bluuebunny/crossref_metadata_2025 huggingface dataset:
An Ante Hoc Enhancement Method for Image-Based Complex Financial Table Extraction
Authors: Peng Weiyu , Li Xuhui
Published: January 2025

In the field of finance, the table is a common form of data organization. Extracting data from these tables in large quantities is a fundamental and important task for researchers. However, this can be a challenging task, as many tables exist in unstructured forms, such as scanned images in PDFs, rather than forms which can be easily processed, such as Excel spreadsheets. In recent years, a large number of table extraction methods utilizing heuristic algorithms or deep learning models have been proposed to free people from manual processing tasks, which are time-consuming and troublesome. Although existing methods achieve high levels of accuracy in processing some kinds of tables, they often fail to achieve optimal results when extracting complex financial tables with multi-line text and missing demarcation lines. In this article, we propose an enhancement method for image-based complex table extraction. This method consists of two modules: a split module and a filter module. The split module uses an OCR (optical character recognition) model to locate text regions, and a heuristic algorithm to obtain candidate demarcation lines. The filter module is based on a text semantic matching model and another heuristic algorithm. The experimental results show that the use of the proposed method can significantly improve the performance of different table extraction methods, with increases in F1 scores of between 5.10 and 14.36 points being recorded.
Cropland Suitability Prediction Method Based on Biophysical Variables from Copernicus Data and Machine Learning
Authors: Radočaj Dorijan , Gašparović Mateo , Jurišić Mladen
Published: January 2025

The goal of this study was to propose and validate a method for predicting cropland suitability based on biophysical variables and machine learning according to an FAO land suitability standard using soybean (Glycine max L.) as a representative crop, aiming to provide an alternative to geographic information system (GIS)-based multicriteria analysis. The peak leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR) from PROBA-V/Sentinel-3 data were calculated according to ground-truth soybean agricultural parcels in continental Croatia during 2015–2021. Four machine learning regression algorithms, including random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB), as well as their combination, were evaluated for predicting the peak LAI and FAPAR on the entire agricultural land in the study area, with RF producing the highest prediction accuracy with an R2 in the range of 0.250–0.590. The translation from K-means classes to the FAO land suitability standard was performed using a relative-based approach, ranking five resulting classes based on their relative mean sums of LAI and FAPAR values. The results of the proposed approach indicate that it is viable for major crops, while cropland suitability prediction for minor crops would require higher spatial resolution, such as vegetation indices from Sentinel-2 imagery.
Advancing Load Frequency Control in Multi-Resource Energy Systems Through Superconducting Magnetic Energy Storage
Authors: Shahgholian Ghazanfar , Fathollahi Arman
Published: January 2025

Given the fundamental importance of the power grid in both supply and demand, frequency stability is critical to the reliable and stable function of energy systems. When energy is stored in the system, it mitigates problems caused by various disturbances that interrupt the energy system’s operation. The energy storage system (ESS) stores excess energy and returns it to the system by reducing power oscillations and improving stability and dependability. Superconducting magnetic energy storage (SMES) is one strategy for storing energy in the power system. As a rotational storage system, its quick dynamic response is a significant advantage. This device can quickly release a substantial amount of energy. A gas power plant in one area, along with a steam and a hydropower plant in another, constitute a multi-resource energy system. This paper’s primary objective is to study and model how SMES affects the dynamic behavior of this energy system. The state-space representation of the power system’s dynamic behavior is given by first-order differential equations. This power system has a complexity of fifteen orders. The outcomes of the simulation using MATLAB software are presented in the time domain, and its correctness is shown by analyzing the power system’s modes. The results show that placing an SMES unit not only eliminates oscillations and frequency deviation but also reduces the induction time in the time responses of power in the connection line and frequency deviation. Different modes are considered for the energy system, and the effect of the power storage unit is shown by presenting the simulation results.
Application of Ultralight Aircraft for Aerosol Measurement Within and Above the Planetary Boundary Layer Above the City of Copenhagen
Authors: Thomas Daniel Charles , Gosewinkel Ulrich , Christiansen Michael Dines , Frohn Lise Marie , Ye Zhuyun , Massling Andreas , Skov Henrik
Published: January 2025

