bluuebunny/crossref_metadata_2025 huggingface dataset:
Viscoelastic and Fatigue Performance of Modified Bitumen Using Polymer and Bio-Based Additives: A Comparative Study
Authors: Almusawi Ali , Nasraldeen Shvan Tahir , Albdairi Mustafa , Norri Hussein H
Published: January 2025

This study investigates the performance and viscoelastic characteristics of unmodified and modified bitumen using Performance Grading, Frequency Sweep, and Linear Amplitude Sweep tests. The bitumen modifications include styrene-butadiene–styrene at 4% and 5%, animal bone powder at concentrations of 4%, 5%, and 6%, and waste cooking oil at 3%, 4%, and 5%. Performance Grading tests were conducted to evaluate the high-temperature performance of bitumen samples. Frequency Sweep tests were used to analyze the complex shear modulus and phase angle, providing insights into stiffness and elasticity. The Linear Amplitude Sweep tests assessed fatigue resistance by monitoring the degradation of the complex shear modulus under cyclic loading. Styrene-butadiene–styrene and animal bone powder significantly enhanced stiffness, elasticity, and fatigue resistance, with styrene-butadiene–styrene-modified samples achieving the highest performance grades and fatigue resistance. Waste cooking oil-modified bitumen reduces stiffness and fatigue resistance, indicating it primarily acts as a plasticizer. Styrene-butadiene–styrene and animal bone powder are effective modifiers for improving bitumen’s mechanical and fatigue properties and are suitable for demanding applications. In contrast, waste cooking oil compromises structural performance despite its environmental benefits, making it less suitable for high-performance use.
A Conceptual Framework for Planning Road Digital Twins
Authors: Buuveibaatar Munkhbaatar , Brilakis Ioannis , Peck Matt , Economides George , Lee Wonhee
Published: January 2025

Digital twin (DT) is an emerging technology gaining traction across various industries. However, its development and application in the architecture, engineering, and construction (AEC) industry remain in their early stage, lagging considerably behind other sectors. This is primarily attributed to the challenges facing the AEC industry, including digital transformation and the lack of formal standards for DT implementation. This study aims to contribute to the conceptualization of DT planning—the early stage of the DT lifecycle—focusing on the road transportation sector, particularly road physical twin planning within the AEC industry. To achieve this, we reviewed the relevant literature defining DT planning. We also examined stakeholders’ relevant guidelines and documents from national bodies that roadmap the road DT planning process to understand the scope and identify knowledge gaps. Based on the findings, mapping the existing road planning process to the constituents of road DT planning was performed for the applicable planning steps. Finally, we proposed a five-layered road DT planning framework that will roadmap future implementations comprising data acquisition, data processing, data modeling and algorithms, data analysis and control, and a service layer plus users. In addition, a case study is incorporated to validate the feasibility of the framework toward applying it further in practice.
Parental Psychological Adjustment in Pediatric Acute Lymphoblastic Leukemia: The Mediating Role of Family Functioning and Resilience
Authors: Ferraz Ana , Faria Susana , Jerónimo Mónica , Pereira M. Graça
Published: January 2025

Background/Objectives: Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, with intense treatments affecting both children and their families. Limited information is available on parental distress and psychological well-being during the first treatment year, with most studies focusing on individuals rather than the family system. This study explores longitudinal changes in parental distress (psychological morbidity and traumatic stress symptoms), coping strategies, family resilience and functioning, and psychological well-being. The study also examines the mediating roles of family resilience, family functioning, and coping strategies in the relationships between parental distress and psychological well-being. Methods: A prospective study was conducted with 46 parents of children newly diagnosed with ALL, assessing parental distress, family functioning and resilience, coping, and psychological well-being across three treatment phases: consolidation (T0), delayed intensification (T1), and maintenance (T2). Results: Parental distress and family resilience significantly decreased from T0 to T2, while parental coping improved over time. Family functioning deteriorated from T0 to T1, stabilizing thereafter. Psychological well-being followed a non-linear trajectory, initially declining from T0 to T1 and improving from T1 to T2. Mediation analyses revealed that family resilience and family functioning partially mediated the relationships between parental distress and psychological well-being. Parental coping did not emerge as a mediator. Conclusions: Parental psychological adjustment in the context of ALL is dynamic and influenced by individual and family factors. Interventions that strengthen family functioning and resilience are crucial for supporting parental psychological well-being during treatment. A family-centered approach in healthcare delivery is essential to address individual and systemic challenges.
Current Landscape of Molecular Biomarkers in Gastroesophageal Tumors and Potential Strategies for Co-Expression Patterns
Authors: Korpan Martin , Puhr Hannah Christina , Berger Julia M. , Friedrich Alexander , Prager Gerald W. , Preusser Matthias , Ilhan-Mutlu Aysegül
Published: January 2025

