bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnosis and Management of Pulmonary Hypertension: New Insights
Authors: Ntiloudi Despoina , Kasinos Nearchos , Kalesi Alkistis , Vagenakis Georgios , Theodosis-Georgilas Anastasios , Rammos Spyridon
Published: September 2024

Over the last decades, significant progress has been achieved in the pulmonary hypertension (PH) field. Pathophysiology of PH has been studied, leading to the classification of PH patients into five groups, while the hemodynamic definition has been recently revised. A diagnostic algorithm has been established and awareness has been raised in order to minimize diagnosis delay. The pulmonary arterial hypertension (PAH) treatment strategy includes the established three pathways of endothelin, nitric oxide-phosphodiesterase inhibitor, and prostacyclin pathway, but new therapeutic options are now being tested. The aim of this review is to summarize the existing practice and to highlight the novelties in the field of PH.
Relative Belief Inferences from Decision Theory
Authors: Evans Michael , Jang Gun Ho
Published: September 2024

Relative belief inferences are shown to arise as Bayes rules or limiting Bayes rules. These inferences are invariant under reparameterizations and possess a number of optimal properties. In particular, relative belief inferences are based on a direct measure of statistical evidence.
On the Analysis of Wealth Distribution in the Context of Infectious Diseases
Authors: Zhang Tingting , Lai Shaoyong , Zhao Minfang
Published: September 2024

A mathematical model is established to investigate the economic effects of infectious diseases. The distribution of wealth among two types of agents in the context of the epidemic is discussed. Using the method of statistical mechanics, the evolution of the entropy weak solutions for the model of the susceptible and the infectious involving wealth density functions is analyzed. We assume that as time tends to infinity, the wealth density function of the infectious is linearly related to the wealth density function of the susceptible individuals. Our results indicate that the spreading of disease significantly affects the wealth distribution. When time tends to infinity, the total wealth density function behaves as an inverse gamma distribution. Utilizing numerical experiments, the distribution of wealth under the epidemic phenomenon and the situation of wealth inequality among agents are discussed.
Evanescent Electron Wave-Spin
Authors: Gao Ju , Shen Fang
Published: September 2024

This study demonstrates the existence of an evanescent electron wave outside both finite and infinite quantum wells by solving the Dirac equation and ensuring the continuity of the spinor wavefunction at the boundaries. We show that this evanescent wave shares the spin characteristics of the wave confined within the well, as indicated by analytical expressions for the current density across all regions. Our findings suggest that the electron cannot be confined to a mathematical singularity and that quantum information, or quantum entropy, can leak through any quantum confinement. These results emphasize that the electron wave, fully characterized by Lorentz-invariant charge and current densities, should be considered the true and sole entity of the electron.
The Many Roles of Precision in Action
Authors: Limanowski Jakub , Adams Rick A. , Kilner James , Parr Thomas
Published: September 2024

Active inference describes (Bayes-optimal) behaviour as being motivated by the minimisation of surprise of one’s sensory observations, through the optimisation of a generative model (of the hidden causes of one’s sensory data) in the brain. One of active inference’s key appeals is its conceptualisation of precision as biasing neuronal communication and, thus, inference within generative models. The importance of precision in perceptual inference is evident—many studies have demonstrated the importance of ensuring precision estimates are correct for normal (healthy) sensation and perception. Here, we highlight the many roles precision plays in action, i.e., the key processes that rely on adequate estimates of precision, from decision making and action planning to the initiation and control of muscle movement itself. Thereby, we focus on the recent development of hierarchical, “mixed” models—generative models spanning multiple levels of discrete and continuous inference. These kinds of models open up new perspectives on the unified description of hierarchical computation, and its implementation, in action. Here, we highlight how these models reflect the many roles of precision in action—from planning to execution—and the associated pathologies if precision estimation goes wrong. We also discuss the potential biological implementation of the associated message passing, focusing on the role of neuromodulatory systems in mediating different kinds of precision.
An MLWE-Based Cut-and-Choose Oblivious Transfer Protocol
Authors: Tang Yongli , Guo Menghao , Huo Yachao , Zhao Zongqu , Yu Jinxia , Qin Baodong
Published: September 2024

The existing lattice-based cut-and-choose oblivious transfer protocol is constructed based on the learning-with-errors (LWE) problem, which generally has the problem of inefficiency. An efficient cut-and-choose oblivious transfer protocol is proposed based on the difficult module-learning-with-errors (MLWE) problem. Compression and decompression techniques are introduced in the LWE-based dual-mode encryption system to improve it to an MLWE-based dual-mode encryption framework, which is applied to the protocol as an intermediate scheme. Subsequently, the security and efficiency of the protocol are analysed, and the security of the protocol can be reduced to the shortest independent vector problem (SIVP) on the lattice, which is resistant to quantum attacks. Since the whole protocol relies on the polynomial ring of elements to perform operations, the efficiency of polynomial modulo multiplication can be improved by using fast Fourier transform (FFT). Finally, this paper compares the protocol with an LWE-based protocol in terms of computational and communication complexities. The analysis results show that the protocol reduces the computation and communication overheads by at least a factor of n while maintaining the optimal number of communication rounds under malicious adversary attacks.
A Novel Short-Term PM2.5 Forecasting Approach Using Secondary Decomposition and a Hybrid Deep Learning Model
Authors: Liu Ruru , Xu Liping , Zeng Tao , Luo Tao , Wang Mengfei , Zhou Yuming , Chen Chunpeng , Zhao Shuo
Published: September 2024

