). By integrating the three dimensions of autonomy, relatedness, and competence, this study addresses a research gap in consumer innovative consumption, offering a deeper understanding of green transportation. The research reveals that psychological factors significantly influence innovative consumption and the purchase intention of EVs, aligning with the existing literature. In sustainable transportation, psychological factors such as motivation, attitude, and inner activities increasingly drive purchase decisions. This study examines the direct and indirect effects of psychological factors on purchase intention by employing Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). It also considers the moderating role of driving experience in the relationship between psychological factors and innovative consumption. This combined data analysis approach provides a comprehensive understanding of the mechanisms influencing purchase intention, highlighting the intricate interplay between psychological determinants and consumer behavior in the adoption of electric vehicles.
Morphological Modulation of TiO2 Nanotube via Optimal Anodization Condition for Solar Water Oxidation
Authors: Heo Jiwon , Zhu Kai , Ha Jun-Seok , Kang Soon-Hyung
Published: July 2024

With the depletion of fossil fuels and the rising global demand for energy, photoelectrochemical (PEC) water splitting presents a promising solution to avert an energy crisis. Titanium dioxide (TiO2), an n-type semiconductor, has gained popularity as a photoanode due to its remarkable PEC properties. Nevertheless, inherent challenges such as a wide band gap (~3.2 eV), charge recombination, and slow oxygen evolution reaction (OER) rates at the surface limit its practical application by constraining light absorption. To overcome these limitations, we have developed TiO2 nanotubes (NTs) using a facile anodization method. This study examines the impact of anodization growth parameters on solar water oxidation performance. Specifically, TiO2 NTs with modified anodization time (referred to as TiO2-6) showed a 3.5-fold increase in photocurrent density compared to the as-grown TiO2 NTs. Furthermore, electrochemical analyses, such as electrochemical impedance spectroscopy (EIS), indicated a significant decrease in charge transfer resistance following the adjustment of on-off anodization time. Additionally, the TiO2-6 photoanode demonstrated a higher electrochemically active surface area (ECSA) than other samples. Therefore, optimal nanostructuring parameters are crucial for enhancing the PEC properties of TiO2 NTs. Overall, our findings offer valuable insights for fabricating high-quality TiO2 NTs photoanodes, contributing to developing efficient PEC systems for sustainable energy production.
Foreword
Authors: Sharifzadeh Hamid
Published: July 2024

The School of Computing at Unitec was proud to host the CITRENZ 2023 conference in Auckland from 27 to 29 September 2023. CITRENZ 2023 was the 14th annual CITRENZ conference, and the theme was Collective Intelligence: Exploring Mahi Kotahitanga (Collaboration) in Computing. The conference featured three keynote speakers, three panel discussions, two special sessions, five paper presentation sessions and two parallel poster sessions. The 2023 conference was sponsored by SAS analytics Australia, Toi Mai Workforce Development Council, and IT Professionals NZ (ITPNZ). We received 71 submissions for the conference, with 45 submissions accepted after peer review. This included 21 papers and 24 posters. The papers covered a wide range of applied computing topics, such as teaching and learning in the era of generative AI, institutional capacity-building and student success, research reports and more. These proceedings present the full text of 20 accepted papers that were presented at the conference.
Assessment Validity in the Era of Generative AI Tools
Authors: Kabbar Eltahir , Barmada Bashar
Published: July 2024

Generative AI tools, a recent disruptive educational technology, are expected to change how education is delivered and administered. This study proposes a risk identification framework to support educators in identifying assessment integrity risks caused by generative AI tools. The framework also suggests possible actions to mitigate these risks. The proposed framework uses four factors (Assessment Type, AI Knowledge, Course Level, and Bloom’s Taxonomy Cognitive Domain Level) to identify the risks associated with an assessment resulting from the usage of generative AI tools. It is critical to have such a framework to ensure the integrity of assessments while the education industry adapts to the generative AI tools era.
Recommendation of Topics and Practical Labs to Teach the Semantic Web in Current Bachelor of Computing Systems
Authors: Dang Daniel
Published: July 2024