The treatment of metastasized gastroesophageal adenocarcinoma largely depends on molecular profiling based on immunohistochemical procedures. Therefore, the examination of HER2, PD-L1, and dMMR/MSI is recommended by the majority of clinical practice guidelines, as positive expression leads to different treatment approaches. Data from large phase-III trials and consequent approvals in various countries enable physicians to offer their patients several therapy options including immunotherapy, targeted therapy, or both combined with chemotherapy. The introduction of novel therapeutic targets such as CLDN18.2 leads to a more complex decision-making process as a significant number of patients show positive results for the co-expression of other biomarkers besides CLDN18.2. The aim of this review is to summarize the current biomarker landscape of patients with metastatic gastroesophageal tumors, its direct clinical impact on daily decision-making, and to evaluate current findings on biomarker co-expression. Furthermore, possible treatment strategies with multiple biomarker expression are discussed.
The Role of Macrophages in Various Types of Tumors and the Possibility of Their Use as Targets for Antitumor Therapy
Authors: Jumaniyazova Enar , Lokhonina Anastasiya , Dzhalilova Dzhuliia , Miroshnichenko Ekaterina , Kosyreva Anna , Fatkhudinov Timur
Published: January 2025

In solid tumors, tumor-associated macrophages (TAMs) are one of the most numerous populations and play an important role in the processes of tumor cell invasion, metastasis, and angiogenesis. Therefore, TAMs are considered promising diagnostic and prognostic biomarkers of tumors, and many attempts have been made to influence these cells as part of antitumor therapy. There are several key principles of action on ТАМs: the inhibition of monocyte/macrophage transition; the destruction of macrophages; the reprogramming of macrophage phenotypes (polarization of M2 macrophages to M1); the stimulation of phagocytic activity of macrophages and CAR-M therapy. Despite the large number of studies in this area, to date, there are no adequate approaches using antitumor therapy based on alterations in TAM functioning that would show high efficacy when administered in a mono-regimen for the treatment of malignant neoplasms. Studies devoted to the evaluation of the efficacy of drugs acting on TAMs are characterized by a small sample and the large heterogeneity of patient groups; in addition, in such studies, chemotherapy or immunotherapy is used, which significantly complicates the evaluation of the effectiveness of the agent acting on TAMs. In this review, we attempted to systematize the evidence on attempts to influence TAMs in malignancies such as lung cancer, breast cancer, colorectal cancer, cervical cancer, prostate cancer, gastric cancer, head and neck squamous cell cancer, and soft tissue sarcomas.
An Assessment of Young Adults’ Awareness and Knowledge Related to the Human Papillomavirus (HPV), Oropharyngeal Cancer, and the HPV Vaccine
Authors: Davis Eric N. , Doyle Philip C.
Published: January 2025

Background/Objectives: The human papillomavirus (HPV) is a prevalent sexually transmitted infection that is a known cause of morbidities such as genital warts and cancers of the cervix, anus, and oropharynx. Non-cervical HPV-related cancers have been a developing problem in North America, increasing in incidence by up to 225% in some instances over a span of two decades. Methods: This study investigated levels of awareness and knowledge of HPV, oropharyngeal cancer (OPC), and the HPV vaccine using a self-administered web-based survey designed specifically for this research. University students (n = 1005) aged 18–30 completed a 42-item questionnaire that included demographic information, awareness questions, and a series of “true/false/I don’t know” knowledge questions. Results: The data gathered revealed that participants had relatively high levels of awareness. However, many respondents had significant gaps in their knowledge of HPV, OPC, and the HPV vaccine. Collectively, the data indicate that awareness and knowledge of HPV and the value of vaccination may place younger individuals at risk for HPV-related infections. Conclusions: Although a relatively high level of awareness concerning HPV was observed, the gaps in knowledge suggest that further efforts are necessary to educate young adults. While all risk factors cannot be reduced, the present data may guide future efforts directed toward better education on HPV and related health concerns and associated risks.
Surfactant-Assisted Manipulation of CeO2@poly(acrylic Acid-Co-Acryl Amide) Nanocomposite for Visible-Light-Driven Persulfate-Activated Photocatalytic Oxidation of Organic Pollutants from Wastewater
Authors: Saadoon Fadya A. , Mekewi Mohamed A. , Al-Musalmee Al-Saeed H. , Darwish Atef S.
Published: January 2025

Herein, anionic (sodium dodecylbenzene sulfonate, SDBS) and cationic (cetyltrimethylammonium bromide, CTAB) surfactants are involved in the synthesis of a poly(acrylic acid-co-acrylamide) copolymer, p(AA-co-AM), containing nanoceria (CeO2). The physicochemical and optical properties of CTAB-CeO2@p(AA-co-AM) and SDBS-CeO2@p(AA-co-AM) nanocomposites can be studied using different techniques. The physicochemical properties of nanoceria-immobilized p(AA-co-AM) are significantly developed when handled with SDBS. Compared to the CTAB-CeO2@p(AA-co-AM) nanocomposite, SDBS-CeO2@p(AA-co-AM) exhibits pronounced negatively charged mesoporous surfaces with Corel reef-like morphology. SDBS-CeO2@p(AA-co-AM) contains ceria nano-cubes of ~30 nm size, evenly dispersed along a copolymeric moiety, displaying narrower energy bandgap. The photocatalytic efficiency of this nanocomposite is performed in activating persulfate-ions (PS) under visible light irradiation, yielding reactive oxygen species that effectively treat dye wastewater. Advanced SDBS-CeO2@p(AA-co-AM)/PS/Vis photocatalytic oxidation system possesses ~100% methylene blue degradation efficiency within 2 h for five consecutive purification-cycles with thorough mineralization performance. Such superior photo-degradability consults efficacious synergistic combinations gathering the nanocomposite, persulphate-ions, and visible light radiation, yielding an escalated synergy-index value (SI = 6) with intensive generation of reactive-oxidizing species (SO4•−/h+ synergistic ratio 1:5.6). Including anionic-surfactant molecules in the synthesis of metal-containing copolymer nanocomposites is indispensably profitable in the future for the treatment of industrial wastewater.
Astrocyte-Secreted Lcn2 Modulates Dendritic Spine Morphology
Authors: Doliwa Marta , Kuzniewska Bozena , Nader Karolina , Reniewicz Patryk , Kaczmarek Leszek , Michaluk Piotr , Kalita Katarzyna
Published: January 2025

