bluuebunny/crossref_metadata_2025 huggingface dataset:
Managing Extreme Rainfall and Flooding Events: A Case Study of the 20 July 2021 Zhengzhou Flood in China
Authors: Zhao Xiaofan , Li Huimin , Cai Qin , Pan Ye , Qi Ye
Published: November 2023

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China’s Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact “black swans”, but turning into high-probability, high-impact “gray rhinos.” In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings.
Surface Modification of Fast-Growing Wood with a Titanium-Dioxide-Based Nanocoating to Improve Weathering Resistance
Authors: Rahayu Istie , Darmawan Wayan , Nawawi Deded Sarip , Prihatini Esti , Ismail Rohmat , Laksono Gilang Dwi , Martha Resa
Published: November 2023

Acacia mangium requires the addition of a finishing material to increase its resistance to weathering. Herein, the effectiveness of a nanocoating containing titanium dioxide nanoparticles (TiO2-NPs) as a finishing material for mangium wood was investigated. The coating material formulations used were oil-based (V1) and water-based (V2) varnishes with TiO2-NP concentrations of 1% (CT1), 5% (CT5), and 10% (CT10) (w/v). The uncoated and coated samples were subjected to weathering periods of 0, 2, and 4 months. The results showed that the addition of TiO2 nanoparticles to the V1 and V2 varnishes resulted in more gradual colour changes after the weathering period. The surface of the mangium wood also became smoother after being coated. However, the surface roughness increased with the duration of the weathering period. The wettability (K-value) of the sample decreased after coating, indicating that the coated sample was more hydrophobic than the uncoated sample. The results of a photocatalyst test, which analysed the effectiveness of the coatings, showed that the best coating material formulas were V1-CT10 and V2-CT10, as they degraded 75.21% and 71.03% of methylene blue content, respectively. Fourier transform infrared analysis showed that mangium wood did not undergo rapid weathering after the nanocoating treatment, as indicated by an insignificant decrease in the peak absorption intensity of the main structural functional groups of wood.
Revolutionizing Wastewater Treatment: Harnessing Metal–Organic Frameworks for Exceptional Photocatalytic Degradation of Azo-Type Dyes
Authors: Barrera-Andrade Jose Manuel , de la Fuente-Maldonado Natali , Lopez-Medina Ricardo , Maubert-Franco Ana Marisela , Rojas-Garcia Elizabeth
Published: November 2023

Due to the high stability of azo-type dyes, conventional treatment processes such as adsorption, flocculation, and activated sludge are not efficient for decolorizing wastewater effluents. An alternative to traditional wastewater treatment is photocatalysis, which has gained significant interest because research has shown it to be a viable and cost-effective process that uses sunlight as an inexhaustible energy source. In heterogeneous photocatalysis, a photocatalyst is required, such as TiO2, ZnO, composite materials, and, more recently, metal–organic frameworks (MOFs). MOFs, also known as “coordination polymers”, exhibit photocatalytic properties and have been proven to be promising materials in the photocatalytic degradation of dyes. This study presents recent advances in using MOFs as photocatalysts to degrade recalcitrant contaminants like azo-type dyes. Recent advancements in developing photocatalysts based on MOFs are focused on two strategies. Firstly, the development of new MOFs composed of complex ligands or a mixed ligand system, and secondly, the synthesis of composite materials based on MOFs and metal oxides, metals, sulfides, nitrides, etc. Both strategies have significantly contributed to the search for new semiconductors to degrade some recalcitrate contaminants in wastewater.
Phenotypically Discordant Anomalies in Conjoined Twins: Quirks of Nature Governed by Molecular Pathways?
Authors: Boer Lucas L. , Winter Eduard , Gorissen Ben , Oostra Roelof-Jan
Published: November 2023

A multitude of additional anomalies can be observed in virtually all types of symmetrical conjoined twins. These concomitant defects can be divided into different dysmorphological patterns. Some of these patterns reveal their etiological origin through their topographical location. The so-called shared anomalies are traceable to embryological adjustments and directly linked to the conjoined-twinning mechanism itself, inherently located within the boundaries of the coalescence area. In contrast, discordant patterns are anomalies present in only one of the twin members, intrinsically distant from the area of union. These dysmorphological entities are much more difficult to place in a developmental perspective, as it is presumed that conjoined twins share identical intra-uterine environments and intra-embryonic molecular and genetic footprints. However, their existence testifies that certain developmental fields and their respective developmental pathways take different routes in members of conjoined twins. This observation remains a poorly understood phenomenon. This article describes 69 cases of external discordant patterns within different types of otherwise symmetrical mono-umbilical conjoined twins and places them in a developmental perspective and a molecular framework. Gaining insights into the phenotypes and underlying (biochemical) mechanisms could potentially pave the way and generate novel etiological visions in the formation of conjoined twins itself.
A Comprehensive Look at Maxillofacial Traumas: On the Basis of Orbital Involvement
Authors: Gokharman Fatma Dilek , Kadirhan Ozlem , Celik Aydin Ozlem , Yalcin Arzu Gulsah , Kosar Pınar , Aydin Sonay
Published: November 2023

