bluuebunny/crossref_metadata_2025 huggingface dataset:
Fast Track Management of Primary Thyroid Lymphoma in the Very Elderly Patient
Authors: Marcy Pierre Yves , Bauduer Frederic , Thariat Juliette , Gisserot Olivier , Ghanassia Edouard , Chetaille Bruno , Boudin Laurys , Morvan Jean Baptiste
Published: June 2023

A rapid growing cervical mass mobile while swallowing is the most common clinical presentation of severe thyroid malignancy. A 91-year-old female patient with a history of Hashimoto thyroiditis presented with clinical compressive neck symptoms. The patient had gastric Maltoma diagnosed that was surgically resected thirty years ago. A straightforward process was needed to reach full histological diagnosis and initiate prompt therapy. Ultrasound (US) showed a 67 mm hypoechoic left thyroid mass with reticulated pattern without signs of locoregional invasion. Percutaneous trans isthmic US-guided 18G core needle biopsy (CNB) disclosed diffuse large B cell lymphoma of the thyroid gland. FDG PET revealed two distinct thyroid and gastric foci (both SUVmax 39.1). Therapy was initiated rapidly to decrease clinical symptoms in this aggressive stage III primitive malignant thyroid lymphoma. The prognostic nomogram was calculated by using a seven-item scale, which disclosed a one-year overall survival rate of 52%. The patient underwent three R-CVP chemotherapy courses, then refused further treatment and died within five months. Real-time US-guided CNB approach led to rapid patient’s management that was tailored to patient’s characteristics. Transformation of Maltoma into diffuse large B cell lymphoma (DLBCL) into two body areas is deemed to be extremely rare.
Marine Invertebrate Neoextinctions: An Update and Call for Inventories of Globally Missing Species
Authors: Carlton James T.
Published: June 2023

The register of global extinctions of marine invertebrates in historical time is updated. Three gastropod and one insect species are removed from the list of extinct marine species, while two gastropods, one echinoderm, and three parasites (a nematode, an amphipod, and a louse) are added. The nine extinct marine invertebrates now recognized likely represent a minute fraction of the actual number of invertebrates that have gone extinct. Urgently needed for evaluation are inventories of globally missing marine invertebrates across a wide range of phyla. Many such species are likely known to systematists, but are either rarely flagged, or if mentioned, are not presented as potentially extinct taxa.
Electricity Pricing and Its Role in Modern Smart Energy System Design: A Review
Authors: Liu Jiaqi , Hu Hongji , Yu Samson S. , Trinh Hieu
Published: June 2023

Energy is the foundation for human survival and socio-economic development, and electricity is a key form of energy. Electricity prices are a key factor affecting the interests of various stakeholders in the electricity market, playing a significant role in the sustainable development of energy and the environment. As the number of distributed energy resources (DERs) increases, today’s power systems no longer rely on a vertical market model and fixed electricity pricing scheme but instead depend on power dispatch and dynamic pricing to match supply and demand. This can help prevent significant fluctuations in supply–load imbalance and maintain system stability. Modern power grids have evolved by integrating information, communication, and intelligent control technologies with traditional power systems, giving rise to the concept of smart electric grids. Choosing an appropriate pricing scheme to manage large-scale DERs and controllable loads in today’s power grid become very important. However, the existing literature lacks a comprehensive review of electricity pricing in power systems and its transformative impact on shaping the energy landscape. To fill this void, this paper provides a survey on the developments, methods, and frameworks related to electricity pricing and energy trading. The review mainly considers the development of pricing in a centralized power grid, peer-to-peer (P2P) and microgrid-to-microgrid (M2M) energy trading and sharing, and various pricing methods. The review will cover the pricing schemes in modern power systems, particularly with respect to renewable energy sources (RESs) and batteries, as well as controllable load applications, and the impact of pricing schemes based on demand-side ancillary services (DSAS) for grid frequency support. Lastly, this review article describes the current frameworks and limitations of electricity pricing in the current energy market, as well as future research directions. This review should offer a great overview and deep insights into today’s electricity market and how pricing methods will drive and facilitate the future establishment of smart energy systems.
A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications
Authors: Zhang Zhengxin , Zhu Lixue
Published: June 2023

In recent years, UAV remote sensing has gradually attracted the attention of scientific researchers and industry, due to its broad application prospects. It has been widely used in agriculture, forestry, mining, and other industries. UAVs can be flexibly equipped with various sensors, such as optical, infrared, and LIDAR, and become an essential remote sensing observation platform. Based on UAV remote sensing, researchers can obtain many high-resolution images, with each pixel being a centimeter or millimeter. The purpose of this paper is to investigate the current applications of UAV remote sensing, as well as the aircraft platforms, data types, and elements used in each application category; the data processing methods, etc.; and to study the advantages of the current application of UAV remote sensing technology, the limitations, and promising directions that still lack applications. By reviewing the papers published in this field in recent years, we found that the current application research of UAV remote sensing research can be classified into four categories according to the application field: (1) Precision agriculture, including crop disease observation, crop yield estimation, and crop environmental observation; (2) Forestry remote sensing, including forest disease identification, forest disaster observation, etc.; (3) Remote sensing of power systems; (4) Artificial facilities and the natural environment. We found that in the papers published in recent years, image data (RGB, multi-spectral, hyper-spectral) processing mainly used neural network methods; in crop disease monitoring, multi-spectral data are the most studied type of data; for LIDAR data, current applications still lack an end-to-end neural network processing method; this review examines UAV platforms, sensors, and data processing methods, and according to the development process of certain application fields and current implementation limitations, some predictions are made about possible future development directions.
Towards Robust Visual Tracking for Unmanned Aerial Vehicle with Spatial Attention Aberration Repressed Correlation Filters
Authors: Zhang Zhao , He Yongxiang , Guo Hongwu , He Jiaxing , Yan Lin , Li Xuanying
Published: June 2023