Learning and memory formation rely on synaptic plasticity, the process that changes synaptic strength in response to neuronal activity. In the tripartite synapse concept, molecular signals that affect synapse strength and morphology originate not only from the pre- and post-synaptic neuronal terminals but also from astrocytic processes ensheathing many synapses. Despite significant progress made in understanding astrocytic contribution to synaptic plasticity, only a few astrocytic plasticity-related proteins have been identified so far. In this study, we present evidence indicating the role of astrocyte-secreted Lipocalin-2 (Lcn2) in neuronal plasticity. We show that Lcn2 expression is induced in hippocampal astrocytes in a kainate-evoked aberrant plasticity model. Next, we demonstrate that chemically induced long-term potentiation (cLTP) similarly increases Lcn2 expression in astrocytes of neuronal–glial co-cultures, and that glutamate causes the immediate release of Lcn2 from these cultures. Additionally, through experiments in primary astrocytic cultures, we reveal that Lcn2 release is triggered by calcium signaling, and we demonstrate that a brief treatment of neuronal–glial co-cultures with Lcn2 alters the morphology of dendritic spines. Based on these findings, we propose Lcn2 as an activity-dependent molecule released by astrocytes that influences dendritic spine morphology.
High-Accuracy Bandgap Reference of <20 ppm/°C: A Review
Authors: Zhuang Haoyu , Chen Xudong , Zhang Enzhe , Li Qiang
Published: January 2025

This review discusses the principle of typical bandgap reference circuits and analyzes their sources of errors. In order to provide readers with a clear perspective, we categorize the error sources into four types: (a) amplifier offset; (b) high-order nonlinearity of VBE; (c) current mirror mismatch; and (d) other error sources. For these error sources, the most commonly used methods to reduce or minimize them to achieve high accuracy are summarized. Furthermore, this review explores sub-1V bandgap reference design techniques, addressing the increasing demand for low-power and low-voltage applications. Finally, we provide some suggestions for a future high-accuracy reference design.
Preparation of High Entropy Alloys Without Pre-Alloying, Using Laser Melt Deposition (LMD) Technique
Authors: Hareancz Ferenc , Juhász Gergely , Windisch Márk , Heczel Anita , Vida Ádám
Published: January 2025

This study explores the fabrication of an equimolar CoCrFeNi high-entropy alloy (HEA) using laser metal deposition (LMD) technique on a 316 L austenitic stainless steel substrate, without pre-alloying. Elemental metal powders were mixed in a planetary ball mill and directly deposited to investigate the effect of layer number on alloy composition and substrate intermixing. Experimental results revealed significant dilution in the first four layers, with substrate intermixing affecting composition. The coarse-grained crystal structure observed in the initial layers persisted in subsequent layers, and hardness measurements indicated the cumulative thermal effects of sequential deposition. From an industrial perspective, this approach offers a cost-effective and flexible manufacturing strategy, eliminating the need for pre-alloying. Moreover, gradient compositional layers can be achieved, enabling tailored material properties. This work demonstrates the feasibility of producing multi-layer HEAs directly from elemental powders while addressing the challenges of compositional stability.
Preparation and Characterization of Mg-Based Biomaterials with Bioactive Surfaces Functionalized with EU/Gd NPs for Bone Tissue Regeneration Obtained via PEO Process
Authors: Kuźmiak Klaudia , Janus Łukasz , Sierakowska-Byczek Aleksandra , Radwan-Pragłowska Julia
Published: January 2025