PM2.5 pollution poses an important threat to the atmospheric environment and human health. To precisely forecast PM2.5 concentration, this study presents an innovative combined model: EMD-SE-GWO-VMD-ZCR-CNN-LSTM. First, empirical mode decomposition (EMD) is used to decompose PM2.5, and sample entropy (SE) is used to assess the subsequence complexity. Secondly, the hyperparameters of variational mode decomposition (VMD) are optimized by Gray Wolf Optimization (GWO) algorithm, and the complex subsequences are decomposed twice. Next, the sequences are divided into high-frequency and low-frequency parts by using the zero crossing rate (ZCR); the high-frequency sequences are predicted by a convolutional neural network (CNN), and the low-frequency sequences are predicted by a long short-term memory network (LSTM). Finally, the predicted values of the high-frequency and low-frequency sequences are reconstructed to obtain the final results. The experiment was conducted based on the data of 1009A, 1010A, and 1011A from three air quality monitoring stations in the Beijing area. The results indicate that the R2 value of the designed model increased by 2.63%, 0.59%, and 1.88% on average in the three air quality monitoring stations, respectively, compared with the other single model and the mixed model, which verified the significant advantages of the proposed model.
A New Carry Look-Ahead Adder Architecture Optimized for Speed and Energy
Authors: Balasubramanian Padmanabhan , Maskell Douglas L.
Published: September 2024

We introduce a new carry look-ahead adder (NCLA) architecture that employs non-uniform-size carry look-ahead adder (CLA) modules, in contrast to the conventional CLA (CCLA) architecture, which utilizes uniform-size CLA modules. We adopted two strategies for the implementation of the NCLA. Our novel approach enables improved speed and energy efficiency for the NCLA architecture compared to the CCLA architecture without incurring significant area and power penalties. Various adders were implemented to demonstrate the advantages of NCLA, ranging from the slower ripple carry adder to the widely regarded fastest parallel-prefix adder viz. the Kogge–Stone adder, and their performance metrics were compared. The 32-bit addition was used as an example, with the adders implemented using a semi-custom design method and a 28 nm CMOS standard cell library. Synthesis results show that the NCLA architecture offers substantial improvements in design metrics compared to its high-speed counterparts. Specifically, an NCLA achieved (i) a 14.7% reduction in delay and a 13.4% reduction in energy compared to an optimized CCLA, while occupying slightly more area; (ii) a 42.1% reduction in delay and a 58.3% reduction in energy compared to a conditional sum adder, with an 8% increase in the area; (iii) a 14.7% reduction in delay and a 37.7% reduction in energy compared to an optimized carry select adder, while requiring 37% less area; and (iv) a 20.2% reduction in energy and a 55.4% reduction in area compared to the Kogge–Stone adder.
Securing Federated Learning: Approaches, Mechanisms and Opportunities
Authors: Moshawrab Mohammad , Adda Mehdi , Bouzouane Abdenour , Ibrahim Hussein , Raad Ali
Published: September 2024

With the ability to analyze data, artificial intelligence technology and its offshoots have made difficult tasks easier. The tools of these technologies are now used in almost every aspect of life. For example, Machine Learning (ML), an offshoot of artificial intelligence, has become the focus of interest for researchers in industry, education, healthcare and other disciplines and has proven to be as efficient as, and in some cases better than, experts in answering various problems. However, the obstacles to ML’s progress are still being explored, and Federated Learning (FL) has been presented as a solution to the problems of privacy and confidentiality. In the FL approach, users do not disclose their data throughout the learning process, which improves privacy and security. In this article, we look at the security and privacy concepts of FL and the threats and attacks it faces. We also address the security measures used in FL aggregation procedures. In addition, we examine and discuss the use of homomorphic encryption to protect FL data exchange, as well as other security strategies. Finally, we discuss security and privacy concepts in FL and what additional improvements could be made in this context to increase the efficiency of FL algorithms.
A Hessian-Based Deep Learning Preprocessing Method for Coronary Angiography Image Analysis
Authors: Li Yanjun , Yoshimura Takaaki , Horima Yuto , Sugimori Hiroyuki
Published: September 2024