The role of the Semantic Web in Web 3.0, the next evolution of the internet, is significant. Web 3.0 is often referred to as the ‘intelligent web’ or the ‘Semantic Web’. The Semantic Web is an essential topic in Web 3.0 because it enables data integration, enhances data search on the World Wide Web, and promotes the development of knowledge graphs that allow computers to derive new insights and generate knowledge. Teaching the Semantic Web to undergraduate students offers numerous benefits. Students gain a deep understanding of cutting-edge web technologies, technical skills in data integration (the ability to develop systems with diverse datasets and linked data), and capabilities in information retrieval and knowledge management (data modelling and linked data querying). Moreover, they are able to design and develop different types of web-based applications such as intelligent data-driven decision-making apps, AI apps, or personalised-recommendation apps. In this article, we present ways to effectively integrate the Semantic Web as a subject in the current Computing Systems curriculum offering at Eastern Institute of Technology (EIT). We also propose a recommended list of theory topics, practical labs and practical projects that should be designed and developed to teach this paper effectively for undergraduate students.
Using Blended HTML-CSS-JS Semantic to Implement Web Accessibility Principles
Authors: Dang Daniel
Published: July 2024

Web accessibility is the inclusive practice to overcome all barriers that prevent interaction with websites or web apps on the World Wide Web (WWW) by people with physical disabilities (cognitive/auditory/ visual limitation), situational disabilities (small screen, bright sunlight), and socioeconomic restrictions on bandwidth and speed. Tim Berners-Lee, W3 Director and inventor of the WWW, stated that “the power of the Web is in its universality, access by everyone regardless of disability is an essential aspect” (World Wide Web Consortium, n.d.). Web accessibility is a crucial aspect of modern technology and is playing an increasingly critical role in shaping a more equitable and accessible future for all users. Teaching web accessibility as a topic to undergraduate students in the Bachelor of Computing Systems (BCS) at EIT is not only a technical necessity (meeting legal requirements and enhancing user experiences) but also promotes inclusivity and fosters social responsibility. As a result, students are prepared for successful and rewarding careers in the technology industry. However, this also comes with challenges. These challenges may stem from various factors, such as technical complexities, time constraints, resource constraints, and lack of awareness and understanding. This article discusses in more detail some challenges to teaching this topic to undergraduate students. It then suggests how to use HTML/CSS/Javascript semantics to implement four web accessibility principles – perceivable, operable, understandable and robust (POUR).
Predicting Learning Outcomes in an Online Learning Platform
Authors: Bai Ying , Bosu Michael , Abuaiadah Diab
Published: July 2024

This paper carried out a comprehensive analysis of a dataset collected from the Open University’s online learning platform, with the aim of understanding the relationships between various factors and the outcomes for learners. Data pre-processing and analysis showed that factors such as age, gender, different course modules, educational background, IMD band and total clicks positively correlate with learners’ performance. The k-means clustering algorithm was utilised to identify distinct learning behaviours among learners by grouping them into three clusters. The random forest algorithm was then used to build machine learning models based on the identified learning behaviours, achieving a higher prediction accuracy of 86.1%. The findings emphasise the importance of targeted interventions and support tailored to the specific needs of different learner groups. The contribution of this paper is that it is the first to use the k-means clustering algorithm to divide the data into groups prior to using the random forest algorithm to predict the final outcomes for learners at the Open University. Furthermore, this is the first study to apply a random forest algorithm to the Open University’s online learning platform dataset, with commendable results in predicting the outcomes for learners>
Recreating Goto in Python: How and Why
Authors: Cerecke Carl
Published: July 2024

The Python language has no unrestricted goto statement, but because of Python’s deep introspection capabilities, along with its dynamic nature, an unrestricted goto can be added to the language by rewriting a function’s bytecode at runtime. Two primary use cases for goto in Python are discussed: porting existing historic code to Python while maintaining the existing code’s flavour, and implementing state machines. While theoretically unnecessary, goto can make the first case easier, and the second case faster. An implementation is described and performance tests on an example state machine show using goto is a very fast method of implementing state machines in Python, and existing efforts to port historic code are already using the goto implementation.
Produção de combustível através da pirólise catalítica de resíduo urbano de Polipropileno (PP) em reator de leito fixo
Authors: Toledo Hannah Almeida , Sarkis Sávio Raider Matos , Lacerda Caroline Dutra , Duvoisin Junior Sergio , Castro Douglas Alberto Rocha de
Published: July 2024