This study aimed to develop a novel type of biodegradable magnesium (Mg)-based implant with enhanced biological activity through surface modification using plasma electrolytic oxidation (PEO) combined with the incorporation of rare earth ions (Eu and Gd). Magnesium is recognized for its lightweight nature, biocompatibility, and bone-like mechanical properties, making it a promising alternative to titanium implants. Unlike titanium, Mg-based biomaterials can be safely used in pediatric surgery due to their ability to degrade naturally within the body. However, pure magnesium is highly reactive in physiological fluids, necessitating surface modifications to mitigate biocorrosion prior to clinical application. To address this challenge, the PEO process was employed, resulting in surface passivation and the formation of a protective coating. Experimental evaluations demonstrated reduced biodegradation rates and magnesium ion release, confirming the beneficial role of rare earth elements in decreasing reactivity. Wettability tests indicated high hydrophilicity, while scanning electron microscopy (SEM) revealed appropriate surface morphology and element deposition conducive to bone regeneration. Electrochemical analyses further validated the protective efficacy of the magnesium oxide layers enhanced with rare earth ions. Finally, in vitro cytotoxicity tests on the MG-63 osteosarcoma cell line confirmed the biocompatibility of the modified magnesium implants. Overall, this study highlights the potential of Mg-based biomaterials, modified through PEO and rare earth ion incorporation, for use in medical implants.
Operational Robustness of Amino Acid Recognition via Transverse Tunnelling Current Across Metallic Graphene Nano-Ribbon Electrodes: The Pro-Ser Case
Authors: Zollo Giuseppe
Published: January 2025

Asymmetric cove-edged graphene nano-ribbons were employed as metallic electrodes in a hybrid gap device structure with zig-zag graphene nano-ribbons terminations for amino acid recognition and peptide sequencing. On a theoretical basis, amino acid recognition is attained by calculating, using the non equilibrium Green function scheme based on density functional theory, the transversal tunnelling current flowing across the gap device during the peptide translocation through the device. The reliability and robustness of this sequencing method versus relevant operations parameters, such as the bias, the gap size, and small perturbations of the atomistic structures, are studied for the paradigmatic case of Pro-Ser model peptide. I evidence that the main features of the tunnelling signal, that allow the recognition, survive for all of the operational conditions explored. I also evidence a sort of geometrical selective sensitivity of the hybrid cove-edged graphene nano-ribbons versus the bias that should be carefully considered for recognition.
Patient-Centered Care for Adolescents and Young Adults with an Uncertain or Poor Cancer Prognosis: A Secondary Analysis of What Is Needed According to Patients, Caregivers, and Healthcare Providers
Authors: Reuvers Milou J. P. , Burgers Vivian W. G. , Manten-Horst Eveliene , Messelink Kim , van der Laan Elsbeth J. H. M. , van der Graaf Winette T. A. , Husson Olga
Published: January 2025

Patient-centered care focuses on aligning healthcare with a person’s values and preferences to support their health and life goals. This approach is especially crucial among adolescents and young adults (AYAs—with a primary cancer diagnosis between the ages of 18 and 39) facing an uncertain or poor cancer prognosis (UPCP), whose care needs differ from those undergoing curative treatment. This study aims to gain insights from AYAs with a UPCP, their informal caregivers, and healthcare professionals (HCPs) to define optimal patient-centered care and identify barriers to its implementation. We conducted semi-structured interviews with 46 AYAs, 39 informal caregivers, and 49 HCPs from various clinical backgrounds. Findings highlighted the need of AYAs for an equal relationship with HCPs and active involvement in decision-making, alongside tailored information addressing their unique challenges. Informal caregivers expressed the need for information to support patients while preferring a minimal focus on themselves. HCPs noted the necessity for specialized training to meet the specific needs of AYAs with a UPCP, reporting difficulties in providing tailored support due to the disease’s uncertainties. This study’s results can lead to improved healthcare for this population and enhance educational modules for HCPs, equipping them to better support AYAs facing a UPCP.
How Visual Design in Dairy Packaging Affects Consumer Attention and Decision-Making
Authors: Riswanto Aura Lydia , Kim Seieun , Williady Angellie , Ha Youngsam , Kim Hak-Seon
Published: January 2025

The design of product packaging significantly impacts consumer behavior by attracting attention and influencing purchasing choices within a competitive market environment. This research explores the effects of visual packaging elements, such as branding, imagery, and descriptive text, on consumer preferences and decisions. By examining regular, organic, and character-themed milk packaging, the study seeks to determine which features effectively capture attention and drive engagement. Employing eye-tracking tools (Tobii Pro Spectrum and Tobii Pro Lab) alongside survey analysis, the study evaluates consumer focus through fixation durations and heatmap visualizations. The findings indicate that character-themed packaging draws the most attention, with colorful illustrations and prominently displayed brand names playing a central role. Fixation data highlight brand names as the most consistently engaging feature across all packaging types. Regression analysis further reveals that cultural familiarity influences preferences, as international participants favored designs resembling those from their home regions or familiar global brands. These insights underscore the importance of visually appealing and culturally relevant designs in building consumer engagement and brand loyalty. The study offers valuable guidance for marketers and designers aiming to create packaging that resonates with diverse audiences and market demands.
Dietary Choline Deprivation Exacerbates Kidney Injury in Streptozotocin-Induced Diabetes in Adult Rats
Authors: Al-Humadi Ahmed W. , le Roux Carel W. , Docherty Neil G. , Al-Najim Werd , Kueh Martin Tze Wah , Lazaris Andreas C. , Liapi Charis
Published: January 2025