Leveraging its high accuracy and stability, deep-learning-based coronary artery detection technology has been extensively utilized in diagnosing coronary artery diseases. However, traditional algorithms for localizing coronary stenosis often fall short when detecting stenosis in branch vessels, which can pose significant health risks due to factors like imaging angles and uneven contrast agent distribution. To tackle these challenges, we propose a preprocessing method that integrates Hessian-based vascular enhancement and image fusion as prerequisites for deep learning. This approach enhances fuzzy features in coronary angiography images, thereby increasing the neural network’s sensitivity to stenosis characteristics. We assessed the effectiveness of this method using the latest deep learning networks, such as YOLOv10, YOLOv9, and RT-DETR, across various evaluation metrics. Our results show that our method improves AP50 accuracy by 4.84% and 5.07% on RT-DETR R101 and YOLOv10-X, respectively, compared to images without special pre-processing. Furthermore, our analysis of different imaging angles on stenosis localization detection indicates that the left coronary artery zero is the most suitable for detecting stenosis with a AP50(%) value of 90.5. The experimental results have revealed that the proposed method is effective as a preprocessing technique for deep-learning-based coronary angiography image processing and enhances the model’s ability to identify stenosis in small blood vessels.
Simulation and Calculation of Temperature Field and Current-Carrying Capacity of Power Cables under Different Laying Methods
Authors: Nie Yongjie , Chen Daoyuan , Zheng Shuai , Xu Xiaowei , Wang Xilian , Wu Zhensheng
Published: September 2024

Precisely determining how cables distribute their current-carrying capacity and temperature field is crucial for the dependable and cost-effective functioning of power grids. Firstly, the power cable structure and the advantages and disadvantages of different laying methods are analyzed in detail. Secondly, the theoretical model of current-carrying capacity calculation and temperature field of power cables, including heat convection, heat conduction, and heat radiation, is constructed, and the method for calculating cable current-carrying capacity, relying on the double-point chordal interception method, is suggested. Then, the COMSOL multiphysics 6.2 finite element simulation software is utilized to create a simulation model that aligns with the real cable laying technique. Finally, the current-carrying capacity and temperature field of power cables are simulated and analyzed for different arrangements of power cables in three laying modes, namely directly buried, row pipe, and trench. The simulation results show that the cable laying method greatly affects the cable’s carrying capacity; the more centralized the cable distribution, the smaller the flow. The method can be realized in different ways of laying power cables in the real-time rapid calculation of flow as the actual laying of power cables has an important reference and reference significance.
Technical Evaluation of a Stand-Alone Photovoltaic Heat Pump Dryer without Batteries
Authors: Quijano Antonio , Lorenzo Celena , Berlanga Antonio , Narvarte Luis
Published: September 2024

This paper presents the results of the technical validation of an innovative prototype for drying alfalfa bales. It is based on a 4.1 kW Heat Pump (HP) that uses an advanced technology (optimized for extracting the humidity from the air) and is directly powered by a 6.6 kWp PV generator without grid or batteries support. The main technical challenges of this work were managing solar irradiance fluctuations due to cloud-passing and achieving good drying efficiency. The prototype has been validated for two consecutive drying campaigns in La Rioja (Spain). There were no abrupt stops generated by cloud-passing. The PRPV, which evaluates the performance of the PV system only during the periods when the PV energy can be used by the HP unit, presented values of 0.82 and 0.85, comparable to a well-performing grid-connected PV system. Although the bales’ initial relative humidity (RH) ranged from 18 to 30%, all but one of them presented a final RH below 16%, which is the limit point to avoid fermentation. The drying times ranged from 1 to 5 h, and the specific energy consumption per liter of water extracted, from 0.7 to 1.46 kWh/L. These values are comparable to traditional diesel and grid-powered systems. It is worth noting that the agricultural drying market represented USD 1.7 billion in 2023.
Analysis of Indoor Air Quality and Fresh Air Energy Consumption Based on Students’ Learning Efficiency under Different Ventilation Methods by Modelica
Authors: Li Xu , Xiong Jingyi , Zhang Qifan , Wang Qiang
Published: September 2024

This paper aimed to explore a suitable ventilation method at a lower cost of energy to pursue a high learning efficiency based on the characteristics of a Chinese student group and campus building. Firstly, the model was established by Modelica and a good agreement between the numerical simulation and the results by CONTAM 3.4.0.3 was obtained. Secondly, the effects of the fixed window-opening ratio method (FWM), switch control window-opening ratio method (SCM), and automatic control window-opening ratio method (ACM) on CO2 concentration, indoor air temperature, and the heating capacity of air conditioning were investigated. The results showed that, when the FWM with 0% opening or 20% opening was adopted, the indoor CO2 concentration (ICC) was higher than the limit value of the classroom air quality standard, which was 1000 ppm. When the fixed window-opening ratio was greater than 40%, the indoor air temperature could not be controlled at the set value of 18 °C, which presented bad indoor thermal comfort. Meanwhile, when the ACM was adopted, the duration to meet good indoor thermal comfort was 57.17% higher than that of the SCM. However, both of them could maintain the average ICC below the set value in the class. Lastly, the fresh air energy consumption under different ventilation methods was compared. When the design temperature was 13.5 °C, it could be revealed that the fresh air energy consumption under the ACM, SCM, and FWM with 40% opening was 46.58%, 48.38%, and 51.26% lower than those at 18 °C. In summary, it was recommended to set the design temperature of the classroom at 13.5 °C, and the ACM was suggested as a suitable ventilation method to provide fresh air for the classroom.
Opportunities and Threats for Supercapacitor Technology Based on Biochar—A Review
Authors: Kwarciany Radosław , Fiedur Marcin , Saletnik Bogdan
Published: September 2024

