bluuebunny/crossref_metadata_2025 huggingface dataset:
Augmenting CT-Guided Bone Biopsies Using 18F-FDG PET/CT Guidance
Authors: Droste Max F. , van Velden Floris H. P. , van Oosterom Matthias N. , Luijk Valentijn J. , Burgmans Mark C. , Buckle Tessa , van Leeuwen Fijs W. B. , Rietbergen Daphne D. D.
Published: July 2024

Computer tomography (CT)-guided percutaneous core biopsies are currently the gold standard in diagnostic procedures for patients with bone lesions of unknown kind. CT-guided biopsies can lead to misdiagnosis or repetition of biopsies in case of small or heterogeneous lesions. We hypothesize that molecular image guidance could be used to optimize the biopsy strategy, by supporting the detection of heterogeneous lesions or lesions without radiographic substrate. To evaluate this hypothesis, we investigated if and how the addition of 2-deoxy-2-18F-fluoro-D-glucose-positron emission tomography (18F-FDG-PET)/CT could augment routine CT-guided bone biopsies. To this end, 106 patients who underwent a CT-guided bone biopsy between April 2019 and April 2020, obtained from either a vertebral or peripheral bone, were included. Patients were divided into 2 groups: 36 patients received an 18F-FDG-PET/CT scan prior to their CT-guided bone biopsy (PET group), while 70 patients only had a morphological CT scan (CT group). Histopathology was used to categorize biopsies into five subgroups (inconclusive, benign, malignant or infectious disease, or normal tissue). In the PET group, the number of conclusive biopsies was significantly higher compared to the CT group (N = 33/36 (92%) versus N = 53/70 (76%); p < 0.05). Furthermore, the number of first-try biopsies was lower in the PET group compared to the CT group (1.9 vs. 2.54, p = 0.051). In conclusion, 18F-FDG-PET/CT imaging significantly increased the success rate of first-try CT-guided bone biopsies by showing less inconclusive biopsies and misdiagnosis.
Fluorescence-Guided Surgical Techniques in Adult Diffuse Low-Grade Gliomas: State-of-the-Art and Emerging Techniques: A Systematic Review
Authors: Picart Thiebaud , Gautheron Arthur , Caredda Charly , Ray Cédric , Mahieu-Williame Laurent , Montcel Bruno , Guyotat Jacques
Published: July 2024

Diffuse low-grade gliomas are infiltrative tumors whose margins are not distinguishable from the adjacent healthy brain parenchyma. The aim was to precisely examine the results provided by the intraoperative use of macroscopic fluorescence in diffuse low-grade gliomas and to describe the new fluorescence-based techniques capable of guiding the resection of low-grade gliomas. Only about 20% and 50% of low-grade gliomas are macroscopically fluorescent after 5-amino-levulinic acid (5-ALA) or fluorescein sodium intake, respectively. However, 5-ALA is helpful for detecting anaplastic foci, and thus choosing the best biopsy targets in diffuse gliomas. Spectroscopic detection of 5-ALA-induced fluorescence can detect very low and non-macroscopically visible concentrations of protoporphyrin IX, a 5-ALA metabolite, and, consequently, has excellent performances for the detection of low-grade gliomas. Moreover, these tumors have a specific spectroscopic signature with two fluorescence emission peaks, which is useful for distinguishing them not only from healthy brain but also from high-grade gliomas. Confocal laser endomicroscopy can generate intraoperative optic biopsies, but its sensitivity remains limited. In the future, the coupled measurement of autofluorescence and induced fluorescence, and the introduction of fluorescence detection technologies providing a wider field of view could result in the development of operator-friendly tools implementable in the operative routine.
The Influence of the ZrO2 Crystal Phase on Cu/ZrO2-Al2O3 Catalysts in Methanol Steam Reforming
Authors: Song Mouxiao , Li Li , Wu Xueshuang , Cai Haiqing , Li Guiying , Hu Changwei
Published: July 2024

Copper-based catalysts are widely used in methanol steam reforming to produce hydrogen. In this paper, the supportive effect of the crystal phase of ZrO2 on Cu-based catalysts in methanol steam reforming is discussed. Monoclinic(m-), Tetragonal(t-) and mixed ZrO2 phases were prepared, and structure–activity relationships were investigated with XRD, H2-TPR, BET, HR-TEM and XPS. It was found that the catalyst with a 81.4% monoclinic ZrO2 crystal phase exhibited the highest methanol conversion (88.5%) and the highest hydrogen production rate (104.6 μmol/gcat·s) at 275 °C as it displayed the best reducing properties and more oxygen vacancies on the catalyst surface. Oxygen vacancies can produce more Cu1+ + Cu0, which is the active species for methanol steam reforming on the catalyst surface, and therefore affect catalytic activity.
Advanced PtCo Catalysts Based on Platinum Acetate Blue for the Preferential CO Oxidation in H2-Rich Mixture
Authors: Shilina Marina , Krotova Irina , Nikolaev Sergey , Cherkashina Natalia , Stolarov Igor , Udalova Olga , Maksimov Sergey , Rostovshchikova Tatiana
Published: July 2024