Background: Choline (Ch) deprivation causes kidney injury and dysfunction, and diabetic nephropathy is also known to be a complication of diabetes; thus, this interplay could potentially aggravate diabetic kidney disease. Aim: This study aims to examine the effect of Ch-deprivation on the severity of kidney injury in streptozotocin (STZ)-induced diabetic rats. Methods: Twenty-four adult male Wistar rats were divided into four groups: control (C), nondiabetic Ch-deprived (CD), diabetic (DM), and diabetic Ch-deprived (DM + CD). Diabetes was induced by the intraperitoneal administration of 50 mg/kg body weight STZ; Ch-deprivation was induced through a choline-deficient diet. Rats were euthanized at week 5 of the study. Biochemical tests, renal histopathology, immunohistochemistry of the kidney injury molecule-1 (KIM-1), and vascular endothelial growth factor-A (VEGF-A) expression were assessed. Results: DM + CD and DM groups demonstrated significant increases in glucose levels and in the homeostasis model of insulin resistance (HOMA IR). Creatinine and blood urea nitrogen levels significantly increased in the DM + CD group compared to the control, and homocysteine levels were higher in the CD group. Kidney histopathology revealed that renal tubular necrosis, mesangial matrix expansion, and renal fibrosis substantially increased in the DM + CD group compared to all other groups, and KIM-1 and VEGF-A expressions were most pronounced in the DM + CD and DM groups, respectively. Conclusions: Ch deprivation affected kidney function and structure in STZ-induced diabetic rats. Choline deficiency and diabetes seem to have a synergistic effect, as evidenced by kidney biochemistry, histopathology, and immunohistochemistry. These findings could highlight the important role of choline in therapeutic strategies for the treatment and, potentially, prevention of chronic diabetic kidney disease.
Integrating Donor Derived Cell-Free DNA Fraction and Absolute Quantification for Enhanced Rejection Diagnosis in Kidney Transplant Recipients
Authors: Nie Weijian , Wang Yan , Fu Qian , Wu Chenglin , Deng Ronghai , Yu Xiaolin , Ye Caiguo , Liu Xiangjun , Xu Bowen , Sun Pingping , Liu Longshan , Li Jun , Zhang Huanxi , Wang Changxi
Published: January 2025

Background: This study aimed to assess the diagnostic accuracy of combining donor-derived cell-free DNA (dd-cfDNA) fraction and absolute quantification in detecting kidney allograft rejection. Methods: A prospective study was conducted from December 2019 to April 2021 at the First Affiliated Hospital of Sun Yat-sen University. Kidney transplant recipients who underwent biopsy, including cases of T-cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), and borderline rejection, were included. dd-cfDNA fraction and absolute concentrations were measured, and diagnostic efficacy was evaluated using receiver operating characteristic (ROC) analysis. The double-positive and double-negative methods were applied to assess performance. Results: A total of 50 kidney transplant recipients were included. The dd-cfDNA fraction cutoff of 1.08% achieved 93.33% sensitivity and 91.43% specificity (AUC = 0.95), with an NPV of 96.97% and a PPV of 82.35%. The absolute dd-cfDNA threshold of 32 cp/mL yielded 80.00% sensitivity and 71.43% specificity (AUC = 0.78), with an NPV of 89.29% and a PPV of 54.55%. The double-positive method provided superior accuracy, with a PPV of 91.67% and an NPV of 89.47%, demonstrating 73.33% sensitivity and 97.14% specificity. The double-negative method achieved 100% NPV and 100% sensitivity. Conclusions: Combining dd-cfDNA fraction and absolute quantification improves diagnostic accuracy for kidney transplant rejection, especially ABMR. The double-positive and double-negative approaches show high predictive value, offering potential clinical value for monitoring kidney transplant recipients.
Control-Oriented Real-Time Trajectory Planning for Heterogeneous UAV Formations
Authors: Qian Weichen , Yi Wenjun , Yuan Shusen , Guan Jun
Published: January 2025

Aiming at the trajectory planning problem for heterogeneous UAV formations in complex environments, a trajectory prediction model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory networks (LSTM) is designed, and a real-time trajectory planning method is proposed based on this model. By pre-training trajectory prediction networks for various types of UAVs, the traditional physics-based models are replaced for flight trajectory prediction. Inspired by Model Predictive Control (MPC), in the trajectory planning stage, the method generates multi-step trajectory points using an improved artificial potential field (APF) method, estimates the actual formation trajectory using the prediction network, and optimizes the trajectory through a multi-objective particle swarm optimization (MOPSO) algorithm after evaluating the planning costs. During actual flight, the optimized parameters generate trajectory points for the formation to follow. Unlike conventional path planning based on simple constraints, the proposed method directly plans trajectory points based on trajectory tracking performance, ensuring high feasibility for the formation to follow. Experimental results show that the CNN-LSTM network outperforms other networks in both short-term and long-term trajectory prediction. The proposed trajectory planning method demonstrates significant advantages in formation maintenance, trajectory tracking, and real-time obstacle avoidance, ensuring flight stability and safety while maintaining high-speed flight.
Unmanned Aerial Vehicle-Enabled Aerial Radio Environment Map Construction: A Multi-Stage Approach to Data Sampling and Path Planning
Authors: Lin Junyi , Wang Hongjun , Wu Tao , Shen Zhexian , Jiang Ruhao , Fan Xiaochen
Published: January 2025