An ultralight aircraft was equipped with atmospheric monitoring instruments and flown above Copenhagen on the 17 June 2022 to measure a range of aerosol parameters and meteorology. Three flights were carried out from sunrise to early afternoon with the aim to capture the boundary layer structure and evolution due to surface warming, emissions from the city, and atmospheric mixing. The data show clear evidence of the boundary layer which expanded from 400–600 m in height at around 07:30 to 1200–1400 m by around 14:30. Additionally, a residual boundary layer was observed in the early morning, and an entrainment of pollution at the top of the boundary layer in the early afternoon. The observed atmospheric features were consistent between monitoring instruments and meteorological sensors, supporting the reliability of the data and aircraft setup. These results demonstrate the merits and limitations of the use of small aircraft for scientific research and monitoring of aerosols in the vertical dimension, especially in densely populated areas and high-traffic airspaces.
The Immunohistochemical Prognostic Value of Nuclear and Cytoplasmic Silent Information Regulator 1 Protein Expression in Saudi Patients with Breast Cancer
Authors: Alharbi Bayan , Aldahlawi Alia , Assidi Mourad , Basingab Fatemah , Zaher Kawther , Alrahimi Jehan , Mokhtar Sara , Al-Maghrabi Jaudah , Buhmeida Abdelbaset , Al-Sakkaf Kaltoom
Published: January 2025

Background: The mammalian NAD-dependent deacetylase sirtuin-1 family (named also silent information regulator or SIRT family, where NAD stands for “nicotinamide adenine dinucleotide” (NAD)) appears to have a dual role in several human cancers by modulating cell proliferation and death. This study examines how SIRT1 protein levels correlate with clinicopathological characteristics and survival outcomes in patients with breast cancer. Methods: A total of 407 BC formalin-fixed paraffin-embedded (FFPE) samples were collected from King Abdulaziz University Hospital, Saudi Arabia. SIRT1 was stained on tissue microarray slides using automated immunohistochemistry. Results: All BC subtypes expressed more nuclear SIRT1 proteins than their cytoplasm counterparts. In luminal A, luminal B, and TNBC, nuclear and cytoplasmic SIRT1 were highly associated (p < 0.001). Kaplan–Meier analysis showed reduced disease-specific survival (DSS) in H2BC with high SIRT1 nuclear expression (p = 0.001, log-rank). Moreover, the cytoplasmic expression of SIRT1 in HER2-positive BC was associated with a larger tumor size (p = 0.036) and lymph node metastasis (p = 0.045). Nuclear SIRT1 expression was also positively associated with lymph node metastasis (LNM) (p = 0.048). As low-grade tumors had a higher frequency of SIRT1 protein expression than other groups, SIRT1 expression was associated with a favorable prognosis in patients with luminal A BC (p < 0.001). Conclusions: SIRT1 expression seems to be involved in different molecular pathways either suppressing or promoting tumor growth depending on the subtype of BC. These molecular functions require further investigations and validation on larger BC cohorts.
Low-Level Social Demand Is Associated with Anxiety-Related Gamma Wave Responses in Autistic Male Youth
Authors: Bitsika Vicki , Sharpley Christopher F. , Evans Ian D. , Watson Christopher B. , Williams Rebecca J. , Vessey Kirstan A.
Published: January 2025

Background: The Autism Spectrum Disorder (ASD) characteristic of difficulties in social communication and interaction has been previously associated with elevated anxiety and the degree of mental effort required to understand and respond to social cues. These associations have implications for the mental health of autistic youth, but they are usually based on correlational statistics between measures of anxiety and social interaction demands that are collected in formal psychological testing settings. Another index of mental effort that has been found to correlate with anxious arousal is gamma wave activity, which is measured via EEG. Methods: To compare data from both of these indicators of mental effort and anxiety, a two-stage study was conducted using (1) standardized test data and (2) in vivo EEG data in a low-demand social setting. Results: As well as significant associations between social cognition and anxiety from standardized scales, there were also meaningful relationships between social cognition and gamma wave activity. Conclusions: Because gamma wave activity represents the highest level of cognitive complexity for brain activity, is an index of hypervigilance under threatening conditions, and has been associated with anxiety in autistic youth, these findings suggest that even low-level demand social interaction settings may initiate high-level anxiety-related behaviour in autistic youth.
Experimental Investigation of Seismic Behavior of Traditional and Eccentric RHS X-Joints Under Brace Axial Cyclic Loading
Authors: Zhong Shaoqi , Zhao Bida , Liu Lianglin
Published: January 2025

This study investigates the seismic behavior of traditional and eccentric rectangular hollow section (RHS) X-joints through a comprehensive experimental program. Four X-joint specimens, including two traditional and two eccentric joints with brace-to-chord width ratios (β) of 0.83 and 1.0, were subjected to quasi-static cyclic axial loading. Test results revealed that joints with β = 0.83 primarily failed due to chord face tearing, while those with β = 1.0 exhibited failure modes, including chord face tearing and significant sidewall buckling. Eccentric joints further experienced tearing of brace wall near the intersection. Increasing β enhanced axial strength but reduced ductility, deformability, and energy dissipation capacity. Eccentric joints with β = 0.83 showed improved strength, ductility, and energy dissipation compared to traditional joints, whereas eccentric joints with β = 1.0 displayed superior ductility but comparable strength and energy dissipation. The findings that current design codes underestimate the compressive strength of traditional joints with medium β and confirm that tensile strength exceeds compressive strength for all tested joints. Additionally, cyclic compressive strength closely static compressive strength.
The Domestic Acoustic Environment in Online Education—Part 2: Different Interference Perception of Sound Sources and While Conducting Academic Tasks
Authors: Puyana-Romero Virginia , Díaz-Márquez Angela María , Garzón Christiam , Ciaburro Giuseppe
Published: January 2025

