bluuebunny/crossref_metadata_2025 huggingface dataset:
Low-Cost Training of Image-to-Image Diffusion Models with Incremental Learning and Task/Domain Adaptation
Authors: Antona Hector , Otero Beatriz , Tous Ruben
Published: February 2024

Diffusion models specialized in image-to-image translation tasks, like inpainting and colorization, have outperformed the state of the art, yet their computational requirements are exceptionally demanding. This study analyzes different strategies to train image-to-image diffusion models in a low-resource setting. The studied strategies include incremental learning and task/domain transfer learning. First, a base model for human face inpainting is trained from scratch with an incremental learning strategy. The resulting model achieves an FID score almost equivalent to that of its batch learning equivalent while significantly reducing the training time. Second, the base model is fine-tuned to perform a different task, image colorization, and, in a different domain, landscape images. The resulting colorization models showcase exceptional performances with a minimal number of training epochs. We examine the impact of different configurations and provide insights into the ability of image-to-image diffusion models for transfer learning across tasks and domains.
A Simple Method for Solving the Power Fluctuation Issue of a Base Station’s Surrounding Areas Based on Half Tyler Distribution
Authors: Duan Lifeng , Zhang Jinling , Zhu Xiongzhi , Zhang Yu , Chang Dunyu , Dong Jiaqi , Zhang Xiaoxian
Published: February 2024

This paper proposes array antennas based on half Tyler (HT) distribution that can realize omnidirectional null-free (ONF) beams. Array 1 employs the usual edge feeding approach, working at 3.5 GHz with a bandwidth of 0.25 GHz, whereas array 2 operates at 26 GHz with a bandwidth of 3 GHz. We evaluated the far-field performance of linear arrays consisting of 6, 8, 12, and 16 elements. The simulation and measurement results show that the proposed HT approach can achieve a near-ONF pattern and cover a broad area of ±42° on an eight-element linear array. The ONF beam reduces community power fluctuations and increases power by 20 dBm in surrounding areas of the base station (BS). The fluctuation treatment effect can be influenced by adjusting the weighting of sidelobe depression (dp): compared to the uniformly excited one, for example, the maximum ONF gain of an eight-element linear operating at 3.5 GHz is only reduced by 0.5 dB when dp = −30 and by 1–2 dB when dp = −60.
Comparative Analysis of Metaheuristic Optimization Methods for Trajectory Generation of Automated Guided Vehicles
Authors: Bayona Eduardo , Sierra-García Jesús Enrique , Santos Matilde
Published: February 2024

This paper presents a comparative analysis of several metaheuristic optimization methods for generating trajectories of automated guided vehicles, which commonly operate in industrial environments. The goal is to address the challenge of efficient path planning for mobile robots, taking into account the specific capabilities and mobility limitations inherent to automated guided vehicles. To do this, three optimization techniques are compared: genetic algorithms, particle swarm optimization and pattern search. The findings of this study reveal the different efficiency of these trajectory optimization approaches. This comprehensive research shows the strengths and weaknesses of various optimization methods and offers valuable information for optimizing the trajectories of industrial vehicles using geometric occupancy maps.
A Novel Enhancement-Mode Gallium Nitride p-Channel Metal Insulator Semiconductor Field-Effect Transistor with a Buried Back Gate for Gallium Nitride Single-Chip Complementary Logic Circuits
Authors: Wang Haochen , Chen Kuangli , Yang Ning , Zhu Jianggen , Duan Enchuan , Huang Shuting , Zhao Yishang , Zhang Bo , Zhou Qi
Published: February 2024