Preferential oxidation of carbon monoxide (CO-PROX) in H2-rich mixture is an effective way of hydrogen purification for fuel cells. High-performance PtCo/ZSM-5 catalysts with reduced Pt loading for this process were prepared using polynuclear platinum acetate complex known as platinum acetate blue (PAB) of the empirical formula Pt(CH3COO)2.5 as a novel precursor. The impregnation of HZSM-5 (Si/Al = 15 and 28) with PAB and its decomposition at 200 °C resulted in the stabilization of highly dispersed Pt0 and PtOx species on the zeolite surface. The catalytic properties were improved by the addition of Co(CH3COO)2 followed by calcination at 450 °C. Produced materials were studied by SEM, TEM, EDX, XPS, and DRIFTS methods and tested in a CO-PROX reaction. The relationship between the synthesis conditions, structure, and catalytic behavior of composites is discussed in this paper. The synergistic effect of Pt and Co was observed when they both were located together in zeolite channels. The Pt-Co interaction provides new active catalytic sites and prevents platinum aggregation during the process. Due to this, the 100% CO conversion in the wide temperature range from 50 to 130 °C is achieved for PtCo/ZSM-5 catalysts (Si/Al = 15), which is the best result compared to low-loaded Pt catalysts prepared with traditional precursors.
Nucleophosmin: A Nucleolar Phosphoprotein Orchestrating Cellular Stress Responses
Authors: Taha Mohamed S. , Ahmadian Mohammad Reza
Published: July 2024

Nucleophosmin (NPM1) is a key nucleolar protein released from the nucleolus in response to stress stimuli. NPM1 functions as a stress regulator with nucleic acid and protein chaperone activities, rapidly shuttling between the nucleus and cytoplasm. NPM1 is ubiquitously expressed in tissues and can be found in the nucleolus, nucleoplasm, cytoplasm, and extracellular environment. It plays a central role in various biological processes such as ribosome biogenesis, cell cycle regulation, cell proliferation, DNA damage repair, and apoptosis. In addition, it is highly expressed in cancer cells and solid tumors, and its mutation is a major cause of acute myeloid leukemia (AML). This review focuses on NPM1’s structural features, functional diversity, subcellular distribution, and role in stress modulation.
Beyond Urban Forests: The Multiple Functions and the Overlooked Role of Semi-Natural Ecosystems in Mediterranean Cities
Authors: Guarino Riccardo , Catalano Chiara , Pasta Salvatore
Published: July 2024

In recent times, the misleading belief that the indiscriminate planting of a million trees is the panacea to some of the most serious and urgent environmental problems of our planet (such as soil erosion, climate change, etc.) has gained increasing popularity. However, the idea of “reforesting the planet” does not seem to adequately consider the fact that forests most often represent the last successional stage of terrestrial ecosystems, thus requiring—at least in the first years after planting within urban contexts—some care (hence time and money resources) to become large enough to fulfil the functions (climate mitigation, particulate capture, air purification, etc.) expected by public opinion. Starting from these critical considerations, this paper aims to highlight the need to carry out in-depth multidisciplinary investigations on the most suitable species and communities, underlining the fact that, to improve the environmental quality in urban areas, it is necessary to make appropriate choices, also considering the biogeographical contexts in which such interventions are made.
Decentralized UAV Swarm Control: A Multi-Layered Architecture for Integrated Flight Mode Management and Dynamic Target Interception
Authors: Xia Bingze , Mantegh Iraj , Xie Wenfang
Published: July 2024

Uncrewed Aerial Vehicles (UAVs) are increasingly deployed across various domains due to their versatility in navigating three-dimensional spaces. The utilization of UAV swarms further enhances the efficiency of mission execution through collaborative operation and shared intelligence. This paper introduces a novel decentralized swarm control strategy for multi-UAV systems engaged in intercepting multiple dynamic targets. The proposed control framework leverages the advantages of both learning-based intelligent algorithms and rule-based control methods, facilitating complex task control in unknown environments while enabling adaptive and resilient coordination among UAV swarms. Moreover, dual flight modes are introduced to enhance mission robustness and fault tolerance, allowing UAVs to autonomously return to base in case of emergencies or upon task completion. Comprehensive simulation scenarios are designed to validate the effectiveness and scalability of the proposed control system under various conditions. Additionally, a feasibility analysis is conducted to guarantee real-world UAV implementation. The results demonstrate significant improvements in tracking performance, scheduling efficiency, and overall success rates compared to traditional methods. This research contributes to the advancement of autonomous UAV swarm coordination and specific applications in complex environments.
Research on a Distributed Cooperative Guidance Law for Obstacle Avoidance and Synchronized Arrival in UAV Swarms
Authors: Liu Xinyu , Li Dongguang , Wang Yue , Zhang Yuming , Zhuang Xing , Li Hanyu
Published: July 2024