An aerial Radio Environment Map (REM) characterizes the spatial distribution of Received Signal Strength (RSS) across a geographic space of interest, which is crucial for optimizing wireless communication in the air. Aerial REM construction can rely on Unmanned Aerial Vehicles (UAVs) to autonomously select interesting positions for sampling RSS data, enhancing the quality of construction. However, due to the lack of prior information about the environment, it is challenging for UAVs to determine suitable sampling positions online. Additionally, achieving efficient exploration of the target area through collaboration among multiple UAVs is difficult. To address this issue, this paper proposes a multi-stage approach to data sampling and path planning with multiple UAVs. Specifically, the UAVs’ data sampling task over the target area is divided into multiple stages. By selecting an appropriate stage position, we use the RSS values at that position to determine whether additional data need to be sampled in a specific local area. At each stage, the area is divided into Voronoi diagrams based on the current position of each UAV, assigning each UAV its own region to explore. In our sampling strategy, the probability distribution for sampling is obtained by estimating the RSS and uncertainty of unsampled positions and then taking the weighted sum of these two values. To obtain the shortest flight path for selected sampling positions, we employ a network structure based on self-attention as the policy network, which is trained through the actor–critic framework to obtain an improvement heuristic strategy, replacing traditional manually designed strategies. Experimental results across three different scenarios indicate that the approach improves the quality of aerial REM construction while efficiently planning the shortest paths for UAVs between sampling positions.
Forecasting Stock Market Indices Using Integration of Encoder, Decoder, and Attention Mechanism
Authors: Thach Tien Thanh
Published: January 2025

Accurate forecasting of stock market indices is crucial for investors, financial analysts, and policymakers. The integration of encoder and decoder architectures, coupled with an attention mechanism, has emerged as a powerful approach to enhance prediction accuracy. This paper presents a novel framework that leverages these components to capture complex temporal dependencies and patterns within stock price data. The encoder effectively transforms an input sequence into a dense representation, which the decoder then uses to reconstruct future values. The attention mechanism provides an additional layer of sophistication, allowing the model to selectively focus on relevant parts of the input sequence for making predictions. Furthermore, Bayesian optimization is employed to fine-tune hyperparameters, further improving forecast precision. Our results demonstrate a significant improvement in forecast precision over traditional recurrent neural networks. This indicates the potential of our integrated approach to effectively handle the complex patterns and dependencies in stock price data.
Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality
Authors: Cheamsawat Krai , Chotibut Thiparat
Published: January 2025

Quantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. Yet, identifying the mechanisms that underlie enhanced performance remains challenging, particularly in many-body open systems where nonlinear interactions and dissipation intertwine in complex ways. Here, we investigate a minimal model of a driven-dissipative quantum reservoir described by two coupled Kerr-nonlinear oscillators, an experimentally realizable platform that features controllable coupling, intrinsic nonlinearity, and tunable photon loss. Using Partial Information Decomposition (PID), we examine how different dynamical regimes encode input drive signals in terms of redundancy (information shared by each oscillator) and synergy (information accessible only through their joint observation). Our key results show that, near a critical point marking a dynamical bifurcation, the system transitions from predominantly redundant to synergistic encoding. We further demonstrate that synergy amplifies short-term responsiveness, thereby enhancing immediate memory retention, whereas strong dissipation leads to more redundant encoding that supports long-term memory retention. These findings elucidate how the interplay of instability and dissipation shapes information processing in small quantum systems, providing a fine-grained, information-theoretic perspective for analyzing and designing QRC platforms.
Structured Dynamics in the Algorithmic Agent
Authors: Ruffini Giulio , Castaldo Francesca , Vohryzek Jakub
Published: January 2025

In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. Here, we study the dynamical aspects of this framework by examining how the requirement of tracking natural data drives the structural and dynamical properties of the agent. We first formalize the notion of a generative model using the language of symmetry from group theory, specifically employing Lie pseudogroups to describe the continuous transformations that characterize invariance in natural data. Then, adopting a generic neural network as a proxy for the agent dynamical system and drawing parallels to Noether’s theorem in physics, we demonstrate that data tracking forces the agent to mirror the symmetry properties of the generative world model. This dual constraint on the agent’s constitutive parameters and dynamical repertoire enforces a hierarchical organization consistent with the manifold hypothesis in the neural network. Our findings bridge perspectives from algorithmic information theory (Kolmogorov complexity, compressive modeling), symmetry (group theory), and dynamics (conservation laws, reduced manifolds), offering insights into the neural correlates of agenthood and structured experience in natural systems, as well as the design of artificial intelligence and computational models of the brain.
Dynamic Linkages Between Economic Policy Uncertainty and External Variables in Latin America: Wavelet Analysis
Authors: Marín-Rodríguez Nini Johana , González-Ruiz Juan David , Botero Sergio
Published: January 2025