Noise is increasingly recognized as a factor impacting health, including its effects on online education. However, differences in the perception of acoustic environmental factors have been scarcely analyzed. This study aimed to evaluate perceived differences in the interference of five types of sound (traffic, voices, TV/radio/household appliances, music, and animals) while conducting autonomous and synchronous activities during online learning. It is also aimed to identify which activities are more affected by the domestic acoustic environment among a group of 4 synchronous and 6 autonomous activities. The data were obtained from an online survey distributed online among the students of the Universidad de las Américas in Quito, Ecuador. The differences between acoustical variables were evaluated using frequentist and inferential analysis. Findings indicated that traffic noise was the least disruptive sound for autonomous activities, likely due to reduced vehicle circulation during the COVID-19 lockdown. In contrast, voices were identified as the most disturbing noise source, underscoring that background speech can significantly disrupt concentration. Additionally, domestic noise is more disturbing while taking exams than during solving problem tasks, comprehensive reading, or group work, probably because during the exams students cannot control unwanted sound sources. These outcomes underscore the need for acoustic strategies in domestic educational settings to reduce noise-related distractions.
Morphological Characteristics and Sustainable Adaptive Reuse Strategies of Regional Cultural Architecture: A Case Study of Fenghuang Ancient Town, Xiangxi, China
Authors: Wang Jingyi , Zakaria Safial Aqbar
Published: January 2025

This study explores the application of sustainable adaptive reuse strategies in preserving historical and cultural buildings, with the goal of establishing a scientifically robust framework of indicators for systematic evaluation and practical application. Focusing on the diaojiaolou (stilted buildings) along the Tuojiang River in the ancient town of Fenghuang, the research integrates findings from an extensive literature review with a theoretical framework to propose a multidimensional indicator system encompassing preservation, rehabilitation, urban renewal, adaptive reuse, urban revitalization, and restoration. Through detailed field investigations and comprehensive case studies, the study examines the cultural significance of the stilted buildings, including their spatial organization, structural design, material composition, and decorative features. It also critically assesses the effectiveness of sustainable adaptive reuse strategies in promoting regional development. The findings reveal that these strategies not only preserve the cultural and historical integrity of the stilted buildings but also enhance their functionality to meet modern needs, achieving a balance among heritage conservation, environmental sustainability, and socio-economic progress. This research validates the scientific rigor and practical utility of the proposed six-dimensional indicator framework as an evaluative tool, offering a model for the sustainable development and cultural preservation of similar regional heritage assets.
Sustainable Building Standards in the Galapagos Islands: Definition, Simulation, and Implementation in Representative Living Labs
Authors: Torres-Barriuso Jorge , Lopez-Villamor Iñigo , Egusquiza Aitziber , Garrido-Marijuan Antonio , Romero-Amorrortu Ander , Egiluz Ziortza
Published: January 2025

The Galapagos Islands are undeniably a highly attractive ecosystem for scientists worldwide. However, the energy efficiency and sustainability aspects of their building stock have not yet been studied in depth, which directly hinders the achievement of sustainability goals for the Archipelago, such as reducing resource consumption, minimizing emissions, and improving overall comfort in buildings. Addressing these issues is critical to preserving the islands’ unique ecosystem, as current construction practices are unsustainable and exacerbate environmental pressures, causing over-consumption of local resources and upsetting the delicate ecological balance that sustains this fragile environment. In line with the National Energy Efficiency Plan promoted by the Government of Ecuador for the Archipelago, this study provides transparent and reliable information and data on the building stock of the islands. This work quantifies the impact of buildings on the use of resources and analyses the potential savings of different strategies for reducing greenhouse gas emissions. Various representative typologies are established based on the collection of architectural, construction, and usage information. For each of these typologies, various energy models are developed to establish the baseline and to analyse the demand and comfort of the buildings under different renovation scenarios in order to validate the sustainable construction strategies to be implemented. Moreover, new standards are also defined in order to reduce energy and water consumption and increase indoor air quality and comfort in buildings. In an attempt to generate evidence and facilitate the replication and implementation of sustainable construction standards, three Living Labs (LLs) are created to validate different strategies and technological solutions in different locations, according to the defined standards: a school in Santa Cruz, a hotel in Isabela, and a residential building in San Cristóbal. The findings highlight the effectiveness of specific energy-saving strategies and water conservation measures validated through Living Labs implemented in different locations across the islands. Furthermore, the knowledge generated is transferred through local training of the agents of the construction chain and administration.
Primary Mediastinal Ewing’s Sarcoma: Post Hoc Analysis from Two International Multicenter Prospective Randomized Trials
Authors: Stork Theresa , Ranft Andreas , Aigner Clemens , Jurgens Heribert , Ladenstein Ruth L. , Timmermann Beate , Van den Berg Henk , Dirksen Uta , Collaud Stéphane
Published: January 2025