This review analyzes in detail the topic of supercapacitors based on biochar technologies, including their advantages, disadvantages, and development potential. The main topic is the formation of precursors in the process of pyrolysis and activation, and the possibility of the application of biochar itself in various fields is brought closer. The structure, division, and principle of operation of supercondensates are discussed, where their good and bad sides are pointed out. The current state of the scientific and legal knowledge on the topic of biocarbon and its applications is verified, and the results of many authors are compared to examine the current level of the research on supercapacitors based on biochar electrodes created from lignocellulosic biomass. Current application sites for supercapacitors in transportation, electronics, and power generation (conventional and unconventional) are also examined, as is the potential for further development of the technology under discussion.
Comparison of the Energy Contributions of Different Types of Ground Heat Exchangers Related to Cost in a Working Ground Source Heat Pump System
Authors: Christou Christakis , Stylianou Iosifina I. , Aresti Lazaros , Florides Georgios A. , Christodoulides Paul
Published: September 2024

Geothermal systems face adoption challenges due to their high initial investment cost. Accurate cost analyses and a more precise understanding of updated prices could assist geothermal industry projects in obtaining investment financing and better money management with the right equipment. As the cost of geothermal installations can vary widely depending on case and location, it seems essential to clarify the factors and parameters that determine the cost of the system. These include the type of loop system, the ground conditions, the type of heat pump, the system size, and the geographical location. The scope of this study is to compare the operation of various types of ground heat exchangers (GHEs) present in a Ground Source Heat Pump (GSHP) system installed in the coastal area of the Mediterranean climate zone of Cyprus. The highlight of this work is that it presents real installation cost data as well as recorded total energy contributed by the GHEs to the GSHP system of a HP cooling and heating capacities of 101 kW and 117 kW, respectively. The input contribution from the GHEs to the HP is 85,650 kWh (308,340 MJ) in summer and 25,880 kWh (93,168 MJ) in winter. It is shown that, among the three groups of GHEs investigated, the open-well GHE complex has the lowest cost per kWh ratio (0.32 EUR/kWh), followed by the vertical GHE complex (1.05 EUR/kWh), and lastly by the helical coil GHE (2.77 EUR/kWh). This clearly suggests that when underground water is available, the open-well GHE is much more favorable than other GHE types.
Enhanced MPPT in Permanent Magnet Direct-Drive Wind Power Systems via Improved Sliding Mode Control
Authors: Ran Huajun , Li Linwei , Li Ao , Wang Xinquan
Published: September 2024

Addressing the challenges of significant speed overshoot, stability issues, and system oscillations associated with the sliding mode control (SMC) strategy in maximum power point tracking (MPPT) for permanent magnet synchronous wind power systems, this paper introduces a fuzzy sliding mode control (FSMC) method employing an innovative exponential convergence law. By incorporating a velocity adjustment function into the traditional exponential convergence law, a novel convergence law was designed to mitigate oscillations during the sliding phase and expedite the convergence rate. Additionally, a fuzzy controller was developed to implement a fuzzy adaptive SMC strategy, optimizing the MPPT for permanent magnet synchronous wind power generation systems. Simulation results indicated that this approach offered a faster response and superior interference rejection capabilities, compared to conventional and modified SMC strategies. The improved FSMC strategy demonstrated a swift, dynamic response and excellent steady-state performance, improving the efficiency of MPPT, thus confirming the effectiveness of the proposed method.
Application of the ALRW-DDPG Algorithm in Offshore Oil–Gas–Water Separation Control
Authors: He Xiaoyong , Pang Han , Liu Boying , Chen Yuqing
Published: September 2024

With the offshore oil–gas fields entering a decline phase, the high-efficiency separation of oil–gas–water mixtures becomes a significant challenge. As essential equipment for separation, the three-phase separators play a key role in offshore oil–gas production. However, level control is critical in the operation of three-phase gravity separators on offshore facilities, as it directly affects the efficacy and safety of the separation process. This paper introduces an advanced deep deterministic policy gradient with the adaptive learning rate weights (ALRW-DDPG) control algorithm, which improves the convergence and stability of the conventional DDPG algorithm. An adaptive learning rate weight function has been meticulously designed, and an ALRW-DDPG algorithm network has been constructed to simulate three-phase separator liquid level control. The effectiveness of the ALRW-DDPG algorithm is subsequently validated through simulation experiments. The results show that the ALRW-DDPG algorithm achieves a 15.38% improvement in convergence rate compared to the traditional DDPG algorithm, and the control error is significantly smaller than that of PID and DDPG algorithms.
Probabilistic Assessment of the Impact of Electric Vehicle Fast Charging Stations Integration into MV Distribution Networks Considering Annual and Seasonal Time-Series Data
Authors: Hernández-Gómez Oscar Mauricio , Abreu Vieira João Paulo
Published: September 2024

Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid requires considering annual and seasonal variations in EV fast-charging energy consumption. Neglecting these variations can lead to either underestimating or overestimating the impacts of FCSs on the networks. This paper introduces a probabilistic method to assess voltage profile violations, overload capacity, and increased power losses due to FCSs. By incorporating annual and seasonal time-series data, the method accounts for uncertainties related to EV fast charging. Applied to an MV feeder in Brazil, our evaluations highlight the impact of annual power consumption seasonality on EV-grid integration studies. Considering seasonal dependency is crucial for precise impact assessments of MV distribution networks. The proposed method aids utility engineers and planners in quantifying and mitigating the effects of EV fast charging, contributing to more reliable MV grid integration strategies.
A Novel Estimating Algorithm of Critical Driving Parameters for Dual-Motor Electric Drive Tracked Vehicles Based on a Nonlinear Observer and an Adaptive Kalman Filter
Authors: Chen Zhaomeng , Hu Songhua , Lv Haoliang , Fu Yimeng
Published: September 2024

High-speed dual-motor electric drive tracked vehicles (DDTVs) have emerged as a research hotspot in the field of tracked vehicles in recent years due to their advantages in fuel economy and the scalability of electrical equipment. The emergency braking of a DDTV at high speed can lead to slipping or even yawing (which is caused by a large deviation of forces at each track directly), posing significant challenges to the vehicle’s stability and safety. Therefore, the accurate real-time acquisition of critical driving parameters, such as the longitudinal force and vehicle speed, is crucial for the stability control of a DDTV. This paper developed a novel estimating algorithm of critical driving parameters for DDTVs equipped with conventional sensors such as rotary transformers at PMSMs and onboard accelerometers on the basis of their dynamics models. The algorithm includes a sensor signal preprocessing module, a longitudinal force estimation method based on a nonlinear observer, and a speed estimation method based on an adaptive Kalman filter. Through hardware-in-loop experiments based on a Speedgoat real-time target machine, the proposed algorithm is proven to estimate the longitudinal force of the track and vehicle speed accurately, whether the vehicle has stability control functions or not, providing a foundation for the further development of vehicle stability control algorithms.
Research on Optimal Scheduling Strategy of Differentiated Resource Microgrid with Carbon Trading Mechanism Considering Uncertainty of Wind Power and Photovoltaic
Authors: Li Bin , Zhou Zhaofan , Hu Junhao , Yi Chenle
Published: September 2024

Accelerating the green transformation of the power system is the inevitable path of the energy revolution; the increasing installed capacity of new energy and the penetration rate of electricity, uncertainty regarding new energy output, and the rising proportion of distributed power supply access have led to the threat against the safe and stable operation of the current power system. With the increasing uncertainty on both sides of power supply and demand, the microgrid (MG) is needed to effectually aggregate, coordinate, and optimize resources, such as adjustable resources, distributed power supply, and distributed energy storage in a certain area on the demand side. Therefore, in this paper, the uncertainty of wind power and PV is first dealt with by Latin hypercube sampling (LHS). Secondly, differentiated resources in the MG region can be divided into adjustable resources, distributed power supply, and energy storage. Adjustable resources are classified according to demand response characteristics. At the same time, the MG operating cost and carbon trading mechanism (CTM) are comprehensively considered. Finally, a low-carbon economy optimal scheduling strategy with the lowest total cost as the optimization goal is formed. Then, in order to verify the effectiveness of the proposed algorithm, three different scenarios are established for comparison. The total operating cost of the proposed algorithm is reduced by about 30%, and the total amount of carbon trading in 24 h can reach nearly 600 kg, bringing economic and social benefits to the MG.
Transcriptome Analyses Reveal Differences in the Metabolic Pathways of the Essential Oil Principal Components of Different Cinnamomum Chemotypes
Authors: Sun Weihong , Ni Hui , Zhao Zhuang , Zou Shuangquan
Published: September 2024