In response to the issue where the original synchronization time becomes inapplicable for UAV swarms after temporal consistency convergence due to obstacle avoidance, a new distributed consultative temporal consistency guidance law that takes into account threat avoidance has been proposed. Firstly, a six-degree-of-freedom dynamic model and a guidance control model for unmanned aerial vehicles (UAVs) are established, and the guidance commands are decomposed into control signals for the pitch and yaw planes. Secondly, based on the theory of dynamic inversion control, a temporal consistency guidance law for a single UAV is constructed. On the other hand, an improved artificial potential field theory is used and integrated with a predictive correction network to generate guidance commands for threat avoidance. A threshold smoothing method is employed to integrate the two guidance systems, and a cluster consultation mechanism is introduced to design a two-layer temporal synchronization architecture, which negotiates to change the synchronization time of the swarm to achieve the convergence of consistency once again. Finally, in typical application scenarios, simulation verification demonstrates the effectiveness of the control method proposed in this paper. The proposed control method achieves the guidance of UAV formations to synchronize their arrival at the target location under complex threat conditions.
Tunneling Currents in the Hyperbolic Phase Space
Authors: Valtierra Ivan F. , Klimov Andrei B.
Published: July 2024

We introduce the quantum currents for quantum systems with an SU(1,1) dynamic symmetry group whose evolution is governed by a non-linear Hamiltonian possessing a continuous spectrum and apply them to the analysis of the tunneling dynamics on the hyperbolic phase space.
A Novel Repeat PI Decoupling Control Strategy with Linear Active Disturbance Rejection for a Three-Level Neutral-Point-Clamped Active Power Filter with an LCL Filter
Authors: Gao Yifei , Zhu Liancheng , Wang Xiaoyang , Lv Xiaoguo , Wei Hongshi
Published: July 2024

The three-level neutral-point-clamped (NPC) active power filter (APF) is suitable for harmonic compensation in high voltage and large capacity applications. And, the harmonic compensation effect of APF depends on its dynamic performance and control. This paper propose a repeat proportional integral (PI) decoupling control strategy with linear active disturbance rejection (LADRC) to address the issues of detection in complex harmonic current and power supply current distortion when the nonlinear load varies. To simplify the design of LADRC, this paper adopts inverter current feedback control. Firstly, repeat control is introduced to optimize the traditional PI controller, which improves the compensation accuracy while ensuring the dynamic response capability of the control system. Then, to address the serious coupling of the system model in the d-q coordinate system, a reduced order linear active disturbance rejection (LADRC) control is introduced. The PI and linear extended state observer (LESO) control method is adopted in the outer voltage loop to maintain stable DC voltage and improve the ability to suppress voltage overshoot during grid connection. The effectiveness of this control method has been verified through MATLAB/Simlink. The results show that, compared with the repeat PI method, the control method based on repeat PI–LADRC can achieve better decoupling control, improve robustness and anti-interference ability, enhance the performance of the original system, and can significantly improve the harmonic suppression capability of the APF.
Design of a 200 W Flying Capacitor Multilevel Flyback Converter
Authors: Graziani Santino , Cook Thomas , Grainger Brandon
Published: July 2024

This directive proposes an efficiency optimization process in which the flying capacitor multilevel flyback converter (FCMFC) will be designed for the highest efficiency based on component selection, the number of flying capacitor stages, with isolation. The application of interest is a front-end voltage-boosting converter that is part of a solar microinverter. The converter will need high gain and high efficiency over a large range due to the variable input voltage supplied by the output of a solar panel. The electrical specifications are 40 V to 400 V conversion for a 200 W load; however, the input voltage and load power are subject to variability.
A Novel SCA-Based SOCP Method for Time-Varying Beamforming Optimization in RIS-Assisted MU-MISO Downlinks
Authors: Yang Fenghui , Liu Ting , Liu Sijia
Published: July 2024

Reconfigurable intelligent surface (RIS) is composed of large quantities of inexpensive passive elements, which is able to adjust phase and amplitude shifts to reduce the system power consumption. However, the complex coupling in the RIS-aided system makes the power minimization (PowerMin) problem more difficult when compared to conventional systems. In this paper, a three-dimensional (3D) time-varying channel model is proposed for RIS-assisted networks and a downlink expression between mobile vehicles and users is derived. Additionally, a successive convex approximation (SCA) method is provided and the transmitter beamformer and RIS phase shifts are updated simultaneously at each iteration to achieve a satisfactory numerical solution. Ultimately, the simulation model in MOSEK version 10.1.28 is utilized to verify the effectiveness of analytical results.
Quality Assessment of Light Field Images Based on Adaptive Attention in ViT
Authors: Du Yifan , Lang Wei , Hu Xinwen , Yu Li , Zhang Hua , Zhang Lingjun , Wu Yifan
Published: July 2024

Light field images can record multiple information about the light rays in a scene and provide multiple views from a single image, offering a new data source for 3D reconstruction. However, ensuring the quality of light field images themselves is challenging, and distorted image inputs may lead to poor reconstruction results. Accurate light field image quality assessment can pre-judge the quality of light field images used as input for 3D reconstruction, providing a reference for the reconstruction results before the reconstruction work, significantly improving the efficiency of 3D reconstruction based on light field images. In this paper, we propose an Adaptive Vision Transformer-based light-field image-quality assessment model (AViT-LFIQA). The model adopts a multi-view sub-aperture image sequence input method, greatly reducing the number of input images while retaining as much information as possible from the original light field image, alleviating the training pressure on the neural network. Furthermore, we design an adaptive learnable attention layer based on ViT, which addresses the lack of inductive bias in ViT by using adaptive diagonal masking and a learnable temperature coefficient strategy, making the model more suitable for training on small datasets of light field images. Experimental results demonstrate that the proposed model is effective for various types of distortions and shows superior performance in light-field image-quality assessment.
Sustainable Management and Advanced Nutrient Recovery from Biogas Energy Sector Effluents
Authors: Zielińska Magdalena , Bułkowska Katarzyna
Published: July 2024