Objective: Ewing sarcoma (EWS) of the mediastinum is extremely rare, with only a few cases reported in the literature. We aimed to gain a better understanding of primary mediastinal EWS, describing patients treated within two international, multicenter, prospective, randomized EWS trials. Methods: Data from patients with primary mediastinal EWS were retrieved from the database of the EURO-E.W.I.N.G.99 (ClinicalTrials.gov identifier: NCT00020566) and EWING 2008 (ClinicalTrials.gov identifier: NCT00987636) trials. Patient and treatment characteristics were analyzed. Results: Out of 2969 patients with EWS, 9 (0.3%) had primary mediastinal EWS. The median age at diagnosis was 30.5 years (4 to 49). At the time of diagnosis, n = 3 (33%) patients had synchronous metastases. All patients underwent multiagent chemotherapy. Local therapy for non-metastatic patients was surgery (n = 2, 22%), surgery and radiotherapy (n = 2, 22%) or radiotherapy alone (n = 2, 22%). Surgery consisted of extended resections in most patients (n = 3, 33%). Five-year survival for the whole cohort was 64%. Apart from one patient who was lost to follow-up, all patients (n = 4) who had undergone surgery were alive at the end of follow-up. Conclusions: Primary mediastinal ES is extremely rare, with a prevalence of 0.3% among EWS. Five-year survival was favorable compared to primary mediastinal sarcoma of all histologies and in line with EWS of different origin.
Chronic Lymphocytic Leukemia Care and Beyond: Navigating the Needs of Long-Term Survivors
Authors: Molica Stefano , Allsup David
Published: January 2025

Chronic lymphocytic leukemia (CLL) treatment has undergone a significant evolution with a shift from historical chemotherapeutic regimens to targeted therapies such as Bruton tyrosine kinase (BTK) and BCL-2 inhibitors. These advancements have been associated with a notable improvement in survival rates with a transformation of CLL into a chronic and manageable condition for most persons with this disease. However, as a consequence of improved outcomes, long-term CLL survivors now face emergent challenges which include a risk of infections, cardiovascular complications, and secondary malignancies. In this changed scenario, holistic models of care are essential to address emergent health risks. Such models of care for CLL patients require a multidisciplinary approach that integrates CLL treatment with the proactive management of frailty, comorbidities, and psychosocial well-being to enhance both survival and quality of life (QoL). CLL predominantly affects older persons, many of whom present with concurrent frailty and comorbidities that may complicate CLL treatment and impact QoL. Comprehensive geriatric assessments (GA) may play a critical role in the identification of persons at a heightened risk of treatment-related toxicity and may help guide rational therapy selection, particularly in very frail persons. In addition to the assessment of hematological responses, the prospective assessment of patient-reported outcomes (PROs) and frailty metrics may offer a more nuanced understanding of the global treatment benefits. A survivorship-focused care model is crucial to address the multifaceted needs of CLL patients with the extension of patient care into the broader domain of long-term health maintenance with associated improvements in QoL.
Pancreaticobiliary Maljunction and Its Relationship with Biliary Cancer: An Updated and Comprehensive Systematic Review and Meta-Analysis on Behalf of TROGSS—The Robotic Global Surgical Society
Authors: Rivero-Moreno Yeisson , Goyal Aman , Bolívar Victor , Osagwu Nnenna , Echevarria Sophia , Gasca-Insuasti José , Pereira-Graterol Freddy , von Ahrens Dagny , Gaytán Fuentes Omar Felipe , Suárez-Carreón Luis Osvaldo , Vladimirov Miljana , Pascotto Beniamino , Azagra Juan Santiago , Calomino Natale , Abou-Mrad Adel , Marano Luigi , Oviedo Rodolfo J.
Published: January 2025