The genus Cinnamomum exhibits a rich variety of chemotypes and is an economically important essential oil (EO)-producing plant belonging to the family Lauraceae. Here, we aimed to explore the potential differences in the terpenoid (the principal components of EOs) biosynthesis pathways of different chemotypes at the molecular level in four Cinnamomum species—C. camphora var. linaloolifera, C. kanehirae, C. longipaniculatum, and C. micranthum. Gas chromatography–mass spectrometry (GC-MS) was employed to elucidate the discrepancies in the chemical profiles and compositions of leaf EO terpenoids among the four Cinnamomum species. The results revealed significant variations in leaf EO yields. The main constituents of the leaf EOs from C. camphora var. linaloolifera and C. kanehirae were the acyclic monoterpene linalool, and those of C. longipaniculatum and C. micranthum were the monoterpene eucalyptol and the sesquiterpene β-caryophyllene, respectively. Furthermore, a comparative transcriptome analysis of the leaves from the four Cinnamomum species revealed that differentially expressed genes (DEGs) were significantly enriched in terpene-related entries. Specifically, 42 and 24 DEGs were significantly enriched to the mevalonate (MVA)/2-methylerythritol 4-phosphate (MEP) pathways and terpene synthase (TPS) activity, respectively. Most genes encoding proteins involved in the terpenoid precursor MVA and MEP pathways exhibited differential expression across the four species, which correlated with the distinct terpenoid profiles observed in their leaf EOs. Four acyclic monoterpene linalool synthase genes—Maker00024100, Maker00014813, Maker00014818, and Maker00018424—were highly expressed in C. camphora var. linaloolifera and C. kanehirae. A monoterpene eucalyptol synthesis gene, Maker00001509, was highly expressed in C. longipaniculatum, and a sesquiterpene β-stigmasterol synthesis gene, Maker00005791, was highly expressed in C. micranthum. These expression levels were subsequently validated through quantitative real-time polymerase chain reaction (qRT-PCR). In conclusion, the combined results of the GC-MS and transcriptome analyses revealed a strong correlation between the metabolite content of the EOs and gene expression. This research contributes to a better understanding of the differences in terpene accumulation in various chemotypes of Cinnamomum at the molecular and mechanistic levels, laying a solid foundation for the cultivation of an ideal Cinnamomum variety.
Successions of Bacterial and Fungal Communities in Biological Soil Crust under Sand-Fixation Plantation in Horqin Sandy Land, Northeast China
Authors: Cao Chengyou , Zhang Ying , Cui Zhenbo
Published: September 2024

Biological soil crusts (BSCs) serve important functions in conserving biodiversity and ecological service in arid and semi-arid regions. Afforestation on shifting sand dunes can induce the formation of BSC on topsoil, which can accelerate the restoration of a degraded ecosystem. However, the studies on microbial community succession along BSC development under sand-fixation plantations in desertification areas are limited. This paper investigated the soil properties, enzymatic activities, and bacterial and fungal community structures across an age sequence (0-, 10-, 22-, and 37-year-old) of BSCs under Caragana microphylla sand-fixation plantations in Horqin Sandy Land, Northeast China. The dynamics in the diversities and structures of soil bacterial and fungal communities were detected via the high-throughput sequencing of the 16S and ITS rRNA genes, respectively. The soil nutrients and enzymatic activities all linearly increased with the development of BSC; furthermore, soil enzymatic activity was more sensitive to BSC development than soil nutrients. The diversities of the bacterial and fungal communities gradually increased along BSC development. There was a significant difference in the structure of the bacterial/fungal communities of the moving sand dune and BSC sites, and similar microbial compositions among different BSC sites were found. The successions of microbial communities in the BSC were characterized as a sequential process consisting of an initial phase of the faster recoveries of dominant taxa, a subsequent slower development phase, and a final stable phase. The quantitative response to BSC development varied with the dominant taxa. The secondary successions of the microbial communities of the BSC were affected by soil factors, and soil moisture, available nutrients, nitrate reductase, and polyphenol oxidase were the main influencing factors.
A Novel Method for Extracting DBH and Crown Base Height in Forests Using Small Motion Clips
Authors: Yang Shuhang , Xing Yanqiu , Yin Boqing , Wang Dejun , Chang Xiaoqing , Wang Jiaqi
Published: September 2024

The diameter at breast height (DBH) and crown base height (CBH) are important indicators in forest surveys. To enhance the accuracy and convenience of DBH and CBH extraction for standing trees, a method based on understory small motion clips (a series of images captured with slight viewpoint changes) has been proposed. Histogram equalization and quadtree uniformization algorithms are employed to extract image features, improving the consistency of feature extraction. Additionally, the accuracy of depth map construction and point cloud reconstruction is improved by minimizing the variance cost function. Six 20 m × 20 m square sample plots were selected to verify the effectiveness of the method. Depth maps and point clouds of the sample plots were reconstructed from small motion clips, and the DBH and CBH of standing trees were extracted using a pinhole imaging model. The results indicated that the root mean square error (RMSE) for DBH extraction ranged from 0.60 cm to 1.18 cm, with relative errors ranging from 1.81% to 5.42%. Similarly, the RMSE for CBH extraction ranged from 0.08 m to 0.21 m, with relative errors ranging from 1.97% to 5.58%. These results meet the accuracy standards required for forest surveys. The proposed method enhances the efficiency of extracting tree structural parameters in close-range photogrammetry (CRP) for forestry. A rapid and accurate method for DBH and CBH extraction is provided by this method, laying the foundation for subsequent forest resource management and monitoring.
A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems
Authors: Shahjehan Waleed , Rathore Rajkumar Singh , Shah Syed Waqar , Aljaidi Mohammad , Sadiq Ali Safaa , Kaiwartya Omprakash
Published: September 2024