In recent years, correlation filtering has been widely used in the field of UAV target tracking for its high efficiency and good robustness, even on a common CPU. However, the existing correlation filter-based tracking methods still have major problems when dealing with challenges such as fast moving targets, camera shake, and partial occlusion in UAV scenarios. Furthermore, the lack of reasonable attention mechanism for distortion information as well as background information prevents the limited computational resources from being used for the part of the object most severely affected by interference. In this paper, we propose the spatial attention aberration repressed correlation filter, which models the aberrations, makes full use of the spatial information of aberrations and assigns different attentions to them, and can better cope with these challenges. In addition, we propose a mechanism for the intermittent learning of the global context to balance the efficient use of limited computational resources and cope with various complex scenarios. We also tested the mechanism on challenging UAV benchmarks such as UAVDT and Visdrone2018, and the experiments show that SAARCF has better performance than state-of-the-art trackers.
Irreversible Geometrothermodynamics of Open Systems in Modified Gravity
Authors: Pinto Miguel A. S. , Harko Tiberiu , Lobo Francisco S. N.
Published: June 2023

In this work, we explore the formalism of the irreversible thermodynamics of open systems and the possibility of gravitationally generated particle production in modified gravity. More specifically, we consider the scalar–tensor representation of f(R,T) gravity, in which the matter energy–momentum tensor is not conserved due to a nonminimal curvature–matter coupling. In the context of the irreversible thermodynamics of open systems, this non-conservation of the energy–momentum tensor can be interpreted as an irreversible flow of energy from the gravitational sector to the matter sector, which, in general, could result in particle creation. We obtain and discuss the expressions for the particle creation rate, the creation pressure, and the entropy and temperature evolutions. Applied together with the modified field equations of scalar–tensor f(R,T) gravity, the thermodynamics of open systems lead to a generalization of the ΛCDM cosmological paradigm, in which the particle creation rate and pressure are considered effectively as components of the cosmological fluid energy–momentum tensor. Thus, generally, modified theories of gravity in which these two quantities do not vanish provide a macroscopic phenomenological description of particle production in the cosmological fluid filling the Universe and also lead to the possibility of cosmological models that start from empty conditions and gradually build up matter and entropy.
Soft Skills and Study-Related Factors: Direct and Indirect Associations with Academic Achievement and General Distress in University Students
Authors: Casali Nicole , Meneghetti Chiara
Published: June 2023

Numerous noncognitive factors have been shown to influence students’ academic and nonacademic outcomes, yet few studies have contemporarily studied these factors to understand their specific roles. The present study tested a model in which five soft skills (i.e., epistemic curiosity, creativity, critical thinking, perseverance, and social awareness) were conceived as personal qualities that influence achievement and general distress through the mediation of four study-related factors (i.e., achievement emotions, self-regulated learning strategies, motivational beliefs, and study resilience). A total of 606 Italian university students (153 males, Mage = 22.74, SDage = 3.72) participated in the study and completed self-report measures of soft skills, study-related factors, and general distress measures; grades were considered for academic achievement. Results showed that all four study-related factors significantly mediated the relationship of soft skills with academic achievement, while only achievement emotions and study resilience emerged as significant mediators between soft skills and general distress. Our findings indicated complex relations between individual factors and students’ outcomes due to several factors. The theoretical and practical implications are discussed.
Exploring the Impact of Fe-Implantation on the Electrical Characteristics of Al/p-Si Schottky Barrier Diodes
Authors: Bodunrin Joseph Oluwadamilola , Oeba Duke Ateyh , Moloi Sabata Jonas
Published: June 2023

The effects of Fe-implantation on the electrical characteristics of Au/p-Si Schottky barrier diodes (SBDs) were studied using current–voltage (I–V) and capacitance–voltage (C–V) techniques. The Rutherford Backscattering Spectrometry (RBS) and Energy Dispersive Spectroscopy (EDS) results showed that Fe ions are well implanted and present in the Fe-implanted Si material. The acquired results from I–V and C–V analysis showed that the diodes were well fabricated, and Fe-implantation changed the normal diode’s I–V behaviour from typical exponential to ohmic. The ohmic behaviour was described in terms of the defect levels induced by Fe in the middle of the band gap of Si. The conduction mechanism for both forward and reverse currents was presented, and the effect of Fe-implantation on the conduction mechanisms was investigated. The C–V results show that Fe generates a high density of minority carriers in p-Si, which agreed with the increase in reverse current observed in the I–V results. The diode parameters in terms of saturation current, ideality factor, Schottky barrier height, doping density, and space charge region (SCR) width were used to investigate the effect of Fe in p-Si based diode. Owing to the observed changes, which were analogous to those induced by dopants that improve the radiation hardness of silicon, it was safe to say that Fe can also assist in the quest to improve the radiation hardness of silicon using the defect-engineering method.
Vehicle to Infrastructure-Based LiDAR Localization Method for Autonomous Vehicles
Authors: Kim Myeong-jun , Kwon Ohsung , Kim Jungha
Published: June 2023