A preocupação global com a poluição causada por plásticos sólidos tem aumentado nas últimas décadas. Pesquisas recentes realizadas no Brasil indicam que o polipropileno é a resina polimérica mais prevalente na indústria, representando mais de 20% do total. Estratégias sustentáveis têm sido desenvolvidas para promover a transição de uma produção linear para um modelo circular desses materiais. Embora alguns plásticos não sejam adequados para reciclagem por repolimerização, a pirólise surgiu como uma alternativa para transformar a incineração de resíduos em produção de combustível, oferecendo uma forma de gerenciar energia a partir de subprodutos e resíduos. Este estudo identifica e avalia os Produtos Líquidos Orgânicos (OLP) provenientes da pirólise térmica e termocatalítica de resíduos sólidos urbanos de polipropileno pós consumo, utilizando o catalisador Na2CO3 e Na2CO3/Ni. Foi estabelecida uma temperatura final de 500 ºC, com uma taxa de aquecimento controlada de 10 ºC/min. Durante o processo, as temperaturas de fundo (Tfundo) ,topo (Ttopo)  e leito (Tleito) foram monitoradas constantemente, os resultados da densidade de pirólise térmica, termocatalítica com Na2CO3 e termocatalítica com Na2CO3 impregnado no Ni atingiram 0,808 g/ml, 0,815 g /ml e 0,793 g /ml  respectivamente, bem como viscosidade cinemática 118,50,  3,08 e 4,85 cSt, e valores de acidez maiores que 0,5 mg NaOH/g, comparada com combustíveis conhecidos da Agência Nacional do Petróleo e Gás (ANP) e estudos,os dados deste trabalho resultaram em média 1,55, sendo a amostra oriunda da pirólise térmica, a amostra com o maior índice deste parâmetro. A análise dos dados revelou as variações na utilização do reator de leito fixo, assim como o tempo médio de formação de gás, o rendimento do processo, a formação da maior área de hidrocarbonetos similares aos da gasolina foi através dos experimentos provenientes das pirólises termocatalíticas, em média 43,47%, e o experimento de pirólise térmica com uma área de 28,86% de hidrocarbonetos.
“Quem planta engajamento colhe inovação... e produtividade!”: impacto da gestão financeira em MPEs varejistas do programa ALI em Carpina/PE
Authors: Lima Alexsandra Maria Alves de , Moura Guilherme Lima , Gatto Maria Fernanda , Vasconcelos Meiriely Beatriz Souza , Lima Acácia de Oliveira Lucena
Published: July 2024

Este estudo investiga a influência do engajamento dos empresários na gestão financeira e na inovação de micro e pequenas empresas (MPEs) varejistas participantes do Programa ALI em Carpina/PE. A pesquisa utilizou o questionário Radar ALI para analisar oito empresas na Zona da Mata Norte de Pernambuco, com foco na dimensão de controles gerenciais. A análise qualitativa revelou que o engajamento ativo dos gestores é crucial para a implementação eficaz de práticas inovadoras e melhorias na produtividade. Resultados mostram que as empresas mais engajadas apresentaram aumentos significativos em faturamento e produtividade, enquanto aquelas com menor engajamento não alcançaram os mesmos benefícios. O estudo destaca a importância da participação ativa dos empresários para o sucesso de programas de apoio e inovação, sugerindo que um maior engajamento pode levar a melhorias substanciais no desempenho empresarial.
Rendimiento académico en cuarto año de primaria: el caso de España
Authors: Mañan Elena Vernazza , Vicente Alar Urruticoechea , Canal Diana Del Callejo , Vaz Ramón Álvarez , Martínez Margarita Canal
Published: July 2024

El rendimiento académico es el grado de adquisición de conocimientos que tiene un escolar cuando es evaluado. Esta puede realizarse mediante pruebas estandarizadas internacionales, nacionales (EGD) y/o locales. El rendimiento es un constructo complejo que abarca múltiples competencias, la EGD lo mide a través de las competencias: matemática, comunicación lingüística, conocimiento e interacción con el mundo físico, y competencia social-ciudadana. En esta investigación se utilizaron 25295 registros de la EGD, con el objetivo de presentar una categorización del rendimiento académico general. Se realizó un análisis de clases latentes complementado con un HJ-Biplot. Los principales resultados muestran que: 1. Pueden identificarse tres clases que definen el rendimiento académico general; 2. La mayor diferencia por sexo se da en los escolares de rendimiento académico bajo; 3. La mayoría de los escolares cuyo rendimiento académico es alto ha realizado la evaluación en castellano y la mayor proporción de escolares cuyo rendimiento académico es bajo han realizado la evaluación en catalán, valenciano y vasco; 4. El 75% de los escolares que tienen rendimiento académico bajo va a escuelas públicas; 5. Únicamente el 2% de los escolares con rendimiento académico alto es repetidor, frente al 17% de escolares cuyo rendimiento académico es bajo; 6. Cuanto mayor es el rendimiento académico mayor es el nivel socioeconómico y cultural al que pertenece el escolar. Como conclusión se destaca que, al utilizar tres clases para categorizar el rendimiento académico surgen resultados que van en sintonía con investigaciones previas.
ANALISIS PREMI TAHUNAN INDIVIDU DENGAN MANFAAT YANG DIBAYARKAN PADA AKHIR TAHUN KEMATIAN
Authors: Krishna Prafidya Romantica  , Paiz Jalaludin
Published: July 2024