In this work, a novel enhancement-mode GaN p-MISFET with a buried back gate (BBG) is proposed to improve the gate-to-channel modulation capability of a high drain current. By using the p-GaN/AlN/AlGaN/AlN double heterostructure, the buried 2DEG channel is tailored and connected to the top metal gate, which acts as a local back gate. Benefiting from the dual-gate structure (i.e., top metal gate and 2DEG BBG), the drain current of the p-MISFET is significantly improved from −2.1 (in the conv. device) to −9.1 mA/mm (in the BBG device). Moreover, the dual-gate design also bodes well for the gate to p-channel control; the subthreshold slope (SS) is substantially reduced from 148 to ~60 mV/dec, and such a low SS can be sustained for more than 3 decades. The back gate effect and the inherent hole compensation mechanism of the dual-gate structure are thoroughly studied by TCAD simulation, revealing their profound impact on enhancing the subthreshold and on-state characteristics in the BBG p-MISFET. Furthermore, the decent device performance of the proposed BBG p-MISFET is projected to the complementary logic inverters by mixed-mode simulation, showcasing excellent voltage transfer characteristics (VTCs) and dynamic switching behavior. The proposed BBG p-MISFET is promising for developing GaN-on-Si monolithically integrated complementary logic and power devices for high efficiency and compact GaN power IC.
Enhancing Privacy in the Internet of Vehicles via Hyperelliptic Curve Cryptography
Authors: Routis George , Dagas Panagiotis , Roussaki Ioanna
Published: February 2024

The Internet of Things (IoT) is a technological paradigm that has gained significant momentum the last decade and, among other features, enables the development of intelligent and interoperable device networks. In this respect, it has triggered the creation and evolution of vehicular ad-hoc networks (VANETs), which are initially implemented in order to guarantee the safety of drivers and the avoidance of traffic accidents. The drawback is that this fast evolution comes with serious concerns in terms of the privacy of users, while the population of attackers or entities that try to eavesdrop and intercept information has significantly increased. This imposes a serious risk for drivers moving across a Smart City. The research presented in this paper aims to evaluate privacy protection mechanisms in VANET environments, based on the efficiency and security level they ensure, considering the fact that VANETs provide limited resources to users/drivers. Moreover, the usage of elliptic curve cryptography in reduced resources environments is discussed. Finally, this paper compares the performance of three cryptographic algorithms, elliptic curve cryptography (ECC), hyperelliptic curve cryptography genus 2 (HECC-2) and HECC genus 3 (HECC-3), employed for an efficient authentication and safe message transmission mechanism in VANETs, aimed at reaching conclusions related to the implementation of each cryptographic scheme in this specific application area. The evaluation results indicate that ECC supersedes HECC-2 and HECC-3 in most metrics. However, HECC-2 and HECC-3 demonstrate better responses than ECC does in selected energy metrics. Overall, it is observed that HECC algorithms are not yet mature enough to compete with ECC. This is due to the fact that the research community has not sufficiently progressed toward the optimization of HECC, and moreover, HECC builds on quite complex mathematics. There are indications, however, that once HECC curves are indeed optimized, HECC will outperform ECC in speed as well as in other metrics, sinceHECC-2 and HECC-3 use a significantly smaller key size with the same level of security as that of ECC.
Working toward Solving Safety Issues in Human–Robot Collaboration: A Case Study for Recognising Collisions Using Machine Learning Algorithms
Authors: Patalas-Maliszewska Justyna , Dudek Adam , Pajak Grzegorz , Pajak Iwona
Published: February 2024

The monitoring and early avoidance of collisions in a workspace shared by collaborative robots (cobots) and human operators is crucial for assessing the quality of operations and tasks completed within manufacturing. A gap in the research has been observed regarding effective methods to automatically assess the safety of such collaboration, so that employees can work alongside robots, with trust. The main goal of the study is to build a new method for recognising collisions in workspaces shared by the cobot and human operator. For the purposes of the research, a research unit was built with two UR10e cobots and seven series of subsequent of the operator activities, specifically: (1) entering the cobot’s workspace facing forward, (2) turning around in the cobot’s workspace and (3) crouching in the cobot’s workspace, taken as video recordings from three cameras, totalling 484 images, were analysed. This innovative method involves, firstly, isolating the objects using a Convolutional Neutral Network (CNN), namely the Region-Based CNN (YOLOv8 Tiny) for recognising the objects (stage 1). Next, the Non-Maximum Suppression (NMS) algorithm was used for filtering the objects isolated in previous stage, the k-means clustering method and Simple Online Real-Time Tracking (SORT) approach were used for separating and tracking cobots and human operators (stage 2) and the Convolutional Neutral Network (CNN) was used to predict possible collisions (stage 3). The method developed yields 90% accuracy in recognising the object and 96.4% accuracy in predicting collisions accuracy, respectively. The results achieved indicate that understanding human behaviour working with cobots is the new challenge for modern production in the Industry 4.0 and 5.0 concept.
MTTEGDM: A Moving Target Evolutionary Game Defense Model Based on Three-Way Decisions
Authors: Zhang Zhihua , Liu Lu , Zhang Chunying , Ren Jing , Ma Jiang , Wang Liya , Liu Bin
Published: February 2024