Wavelet coherence analysis (WCA) examines the dynamic interactions between economic policy uncertainty (EPU) in Brazil, Chile, Colombia, and Mexico and key external variables, using monthly data from 2010 to 2022. The findings reveal the following: (i) medium-term co-movements (4–16 months) between EPU and global financial indicators, including the Chicago Board Options Exchange (CBOE) Market Volatility Index (RVIX), Merrill Lynch Option Volatility Estimate Index (RMOVE), and Global EPU Index (RGEPU), emphasizing the sustained influence of financial volatility on domestic policy environments, particularly during global turbulence; (ii) significant interactions between EPU and the Climate Policy Uncertainty Index (RCPU) in resource-dependent economies like Brazil and Colombia, with pronounced effects in medium- and long-term horizons; (iii) bidirectional relationships between Brent crude oil prices (RBRENT) and EPU in Brazil, Colombia, and Mexico, where oil price fluctuations shape policy uncertainty, especially during global market disruptions; and (iv) notable co-movements between EPU and the Dow Jones Sustainability World Index (RW1SGI) in Brazil, Chile, and Mexico, highlighting sensitivity to shifts in sustainability-driven markets. These results underscore the need for economic diversification, strengthened financial safeguards, and integrated climate risk management to mitigate external shocks. By exploring the time–frequency dynamics of global uncertainties and domestic policy environments, this study provides actionable insights for fostering resilience and stability in Latin America’s interconnected economies while addressing vulnerabilities to global market volatility and sustainability transitions.
Assessment of the Sustainability of University Academic Programs for the Accreditation: A Complex Challenge
Authors: La Scalia Giada , Mancini Simona , Gambino Roberto , Ciaccio Maria
Published: January 2025

The accreditation of university academic programs is a critical process in ensuring the quality and standards of higher education. A significant component of this process is the assignment of reference lecturers who make these academic programs sustainable. The problem of determining the appropriate faculty members to accredit university academic programs is a multifaceted challenge. The selection of reference lecturers for accreditation is influenced by various factors, including their academic positions, the subject area of their sectors according to the bachelor’s or master’s degree in which they are delivered, and the number of students enrolled compared to the degree classes. Moreover, the evolving nature of higher education, given its increased emphasis on interdisciplinary topics, further complicates this assessment due also to the presence of professors or researchers coming from other departments. The development of an optimization algorithm capable of simultaneously considering all the constraints of the problem is therefore needed to address these challenges and achieve to a balanced approach for a sustainable didactic offer. The optimization algorithm works by maximizing the number of lecturers available as reference lecturers for other departments and minimizing those needed from other departments and from external teaching contracts. The problem of reference lecturers does not refer to the department alone but to the entire atheneum.
Power Insulator Defect Detection Method Based on Enhanced YOLOV7 for Aerial Inspection
Authors: Hu Jun , Wan Wenwei , Qiao Peng , Zhou Yongqi , Ouyang Aiguo
Published: January 2025

As a principal insulating component in power transmission systems, the integrity of the insulator is of paramount importance for ensuring the safe and reliable operation of transmission lines. While the deployment of aerial photography technology has markedly enhanced the efficacy of power facility inspections, the intricate backgrounds, multifarious viewpoint alterations, and erratic lighting circumstances inherent in the captured images present novel challenges for the algorithmic detection of insulator defects. To address these issues, this study proposes an enhanced version of the YOLOV7 detection algorithm. The introduction of the contextual transformer network (CoTNet) structure and an EMA attention mechanism enhances the model’s capacity to perceive global contextual information in images and to model long-distance feature dependencies. Experiments based on a real aerial photography dataset demonstrate that the proposed algorithm outperforms the benchmark model in all key performance indicators, including accuracy, recall, and F1 score, which improved by 0.6%, 1.8%, and 0.8%, respectively. Additionally, the average precision (mAP@[0.5]) and mAP@[0.5:0.95] improved by 0.6% and 4.4%, respectively. The superiority of the algorithm in feature extraction and target localization is verified through Grad-CAM visual analysis, which provides a high-precision detection method for intelligent inspection of power transmission systems.
Evaluation of the Efficiency of Solutions Used at Active Pedestrian Crossings
Authors: Pawlak Agnieszka , Pawelec Artur , Kossakowski Paweł Grzegorz
Published: January 2025

This article examines the components of active pedestrian crossing systems, focusing on an innovative solution implemented at Jaworski Street in Kielce. The proposed method for evaluating the effectiveness of this system is based on observations and performance analysis under conditions of limited visibility and increased pedestrian traffic. The key elements of the methodology include assessing the accuracy of pedestrian detection using IR/MW and curtain sensors, analyzing system errors such as false activations or failures to detect pedestrians, and evaluating driver responses to warning signals, with an emphasis on optimizing signal activation timing. The innovation of the method lies in its flexibility and real-time adaptability to dynamic traffic conditions, significantly enhancing system performance and pedestrian safety at crossings. Through integrated detection and activation time management mechanisms, the system can respond to changing conditions in real time, ensuring optimal operational effectiveness.
Negative Capacitance Analysis of Multi-Quantum-Well Light-Emitting Diodes
Authors: Xiao Yang , Feng Xiaoyu , Meng Yuan , He Longzhen , Zhang Pengzhe , Zhang Dongyan , Gao Shoushuai , Shields Philip , Tian Haitao , Liu Hongwei
Published: January 2025