Introduction: Orbital wall fractures that may develop in maxillofacial traumas (MFTs) may cause ophthalmic complications (OCs). The aim of this study is to determine the frequency of orbital fractures (OFs) accompanying MFTs and findings suspicious for orbital traumatic involvement. Materials and Methods: Computed tomography (CT) images of 887 patients who presented to the emergency department within a 1-year period with a history of MFT were retrospectively scanned. During the examination, patients with orbital wall fractures, craniofacial bone fractures, and posttraumatic soft tissue changes were recorded. Results: OF was observed in 47 (5.3%) of the patients admitted for MFT. In cases with OFs, accompanying nasal (25.5%), ethmoid (2.1%), frontal (19.1%), maxillary (38%), and zygomatic bone fracture (10.6%), sphenoid (4.3%), and soft tissue damage (55.3%) were observed. It was observed that the pathologies mentioned at these levels were significantly higher than in patients without orbital involvement (p < 0.05). In our study, mild (48.9%) and moderate-severe (2.12–4.25%) OCs accompanying OFs were observed after MFT. Conclusions: The frequency of MFT varies depending on various factors, and such studies are needed to take preventive measures. Knowing the risk and frequency of orbital damage accompanying MFTs may help reduce complications by allowing rapid and accurate diagnosis.
TLFND: A Multimodal Fusion Model Based on Three-Level Feature Matching Distance for Fake News Detection
Authors: Wang Junda , Zheng Jeffrey , Yao Shaowen , Wang Rui , Du Hong
Published: November 2023

In the rapidly evolving information era, the dissemination of information has become swifter and more extensive. Fake news, in particular, spreads more rapidly and is produced at a lower cost compared to genuine news. While researchers have developed various methods for the automated detection of fake news, challenges such as the presence of multimodal information in news articles or insufficient multimodal data have hindered their detection efficacy. To address these challenges, we introduce a novel multimodal fusion model (TLFND) based on a three-level feature matching distance approach for fake news detection. TLFND comprises four core components: a two-level text feature extraction module, an image extraction and fusion module, a three-level feature matching score module, and a multimodal integrated recognition module. This model seamlessly combines two levels of text information (headline and body) and image data (multi-image fusion) within news articles. Notably, we introduce the Chebyshev distance metric for the first time to calculate matching scores among these three modalities. Additionally, we design an adaptive evolutionary algorithm for computing the loss functions of the four model components. Our comprehensive experiments on three real-world publicly available datasets validate the effectiveness of our proposed model, with remarkable improvements demonstrated across all four evaluation metrics for the PolitiFact, GossipCop, and Twitter datasets, resulting in an F1 score increase of 6.6%, 2.9%, and 2.3%, respectively.
Cognitive Empathy and the Dark Triad: A Literature Review
Authors: Duradoni Mirko , Gursesli Mustafa Can , Fiorenza Maria , Donati Alessia , Guazzini Andrea
Published: November 2023

This literature review aims to analyze studies published by researchers on the topic of the relationship between the psychological constructs of the Dark Triad and Cognitive Empathy. This study hypothesizes how having good cognitive empathic skills could benefit people who demonstrate Dark Triad traits, as this could facilitate the implementation of manipulative strategies. Through the process of identifying studies via databases and registers, 23 studies were included in this literature review, and the results and theories brought forward by the researchers find more agreement regarding the individual components of the Dark Triad than the whole construct: narcissism seems to have, for the most part, relatively small and typical positive correlations (more than 50% of correlations), Machiavellianism has relatively small and typical negative relationships (about 80% of correlations), and psychopathy has relatively large negative relationships (about 90% of correlations). This study conveys that Machiavellians and psychopaths, having reduced empathic abilities, use manipulation techniques that do not have to do with empathy (for example seduction, intimidation etc.), while narcissists would be, among these three dimensions, those most likely to understand others’ states of mind and thus be able to use this knowledge to their advantage—although there are doubts about the veracity of the statements and answers given by narcissists in the tests administered to them. This literature review could be a valid aid to professionals dealing with people who exhibit Dark Triad traits; understanding how those exhibiting Dark Triad traits manage their empathic abilities, the areas in which the various dimensions show deficits or not, and how they act to implement their manipulative and controlling tactics could aid in the development of more effective helping strategies to be utilized in therapy settings.
An Adaptive Multi-Content Complementary Network for Salient Object Detection
Authors: Huo Lina , Guo Kaidi , Wang Wei
Published: November 2023