The localization of autonomous vehicles using light detection and ranging (LiDAR) sensors relies on high-definition (HD) maps, which are essential for accurate positioning. However, the large storage capacity required for HD maps poses challenges for real-time performance. To address this issue, we propose a vehicle to infrastructure (V2I)-based LiDAR localization method. In this approach, real-time HD maps are transmitted to vehicles in the vicinity of the infrastructure, enabling localization without the need for map data. We conducted tests to determine the optimal size of the HD maps and the distance between vehicles and the infrastructure, considering the impact on transmission speed. Additionally, we compared the matching performance between the complete HD map and sub maps received from the infrastructure, to evaluate the effectiveness of our method in a qualitative manner.
Privacy-Enhancing Technologies in Federated Learning for the Internet of Healthcare Things: A Survey
Authors: Mosaiyebzadeh Fatemeh , Pouriyeh Seyedamin , Parizi Reza M. , Sheng Quan Z. , Han Meng , Zhao Liang , Sannino Giovanna , Ranieri Caetano Mazzoni , Ueyama Jó , Batista Daniel Macêdo
Published: June 2023

Advancements in wearable medical devices using the IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), efficient healthcare services can be provided to patients. Healthcare professionals have effectively used AI-based models to analyze the data collected from IoHT devices to treat various diseases. Data must be processed and analyzed while avoiding privacy breaches, in compliance with legal rules and regulations, such as the HIPAA and GDPR. Federated learning (FL) is a machine learning-based approach allowing multiple entities to train an ML model collaboratively without sharing their data. It is particularly beneficial in healthcare, where data privacy and security are substantial concerns. Even though FL addresses some privacy concerns, there is still no formal proof of privacy guarantees for IoHT data. Privacy-enhancing technologies (PETs) are tools and techniques designed to enhance the privacy and security of online communications and data sharing. PETs provide a range of features that help protect users’ personal information and sensitive data from unauthorized access and tracking. This paper comprehensively reviews PETs concerning FL in the IoHT scenario and identifies several key challenges for future research.
Dynamic Selection Slicing-Based Offloading Algorithm for In-Vehicle Tasks in Mobile Edge Computing
Authors: Han Li , Bin Yanru , Zhu Shuaijie , Liu Yanpei
Published: June 2023

With the surge in tasks for in-vehicle terminals, the resulting network congestion and time delay cannot meet the service needs of users. Offloading algorithms are introduced to handle vehicular tasks, which will greatly improve the above problems. In this paper, the dependencies of vehicular tasks are represented as directed acyclic graphs, and network slices are integrated within the edge server. The Dynamic Selection Slicing-based Offloading Algorithm for in-vehicle tasks in MEC (DSSO) is proposed. First, a computational offloading model for vehicular tasks is established based on available resources, wireless channel state, and vehicle loading level. Second, the solution of the model is transformed into a Markov decision process, and the combination of the DQN algorithm and Dueling Network from deep reinforcement learning is used to select the appropriate slices and dynamically update the optimal offloading strategy for in-vehicle tasks in the effective interval. Finally, an experimental environment is set up to compare the DSSO algorithm with LOCAL, MINCO, and DJROM, the results show that the system energy consumption of DSSO algorithm resources is reduced by 10.31%, the time latency is decreased by 22.75%, and the ratio of dropped tasks is decreased by 28.71%.
Improvement of Power Recovery by Applying a Multi-Pulse Electric Field in the Thermoelectric Cycle Power Generation Process with Pyroelectric Materials
Authors: Sodige Buddhika Amila Kumara , Furuno Hideto , Ngo Nguyen Chi Trung , Sugiyama Hironari , Baba Masaaki , Niihara Koichi , Nakayama Tadachika
Published: June 2023

Nanogenerator energy harvesting technologies that transform thermal energies into electricity may help address the growing need for green power. Therefore, this research aims to increase power generation by combining waste heat with pyroelectric nanogenerators as a sustainable energy source. Under optimal conditions, an external multi-pulse electric field can be utilized to generate power using thermoelectric cycle power generation. The greatest power may be gathered by applying various pulses of the external electric field at temperature changes on the surface of the pyroelectric materials. To generate pyroelectric power, a C9 BZT sample was used, and the lowest temperature difference for accomplishing this was 20 °C, with all measurements made on a sample with a lower limit of 120 °C. The maximum generation density was 0.104 mJ/cm2°CkV for a pulse width of 10 ms and 20 pulses of a low voltage (250 V/mm) input electric field. A multi-pulse electric field with low input voltage increases the power generation performance ratio (η) with the pulse count. At the largest number of pulses, the greatest η value for 250 V/mm was 7.834. Finally, it was determined that the developed pyroelectric power generation system may be more effective if a low-voltage, multi-pulse electric field is used.
Vision Transformer-Based Photovoltaic Prediction Model
Authors: Kang Zaohui , Xue Jizhong , Lai Chun Sing , Wang Yu , Yuan Haoliang , Xu Fangyuan
Published: June 2023