As the world braces for an era of ubiquitous and seamless connectivity, hybrid beamforming stands out as a beacon guiding the evolutionary path of wireless communication technologies. Several hybrid beamforming technologies are explored for millimeter-wave multiple-input multi-output (MIMO) communication. The aim is to provide a roadmap for hybrid beamforming that enhances wireless fidelity. In this systematic review, a detailed literature review of algorithms/techniques used in hybrid beamforming along with performance metrics, characteristics, limitations, as well as performance evaluations are provided to enable communication compatible with modern Wireless Intelligent Transport Systems (WITSs). Further, an in-depth analysis of the mmWave hybrid beamforming landscape is provided based on user, link, band, scattering, structure, duplex, carrier, network, applications, codebook, and reflecting intelligent surfaces to optimize system design and performance across diversified user scenarios. Furthermore, the current research trends for hybrid beamforming are provided to enable the development of advanced wireless communication systems with optimized performance and efficiency. Finally, challenges, solutions, and future research directions are provided so that this systematic review can serve as a touchstone for academics and industry professionals alike. The systematic review aims to equip researchers with a deep understanding of the current state of the art and thereby enable the development of next-generation communication in WITSs that are not only adept at coping with contemporary demands but are also future-proofed to assimilate upcoming trends and innovations.
Microbial and Quality Attributes of Beef Steaks under High-CO2 Packaging: Emitter Pads versus Gas Flushing
Authors: Mortazavi Seyed Mohammad Hassan , Kaur Mandeep , Farahnaky Asgar , Torley Peter Joseph , Osborn Andrew Mark
Published: September 2024

Over 21 days of cold storage, the quality and microbial composition of beef steaks in response to different high-CO2 packaging conditions achieved by flushing gas mixtures or embedding gas emitters into the packages were studied. The results revealed that the high levels of CO2, achieved by either the gas flushing or the CO2 emitter pads, effectively controlled the number of aerobic counts. The headspace CO2 increased quickly in response to using the CO2 emitter pads, and the meat samples presented different pH levels and surface color (a* and b*) values compared to the samples packaged with the gas flushing technique. Excessive accumulation of gas in the packages that contained CO2 emitters resulted in package swelling and higher levels of drip loss. The longest overall quality and attractive red color of the meat samples were observed when the packages were initially flushed with the headspace gas mixture containing high levels of oxygen. Overall, using CO2 emitters for meat packaging can be suggested when a topfilm with proper permeability to O2 and CO2 gases is used to regulate the internal CO2/O2 and gas/product ratios.
Cookies Fortified with Clitoria ternatea Butterfly Pea Flower Petals: Antioxidant Capacity, Nutritional Composition, and Sensory Profile
Authors: Multisona Ribi Ramadanti , Myszka Kamila , Kulczyński Bartosz , Arnold Marcellus , Brzozowska Anna , Gramza-Michałowska Anna
Published: September 2024

This study aimed to fortify cookies to be functional food by adding Clitoria ternatea flower (CT) at concentrations ranging from 0 to 8%. Sensory profiling identified 6% CT as optimal for organoleptic attributes. The addition of CT did not significantly impact protein, lipid, and ash content but decreased energy value and increased insoluble and soluble fibre levels. The inclusion of 6% CT had a significant effect on the overall total phenolic content (TPC), which increased compared to the control sample. Antioxidative activity analyses showed enhanced antioxidative activity in ABTS, DPPH, ORACFL, and PCL assays. The addition of 6% CT inhibited hydroperoxide production in cookies. However, over a period of 6 weeks, a significant rise in peroxide value was observed during the 4th and 6th weeks of storing fortified cookies. All assessed products met the high microbiological quality standards. The sensory evaluation scores showed that CT can create cookies with health benefits and a good overall acceptance score. The texture of the cookies gradually became softer, but no significant changes in visual appearance were observed. CT can be extensively used in baked cookies as a rich source of polyphenols with strong antioxidant properties and high fibre content, as well as a fortification source for the development of functional foods.
Epidermal Growth Factor Receptor Emerges as a Viable Target for Reducing Tumorigenicity of MDCK Cells
Authors: Yang Di , Liao Yuejiao , Huang Lingwei , Shi Jiachen , Wang Jiamin , Qiao Zilin , Ma Zhongren , Yu Sijiu
Published: September 2024