Deep learning methods for salient object detection (SOD) have been studied actively and promisingly. However, the existing methods mainly focus on the decoding process and ignore the differences in the contributions of different encoder blocks. To address this problem for SOD, we propose an adaptive multi-content complementary network (PASNet) for salient object detection which aims to exploit the valuable contextual information in the encoder fully. Unlike existing CNN-based methods, we adopt the pyramidal visual transformer (PVTv2) as the backbone network to learn global and local representations with its self-attention mechanism. Then, we follow the coarse-to-fine strategy and introduce two novel modules, including an advanced semantic fusion module (ASFM) and a self-refinement module (SRM). Among these, the ASFM takes local branches and adjacent branches as inputs and collects semantic and location information of salient objects from high-level features to generate an initial coarse saliency map. The coarse saliency map serves as the location guidance for low-level features, and the SRM is applied to capture detailed information disguised in low-level features. We expand the location information with high-level semantics from top to bottom across the salient region, which is effectively fused with detailed information through feature modulation. The model effectively suppresses noises in the features and significantly improves their expressive capabilities. To verify the effectiveness of our PASNet, we conducted extensive experiments on five challenging datasets, and the results show that the proposed model is superior to some of the current state-of-the-art methods under different evaluation metrics.
Swarm Intelligence Response Methods Based on Urban Crime Event Prediction
Authors: Wang Changhao , Tian Feng , Pan Yan
Published: November 2023

Cities attract a large number of inhabitants due to their more advanced industrial and commercial sectors and more abundant and convenient living conditions. According to statistics, more than half of the world’s population resides in urban areas, contributing to the prosperity of cities. However, it also brings more crime risks to the city. Crime prediction based on spatiotemporal data, along with the implementation of multiple unmanned drone patrols and responses, can effectively reduce a city’s crime rate. This paper utilizes machine learning and data mining techniques, predicts crime incidents in small geographic areas with short timeframes, and proposes a random forest algorithm based on oversampling, which outperforms other prediction algorithms in terms of performance. The research results indicate that the random forest algorithm based on oversampling can effectively predict crimes with an accuracy rate of up to 95%, and an AUC value close to 0.99. Based on the crime prediction results, this paper proposes a multi-drone patrol response strategy to patrol and respond to predicted high-crime areas, which is based on target clustering and combined genetic algorithms. This strategy may help with the pre-warning patrol planning within an hourly range. This paper aims to combine crime event predictions with crowd-sourced cruise responses to proactively identify potential crimes, providing an effective solution to reduce urban crime rates.
Small Foreign Object Detection in Automated Sugar Dispensing Processes Based on Lightweight Deep Learning Networks
Authors: Lu Jiaqi , Lee Soo-Hong , Kim In-Woo , Kim Won-Joong , Lee Min-Soo
Published: November 2023

This study addresses the challenges that conventional network models face in detecting small foreign objects on industrial production lines, exemplified by scenarios where a single piece of iron filing occupies approximately 0.002% of the image area. To tackle this, we introduce an enhanced YOLOv8-MeY model for detecting foreign objects on the surface of sugar bags. Firstly, the introduction of a 160 × 160-scale small object detection layer and integration of the Global Attention Mechanism (GAM) attention module into the feature fusion network (Neck) increased the network’s focus on small objects. This enhancement improved the network’s feature extraction and fusion capabilities, which ultimately increased the accuracy of small object detection. Secondly, the model employs the lightweight network GhostNet, replacing YOLOv8’s principal feature extraction network, DarkNet53. This adaptation not only diminishes the quantity of network parameters but also augments feature extraction capabilities. Furthermore, we substituted the Bottleneck in the C2f of the YOLOv8 model with the Spatial and Channel Reconstruction Convolution (SCConv) module, which, by mitigating the spatial and channel redundancy inherent in standard convolutions, reduced computational demands while elevating the performance of the convolutional network model. The model has been effectively applied to the automated sugar dispensing process in food factories, exhibiting exemplary performance. In detecting diverse foreign objects like 2 mm iron filings, 7 mm wires, staples, and cockroaches, the YOLOv8-MeY model surpasses the Faster R-CNN model and the contemporaneous YoloV8n model of equivalent parameter scale across six metrics: precision, recall, mAP@0.5, parameters, GFLOPs, and model size. Through 400 manual placement tests involving four types of foreign objects, our statistical results reveal that the model achieves a recognition rate of up to 92.25%. Ultimately, we have successfully deployed this model in automated sugar bag dispensing scenarios.
A 65-nm CMOS Self-Supplied Power Management System for Near-Field Wirelessly Powered Biomedical Devices
Authors: Nabavi Seyedfakhreddin , Bhadra Sharmistha
Published: November 2023