Objective: This systematic review and meta-analysis aimed to determine the degree to which pancreaticobiliary maljunction (PBM) increases the risk of different types of biliary cancer (BC). Methods: A systematic review and meta-analysis were carried out using the following databases: PubMed, Embase, Cochrane Library, Scopus, Web of Science, and Science Direct. We systematically searched from inception to April 2024. The search terms included were derived from the keywords “Pancreaticobiliary Maljunction” OR “Anomalous Pancreaticobiliary Junction” AND “Cancer” OR “Malignancy”. Studies that provided data comparing BC rates in relation to PBM presence or vice versa were included. The Newcastle–Ottawa Scale (NOS) was used for quality assessment. The random-effects model was used. Results: Fifteen studies were included with a total sample of 8604 patients, of whom 5015 (58.29%) were female with a mean age of 54.58 years. Patients with PBM had 8.42 (95% CI = 3.57–19.87) more risk of developing any type of BC, with a higher risk of GBC than BDC (OR = 16.91 vs. OR = 3.36, p-value = 0.003). There was a higher risk of having PBM in patients with GBC than BDC only when considering the Asian population (OR = 3.12, 95% CI = 1.09–8.94). Meta-regression analysis revealed that neither mean age (p = 0.087) nor percentage of female patients in the study population (p = 0.197) were statistically associated with the variations in OR for the risk of BC based on the presence of PBM. Conclusions: There is a significant association between PBM and the risk of having BC, mainly GBC when compared to BDC. Most of the studies published reported data from Japanese patients, which limits the generalization of the results. The age of patients and sex were not significantly associated with the relation between PBM and BC. Further prospective studies in broader populations will provide additional details to take measures for screening and early management of PBM and BC.
In Vitro 3D Models of Haematological Malignancies: Current Trends and the Road Ahead?
Authors: Mattioda Carlotta , Voena Claudia , Ciardelli Gianluca , Mattu Clara
Published: January 2025

Haematological malignancies comprise a diverse group of life-threatening systemic diseases, including leukaemia, lymphoma, and multiple myeloma. Currently available therapies, including chemotherapy, immunotherapy, and CAR-T cells, are often associated with important side effects and with the development of drug resistance and, consequently, disease relapse. In the last decades, it was largely demonstrated that the tumor microenvironment significantly affects cancer cell proliferation and tumor response to treatment. The development of biomimetic, in vitro models may promote the investigation of the interactions between cancer cells and the tumor microenvironment and may help to better understand the mechanisms leading to drug resistance. Although advanced in vitro models have been largely explored in the field of solid tumors, due to the complex nature of the blood cancer tumor microenvironment, the mimicking of haematological malignancies mostly relies on simpler systems, often limited to two-dimensional cell culture, which intrinsically excludes the microenvironmental niche, or to ethically debated animal models. This review aims at reporting an updated overview of state-of-the-art hematological malignancies 3D in vitro models, emphasizing the key features and limitations of existing systems to inspire further research in this underexplored field.
Impact of Solvent-Mediated Phase Transitions by Artificial Gastrointestinal Buffers on Efavirenz Polymorphs
Authors: Wardhana Yoga Windhu , Nuraisyah Eli , Kautsar Angga Prawira , Husni Patihul , Budiman Arif , Chaerunisaa Anis Yohana
Published: January 2025

The implications of various pH solutions in the gastrointestinal fluid system as solvent-mediated phase transitions on concurrent polymorphism transformation, notably metastable polymorphic forms of Efavirenz (EFV), has never been investigated. The impact will be shifting in the solubility and crystallinity of EFV polymorphisms, particularly metastable Forms II and III. EFV’s metastable form is generated by recrystallization with n-hexane and methanol, which were all immersed in artificial digestion buffer solutions for 10 and 100 h, respectively. Form II showed a 9–13.2% increase in solubility, whereas Form III increased by 2–7.3% over Form I. Interestingly, Form II revealed decreased crystallinity, but Form III tended to retain or slightly increase. In acidic solutions, all metastable polymorphs had the highest solubility and crystallinity. Form III appears to have a lower impact on phase transitions owing to pH variations than Form II. These findings indicate that variability in the pH of digestive secretions are essential steps in developing successful pharmaceutical formulations. Finally, our findings provide information on the complex interaction between solvents, pH variations, and EFV polymorphs. The findings identified the importance of these factors in the development of successful pharmaceutical formulations.
Expert-Based Narrative Review on Compression UltraSonography (CUS) for Diagnosis and Follow-Up of Deep Venous Thrombosis (DVT)
Authors: D’Oria Mario , Girardi Laura , Amgad Ahmed , Sherif Mohab , Piffaretti Gabriele , Ruaro Barbara , Calvagna Cristiano , Dueppers Philip , Lepidi Sandro , Donadini Marco Paolo
Published: January 2025