Sensing the cloud movement information has always been a difficult problem in photovoltaic (PV) prediction. The information used by current PV prediction methods makes it challenging to accurately perceive cloud movements. The obstruction of the sun by clouds will lead to a significant decrease in actual PV power generation. The PV prediction network model cannot respond in time, resulting in a significant decrease in prediction accuracy. In order to overcome this problem, this paper develops a visual transformer model for PV prediction, in which the target PV sensor information and the surrounding PV sensor auxiliary information are used as input data. By using the auxiliary information of the surrounding PV sensors and the spatial location information, our model can sense the movement of the cloud in advance. The experimental results confirm the effectiveness and superiority of our model.
Sewage Sludge Gasification Process Optimization for Combined Heat and Power Generation
Authors: Carotenuto Alberto , Di Fraia Simona , Massarotti Nicola , Sobek Szymon , Uddin M. Rakib , Vanoli Laura , Werle Sebastian
Published: June 2023

This work aims to assess the effect of the operating parameters of the gasifying agent preheating temperature and equivalence ratio (ER) on the conversion of sewage sludge (SS) to syngas through gasification and combined heat and power (CHP) generation. A novel gasification model was simulated in Aspen Plus to represent a fixed-bed updraft gasifier to generate syngas from SS through an equilibrium approach restricted by temperature. The novelty of this work is that the model was developed by applying the gasifying agent preheating temperature as an operating variable instead of the gasification temperature. It was calibrated by using a set of experimental values and then validated by comparing the numerical results with the experimental outcomes related to nine different operating conditions of air preheating temperatures and ER. A good agreement between the simulation and experimental results was observed. The optimum gasification process parameters of the air preheating temperature and ER were predicted to be 150 °C and 0.2, respectively. The CHP generation potentiality of SS was assessed to be 2.54 kW/kg SS as dry solids (DS), of which 0.81 kW was electrical and the remainder was thermal power. The conversion of SS to CHP through the proposed treatment can reduce 0.59 kg CO₂/kg SS as DS emissions compared with that of natural gas combustion to generate a similar quantity of energy.
An Event-Driven Self-Clocked Digital Low-Dropout Regulator with Adaptive Frequency Control
Authors: Chen Yen-Ming , Chen Ching-Jan
Published: June 2023

Digital low-dropout (DLDO) is widely used for power management in the system-on-chip (SoC) because of its low-voltage operation and process scalability. However, conventional DLDOs suffer from the trade-off between transient response and power consumption of the DLDO and the clock generator. This paper proposes an event-driven self-clocked DLDO regulator. The proposed low quiescent current (IQ) event-driven adaptive frequency clock generator (EACG) adapts its frequency in different load conditions without a current sensor or complex compensation circuit for stable operation in the entire load range. The proposed DLDO does not need any external clocking signal and can maintain low output ripple and low power consumption in the steady-state. The clock-less transient detector (CLTD), consisting of two clock-independent transient detection paths, uses power more efficiently and improves the transient response significantly without sacrificing the power consumption. This work was fabricated in a 40 nm CMOS process with an 0.3 nF on-chip capacitor. The measurement results show that with the step load current between 1 mA and 60 mA, the proposed DLDO achieves a transient recovery time of 220 ns. The total IQ of the proposed DLDO is only 26 μA in steady-state, and it achieves stable operation in the entire load range.
Hot-Water Extraction (HWE) Method as Applied to Lignocellulosic Materials from Hemp Stalk
Authors: Leszczyński Mateusz , Roman Kamil
Published: June 2023

The article describes the process of hot water extraction treatment of a specific material—in this case, shavings of hemp shives of different thicknesses, sorted by their thickness into three different fractions of 0–4 mm, 4–8 mm, and 8–12 mm. In addition, each sample from a given fraction was separately subjected to one, two, and three extraction processes. After the material was treated with extraction, cellulose determination was performed using the Kürschner–Hoffer method in order to find out the effect that hot water extraction had on the cellulose content of the test material. This research aims to determine whether hot water extraction strongly alters the cellulose content, which may translate into a change in efficiency when producing second-generation biofuel produced from this material. The cellulose determination showed the smallest cellulose losses were in chips 4–8 mm thick, while the largest were in chips 0–4 mm thick. Each repetition resulted in a loss of cellulose, with the steepest loss occurring after the second repetition of HWE, and the smallest after the third repetition—the exception being the 4–8 fraction, in which the smallest decrease occurred after the first repetition of the HWE (Hot Water Extraction) process.
Assessing Energy Performance and Environmental Impact of Low GWP Vapor Compression Chilled Water Systems
Authors: Mansouri Rami , Mungyeko Bisulandu Baby-Jean Robert , Ilinca Adrian
Published: June 2023