Anaerobic digestion (AD) is an effective technology for the sustainable management of organic agricultural waste, producing both biogas and nutrient-rich digestate. This study aims to review and evaluate different methods for obtaining valuable products from digestate, with a focus on innovative and sustainable approaches. The main objectives are to identify effective technologies for the recovery of nutrients and organic matter, assess their environmental and economic impact and outline the challenges and prospects in this area. The review covers established techniques (with a technology readiness level (TRL) of six to nine, indicating their maturity from pilot to full scale) such as struvite precipitation and ammonia stripping, which are very effective in recovering nitrogen and phosphorus from digestate and converting it into valuable biofertilizers. Struvite, for example, offers an option for slow-release fertilizers that reduces dependence on synthetic fertilizers. A comparative analysis shows that ammonia stripping can efficiently capture nitrogen and produce fertilizer without harming the environment. New methods, such as microalgae cultivation, use digestate as a nutrient source for the production of biofuels and bioplastics, contributing to renewable energy and sustainable material production. The study also examines composting and vermicomposting, where digestate is converted into nutrient-rich soil conditioners that significantly improve soil health and fertility. The production of biochar through pyrolysis is highlighted for its benefits in improving soil properties and sequestering carbon, providing a dual benefit for waste management and climate change mitigation. Membrane technologies, including ultrafiltration (UF) and reverse osmosis (RO), are being investigated for their effectiveness in nutrient recovery, despite challenges such as membrane fouling and high operating costs. The study highlights the potential of these valorization processes to improve the sustainability and economic viability of AD systems and to align with circular economy principles. The results suggest that the continuous optimization of these technologies and the integration of recycling processes are crucial to overcome existing challenges and realize their full potential.
A New Method of Transformer Short-Circuit Impedance Regulation Based on Magnetic Shunts
Authors: Ye Zhijun , Jia Hao , Cai Wei , Zeng Wenhui
Published: July 2024

Short-circuit impedance is an important economic and technical index to test the cost, efficiency and operation safety of transformers. Increasing the short-circuit impedance of the transformer can reduce the influence of the transformer fault current on the system. The short-circuit impedance of a general power transformer is 4~7%. When the short-circuit impedance is too small, the short-circuit current is too large, which will cause harm to electrical equipment. This paper proposes a method to adjust the short-circuit impedance by adding magnetic shunts of different thicknesses between the high and low voltage windings of the transformer. Compared with other methods, this method does not change the structure of the transformer core and winding, and is simple and efficient. In this paper, a three-dimensional simulation model of a single-phase multi-winding transformer is established by Altair Flux to study the influence of the thickness of magnetic shunts on the short-circuit impedance of a transformer. The feasibility of the proposed method is verified by comparing the simulation with the measured values. The magnetic shunt is also introduced into the three-phase transformer. The result shows that adding magnetic shunts of different thicknesses between the high and low voltage windings of the transformer will change the distribution and size of the leakage of the magnetic field. The short-circuit impedance increases significantly with the increase in the thickness of the magnetic shunt, but a certain number of magnetic shunts have minimal effects on the efficiency of the transformer.
Reforming Climate and Development Finance for Clean Cooking
Authors: Coldrey Olivia , Lant Paul , Ashworth Peta , LaRocco Philip , Eibs Singer Christine
Published: July 2024

A transition to clean fuels and technology for cooking is increasingly recognised as a cornerstone of sustainable development. However, sufficient, appropriate, affordable finance to support the transition is lacking. Grounded in primary data collection via expert interviews, this study’s research objective was to critically assess development finance institutions’ (DFIs) delivery of climate and development finance to address cooking poverty. Interview findings underscore DFIs’ important role in the transition, including to create the ecosystem conditions conducive to sustained investment. However, as a group they are not demonstrating the risk appetite and financial solutions that clean cooking markets need. Nor are they operating with the agility and flexibility required for rapid scale-up. Consequently, DFIs are not optimally fulfilling their mandates to create additionality and mobilise private capital in these markets. Interviewees call for DFIs to reconsider their approach, and we rely on these findings to posit a theory of change for clean cooking finance.
Stochastic Optimal Strategies and Management of Electric Vehicles and Microgrids
Authors: Lin Faa-Jeng , Lu Su-Ying , Hu Ming-Che , Chen Yen-Haw
Published: July 2024

This study combines the Nash–Cournot competition model and the stochastic optimization model to examine the impact of electric vehicle (EV) quantity fluctuations on microgrid operations, aiming to optimize energy usage in a competitive electricity market. Integrating distributed energy resources and bidirectional charging, microgrids offer a novel approach for energy optimization, aiding in renewable energy generation, peak demand management, and emission reduction. Empirical evidence highlights benefits in Taiwan’s electricity market and net-zero emissions target by 2050, with a case study demonstrating enhanced local renewable energy generation due to EVs and microgrid integration. As the number of EVs increases, electricity sales from microgrids decline, but electricity purchases remain stable. The degree of electricity liberalization also influences the supply and demand dynamics of the electricity market. Microgrids selling electricity only to the main grid increases total power consumption by 65.55 million MWh, reducing the market share of the state-owned utility (Taipower). Conversely, allowing retailers to purchase from microgrids increases total consumption by 30.87 million MWh with a slight market share decrease for Taipower. This study contributes to providing an adaptable and flexible general model for future studies to modify and expand based on different scenarios and variables to shape energy and environmental policies.
A New Power-Sharing Strategy with Photovoltaic Farms and Concentrated Diesel Generators to Increase Power System Resilience
Authors: Zamanzad Ghavidel Behnam , Liao Yuan
Published: July 2024