This paper proposes a self-supplied power management system to efficiently rectify and regulate the AC voltage received from wireless power transmission techniques to power or recharge biomedical devices. The proposed power management system comprises three integrated functional units, namely, a fully cross-coupled rectifier, a self-biased reference voltage, and a capacitor-less low-dropout regulator (LDO). To reduce the current complexity of designing capacitor-less LDOs, a new architecture based on a pair of diode-connected transistors at the load of the LDO is devised which alleviates the need for a large load capacitor. The proposed power management system is implemented in a 65-nm CMOS process with an active chip area of 0.0810 mm2. Experimental results indicate that this system is capable of rectifying an AC signal up to 5 V at a frequency of 6.78 MHz. This rectified signal is then regulated to a fixed DC voltage of 1.75 V, while the load current can vary between 0 and 75 mA, with a maximum voltage dropout of 170 mV. Advantageously, the proposed power management system is significantly robust to temperature, as a 55 °C change in ambient temperature leads to only a 9% degradation in its overall performance. Furthermore, the ability of the power management system to drive low-power consumer electronics is demonstrated, and its superiority is evidenced by a performance comparison with the latest integrated power management systems presented in the literature.
Synergistic Optimization Design Method to Improve the Overload Capacity and Efficiency of Canned Permanent Magnet Synchronous Motor for Vacuum Pump
Authors: Li Ming , Chen Zilin , Mu Haiqi , Lun Shuxian
Published: November 2023

The efficiency and overload capacity are crucial performance factors during the design of the canned permanent magnet synchronous motors (CPMSMs) intended for driving vacuum pumps, due to their unique operational characteristics. The conventional multi-objective optimization design method is not suitable for the CPMSM due to the need to carefully consider additional influential factors, including the flat structure, eddy current losses in the cans, can thickness, and can material. To enhance the efficiency and overload capacity of the CPMSM, this paper introduces a synergistic optimization design approach that integrates the equivalent magnetic circuit method and the finite element method. A design example of a 1.5 kW CPMSM is presented, and experiments are performed to verify the effectiveness of the proposed method.
Enhancing Consensus Security and Privacy with Multichain Ring Signatures Based on HotStuff
Authors: Gao Mingan , Wang Zhiyuan , Lu Gehao
Published: November 2023

The paper introduces a novel consensus algorithm named MRPBFT, which is derived from the HotStuff consensus protocol and improved upon to address security deficiencies in traditional consensus algorithms within the domain of digital asset transactions. MRPBFT aims to enhance security and privacy protection while pursuing higher consensus efficiency. It employs a multi-primary-node approach and a ring signature mechanism to reinforce security and privacy preservation features in the consensus system. This algorithm primarily focuses on two main improvements: Firstly, it proposes the ed25519LRS signature algorithm and discusses its anonymity for transaction participants and the non-forgeability of signature information in the identity verification and message verification processes within the consensus algorithm. Secondly, the paper introduces MPBFT asynchronous view changes and a multi-primary-node mechanism to enhance consensus efficiency, allowing for view switching in the absence of global consensus. With the introduction of the multi-primary-node mechanism, nodes can be flexibly added or removed, supporting parallel processing of multiple proposals and transactions. Finally, through comparative experiments, the paper demonstrates that the improved algorithm performs significantly better in terms of throughput and network latency.
A Multireservoir Echo State Network Combined with Olfactory Feelings Structure
Authors: Lun Shuxian , Wang Qian , Cai Jianning , Lu Xiaodong
Published: November 2023

As a special form of recurrent neural network (RNN), echo state networks (ESNs) have achieved good results in nonlinear system modeling, fuzzy nonlinear control, time series prediction, and so on. However, the traditional single-reservoir ESN topology limits the prediction ability of the network. In this paper, we design a multireservoir olfactory feelings echo state network (OFESN) inspired by the structure of the Drosophila olfactory bulb, which provides a new connection mode. The connection between subreservoirs is transformed into the connection between each autonomous neuron, the neurons in each subreservoir are sparsely connected, and the neurons in different subreservoirs cannot communicate with each other. The OFESN greatly simplifies the coupling connections between neurons in different libraries, reduces information redundancy, and improves the running speed of the network. The findings from the simulation demonstrate that the OFESN model, as introduced in this study, enhances the capacity to approximate sine superposition function and the Mackey–Glass system when combined. Additionally, this model exhibits improved prediction accuracy by 98% in some cases and reduced fluctuations in prediction errors.
Enhancing Multi-Objective Optimization with Automatic Construction of Parallel Algorithm Portfolios
Authors: Ma Xiasheng , Liu Shengcai , Hong Wenjing
Published: November 2023

It has been widely observed that there exists no universal best Multi-Objective Evolutionary Algorithm (MOEA) dominating all other MOEAs on all possible Multi-Objective Optimization Problems (MOPs). In this work, we advocate using the Parallel Algorithm Portfolio (PAP), which runs multiple MOEAs independently in parallel and gets the best out of them, to combine the advantages of different MOEAs. Since the manual construction of PAPs is non-trivial and tedious, we propose to automatically construct high-performance PAPs for solving MOPs. Specifically, we first propose a variant of PAPs, namely MOEAs/PAP, which can better determine the output solution set for MOPs than conventional PAPs. Then, we present an automatic construction approach for MOEAs/PAP with a novel performance metric for evaluating the performance of MOEAs across multiple MOPs. Finally, we use the proposed approach to construct an MOEAs/PAP based on a training set of MOPs and an algorithm configuration space defined by several variants of NSGA-II. Experimental results show that the automatically constructed MOEAs/PAP can even rival the state-of-the-art multi-operator-based MOEAs designed by human experts, demonstrating the huge potential of the automatic construction of PAPs in multi-objective optimization.
Improving Wind Power Generation Forecasts: A Hybrid ANN-Clustering-PSO Approach
Authors: Finamore Antonella R. , Calderaro Vito , Galdi Vincenzo , Graber Giuseppe , Ippolito Lucio , Conio Gaspare
Published: November 2023