Deep venous thrombosis (DVT) is a pathological condition that develops when a thrombus forms within the deep venous system. Typically, it involves the lower limbs and, less frequently, the upper extremities or other unusual districts such as cerebral or splanchnic veins. While leg DVT itself is rarely fatal and occasionally can lead to limb-threatening implications, its most fearsome complication, namely pulmonary embolism, is potentially fatal and significantly contributes to increased healthcare costs and impaired quality of life in affected patients and caregivers. Thanks to its high accuracy, ease of use, and safety profile, duplex ultrasound (DUS), particularly compression ultrasound (CUS), has emerged as the first-line imaging modality for DVT diagnosis. The evaluation of suspected DVT needs a multifaceted approach, and in this context, CUS rapidly became a key diagnostic tool owing to its many unique advantages. Its central role in the diagnostic algorithm of suspected DVT is clearly established in the latest clinical practice guidelines from the European Society for Vascular Surgery and the American Society of Haematology. Indeed, DUS effectively visualizes blood flow and identifies abnormalities like clot formation with high sensitivity (typically exceeding 90% for proximal DVT) and specificity (often approaching 100% for proximal DVT). Additionally, CUS is non-invasive, readily available at the bedside, and avoids radiation exposure, resulting in an ideal method for various clinical settings. CUS has been shown to have a substantial role not only in the diagnosis of an acute DVT but also in the follow-up of its management. Moreover, this method can provide a prognostic assessment, mostly in terms of risk stratification for recurrent thrombosis and/or for potential complications, such as post-thrombotic syndrome. In summary, given its established benefits, CUS is a technique that many physicians should be familiar with, especially those working in emergency departments, intensive care units, or general wards. When needed, healthcare operators with more advanced US skills (such as radiologists, angiologists, or vascular surgeons) may be called upon to provide a second look in case of uncertainty and/or need for additional information.
On Defining Expressions for Entropy and Cross-Entropy: The Entropic Transreals and Their Fracterm Calculus
Authors: Bergstra Jan A. , Tucker John V.
Published: January 2025

Classic formulae for entropy and cross-entropy contain operations x0 and log2x that are not defined on all inputs. This can lead to calculations with problematic subexpressions such as 0log20 and uncertainties in large scale calculations; partiality also introduces complications in logical analysis. Instead of adding conventions or splitting formulae into cases, we create a new algebra of real numbers with two symbols ±∞ for signed infinite values and a symbol named ⊥ for the undefined. In this resulting arithmetic, entropy, cross-entropy, Kullback–Leibler divergence, and Shannon divergence can be expressed without concerning any further conventions. The algebra may form a basis for probability theory more generally.
Towards Secure Internet of Things: A Coercion-Resistant Attribute-Based Encryption Scheme with Policy Revocation
Authors: Zhai Yuan , Wang Tao , Zhou Yanwei , Zhu Feng , Yang Bo
Published: January 2025

With the development and application of the Internet of Things (IoT), the volume of data generated daily by IoT devices is growing exponentially. These IoT devices, such as smart wearable devices, produce data containing sensitive personal information. However, since IoT devices and users often operate in untrusted external environments, their encrypted data remain vulnerable to potential privacy leaks and security threats from malicious coercion. Additionally, access control and management of these data remain critical issues. To address these challenges, this paper proposes a novel coercion-resistant ciphertext-policy attribute-based encryption scheme. The scheme leverages chameleon hashing to enhance deniable encryption, achieving coercion resistance, thereby enabling IoT data to resist coercion attacks. Moreover, the scheme employs attribute-based encryption to secure IoT data, enabling fine-grained access control and dynamic user access management, providing a secure and flexible solution for vast IoT data. We construct the scheme on a composite order bilinear group and provide formal proofs for its coercion resistance, correctness, and security. Finally, through experimental comparisons, we demonstrate the efficiency and feasibility of the proposed scheme.
Intergroup Dialogue Empowering Action for Transforming Equity in Higher Education
Authors: Brar Manpreet Dhillon , Morales-Chicas Jessica , Morris Stacy , Rivera Imalay , Cannara Rebecca
Published: January 2025

As universities grapple with contentious socio-political climates, promoting intergroup relations efforts remains critical in mitigating these conflicts. Intergroup dialogue (IGD) provides one approach to improving intergroup relations in higher education. Prior evidence suggests that IGD reduces prejudice, increases empathy, builds critical consciousness, and improves intergroup relations. However, scant studies document virtual and multi-site IGD, especially those that include varied stakeholders. The current study sought to close these gaps by offering a facilitated and sustained four-stage model of IGD that concluded with collaborative action projects. A total of 32 students, faculty, and staff from eight universities in California participated in a virtual 20-hour, two-semester IGD program aimed to (1) generate dialogue around systemic barriers to graduation and (2) create action projects that address equity issues. Pre- and post-surveys with 22 participants showed increased intergroup empathy, improved comfort in having difficult conversations, and increased interest in future action behaviors. The participants also developed 10 action projects aimed at closing equity gaps through data storytelling, resource dissemination, dialogue programming, and policy advocacy. Our study adds to the effectiveness of IGD in higher education, offers important lessons learned, and highlights the implications of this work for both IGD practitioners and universities.
Enhancing Transparency and Fraud Detection in Carbon Credit Markets Through Blockchain-Based Visualization Techniques
Authors: Tsai Yun-Cheng
Published: January 2025