This paper provides a power-sharing strategy designed for an islanded grid that becomes isolated from the main grid due to faults or natural disasters. The proposed topology is introduced for post-disaster scenarios where the restoration process may be time-consuming (from a few hours to a few months). This system is equipped with a step-by-step power-sharing strategy based on priority, inputs from photovoltaic sources, and a diesel generator to enhance reliability. The DC–AC inverter control and AC–DC–AC control for the diesel generator are presented, which provide flexible real and reactive control. The system is divided into three priority load areas, and power sharing is conducted based on these priorities. The distinctive feature of the proposed strategy lies in its ability to manage power-sharing under different power generation conditions, prioritizing critical loads. The proposed method is implemented using the MATLAB Simulink environment. Simulation studies are performed under different solar irradiances and variations in the diesel generator’s output to validate the performance of the proposed method. The results demonstrate the practicality of the proposed algorithm in harnessing renewable resources and diesel generators and dynamically managing the energy consumption in loads.
Machine-Learning-Based Anomaly Detection for GOOSE in Digital Substations
Authors: Nhung-Nguyen Hong , Girdhar Mansi , Kim Yong-Hwa , Hong Junho
Published: July 2024

Digital substations have adopted a high amount of information and communication technology (ICT) and cyber–physical systems (CPSs) for monitoring and control. As a result, cyber attacks on substations have been increasing and have become a major concern. An intrusion-detection system (IDS) could be a solution to detect and identify the abnormal behaviors of hackers. In this paper, a Deep Neural Network (DNN)-based IDS is proposed to detect malicious generic object-oriented substation event (GOOSE) communication over the process and station bus network, followed by the multiclassification of the cyber attacks. For training, both the abnormal and the normal substation networks are monitored, captured, and logged, and then the proposed algorithm is applied for distinguishing normal events from abnormal ones within the network communication packets. The designed system is implemented and tested with a real-time IEC 61850 GOOSE message dataset using two different approaches. The experimental results show that the proposed system can successfully detect intrusions with an accuracy of 98%. In addition, a comparison is performed in which the proposed IDS outperforms the support vector machine (SVM)-based IDS.
Satellite Remote Sensing Images of Crown Segmentation and Forest Inventory Based on BlendMask
Authors: Ji Zicheng , Xu Jie , Yan Lingxiao , Ma Jiayi , Chen Baozhe , Zhang Yanfeng , Zhang Li , Wang Pei
Published: July 2024

This study proposes a low-cost method for crown segmentation and forest inventory based on satellite remote sensing images and the deep learning model BlendMask. Taking Beijing Jingyue ecoforestry as the experimental area, we combined the field survey data and satellite images, and constructed the dataset independently, for model training. The experimental results show that the F1-score of Sophora japonica, Pinus tabulaeformis, and Koelreuteria paniculata reached 87.4%, 85.7%, and 86.3%, respectively. Meanwhile, we tested for the study area with a total area of 146 ha, and 27,403 tree species were identified in nine categories, with a total crown projection area of 318,725 m2. We also fitted a biomass calculation model for oil pine (Pinus tabulaeformis) based on field measurements and assessed 205,199.69 kg of carbon for this species across the study area. Additionally, we compared the model to U-net, and the results showed that BlendMask has strong crown-segmentation capabilities. This study demonstrates that BlendMask can effectively perform crown segmentation and forest inventory in large-scale complex forest areas, showing its great potential for forest resource management.
MIMA: Multi-Feature Interaction Meta-Path Aggregation Heterogeneous Graph Neural Network for Recommendations
Authors: Li Yang , Yan Shichao , Zhao Fangtao , Jiang Yi , Chen Shuai , Wang Lei , Ma Li
Published: July 2024

Meta-path-based heterogeneous graph neural networks have received widespread attention for better mining the similarities between heterogeneous nodes and for discovering new recommendation rules. Most existing models depend solely on node IDs for learning node embeddings, failing to leverage attribute information fully and to clarify the reasons behind a user’s interest in specific items. A heterogeneous graph neural network for recommendation named MIMA (multi-feature interaction meta-path aggregation) is proposed to address these issues. Firstly, heterogeneous graphs consisting of user nodes, item nodes, and their feature nodes are constructed, and the meta-path containing users, items, and their attribute information is used to capture the correlations among different types of nodes. Secondly, MIMA integrates attention-based feature interaction and meta-path information aggregation to uncover structural and semantic information. Then, the constructed meta-path information is subjected to neighborhood aggregation through graph convolution to acquire the correlations between different types of nodes and to further facilitate high-order feature fusion. Furthermore, user and item embedding vector representations are obtained through multiple iterations. Finally, the effectiveness and interpretability of the proposed approach are validated on three publicly available datasets in terms of NDCG, precision, and recall and are compared to all baselines.
Spatio-Temporal Analysis of Wildfire Regimes in Miombo of the LevasFlor Forest Concession, Central Mozambique
Authors: Meneses Osvaldo M. , Ribeiro Natasha S. , Shirvani Zeinab , Andrew Samora M.
Published: July 2024