Aiming at the fact that the moving target defense game model fails to accurately portray attack and defense gains, resulting in bias in attack and defense games and the inability to select effective defense strategies, we construct the moving target three-way evolutionary game defense model (MTTEGDM). Firstly, the model is defined and analyzed theoretically under the premise of uncertainty and irrationality. Then, combined with the three-way decisions, the attack intention is introduced into the target network loss calculation, and a dynamic weight adjustment algorithm based on the three-way decisions is proposed to accurately characterize the attack and defense gains from a multi-attribute perspective. Finally, the evolutionary game model is used to analyze the evolution trend of the multi-stage defense strategy, so as to carry out feasible and effective defense behavior. The simulation results show that the model can accurately predict the optimal defense strategy of moving targets in different stages. Through a Monte Carlo simulation experiment, the proposed algorithm is compared with the traditional evolutionary game model, and the effectiveness and security of the proposed algorithm are verified.
Evaluation of Human Perception Thresholds Using Knowledge-Based Pattern Recognition
Authors: Ogiela Marek R. , Ogiela Urszula
Published: February 2024

This paper presents research on determining individual perceptual thresholds in cognitive analyses and the understanding of visual patterns. Such techniques are based on the processes of cognitive resonance and can be applied to the division and reconstruction of images using threshold algorithms. The research presented here considers the most important parameters that affect the determination of visual perception thresholds. These parameters are the thematic knowledge and personal expectations that arise at the time of image observation and recognition. The determination of perceptual thresholds has been carried out using visual pattern splitting techniques through threshold methods. The reconstruction of the divided patterns was carried out by combining successive components that, as information was gathered, allowed more and more details to become apparent in the image until the observer could recognize it correctly. The study being carried out in this way made it possible to determine individual perceptual thresholds for dozens of test subjects. The results of the study also showed strong correlations between the determined perceptual thresholds and the participants’ accumulated thematic knowledge, expectations and experiences from a previous recognition of similar image patterns.
Electromagnetic Environment Assessment and Safety Research of Electrified High-Speed Railway Carriages
Authors: Shi Lei , Liang Junyi , Liu Yazhi , Zhao Yuanyuan , Li Xinran
Published: February 2024

With the advent of modern, high-speed electrified rail systems, there has been increasing concern about electromagnetic safety in rail carriages. The aim of this study was to assess the electromagnetic safety of passengers on trains by utilizing advanced 3D electromagnetic simulation software. A comprehensive model of the electromagnetic environment experienced by passengers on a CR400AF train, specifically under the influence of catenary radiation, was constructed. We analyzed the magnetic field strength, electric field strength, and current density in the brains of 20 passengers in various positions in the train. The findings revealed that among the 20 passengers analyzed, the maximum and minimum magnetic induction intensity recorded in the brain were 8.41 and 0.01 μT, respectively. The maximum and minimum induced electric field intensities were 1110 and 10 μV/m, respectively. Lastly, the maximum and minimum induced current densities were 1200 and 10 μA/m2, respectively. The results show that when people ride on the CR400AF train, the magnetic induction intensity, induced electric field strength, and induced current density in the brain are below the recommended basic limits of exposure to power frequency electromagnetic fields in the guidelines of the International Committee on Non-Ionizing Radiation Protection. The power frequency magnetic field generated by the catenary can be effectively shielded by the aluminum alloy car body. The final result of this study indicates that the electromagnetic exposure from the contact wire at the level 25 kV does not pose a threat to the health of passengers on the CR400AF train.
A Multi-View Temporal Knowledge Graph Reasoning Framework with Interpretable Logic Rules and Feature Fusion
Authors: Xu Hongcai , Bao Junpeng , Li Hui , He Chao , Chen Feng
Published: February 2024