To explain the negative capacitance (NC) characteristic of multi-quantum-well (MQW) LEDs, we calculated the continuity equation for a 10-period AlGaInP/GaInP multi-quantum-well (MQW) LED with a mesa size of 90 × 150 μm and build an MQW LED capacitor model. The carrier concentrations and capacitance–voltage characteristics across every quantum well region were analyzed by accounting for carrier spontaneous, Auger, and SRH recombination. In our model, a dynamic carrier lifetime iteration method with an iterative error of less than 1 × 10−14 ns was used to decouple carrier lifetime and electric field variables in the carrier continuity equation, providing a new way to enhance the accuracy of MQW continuous equations. Based on the calculated carrier concentration and lifetime of MQWs, we derived a multilayer epitaxial material LED capacitance equivalent circuit. The theoretical model characterizes the negative capacitance phenomenon at 1.75 V, which is consistent with the actual test results of the sample. Our theoretical analysis indicates that the negative capacitance mainly comes from the carrier recombination in the MQW region. Under low-frequency AC bias conditions, the negative capacitance phenomenon becomes more obvious. This work provides a useful reference for analyzing the capacitance and bandwidth characteristics of LEDs in the fields of display dimming and visible-light communication.
Optimization of Residential Indoor Thermal Environment by Passive Design and Mechanical Ventilation in Tropical Savanna Climate Zone in Nigeria, Africa
Authors: Xi Tianyu , Sa’ad Salanke Umar , Liu Xinyu , Sun Haibo , Wang Ming , Guo Fei
Published: January 2025

Thermal comfort is a fundamental goal of architecture aiming at protecting individuals from harsh weather conditions. In Nigeria’s savanna climate zone, such as Kaduna, poor indoor thermal comfort leads to over-reliance on air-conditioning systems. There is limited research on the application of passive design strategies in the Nigerian savanna climate, which creates a barrier to their widespread implementation in residential buildings. In response to the increased awareness of climate change and the need for sustainable design, this study explores the potential of passive design strategies, focusing on the combination of rooftop insulation and reflective materials with mechanical ventilation as a means of improving indoor thermal comfort solutions. This study conducted a 3-day field experiment of typical dwellings in Kaduna, a major city in the Nigerian savanna climate zone. The data collected from this experiment served as the basis for a simulation study using EnergyPlus software, which tested and evaluated 3 different strategies: passive design (roof insulation + reflective materials), mechanical ventilation, and a combination of passive design and mechanical ventilation. This study highlights the potential for passive design strategies to provide a more sustainable, cost-effective solution, reducing dependence on air conditioning while supporting indoor comfort. Additionally, the research methodology and insights gained offer a basis for developing future building codes in Nigeria that emphasize sustainable practices. Such codes would guide architects, builders, and policymakers in designing homes that respond to local climate needs and align with broader sustainability goals. Further research could explore additional passive measures, including advanced window technologies, shading, and natural ventilation, to maximize sustainable residential design potential in tropical savanna climates.
A Novel Approach to Production Allocation for Multi-Layer Commingled Tight Gas Wells: Insights from the Ordos Basin, NW China
Authors: Cheng Gang , Wei Yunsheng , Guo Zhi , Fu Bin , Wang Qifeng , Wang Guoting , Jiang Yanming , Meng Dewei , Han Jiangchen , Shen Yajing , Zhu Hanqing , Chen Kefei
Published: January 2025

During the development of multi-layer tight sandstone gas reservoirs in Ordos Basin, China, it has not been easy to calculate accurately the production of each individual layer in gas wells. However, production allocation provides a vital basis for evaluating dynamic reserves and drainage areas of gas wells and remaining gas distributions of gas layers. To improve the accuracy and reliability of production allocation of gas wells, a new model was constructed based on the seepage equation, material balance equation, and pipe string pressure equation. In particular, this new model introduced the seepage equation with an elliptical boundary to accurately capture the fluid flow characteristics within a lenticular tight gas reservoir. The new model can accurately calculate the production and reservoir pressure of each individual layer in gas wells. In addition, the new model was validated and applied in the Sulige gas field, Ordos Basin. The following conclusions were drawn: First, The gas production contribution rates of pay zones based on the new model are fairly close to the measurements of the production profile logging, with errors less than 10%. Second, The overall drainage area of a gas well lies among those of each pay zone, and the total dynamic reserves of the well are close to the sum of the dynamic reserves of pay zones. Third, Higher permeability may lead to higher initial gas production of the pay zone, but the ultimate gas production contributions of pay zones are affected jointly by permeability and dynamic reserves. Finally, The new model has been successfully applied to the SZ block of the Sulige gas field, in which the fine evaluation of dynamic reserves, drainage areas, gas production, recovery factors, and remaining gas distributions of different layers was delivered, and the application results provide technical support for the future well placement and enhanced gas recovery of the block.