Wildfires are an intrinsic and vital driving factor in the Miombo ecosystem. Understanding fire regimes in Miombo is crucial for its ecological sustainability. Miombo is dominant in Central Mozambique, having one of the highest fire incidences in the country. This study evaluated the spatio-temporal patterns of fire regimes (intensity, seasonality, frequency and fire return interval) in the LevasFlor Forest Concession (LFC), Central Mozambique using remotely sensed data from 2001 to 2022. We conducted hotspot spatial statistics using the Getis-Ord Gi* method to assess fire distribution and patterns. The results revealed that 88% of the study area was burnt at least once from 2001 to 2022, with an average burned area of 9733 ha/year (21% of LFC’s total area). Fires were more likely to occur (74.4%) in open and deciduous Miombo types. A total of 84% of the studied area, burned in a range of 4 to 22 years of fire return interval (FRI) over the 21 assessed. Only 16% of the area was affected by high to very high FRI (1 to 4 years), with an average FRI of 4.43 years. Generally, fires are more frequent and intense in September and October. These results highlight the usefulness of remote sensing in evaluating long-term spatiotemporal fire trends for effective fire management strategies and control measures in African savanna ecosystems.
Influence of Adding Small Instream Wood on Fishes and Hydraulic Conditions in Channelized Agricultural Headwater Streams
Authors: Gates Eric J. , Smiley Peter C.
Published: July 2024

Instream wood is important for fish in headwater streams because it promotes the development of pool habitat and provides cover from predators during periods of low flow. The benefits of large instream wood (length > 1 m and diameter > 0.1 m) have been extensively documented, but little is known about the influence of small instream wood (length ≤ 1 m or diameter ≤ 0.1 m) on fish communities and hydraulic conditions (i.e., water depth, water velocity, wetted width, discharge, pool area) in channelized agricultural headwater streams in North America and Europe. Understanding the influence of small instream wood will provide information that can guide the development of novel management strategies for fishes within these degraded streams. We conducted a two-part field experiment in the summer of 2011 in channelized agricultural headwater streams in central Ohio, consisting of an initial instream wood survey to document the amounts and types of instream wood found in these streams, and then conducted a before–after–control–impact experiment where we sampled fishes and hydraulic variables before and after the addition of small instream wood to pools. The instream wood survey documented that instream wood density ranged from 0 to 0.29 pieces/m2, small simple pieces were the most frequently occurring type of instream wood, and parallel was the most frequently occurring instream wood orientation. The amount of instream wood was greater (p < 0.05) in the treatment pools than the control pools after the small instream wood addition. No differences (p > 0.450) in fish community structure or hydraulic variables occurred between control and treatment pools before or after the addition of small instream wood. Our results suggest the addition of large instream wood might be needed to elicit a fish community response, and it is possible to add instream wood to channelized agricultural headwater streams without impeding the downstream water flow.
Analysis of Truncated M-Fractional Mathematical and Physical (2+1)-Dimensional Nonlinear Kadomtsev–Petviashvili-Modified Equal-Width Model
Authors: Alomair Mohammed Ahmed , Junjua Moin-ud-Din
Published: July 2024

This study focuses on the mathematical and physical analysis of a truncated M-fractional (2+1)-dimensional nonlinear Kadomtsev–Petviashvili-modified equal-width model. The distinct types of the exact wave solitons of an important real-world equation called the truncated M-fractional (2+1)-dimensional nonlinear Kadomtsev–Petviashvili-modified equal-width (KP-mEW) model are achieved. This model is used to explain ocean waves, matter-wave pulses, waves in ferromagnetic media, and long-wavelength water waves. The diverse patterns of waves on the oceans are yielded by the Kadomtsev–Petviashvili-modified equal-width (KP-mEW) equation. We obtain kink-, bright-, and periodic-type soliton solutions by using the expa function and modified extended tanh function methods. The solutions are more valuable than the existing results due to the use of a truncated M-fractional derivative. These solutions may be useful in different areas of science and engineering. The methods applied are simple and useful.
Quantum Laplace Transforms for the Ulam–Hyers Stability of Certain q-Difference Equations of the Caputo-like Type
Authors: Etemad Sina , Stamova Ivanka , Ntouyas Sotiris K. , Tariboon Jessada
Published: July 2024

We aim to investigate the stability property for the certain linear and nonlinear fractional q-difference equations in the Ulam–Hyers and Ulam–Hyers–Rassias sense. To achieve this goal, we prove that three types of the linear q-difference equations of the q-Caputo-like type are Ulam–Hyers stable by using the quantum Laplace transform and quantum Mittag–Leffler function. Moreover, after proving the existence property for a nonlinear Cauchy q-difference initial value problem, we use the same quantum Laplace transform and the q-Gronwall inequality to show that it is generalized Ulam–Hyers–Rassias stable.
Adaptive Morphing Activation Function for Neural Networks
Authors: Herrera-Alcántara Oscar , Arellano-Balderas Salvador
Published: July 2024