This study introduces a novel hybrid forecasting model for wind power generation. It integrates Artificial Neural Networks, data clustering, and Particle Swarm Optimization algorithms. The methodology employs a systematic framework: initial clustering of weather data via the k-means algorithm, followed by Pearson’s analysis to pinpoint pivotal elements in each cluster. Subsequently, a Multi-Layer Perceptron Artificial Neural Network undergoes training with a Particle Swarm Optimization algorithm, enhancing convergence and minimizing prediction discrepancies. An important focus of this study is to streamline wind forecasting. By judiciously utilizing only sixteen observation points near a wind farm plant, in contrast to the complex global numerical weather prediction systems employed by the European Center Medium Weather Forecast, which rely on thousands of data points, this approach not only enhances forecast accuracy but also significantly simplifies the modeling process. Validation is performed using data from the Italian National Meteorological Centre. Comparative assessments against both a persistence model and actual wind farm data from Southern Italy substantiate the superior performance of the proposed hybrid model. Specifically, the clustered Particle Swarm Optimization-Artificial Neural Network-Wind Forecasting Method demonstrates a noteworthy improvement, with a reduction in mean absolute percentage error of up to 59.47% and a decrease in root mean square error of up to 52.27% when compared to the persistence model.
Comprehensive Review on Cooling of Permanent Magnet Synchronous Motors and Their Qualitative Assessment for Aerospace Applications
Authors: König Paul , Sharma Dikshant , Konda Karunakar Reddy , Xie Tianxiao , Höschler Klaus
Published: November 2023

The permanent magnet synchronous motor (PMSM) can be a suitable candidate for electrified propulsion in aviation. Despite the very high efficiency, heat dissipation during operation leads to performance limitations. Elevated temperatures in the electrical insulations and the magnets pose a potential safety risk that must be reduced by selective cooling. A comprehensive review is conducted to capture current research interests in cooling methods in PMSM. Cooling methods are described according to their heat transfer mechanism, grouped, and assigned to the components within the motor. Key findings of the literature reviewed are described in the context of PMSM cooling. Information on cooling media and potential combinations of cooling methods in components is gathered. Assessment parameters such as safety, weight, effectiveness, integrability, complexity and cost are defined to enable a subsequent qualitative analysis for six selected cooling methods. A point-weighted evaluation approach, according to VDI 2225, was applied to identify the most promising cooling approach for successful implementation in aviation.
The Potential Effect on the Performance of CrN/Cr-Coated SS316L Bipolar Plates and Their Durability in Simulated Cathodic HT-PEFC Environments
Authors: Li Ruiyu , Cai Yun , Liu Yilin , Xie Ziqi , Wippermann Klaus , Lehnert Werner
Published: November 2023

This study further investigates the effect of potential on the corrosion resistance, the self-healing performance and the durability of CrN/Cr-coated SS316L bipolar plates with artificial defects (CR-316) in simulated cathodic HT-PEFC environments by means of electrochemical methods. The self-healing ability initiated by oxygen is relatively weak and needs the assistance of the cathode working potential for sealing. In some cases, the defects have spread over large parts of the bipolar plate. The influence of the potential on the corrosion resistance of the bare 316L and CR-316 specimens in the simulated cathodic HT-PEFC environments were investigated by electrochemical impedance spectroscopy. Moreover, the durability of the CR-316 specimens was examined under the various potential cycles in the simulated cathodic environment of HT-PEFC and O2 atmosphere. After 5000 CV cycles in the potential range of 0.4–1.0 V vs. RHE, the CR-316 specimens could maintain the integrity and good corrosion resistance against the hot phosphoric acid. The results demonstrate the superior performance of CR-316 and make it a prime candidate as a non-precious coating for metallic bipolar plates on the cathode side of HT-PEFCs.
Research on Neutronics Safety Parameters of the AP1000 Nuclear Reactor under Different Conditions
Authors: Niu Xinyi , Liu Jianquan , Dong Zenghao , Wei Jie , Zhou Wenlong
Published: November 2023