Life insurance is an insurance product that provides guarantees in the form of benefits to the insured's family if the insured dies in the future. The amount of this benefit is influenced by the amount of the annual premium paid by the insurer to the insured. The researcher will calculate the amount of the individual's annual premium on endowment insurance. The researcher will use a fixed interest rate to calculate the discount factor and the Gompertz distribution approach to calculate the insurer's chance of survival. Previously, the researcher will estimate the Gompertz distribution parameters using the Maximum Likelihood Method (MLE) based on the 2011 Indonesian Mortality Table (female). Furthermore, the researcher will calculate the insurer's chance of survival using the Gompertz distribution to obtain the actuarial present value of the initial term annuity and the actuarial present value of the endowment life insurance. In addition, the researcher will calculate the comparison of the present value of the endowment life insurance to the present value of the life annuity. The last step is that the researcher will multiply the comparison of this present value by the benefits received to calculate the amount of the individual's annual premium. The calculation results show that the comparison of the present value of dual-purpose life insurance to the present value of a living annuity is getting smaller as the policy coverage period increases. As a result, the amount of the individual's annual premium will also be smaller. This shows that the amount of the annual premium is influenced by interest rate factors, the insurer's life chances, and the length of the coverage period.
Microsecond-Scale Transient Thermal Sensing Enabled by Flexible Mo
1−x
W
x
S
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Alloys
Authors: Li Weiwei , Kong Lingyan , Xu Manzhang , Gao Jiuwei , Luo Lei , Li Yingzhe , Wang Kexin , Zhou Yilin , Li Lei , Yuan Wei  , Zhang Xiaoshan , Zhao Ruoqing , Chen Mengdi , Yan Yuting , Luo Xiaoguang , Dai Zhaohe , Zheng Lu , Wang Xuewen , Huang Wei
Published: July 2024

Real-time thermal sensing through flexible temperature sensors in extreme environments is critically essential for precisely monitoring chemical reactions, propellant combustions, and metallurgy processes. However, despite their low response speed, most existing thermal sensors and related sensing materials will degrade or even lose their sensing performances at either high or low temperatures. Achieving a microsecond response time over an ultrawide temperature range remains challenging. Here, we design a flexible temperature sensor that employs ultrathin and consecutive Mo

1−
x

W

x

S
2
alloy films constructed via inkjet printing and a thermal annealing strategy. The sensing elements exhibit a broad work range (20 to 823 K on polyimide and 1,073 K on flexible mica) and a record-low response time (about 30 μs). These properties enable the sensors to detect instantaneous temperature variations induced by contact with liquid nitrogen, water droplets, and flames. Furthermore, a thermal sensing array offers the spatial mapping of arbitrary shapes, heat conduction, and cold traces even under bending deformation. This approach paves the way for designing unique sensitive materials and flexible sensors for transient sensing under harsh conditions.
ЧИТАЦЬКА КОМПЕТЕНТНІСТЬ У СУЧАСНОМУ ІНФОРМАЦІЙНОМУ СУСПІЛЬСТВІ ЯК ЧИННИК ФОРМУВАННЯ МАЙБУТНІХ ЛІДЕРІВ
Authors: Ткач П. Б.
Published: July 2024

У дослідженні визначено поняття «читацька грамотність» у контексті міжнародного дослідження PISA. Зазначено результати дослідження щодо читацької грамотності українського учнівства, отриманні в межах досліджень 2018 та 2022 років. Окреслено чинники, що визначають оцінювання читацької компетентності, зокрема наявність завдань, що стосуються множинних динамічних текстів різного типу, а також контекстів (сценаріїв). Запропоновано один зі шляхів розв’язання проблеми формування читацької компетентності – інтегроване навчання, для реалізації якого створені модельні програми «Інтегрований мовно-літературний курс (українська мова, українська та зарубіжні літератури)» для 5–6 та 7–9 класів.