A novel morphing activation function is proposed, motivated by the wavelet theory and the use of wavelets as activation functions. Morphing refers to the gradual change of shape to mimic several apparently unrelated activation functions. The shape is controlled by the fractional order derivative, which is a trainable parameter to be optimized in the neural network learning process. Given the morphing activation function, and taking only integer-order derivatives, efficient piecewise polynomial versions of several existing activation functions are obtained. Experiments show that the performance of polynomial versions PolySigmoid, PolySoftplus, PolyGeLU, PolySwish, and PolyMish is similar or better than their counterparts Sigmoid, Softplus, GeLU, Swish, and Mish. Furthermore, it is possible to learn the best shape from the data by optimizing the fractional-order derivative with gradient descent algorithms, leading to the study of a more general formula based on fractional calculus to build and adapt activation functions with properties useful in machine learning.
A Review of Power System False Data Attack Detection Technology Based on Big Data
Authors: Chang Zhengwei , Wu Jie , Liang Huihui , Wang Yong , Wang Yanfeng , Xiong Xingzhong
Published: July 2024

As power big data plays an increasingly important role in the operation, maintenance, and management of power systems, complex and covert false data attacks pose a serious threat to the safe and stable operation of the power system. This article first explores the characteristics of new power systems, and the challenges posed by false data attacks. The application of big data technology in power production optimization, energy consumption analysis, and user service improvement is then investigated. The article classifies typical attacks against the four stages of power big data systems in detail and analyzes the characteristics of the attack types. It comprehensively summarizes the attack detection technologies used in the four key stages of power big data, including state estimation, machine learning, and data-driven attack detection methods in the data collection stage; clock synchronization monitoring and defense strategies in the data transmission stage; data processing and analysis, data integrity verification and protection measures of blockchain technology in the third stage; and traffic supervision, statistics and elastic computing measures in the control and response stage. Finally, the limitations of attack detection mechanisms are proposed and discussed from three dimensions: research problems, existing solutions, and future research directions. It aims to provide useful references and inspiration for researchers in power big data security to promote technological progress in the safe and stable operation of power systems.
Predicting the Current and Future Distribution of Monolepta signata (Coleoptera: Chrysomelidae) Based on the Maximum Entropy Model
Authors: Liu Qingzhao , Zhao Jinyu , Hu Chunyan , Ma Jianguo , Deng Caiping , Ma Li , Qie Xingtao , Yuan Xiangyang , Yan Xizhong
Published: July 2024

Monolepta signata is a polyphagous and highly destructive agricultural pest, currently only distributed in Asia. In its place of origin, it poses a serious threat to important economic crops, for instance, maize (Zea mays L.) and cotton (Gossypium hirsutum L.). Based on morphological and molecular data research, it has been found that M. quadriguttata (Motschulsky), M. hieroglyphica (Motschulsky), and M. signata are actually the same species. This discovery means that the range of this pest will expand, and it also increases the risk of it spreading to non-native areas worldwide. It is crucial for global agricultural production to understand which countries and regions are susceptible to invasion by M. signata and to formulate corresponding prevention, control, and monitoring strategies. This study uses the maximum entropy model, combined with bioclimatic variables and elevation, to predict the potentially suitable areas and diffusion patterns of M. signata worldwide. The results indicate that in its suitable area, M. signata is mainly affected by three key climatic factors: Precipitation of Wettest Month (bio13), Mean Temperature of Warmest Quarter (bio10), and Temperature Seasonality (bio4). Under the current status, the total suitable region of M. signata is 252,276.71 × 104 km2. In addition to its native Asia, this pest has potentially suitable areas in Oceania, South America, North America, and Africa. In the future, with climate change, the suitable area of M. signata will expand to high-latitude areas and inland areas. This study found that by the 2070s, under the SSP5-8.5 climate scenario, the change in the potentially suitable area of this insect is the largest. By identifying the potentially suitable areas and key climatic factors of M. signata, we can provide theoretical and technical support to the government, enabling them to more effectively formulate strategies to deal with the spread, outbreak, and invasion of M. signata.
Discriminating Malignant from Benign Testicular Masses Using Multiparametric Magnetic Resonance Imaging—A Prospective Single-Center Study
Authors: Törzsök Peter , Deininger Susanne , Abenhardt Michael , Oswald David , Lusuardi Lukas , Deininger Christian , Forstner Rosemarie , Meissnitzer Matthias , Brandtner Herwig , Hecht Stefan
Published: July 2024