The MDCK cell line is perceived as better than the embryos of hen eggs for the production of influenza vaccines, but the tumorigenicity of these cells is concerning. Epidermal growth factor receptor (EGFR) is likely to be a crucial target that contributes to the tumorigenicity of MDCK cells. In this study, EGFR-knockdown and EGFR-overexpression cell lines were established. EGFR’s influence on cell growth, migration, clonogenic ability, and flu virus susceptibility was evaluated in vitro, and its role in cell tumorigenicity was examined in nude mice. GST pull-down coupled with mass spectrometry (MS) and bioinformatics analysis identified EGFR-interacting proteins. The expression levels of these proteins, as well as those of PI3K–AKT- and MAPK–ERK-signaling-pathway-related molecules, were confirmed at both gene and protein levels. The result indicates that EGFR overexpression can enhance cell proliferation, migration, and clonal formation; EGFR knockdown could effectively curtail tumorigenesis and amplify the titers of influenza viruses in MDCK cells. An analysis of the underlying mechanism identified a total of 21 interacting proteins implicated in tumor formation, and among these, AKT1, CDK4, GNB2, and MAPK8 were confirmed at both gene and protein levels. EGFR can activate key factors of the PI3K–AKT signaling pathway, AKT and PI3K, and promote their phosphorylation levels. Consequently, we concluded that EGFR interacts with GNB2, facilitating transmembrane signal transduction, activating the PI3K–AKT signaling cascade, controlling cell cycle alterations, stimulating cell proliferation, and promoting tumorigenesis.
Molecular Cloning of the scd1 Gene and Its Expression in Response to Feeding Artificial Diets to Mandarin Fish (Siniperca chuatsi)
Authors: Wang Jiangjiang , Zhang Lihan , Gao Xiaowei , Sun Yanfeng , Zhao Chunlong , Gao Xiaotian , Wu Chengbin
Published: September 2024

Background/Objectives: Stearoyl-coenzyme A desaturase 1 (SCD1) plays a crucial role in fatty acid metabolism. However, its roles in the feeding habit transformation of mandarin fish (Siniperca chuatsi) remain largely unknown. Methods: Juvenile mandarin fish (10.37 ± 0.54)g were trained to feed on an artificial diet and then divided into artificial diet feeders and nonfeeders according to their feed preference. Afterwards, the scd1 gene of mandarin fish (Sc-scd1) was identified and characterized, and its transcription difference was determined between S. chuatsi fed live artificial diets and those fed prey fish. Results: Our results show that Sc-scd1 coding sequence is 1002 bp long, encoding 333 amino acids. The assumed Sc-SCD1 protein lacks a signal peptide, and it contains 1 N-linked glycosylation site, 24 phosphorylation sites, 4 transmembrane structures, and 3 conserved histidine elements. We found that Sc-SCD1 exhibits a high similarity with its counterparts in other fish by multiple alignments and phylogenetic analysis. The expression level of Sc-scd1 was detected with different expression levels in all tested tissues between male and female individuals fed either live prey fish or artificial diets. Conclusions: In particular, the Sc-scd1 expression level was the highest in the liver of both male and female mandarin fish fed artificial diets, indicating that scd1 genes may be associated with feed adaption of mandarin fish. Taken together, our findings offer novel perspectives on the potential roles of scd1 in specific domestication, and they provide valuable genetic information on feeding habits for the domestication of mandarin fish.
AI-Driven Innovations in Earthquake Risk Mitigation: A Future-Focused Perspective
Authors: Plevris Vagelis
Published: September 2024

This study explores the transformative potential of artificial intelligence (AI) in revolutionizing earthquake risk mitigation across six key areas. Unlike traditional approaches, this paper examines how AI-driven innovations can uniquely enhance early warning systems, enabling real-time structural health monitoring, and providing dynamic, multi-hazard risk assessments that seamlessly integrate seismic data with other natural hazards such as tsunamis and landslides. It introduces groundbreaking applications of AI in earthquake-resilient design, where generative design algorithms and predictive analytics create structures that optimally balance safety, cost, and sustainability. The study also presents a novel discussion on the ethical implications of AI in this domain, stressing the critical need for transparency, accountability, and bias mitigation. Looking forward, the manuscript envisions the development of advanced AI platforms capable of delivering real-time, personalized risk assessments, immersive public training programs, and collaborative design tools that adapt to evolving seismic data. These innovations promise not only to significantly enhance current earthquake preparedness but also to pave the way toward a future where the societal impact of earthquakes is drastically reduced. This work underscores the potential of AI’s role in shaping a safer, more resilient future, emphasizing the importance of continued innovation, ethical governance, and collaborative efforts.
Die Politik von Caligari: Totalitarian Anxieties in Adaptations of Robert Weine’s Das Cabinet des Dr. Caligari
Authors: Zapkin Phillip Louis
Published: September 2024

Contemporary politics is filled with anxiety about the survival of democracy—particularly within a framework pitting liberal representative democracy against authoritarianism. In times of anxiety about authoritarianism, Western artists repeatedly return to a masterpiece of relatively early cinema: Robert Weine’s silent film Das Cabinet des Dr. Caligari, or The Cabinet of Dr. Caligari. This essay examines three twenty-first century adaptations: David Lee Fisher’s 2005 remake of the film; James Morrow’s 2017 novel, The Asylum of Dr. Caligari; and Georgie Bailey’s 2022 play Caligari. I argue that while the direct politico-cultural anxieties of Weine’s film have often been overstated, the emergence of adaptations during periods of heightened concern about authoritarianism reflects a deep-seated reception of the film as anticipating autocratic governance. However, for all its fears about power, control, and the loss of self-determination, Weine’s movie also contains the seeds of liberation. Cesare ultimately sacrifices his own life rather than murdering Jane. And it is this gesture that the adaptations examined here seek—a gesture of resistance. The sleepwalker can awaken and assert a form of just resistance in the world, even if the penalties are steep.