Changes in temperature during reactor operation may cause changes in physical parameters, leading to core overheating and accidents. It is essential to analyze and assess the safety parameters of the core under different operating conditions. This paper investigates the effects of fuel temperature, moderator density, boron concentration, and control rod state on AP1000 safety parameters. The study uses RMC and NJOY to calculate the changes in reactivity factor, effective delayed neutron fraction, and neutron generation time of the AP1000 reactor under different operating conditions. The changes in reactivity coefficients, neutron fluxes, and relative power densities of AP1000 reactors are analyzed for normal and accidental operating conditions. The results indicated that the reactivity coefficient remained negative under accident conditions, which ensured the safe operation of the reactor. The delayed neutron fraction, neutron flux, and power density distributions are affected by fuel temperature, moderator density, and control rod position. The control rod worth was sufficient for the emergency shutdown of the reactor under accidental conditions. It is demonstrated that the operation of the AP1000 reactor under study conditions is safe and controllable.
Liquefied Natural Gas Prices and Their Relationship with a Country’s Energy Mix: A Case Study for Greece
Authors: Bentsos Christos , Koursaros Demetris , Louka Kyriaki G. , Melas Konstantinos D. , Michail Nektarios A.
Published: November 2023

Using daily data, we investigate the relationship between European LNG prices, carbon prices (CO2), electricity wholesale prices and changes in the electricity sector’s energy mix in Greece, using a vector error correction model (VECM). The results indicate that an increase in the daily average price of natural gas has the expected impact on Greece’s wholesale electricity price. As expected, gas and other fossil fuels act as substitute goods, while higher imports of electricity lower prices and have a negative impact on fossil fuel shares. Interestingly, carbon prices do not appear to have any significant impact on any variables, while the higher production of electricity from renewable sources pushes wholesale electricity prices down.
Modification and Application of Bamboo-Based Materials: A Review—Part I: Modification Methods and Mechanisms
Authors: Zheng Zhiyu , Yan Nina , Lou Zhichao , Jiang Xizhi , Zhang Xiaomei , Chen Shan , Xu Rui , Liu Chun , Xu Lei
Published: November 2023

In light of continual societal advancement and escalating energy consumption, the pursuit of green, low-carbon, and environmentally friendly technologies has become pivotal. Bamboo, renowned for its diverse advantages encompassing swift growth, ecological compatibility, robust regenerative properties, commendable mechanical characteristics, heightened hardness, and abundant availability, has discovered applications across various domains, including furniture and construction. Nevertheless, natural bamboo materials are plagued by inherent limitations, prominently featuring suboptimal hydrophobicity and vulnerability to fracture, thereby constraining their broad-scale application. Thus, the paramount concern is to enhance the performance of bamboo materials through modification. However, prevailing reviews of bamboo modification predominantly concentrate on physical or chemical approaches, resulting in a conspicuous absence of a comprehensive overview of bamboo modification techniques. This review explores an array of bamboo treatment modalities and delivers a valuable assessment of bamboo modification, offering significant guidance for forthcoming bamboo enhancement and utilization endeavors.
Response of a Sylvan Moss Species (Didymodon validus Limpr.) with a Narrow Distribution Range to Climate Change
Authors: Wu Tingting , Pan Chuntong , Bian Tao , Wang Qiaoxin , Kou Jin , Zhou Bangwei
Published: November 2023

Mosses are particularly susceptible to climate change owing to their close biological and ecological associations with climatic conditions. However, there is a limited understanding of the changes in distribution patterns of the moss species in forest ecosystems under climate change, especially in mosses with narrow ranges. Therefore, we reconstructed historical, simulated present, and predicted future potential distribution patterns of Didymodon validus, a narrow-range moss species in the forest ecosystem, using the MaxEnt model. The aim of this study was to explore its unique suitable habitat preference, the key environmental factors affecting its distribution, and the distributional changes of D. validus under climate change at a long spatial-time scale. Our findings indicate that the most suitable locations for D. validus are situated in high-altitude regions of southwestern China. Elevation and mean temperature in the wettest quarter were identified as key factors influencing D. validus distribution patterns. Our predictions showed that despite the dramatic climatic and spatial changes over a long period of time, the range of D. validus was not radically altered. From the Last Interglacial (LIG) to the future, the area of the highly suitable habitat of D. validus accounted for only 15.3%–16.4% of the total area, and there were weak dynamic differences in D. validus at different climate stages. Under the same climate scenarios, the area loss of suitable habitat is mainly concentrated in the northern and eastern parts of the current habitat, while it may increase in the southern and eastern margins. In future climate scenarios, the distribution core zone of suitable habitat will shift to the southwest for a short distance. Even under the conditions of future climate warming, this species may still exist both in the arid and humid regions of the QTP in China. In summary, D. validus showed cold and drought resistance. Our study provides important insights and support for understanding the impact of climate change on the distribution of D. validus, as well as its future distribution and protection strategies.
Effect of the Timber Legality Requirement System on Lumber Trade: Focusing on EUTR and Lacey Act
Authors: Kim Ki-Dong , Shim Gyuhun , Choi Hyun-Im , Kim Dong-Hyun
Published: November 2023