Objective: The objective of this study was to prospectively assess the extent to which magnetic resonance imaging (MRI) can differentiate malignant from benign lesions of the testis. Materials and Methods: All included patients underwent multiparametric testicular MRI, including diffusion-weighted imaging (DWI) and subtraction dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). Subsequently, all patients underwent a histopathological examination via orchiectomy or testicular biopsy/partial resection. The Kolmogorov–Smirnov test, t-test, Mann–Whitney U test, Fisher’s exact test, and logistic regression were applied for statistical analysis. Results: We included 48 male patients (median age 37.5 years [range 18–69]) with testicular tumors. The median tumor size on MRI was 2.0 cm for malignant tumors and 1.1 cm for benign tumors (p < 0.05). A statistically significant difference was observed for the type (type 0-III curve, p < 0.05) and pattern of enhancement (homogeneous, heterogeneous, or rim-like, p < 0.01) between malignant and benign tumors. The minimum apparent diffusion coefficient (ADC) value was 0.9 for benign tumors and 0.7 for malignant tumors (each ×103 mm2/s, p < 0.05), while the mean ADC was 0.05. The mean ADC value was significantly lower for malignant tumors; the mean ADC value was 1.1 for benign tumors and 0.9 for malignant tumors (each ×103 mm2/s, p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of multiparametric MRI for differentiating malignant from benign testicular lesions were 94.3%, 76.9%, 91.7%, and 83.3%, respectively. The surgical procedures performed included orchiectomy (n = 33; 71.7%) and partial testicular resection (n = 11; 23.9%). Histopathology (HP) revealed malignancy in 35 patients (72.9%), including 26 with seminomas and 9 with non-seminomatous germ cell tumors (NSGCTs). The HP was benign in 13 (27.1%) patients, including 5 with Leydig cell tumors. Conclusions: Malignant and benign tumors differ in MRI characteristics in terms of the type and pattern of enhancement and the extent of diffusion restriction, indicating that MRI can be an important imaging modality for the accurate diagnosis of testicular lesions.
How the Mode of Delivery Is Influenced by Patient’s Opinions and Risk-Informed Consent in Women with a History of Caesarean Section? Is Vaginal Delivery a Real Option after Caesarean Section?
Authors: Cobec Ionut Marcel , Rempen Andreas , Anastasiu-Popov Diana-Maria , Eftenoiu Anca-Elena , Moatar Aurica Elisabeta , Vlad Tania , Sas Ioan , Varzaru Vlad Bogdan
Published: July 2024

Background/Objectives: In recent years, there has been a noticeable increase in the rates of caesarean section (CS), being one of the most commonly performed surgical procedures. For the following pregnancy, the previous CS represents the backbone of the risks and complications, such as uterine scar formation, uterine rupture, massive bleeding, and serious negative outcomes for both the mother and child. Our study followed patients with a history of CS from the birth planning prenatal check-up to delivery. Methods: We reviewed the records of 125 pregnant women with previous CS who presented in the third trimester for a prenatal check-up and completed our questionnaire from March 2021 to April 2022 in the Clinic of Obstetrics and Gynecology, Diakoneo Diak Klinikum Schwäbisch Hall, Germany. Results: Before the prenatal check-up, 74 patients (59.2%) preferred vaginal delivery (VD), while 51 (40.8%) preferred CS. After discussing birth planning with the obstetrician, 72 women (57.6%) decided upon VD, while 53 (42.4%) preferred CS. Ultimately, 78 (62.4%) of women gave birth through CS (either planned or by medical necessity) and 47 (37.6%) gave birth vaginally (either natural or per vacuum extraction). Conclusions: VD for patients with CS in their medical history is a real option. The patient must be well informed about the risks and benefits of the medical situation and should be empowered and supported on their chosen mode of delivery, which should be respected.
The Role of Bone Tacks in Sinus Floor Lift Surgery: A Single-Center Experience
Authors: Chisci Glauco , Fredianelli Luca , Brunacci Maria Giulia , Hatia Arjeta , Minichilli Fabrizio
Published: July 2024

Background: Maxillar atrophy is a prevalent condition associated with diminished bone volume, which precludes the conventional placement of dental implants. Sinus floor lift is a surgical procedure that aims to address this atrophy through the insertion of a graft within the sinus cavity. A multitude of techniques have been documented in the international literature for the management of the sinus bone window, though each approach has its own set of advantages and disadvantages. Methods: The present study is a retrospective analysis of traditional sinus floor lift surgery, comparing the outcomes of two surgical approaches: placement of a collagen membrane over the maxillary lateral bone window with or without bone tacks. The study enrolled a total of 48 consecutive patients. Twenty-four patients underwent sinus floor lift surgery, with the placement of a collagen membrane over the maxillary lateral bone window without bone tacks (control group). The remaining 24 patients underwent the same procedure, but with bone tacks (study group). All patients received an amoxicillin 875 mg + clavulanic acid 125 mg administration for six days and underwent Cone Beam Computed Tomography (CBCT) before the sinus floor lift surgery and six months later before the implant surgery. The parameters measured on the preoperative Cone Beam Computed Tomography (CBCT) scan included residual bone, the preoperative thickness of the lateral bone in the center, and the distance between the lateral wall and the medial wall of the sinus. Only the bone height increment was measured on the postoperative CBCT scan. Postoperative complications and the visual analogue scale (VAS) score were also recorded. A statistical analysis was performed, and the correlation between the parameters was evaluated using Pearson’s correlation coefficient. A comparison of the mean of the parameters between the treatment group and the control group was conducted using the t-test. Results and Conclusions: The study group was found to have superior outcomes in terms of bone height increment (p = 0.001) and VAS after 7 days (p = 0.11) compared to the control group. The novel application of bone tacks on the collagen membrane over the bone window following sinus elevation surgery was associated with superior outcomes in terms of bone height and reduced pain at seven days, as measured by the VAS, with no postoperative complications.