The global concern regarding the environmental repercussions of refrigerants has escalated due to their adverse effects. These substances deplete the ozone layer and intensify the greenhouse effect. International agreements such as the Montreal and Kyoto Protocols and COP21 have imposed restrictions on refrigerants with high global warming potential (GWP) to address these issues. This study aims to explore the feasibility, energy efficiency, and environmental impact of utilizing the HFO (hydrofluoric-olefin) refrigerant R1234ze as a substitute for HFCs (hydrofluoric-carbon) (R134a, R407C, and R410A) and HCFCs (R22) in air-cooled vapor compression refrigeration and air conditioning systems. To determine their effectiveness, we evaluate the energy performance of various refrigerant operating cycles across a wide range of ambient and evaporating temperatures. Additionally, we conduct environmental impact analyses based on the total equivalent warming impact (TEWI) parameter calculated for commercially available chillers that utilize the fluids mentioned above. Our findings indicate that vapor compression chilled water systems employing R1234ze exhibit the highest performance coefficient and the lowest annual TEWI.
A Family of Zero-Voltage-Transition Magnetic Coupling Bidirectional DC/DC Converters
Authors: Wang Shanshan , Gao Ming , Shi Jianjiang
Published: June 2023

In this paper, a family of zero-voltage-transition (ZVT) magnetic coupling bidirectional DC/DC converters (BDCs) is proposed. The coupling inductor has two functions: to serve as a filter; and to provide the auxiliary current. In addition, the phase-shifting control method is used to reduce the conduction loss of the auxiliary circuit. The auxiliary switches are all working under zero-current-switching (ZCS) conditions; thus, all the switches have no switching loss. Furthermore, compared with the traditional ZVT implementation method based on the coupled inductor, this topology avoids the input source current notch and has a smaller ripple. Finally, a prototype of 800 W BDC is built to verify the feasibility of the proposed topology.
Integrated Demand Response in Multi-Energy Microgrids: A Deep Reinforcement Learning-Based Approach
Authors: Xu Chenhui , Huang Yunkai
Published: June 2023

The increasing complexity of multi-energy coordinated microgrids presents a challenge for traditional demand response providers to adapt to end users’ multi-energy interactions. The primary aim of demand response providers is to maximize their total profits via designing a pricing strategy for end users. The main challenge lies in the fact that DRPs have no access to the end users’ private preferences. To address this challenge, we propose a deep reinforcement learning-based approach to devise a coordinated scheduling and pricing strategy without requiring any private information. First, we develop an integrated scheduling model that combines power and gas demand response by converting multiple energy sources with different types of residential end users. Then, we formulate the pricing strategy as a Markov Decision Process with an unknown transition. The novel soft actor-critic algorithm is utilized to efficiently train neural networks with the entropy function and to learn the pricing strategies to maximize demand response providers’ profits under various sources of uncertainties. Case studies are conducted to demonstrate the effectiveness of the proposed approach in both deterministic and stochastic environment settings. Our proposed approach is also shown to be effective in handling different levels of uncertainties and achieving the near-optimal pricing strategy.
Ecological Factors Driving Tree Diversity across Spatial Scales in Temperate Forests, Northeast China
Authors: Gu Yue , Zhang Junhui , Ma Wang , Feng Yue , Yang Leilei , Li Zhuo , Guo Yanshuang , Shi Guoqiang , Han Shijie
Published: June 2023

Species diversity has been shown to be influenced by environmental factors, but the mechanism underlying their relationship remains unclear across spatial scales. Based on field investigation data collected from 3077 sample plots in temperate forest ecosystems, we compared tree species richness, evenness and dominance at 10 km × 10 km, 30 km × 30 km and 90 km × 90 km spatial scales. Then, we detected the scale dependence of changes in tree species composition on climate, topography and forest structure using variation partitioning and quantified their contribution to tree diversity with gradient–boosted models (GBMs) and fitted their relationships. The magnitude of tree richness, evenness and dominance significantly increased with spatial scale. Ecological factors jointly accounted for 24.3%, 26.5% and 38.5% of the variation in tree species composition at the three spatial scales, respectively. The annual mean temperature had a strong impact on tree richness, evenness and dominance and peaked at an intermediate scale. Tree evenness and dominance increased with the variation of temperature but had upper and lower limits. Tree richness obviously increased with annual precipitation on multiple scales and decreased with annual sunshine duration at large spatial scales. Tree richness, evenness and dominance obviously increased with the variation in elevation and diameter at breast height at large scales and small scales, respectively. Tree dominance decreased with tree height at a small scale. The dependence of tree diversity on ecological factors increased with spatial scales. Furthermore, different factors exert various controls on tree diversity at different spatial scales, representing a comprehensive mechanism regulating tree diversity.
Tree Species Classification Based on PointNet++ and Airborne Laser Survey Point Cloud Data Enhancement
Authors: Fan Zhongmou , Wei Jinhuang , Zhang Ruiyang , Zhang Wenxuan
Published: June 2023