This study provides novel insights into the policy effects of timber legality verification methods, specifically Due-diligence (under the European Union Timber Regulation (EUTR)) and Due-care (under the Lacey Act), on coniferous and non-coniferous lumber trade, highlighting their significance in the context of global lumber trade. Timber legality verification plays a pivotal role in the global timber trade. We comprehensively assess the impact of verification methods on coniferous and non-coniferous lumber trade, utilizing two decades of trade data (1997–2017) across approximately 160 countries. We employ the difference-in-differences method based on the gravity model of international trade, utilizing robust export–import data and demographic profiles. Our findings demonstrate that the effect of EUTR on coniferous lumber imports ranged between −0.32% and −0.05%, and that on non-coniferous lumber imports ranged between −0.44% and −0.05%, whereas the effect of the Lacey Act on coniferous lumber imports ranged between −0.93% and −0.09%. Non-coniferous lumber imports remained unaffected. The Voluntary Partnership Agreement (VPA) led to decreased exports to the EU and US. Our findings hold two key implications. First, Due-diligence exhibits more consistent policy effects than Due-care. Second, supporting VPA-participating countries is crucial for facilitating timber trade. These insights inform timber trade policies and sustainable practices.
Effects of a Forest Therapy Program on Physical Health, Mental Health, and Health Behaviors
Authors: Chun Hae-ryoung , Cho Inhyung , Choi Yoon Young , Park Sujin , Kim Geonwoo , Cho Sung-il
Published: November 2023

(1) Background: Although interest in the health-promoting effects of forest therapy is increasing, few researchers have investigated the mid-long-term impact of such therapy on health indicators or exercise behaviors. We explored changes in physical health, mental health, and exercise behaviors 1, 2, and 4 weeks after a forest therapy program concluded. We sought to establish a solid foundation for such programs and a standardized evaluation system. (2) Method: We measured the blood pressure and heart rate variability of 99 adults before and after participation in a forest therapy program. We used the State-Trait Anxiety Inventory to assess anxiety, the Beck Depression Inventory to evaluate both anxiety and depression, the Profile of Mood States to explore mood, the Euro-Quality of Life-5 Dimension scale to assess the overall quality of life, and the Positive and Negative Effect Schedule to measure positive and negative mood. We employed the Global Physical Activity Questionnaire to determine exercise time, intensity, and changes in exercise type before the program and 1–4 weeks after program completion. (3) Results: Anxiety, depression, mood, quality of life, heart rate, and blood pressure control improved significantly after the program. The reduced depression and increased medium-intensity exercise time persisted for 1, 2, and 4 weeks after the end of the program. (4) Conclusions: We tracked various health indicators and clearly distinguished those that were useful in the short term from those more appropriate for evaluation in the long term. This is the first report to show that a forest therapy program affects exercise behavior; this suggests that health behaviors should be continuously tracked.
Effect of a Multi-Strain Probiotic on Growth Performance, Lipid Panel, Antioxidant Profile, and Immune Response in Andaman Local Piglets at Weaning
Authors: Sarkar Gopal , Mondal Samiran , Bhattacharya Debasis , Ponraj Perumal , Sawhney Sneha , Bala Prokasananda , Chakraborty Dibyendu , Sunder Jai , De Arun Kumar
Published: November 2023

This study aimed to investigate the role of a multi-strain probiotic compound containing Bacillus mesentericus, Bacillus coagulans, Enterococcus faecalis, and Clostridium butyricum as an in-feed zinc oxide (ZnO) alternative in growth performance, diarrhea incidence, antioxidant profile, lipid panel, stress, and immunity in piglets at weaning. Seventy-two piglets weaned at 27 ± 1 day were divided randomly into three groups with four replicates of six piglets each: (i) a negative control group (WC) fed only a basal diet, (ii) a probiotic group (WB) fed a basal diet with the current probiotic formulation, and (iii) a positive control (PC) group fed a basal diet with 2500 mg/kg ZnO. The experiment was conducted for 28 days. Probiotic supplementation showed a positive effect on growth performance and reduced the diarrhea rate. The mean body weight of the piglets in the WB and PC groups was significantly higher than that of piglets in the WC group (14.88 ± 0.12, 14.97 ± 0.13 vs. 13.80 ± 0.06 kg; p ≤ 0.001). The addition of probiotic to the diet improved the lipid panel; the WB group showed a significantly higher level of high-density lipoprotein cholesterol (mg/dL) (32.67 ± 0.85 in WB vs. 12.48 ± 0.76 in WC; p ≤ 0.001) and lower levels of total cholesterol (mg/dL) (59.78 ± 1.97 in WB vs. 119.11 ± 2.12 in WC; p ≤ 0.001) and low-density lipoprotein cholesterol (mg/dL) (17.90 ± 1.12 in WB vs. 69.10 ± 3.37 in WC; p ≤ 0.001) compared with the negative control group. Moreover, probiotic supplementation enhanced the antioxidant defense system and provided protection from oxidative damage by increasing the concentrations of serum catalase, glutathione-S-transferase, and superoxide dismutase and by decreasing the concentrations of serum malonyldialdehyde and total nitric oxide. Heat shock proteins and other stress markers, such as serum cortisol, were reduced in the probiotic-fed group. The probiotic group also displayed higher levels of serum IgG and IgM at all time points and higher IgA on day 28 compared with the negative control group. Altogether, these results indicate that feeding with the currently used multi-strain probiotic formulation minimizes weaning stress, thereby improving the growth performance, antioxidant profile, lipid panel, and systemic and mucosal immunity. Therefore, multi-strain probiotic compounds may be used to replace ZnO in weaned piglets.
Simulation of Relaxation Processes in Hypersonic Flows with One-Temperature Non-Equilibrium Model
Authors: Karpenko Anton , Tolstoguzov Semen , Volkov Konstantin
Published: November 2023