Net-zero emission targets require transparent and efficient carbon credit trading systems. This paper introduces a blockchain-based data visualization framework to enhance decision-making in the production and logistics sectors by simplifying blockchain transaction records and identifying potential arbitrage activities. The framework integrates real-time decision support tools, enabling production system managers to monitor carbon offset activities, detect fraudulent behaviors, and streamline operations. This research provides actionable insights into supply chain emissions management and operational risk reduction by leveraging advanced visualization techniques. The proposed approach offers innovative solutions to address the complexities of blockchain-based carbon trading, emphasizing transparency and sustainability. Our analysis demonstrates the effectiveness of these techniques in mitigating fraud and supporting compliance with international carbon trading standards. The findings contribute to integrating advanced technologies into sustainable production systems, offering practical implications for achieving global climate change mitigation goals and fostering a more efficient and secure carbon credit market.
A Practical Approach for Fault Location in Transmission Lines with Series Compensation Using Artificial Neural Networks: Results with Field Data
Authors: Rocha Simone Aparecida , de Mattos Thiago Gomes , da Silveira Eduardo Gonzaga
Published: January 2025

This paper presents a new method for fault location in transmission lines with series compensation, using data from voltage and current measurements at both terminals, applied to artificial neural networks. To determine the fault location, we present the proposal of using current phasors, obtained from the oscillography recorded during the short circuit, as the input to the neural network for training. However, the method does not rely on the internal voltage values of the sources or their respective equivalent Thevenin impedances to generate training files for the neural network in a transient simulator. The source data are not known exactly at the time of the short circuit in the transmission line, leading to greater errors when neural networks are applied to real electrical systems of utility companies, which reduces the dependency on electrical network parameters. To present the new method, a conventional fault location algorithm based on neural networks is initially described, highlighting how the dependency on source parameters can hinder the application of the artificial neural network in real cases encountered in utility electrical systems. Subsequently, the new algorithm is described and applied to simulated and real fault cases. Low errors are obtained in both situations, demonstrating its effectiveness and practical applicability. It is noted that the neural networks used for real cases are trained using simulated faults but without any data from the terminal sources. Although we expect the findings of this paper to have relevance in transmission lines with series compensation, the new method can also be applied to conventional transmission lines, i.e., without series compensation, as evidenced by the results presented.
Pinpointing Defects in Grounding Grids with Multistatic Radars
Authors: de Oliveira Rodrigo M. S. , Maia Pedro G. B.
Published: January 2025

In this paper, we propose a method for locating discontinuities in grounding grids using a multistatic radar. The objective is to determine the fault position in the structure by injecting an ultra-wideband pulse (Gaussian monocycle) at one of the corners of the grid and analyzing the transient signals obtained at two sensors and at the transceiver. To perform the analysis and validation of the developed method, simulations based on the finite-difference time-domain (FDTD) technique were carried out to numerically solve Maxwell’s equations. The voltage signals obtained in an intact grounding grid are used as a reference. Differences between these reference voltages and the voltages obtained with the faulty grid are calculated. With these difference signals, the parameters of the radar ellipses and circle are obtained, which delimit the area where the fault can be found. These parameters depend on the wave propagation speed and the arrival times of the signals at the sensors and the transceiver. The results show that the proposed method is able to reduce the estimated fault location area to a range of 2% to 19% of the total grid area. In addition, the average distance between the actual fault and the center of the estimated region varies between 3.0 and 4.0 m.
Multi-Stage Planning Approach for Distribution Network Considering Long-Term Variations in Load and Renewable Energy
Authors: Lou Qihe , Li Yanbin , Li Zhenwei , Han Liu , Xu Ying , Yi Zhongkai
Published: January 2025

Currently, the world is rapidly advancing in terms of the construction of new power systems, and planning suitable distribution network planning while also considering renewable energy has become a hot issue. Based on this background, this paper studies the distribution network planning problem. Compared with the traditional planning method, the paper considers the impact of load growth and renewable energy penetration and uses the multi-stage planning method to build the planning model; at the same time, in the scenarios selection, the affinity propagation (AP) clustering algorithm is adopted, which can automatically obtain the number of clusters. Based on the proposed model, an IEEE 33-node is used for simulation. The simulation results show that, compared with the traditional static planning method, the total economic cost of the proposed method is reduced by 4.87% and the wind–solar curtailment rate is reduced by 59.01%; in addition, according to the proposed method, the impact of energy storage equipment and wind–solar permeability on the planning results is studied. It is found that, when considering energy storage, the amount of abandoned wind and light decreases by 22.35% and the total cost first decreases and then increases with the increase in wind–solar permeability, while the total economic cost reaches the minimum at about 40%. The impact of load growth rate on the planning results is also studied. Finally, the generalizability of the proposed method is investigated while using the IEEE 69-node system as an example.
Development of a Comprehensive Comparison Software for Automated Decision-Making in Impulse Testing of Power Transformers, Including a Review of Practices from Analog to Digital
Authors: Bassi Welson
Published: January 2025