Compared with ground-based light detection and ranging (LiDAR) data, the differential distribution of the quantity and quality of point cloud data from airborne LiDAR poses difficulties for tree species classification. To verify the feasibility of using the PointNet++ algorithm for point cloud tree species classification with airborne LiDAR data, we selected 11 tree species from the Minjiang River Estuary Wetland Park in Fuzhou City and Sanjiangkou Ecological Park. Training and testing sets were constructed through pre-processing and segmentation, and direct and enhanced down-sampling methods were used for tree species classification. Experiments were conducted to adjust the hyperparameters of the proposed algorithm. The optimal hyperparameter settings used the multi-scale sampling and grouping (MSG) method, down-sampling of the point cloud to 2048 points after enhancement, and a batch size of 16, which resulted in 91.82% classification accuracy. PointNet++ could be used for tree species classification using airborne LiDAR data with an insignificant impact on point cloud quality. Considering the differential distribution of the point cloud quantity, enhanced down-sampling yields improved the classification results compared to direct down-sampling. The MSG classification method outperformed the simplified sampling and grouping classification method, and the number of epochs and batch size did not impact the results.
Preferential Flow and Preferential Path Characteristics of the Typical Forests in the Karst Region of Southwest China
Authors: Guan Ning , Cheng Jinhua , Shi Xueqi
Published: June 2023

The ecological environment in the karst region of southwest China is fragile, and vegetation degradation is considered the main cause of this phenomenon. Vegetation growth is affected by preferential flow due to a large number of fissures and macropores in the soil. Therefore, the preferential flow and preferential paths in local typical vegetation need to be studied. The distribution and developmental characteristics of preferential flow and preferential paths in three typical local stands were obtained by conducting field staining tracer experiments and using image processing techniques. The results showed that there was preferential flow movement in the soil moisture of the local understorey and that there was a high degree of preferential flow development and high variability. The degree of preferential flow in several typical forests can be expressed, from highest to lowest, in the following order: secondary forests, Cupressus duclouxiana Hickel (Hickel., 1814) forest, and Pinus massoniana (Lamb., 1803) forest. The preferential paths in the soil were mainly distributed above 15 cm, and the number of preferential paths with a small influence radius was much greater than that with a large influence radius. The preferential paths with an influence radius of 2.5~5 mm accounted for the largest proportion. The total number of preferential paths in the P. massoniana forest was small. The preferential paths in the secondary and C. duclouxiana Hickel forests were similar in number, but the secondary forests had more preferential paths with a large influence radius. This study investigated the characteristics of preferential flow and preferential paths in the typical forests of the karst region in southwest China, and it can provide data and research directions for the study of hydrological processes in local forest vegetation.
The Role of Vegetation on Urban Atmosphere of Three European Cities. Part 2: Evaluation of Vegetation Impact on Air Pollutant Concentrations and Depositions
Authors: Mircea Mihaela , Borge Rafael , Finardi Sandro , Briganti Gino , Russo Felicita , de la Paz David , D’Isidoro Massimo , Cremona Giuseppe , Villani Maria Gabriella , Cappelletti Andrea , Adani Mario , D’Elia Ilaria , Piersanti Antonio , Sorrentino Beatrice , Petralia Ettore , de Andrés Juan Manuel , Narros Adolfo , Silibello Camillo , Pepe Nicola , Prandi Rossella , Carlino Giuseppe
Published: June 2023

This is the first study that quantifies explicitly the impact of present vegetation on concentrations and depositions, considering simultaneously its effects on meteorology, biogenic emissions, dispersion, and dry deposition in three European cities: Bologna, Milan, and Madrid. The behaviour of three pollutants (O3, NO2, and PM10) was investigated considering two different scenarios, with the actual vegetation (VEG) and without it (NOVEG) for two months, representative of summer and winter seasons: July and January. The evaluation is based on simulations performed with two state-of-the-art atmospheric modelling systems (AMS) that use similar but not identical descriptions of physical and chemical atmospheric processes: AMS-MINNI for the two Italian cities and WRF-CMAQ for the Spanish city. The choice of using two AMS and applying one of them in two cities has been made to ensure the robustness of the results needed for their further generalization. The analysis of the spatial distribution of the vegetation effects on air concentrations and depositions shows that they are highly variable from one grid cell to another in the city area, with positive/negative effects or high/low effects in adjacent cells being observed for the three pollutants investigated in all cities. According to the pollutant, on a monthly basis, the highest differences in concentrations (VEG-NOVEG) produced by vegetation were estimated in July for O3 (−7.40 μg/m3 in Madrid and +2.67 μg/m3 in Milan) and NO2 (−3.01 μg/m3 in Milan and +7.17 μg/m3 in Madrid) and in January for PM10 (−3.14 μg/m3 in Milan +2.01 μg/m3 in Madrid). Thus, in some parts of the cities, the presence of vegetation had produced an increase in pollutant concentrations despite its efficient removal action that ranges from ca. 17% for O3 in Bologna (January) to ca. 77% for NO2 in Madrid (July).
Numerical Modeling of Hydrogen Combustion: Approaches and Benchmarks
Authors: Yakovenko Ivan , Kiverin Alexey
Published: June 2023