Steady-state one-dimensional flows of five-component air behind a normal shock wave are considered with a one-temperature model. A mathematical model is formulated to describe the relaxation of a five-component air mixture with a one-temperature non-equilibrium approximation. A numerical study of non-equilibrium flows of a reacting five-component air mixture behind shock waves at different heights and velocities of free flow is performed. The contribution of different types of reactions to the overall relaxation of the mixture is discussed, and the distributions of macro-parameters of the flow behind the shock wave front are calculated. The lengths of the relaxation zones behind the shock wave front are compared at different initial conditions. Calculations are performed for the standard model of atmosphere.
Simulating Flow in an Intestinal Peristaltic System: Combining In Vitro and In Silico Approaches
Authors: Liu Xinying , Zhong Chao , Fletcher David F. , Langrish Timothy A. G.
Published: November 2023

Transport and mixing in the gastric duct occur via peristaltic flow. In vivo data are hard to collect and require strict ethical approval. In contrast, both in vitro and in silico studies allow detailed investigation and can be constructed to answer specific questions. Therefore, the aim of this study was to design a new elastic thermoplastic polyurethane (TPU) intestine model and to compare the flow patterns observed experimentally with those predicted by a Fluid Structure Interaction (FSI) simulation. Here, we present complementary studies that allow feedback to improve both techniques and provide mutual validation. The experimental work provides direct measurement of mixing, and the simulation allows the experimental setup to be studied to determine the impacts of various parameters. We conclude by highlighting the utility of this approach.
Effects of Pig Dietary n-6/n-3 Polyunsaturated Fatty Acids Ratio and Gender on Carcass Traits, Fatty Acid Profiles, Nutritional Indices of Lipid Depots and Oxidative Stability of Meat in Medium–Heavy Pigs
Authors: Minelli Giovanna , D’Ambra Katia , Macchioni Paolo , Lo Fiego Domenico Pietro
Published: November 2023

The effects of different dietary n-6/n-3 polyunsaturated fatty acids (PUFA) ratios and gender on key carcass traits, as well as the nutritional and technological quality of lipids in medium–heavy pig tissues have been poorly studied. To investigate the subject, 24 Large White, barrows and gilts, evenly divided into two groups of 12, were fed from 80 kg of live-weight (LW) until slaughter at 150 kg LW, either a high (9.7:1) (HPR) or low (1.4:1) (LPR) dietary n-6/n-3 PUFA ratio. On individual samples of longissimus thoracis muscle (LTM), subcutaneous (SF) and perirenal (PF) adipose tissues (ATs), the fatty acid (FA) composition was determined by gas chromatography, and lipid nutritional indices (LNIs) were calculated. The oxidative stability of meat was evaluated by determining the malondialdehyde content on raw and cooked (24 h postmortem) and refrigerated (8 days postmortem) LTM samples. The carcass traits did not vary between genders and diets. The LPR group showed a higher n-3 PUFA level and a lower n-6/n-3 PUFA ratio in all the tissues examined and better LNI, especially in the ATs. Diet did not affect the oxidative stability of meat. Gender did not influence the n-6/n-3 PUFA ratio, while barrows showed improvements in some LNI in ATs. Reducing the n-6/n-3 ratio in the diet of growing–finishing medium–heavy pigs improved the FA profile in all tissues and most LNI in ATs without impairing the oxidative stability of meat.
Rice-Based Gluten-Free Foods and Technologies: A Review
Authors: Park Jiyoung , Kim Hong-Sik
Published: November 2023

Rice, one of the most widely consumed staples worldwide, serves as a versatile gluten-free substitute. However, review articles on technological developments in grain-free production focusing on rice are scarce. This review assesses various research results concerning the quality attributes of rice-based gluten-free foods, including bread, pasta, and beer. To optimize the key attributes in processed products, such as dough leavening in bread and the physical and cooking properties of noodles and pasta, research has focused on blending different gluten-free grains and incorporating additives that mimic the gluten function. Additionally, various processing technologies, such as starch preprocessing and extrusion puffing processes, have been employed to boost the quality of rice-based gluten-free products. Today, a variety of products, including bread, noodles, and beer, use rice as a partial replacement for barley or wheat. With rapid advancements in technology, a noticeable portion of consumers now shows a preference for products containing rice as a substitute. This trend indicates that rice-based gluten-free foods can be enhanced by leveraging the latest developments in gluten-free product technologies, particularly in countries where rice is a staple or is predominantly cultivated.