Power transformers are fundamental components in electrical grids, requiring robust insulation to operate reliably under various abnormal conditions, including overvoltages caused by lightning or switching. As defined by existing standards, the Basic Insulation Level (BIL) or Switching Insulation Level (SIL) of a transformer validates its reliability through impulse testing. These tests presume linearity in the overall system and equipment being tested. They compare waveforms at reduced and full impulse levels to detect or enhance insulation failures. Traditionally, this relies on visual inspection due to subjective acceptance criteria. This article presents a historical background review of the practices involving the use of analogue instruments evolved into digital oscilloscopes and digitizers, and the ways in which they enhance waveform acquisition and analysis capabilities. Despite advances in digital processing, including analyses on the frequency domain rather than only on time, such as transfer function analysis and coherence functions, and other signal transformations, such as wavelet calculation, interpreting differences in waveform records remains subjective. This article presents the development of a tool designed to emulate traditional photographic methods for waveform comparison. Moreover, the TRIMP software used enables multiple comparisons using various similarity and dissimilarity metrics in both the time and frequency domains, providing a robust system for identifying significant differences. The developed methodology and implemented metrics can form the basis for future machine learning or artificial intelligence (AI) applications. While digital tools offer significant advantages in impulse testing, improve reliability, reduce subjectivity, and provide robust decision-making metrics, their test approval remains based on visual comparisons due to consolidated engineering practices. Regardless of the metrics or indications obtained, the developed tool is a powerful graphic visualizer.
Does the Regional Comprehensive Economic Partnership Promote Forest Product Exports? Evidence on Bilateral Export Performance from China
Authors: Zhang Xi , Han Shufan , Zheng Xiuxiu , Chen Yong
Published: January 2025

This study examines the quarterly export data of forest products at the Harmonized System 6-digit level from China′s 31 provinces to destination economies from 2017 to 2023 to examine the impact of the Regional Comprehensive Economic Partnership agreement on bilateral forest product trade. A time-varying Difference-in-Differences model is constructed using the effective dates of the agreement for each member, combined with the Propensity Score Matching method, comparing export flows between China with member and non-member economies in the pre- and post-agreement periods. The main findings indicate that the effective commitments of the Regional Comprehensive Economic Partnership in destination economies have significantly enhanced the bilateral exports of forest products from China’s provinces. Compared with non-member destination economies, China’s exports of timber forest products to member countries increased by over 22% after the agreement came into effect, with notable increases in eastern coastal provinces and in processed forest products including wooden furniture and paper products. To maximize the promotion of forest product exports under this framework, it is suggested that China enhance transportation links between its central and western inland provinces to reduce transportation costs. Additionally, closer trade cooperation among member countries is recommended to facilitate the development of trade in intermediate products. Furthermore, the strengthened collaboration between upstream and downstream industries could facilitate the integrated development of the regional timber processing industry supply chain.
Selection of Trees for Thinning Using Machine Learning Algorithms and Competition Indices
Authors: Lee Yong-Kyu , Lee Jung-Soo , Han Sang-Kyun , Ji Hyo-Vin , Park Jin-Woo
Published: January 2025

In artificial forests, regular thinning is required to promote diameter growth for producing high-quality, large-diameter timber. However, selecting trees for thinning often relies on qualitative and subjective assessments by field workers. The purpose of this study was to develop a quantitative method for selecting trees for thinning by combining machine learning algorithms and competition indices. Our study site included the Pinus koraiensis area within a Kangwon National University research forest in the Republic of Korea. Data from a model development site were used for the basic crown classification model for Pinus koraiensis. The model was optimized by adjusting hyperparameters. Different algorithms, including Random Forest, XGBoost, and LightGBM (LGBM), were improved using Random Search. LGBM showed the highest accuracy of 71.6%. LGBM—in combination with the competition indices—was used to classify the crown class in the application site and select trees for thinning. Compared to the combination of Braathe and Martin-EK indices, the combination of LGBM and Hegyi index enabled the even distribution of the residual stand in the entire site after thinning. It lowered the distribution of hot spots, which represent competition. Thus, the combination of LGBM and Hegyi index was the most effective option to improve the spatial distribution of trees after thinning. Our findings can improve forest management by providing a quantitative and objective method for selecting trees for thinning.