The paper is devoted to the analysis of two different approaches for the numerical simulation of gaseous combustion. The first one is based on a full system of Navier-Stokes equations describing the dynamics of the compressible reactive medium, while the second one utilizes low-Mach number approximation. The compressible model is realized by the traditional low-order numerical scheme and the contemporary CABARET method. The low-Mach approach is implemented on the base of a widely known FDS numerical scheme. The benefits and disadvantages of compressible and low-Mach approaches are discussed and demonstrated on a specially developed set of problem setups, applicable for validation and verification of the numerical methods for combustion analysis. In particular, the laminar flame velocity test, spherical bomb test, and multidimensional modeling of combustion development inside the rectangular closed vessel are performed via both techniques that allowed to determine the applicability limits of the low-Mach number approximation.
Geovisualization and Analysis of Landscape-Level Wildfire Behavior Using Repeat Pass Airborne Thermal Infrared Imagery
Authors: Shennan Keaton , Stow Douglas A. , Nara Atsushi , Schag Gavin M. , Riggan Philip
Published: June 2023

Geovisualization tools can supplement the statistical analyses of landscape-level wildfire behavior by enabling the discovery of nuanced information regarding the relationships between fire spread, topography, fuels, and weather. The objectives of this study were to develop and evaluate the effectiveness of geovisualization tools for analyzing wildfire behavior and specifically to apply those tools to study portions of the Thomas and Detwiler wildfire events that occurred in California in 2017. Fire features such as active fire fronts and rate of spread (ROS) vectors derived from repetitive airborne thermal infrared (ATIR) imagery sequences were incorporated into geovisualization tools hosted in a web geographic information systems application. This geovisualization application included ATIR imagery, fire features derived from ATIR imagery (rate of spread vectors and fire front delineations), growth form maps derived from NAIP imagery, and enhanced topographic rasters for visualizing changes in local topography. These tools aided in visualizing and analyzing landscape-level wildfire behavior for study portions of the Thomas and Detwiler fires. The primary components or processes of fire behavior analyzed in this study were ROS, spotting, fire spread impedance, and fire spread over multidirectional slopes. Professionals and researchers specializing in wildfire-related topics provided feedback on the effectiveness and utility of the geovisualization tools. The geovisualization tools were generally effective for visualizing and analyzing (1) fire spread over multidirectional slopes; (2) differences in spread magnitudes within and between sequences over time; and (3) the relative contributions of fuels, slope, and weather at any given point within the sequences. Survey respondents found the tools to be moderately effective, with an average effectiveness score of 6.6 (n = 5) for the visualization tools on a scale of 1 (ineffective) to 10 (effective) for postfire spread analysis and visualizing fire spread over multidirectional slopes. The results of the descriptive analysis indicate that medium- and fine-scale topographic features, roads, and riparian fuels coincided with cases of fire spread impedance and exerted control over fire behavior. Major topographic features such as ridges and valleys slowed, or halted, fire spread consistently between study areas. The relationships between spotting, fuels, and topography were inconclusive.
Construction and In Vitro Digestibility of Recrystallized Starch Encapsulated in Calcium Alginate Beads
Authors: Qin Kaili , Zhang Rongyu , Qin Weili , Ji Na , Qin Yang , Dai Lei , Xiong Liu , Sun Qingjie
Published: June 2023

In order to reduce the digestion rate of starch in human body and improve the content of slowly digestible starch (SDS) and resistant starch (RS), millimeter calcium alginate beads encapsulated with different proportions of recrystallized starch were constructed in this study. First, we prepared recrystallized starch (RS3) by debranching waxy corn starch and retrogradation, and then encapsulated RS3 in calcium alginate beads by the ionic gel method. The microstructure of the beads was observed by scanning electron microscope, and the gel texture properties, swelling properties, and in vitro digestibility of the beads were studied. The results showed that the beads after cooking still maintained high hardness and chewiness, and the swelling power and solubility of the beads were lower than that of native starch. Compared with native starch, the content of rapidly digestible starch (RDS) in beads decreased, while the content of SDS and RS increased. The sample with the highest content of RS is RS31@Alginate1, whose content of RS is 70.10%, 52.11 times higher than that of waxy corn starch and 1.75 times higher than that of RS3. RS3 encapsulated in calcium alginate beads has a good encapsulation effect, and the content of SDS and RS is greatly increased. This study has important implications for reducing the digestion rate of starch and regulating the health of people with diabetes and obesity.
A Comprehensive Review of the Hermite–Hadamard Inequality Pertaining to Quantum Calculus
Authors: Tariq Muhammad , Ntouyas Sotiris K. , Shaikh Asif Ali
Published: June 2023

A review of results on Hermite–Hadamard (H-H) type inequalities in quantum calculus, associated with a variety of classes of convexities, is presented. In the various classes of convexities this includes classical convex functions, quasi-convex functions, p-convex functions, (p,s)-convex functions, modified (p,s)-convex functions, (p,h)-convex functions, tgs-convex functions, η-quasi-convex functions, ϕ-convex functions, (α,m)-convex functions, ϕ-quasi-convex functions, and coordinated convex functions. Quantum H-H type inequalities via preinvex functions and Green functions are also presented. Finally, H-H type inequalities for (p,q)-calculus, h-calculus, and (q−h)-calculus are also included.
Generalized Thermoelastic Infinite Annular Cylinder under the Hyperbolic Two-Temperature Fractional-Order Strain Theory
Authors: Al-Lehaibi Eman A. N.
Published: June 2023

This work introduces a new thermoelastic model of an isotropic and homogeneous annular cylinder. The cylinder’s bounding inner surface is shocked thermally, and the bounding outer surface has no temperature increment and volumetric strain. The governing equations in the context of the hyperbolic two-temperature generalized thermoelasticity with fractional-order strain theory have been derived. The numerical solutions of the conductive temperature, dynamic temperature, displacement, strain, and stress are illustrated in figures that use various values of fractional-order and two-temperature parameters to stand on their effects on the thermal and mechanical waves. The fractional-order parameter has significant impacts on the displacement, strain, and stress distributions. However, it does not affect dynamic or conductive temperatures. The hyperbolic two-temperature model is a successful model for making thermal and mechanical waves propagate at limited speeds.
Variational Problems Involving a Generalized Fractional Derivative with Dependence on the Mittag–Leffler Function
Authors: Almeida Ricardo
Published: June 2023

In this paper, we investigate the necessary conditions to optimize a given functional, involving a generalization of the tempered fractional derivative. The exponential function is replaced by the Mittag–Leffler function, and the kernel depends on an arbitrary increasing function. The Lagrangian depends on time, the state function, its fractional derivative, and we add a terminal cost function to the formulation of the problem. Since this new fractional derivative is presented in a general form, some previous works are our own particular cases. In addition, for different choices of the kernel, new results can be deduced. Using variational techniques, the fractional Euler–Lagrange equation is proved, as are its associated transversality conditions. The variational problem with additional constraints is also considered. Then, the question of minimizing functionals with an infinite interval of integration is addressed. To end, we study the case of the Herglotz variational problem, which generalizes the previous one. With this work, several optimization conditions are proven that can be useful for different optimization problems dealing with various fractional derivatives.
Comparing Market Efficiency in Developed, Emerging, and Frontier Equity Markets: A Multifractal Detrended Fluctuation Analysis
Authors: Lee Min-Jae , Choi Sun-Yong
Published: June 2023

In this article, we investigate the market efficiency of global stock markets using the multifractal detrended fluctuation analysis methodology and analyze the results by dividing them into developed, emerging, and frontier groups. The static analysis results reveal that financially advanced countries, such as Switzerland, the UK, and the US, have more efficient stock markets than other countries. Rolling window analysis shows that global issues dominate the developed country group, while emerging markets are vulnerable to foreign capital movements and political risks. In the frontier group, intensive domestic market issues vary, making it difficult to distinguish similar dynamics. Our findings have important implications for international investors and policymakers. International investors can establish investment strategies based on the degree of market efficiency of individual stock markets. Policymakers in countries with significant fluctuations in market efficiency should consider implementing new regulations to enhance market efficiency. Overall, this study provides valuable insights into the market efficiency of global stock markets and highlights the need for careful consideration by international investors and policymakers.
Molecular Mechanism of MYL4 Regulation of Skeletal Muscle Development in Pigs
Authors: Xu Xueli , Yu Zonggang , Ai Nini , Liufu Sui , Liu Xiaolin , Chen Bohe , Li Xintong , Jiang Jun , Zhang Yuebo , Ma Haiming , Yin Yulong
Published: June 2023

The processes of muscle growth and development, including myoblast proliferation, migration, differentiation, and fusion, are modified by a variety of regulatory factors. MYL4 plays an important role in atrial development, atrial cardiomyopathy, muscle-fiber size, and muscle development. The structural variation (SV) of MYL4 was found via the de novo sequencing of Ningxiang pigs, and the existence of SV was verified in the experiments. The genotype distribution of Ningxiang pigs and Large White pigs was detected, and it was found that Ningxiang pigs were mainly of the BB genotype and that Large White pigs were mainly of the AB genotype. However, the molecular mechanisms behind the MYL4-mediated regulation of skeletal muscle development need to be deeply explored. Therefore, RT-qPCR, 3′RACE, CCK8, EdU, Western blot, immunofluorescence, flow cytometry, and bioinformation analysis were used to explore the function of MYL4 in myoblast development. The cDNA of MYL4 was successfully cloned from Ningxiang pigs, and its physicochemical properties were predicted. The expression profiles in six tissues and four stages of Ningxiang pigs and Large White pigs were found to be the highest in the lungs and 30 days after birth. The expression of MYL4 increased gradually with the extension of the myogenic differentiation time. The myoblast function test showed that the overexpression of MYL4 inhibited proliferation and promoted apoptosis and differentiation. The knockdown of MYL4 showed the opposite result. These results enhance our understanding of the molecular mechanisms of muscle development and provide a solid theoretical foundation for further exploring the role of the MYL4 gene in muscle development.