A temporal knowledge graph represents temporal information between entities in a multi-relational graph. Its reasoning aims to infer and predict potential links among entities. Predicting time-aware entities is a challenging task due to significant differences in entity appearances over time, such as different timestamps and frequencies. Current embedding-based similarity-matching methods have been introduced for predicting temporal facts. However, they lack deterministic logical explainability and cannot model the dynamic evolution of entities over time. To address these challenges, we propose a novel framework for temporal knowledge graph reasoning based on multi-view feature fusion (MVFF). First, MVFF extracts logical rules and uses the Gumbel-Softmax trick to sample high-quality rules. Second, it integrates logical rules, temporal quadruples, and factual triples to capture semantic features, temporal information, and structural information to solve link prediction tasks. Through experiments on four benchmark datasets, we show that MVFF outperforms state-of-the-art methods, providing not only better performance but also interpretable results.
A Backup Protection Based on Compensated Voltage for Transmission Lines Connected to Wind Power Plants
Authors: Wang Hao , Li Xiaopeng , Dong Xinzhou , Jiang Xiaofeng
Published: February 2024

Due to the influence of complex control, the short circuit current provided by wind power generation units will exhibit new characteristics, such as limited amplitude and controlled phase, affecting the performance of traditional protections. This paper analyzes the work principle and defects of one kind of multiphase compensated distance protection. Drawing on the idea of fault identification by multiphase compensated distance protection, novel pilot protection using the compensated voltage on both sides is proposed. The proposed method has a strong anti-fault resistance ability. The test results indicate that the proposed method can distinguish the internal faults and external faults reliably, unaffected by the new characteristics of short circuit current.
A Voltage-Aware P2P Power Trading System Aimed at Eliminating Unfairness Due to the Interconnection Location
Authors: Takayama Satoshi , Ishigame Atsushi
Published: February 2024

P2P power trading is necessary for efficiently using consumer electricity not subject to FIT. However, the execution rules for P2P power trading do not include restrictions on voltage, and there is a trade-off between the activation of the P2P power trading market through the mass introduction of PV and the optimization of the voltage of the power distribution system. In addition, there is a tendency for output curtailment to be biased toward consumers connected to the end of the grid. Since consumers cannot choose the interconnection location, there are concerns about unfairness. In this study, we investigate a new P2P model that includes voltage constraints for the execution rules of P2P power trading to avoid voltage deviation while ensuring benefits and fairness for the participants. In the proposed model, to increase the incentive to participate in the P2P power trading market, we consider compensating consumers who receive output curtailment signals due to voltage constraints. In addition, the profit is secured by differentiating the compensation cost unit price depending on the contract’s availability. A case study was conducted on this model using the IEEE 33 bus system. The results show that the proposed model is superior.
An Indicator Framework for Evaluating Building Renovation Potential
Authors: Danielsen Barbara Eschen , Baxter Morten Niels , Nielsen Per Sieverts
Published: February 2024

Implementation of a new European Union directive on energy renovation in Denmark can be expected to have a strong impact on the country’s energy renovation requirements. Accordingly, an indicator framework has been developed with the aim of identifying and quantifying the energy renovation potential of a specific Danish municipality. We identified and selected four indicators—energy consumption, CO2 emissions, heating costs and current energy labels—specifically for detached dwellings. The physical renovation potential was then quantified based on the indicator results, and an average score for the four indicators was calculated for each of the 10,228 detached dwellings in the municipality. All four indicators were weighted equally in the calculations of the total renovation potential score. The methods used in this study can be applied more widely as they rank detached dwellings according to their renovation potential. However, we also found that more detailed data are necessary to determine the specific renovation potential of detached dwellings. A greater effort to collect more data on the part of the municipalities would improve the accuracy of analyses.
Multi-Output Regression Algorithm-Based Non-Dominated Sorting Genetic Algorithm II Optimization for L-Shaped Twisted Tape Insertions in Circular Heat Exchange Tubes
Authors: Li Shijie , Qian Zuoqin , Liu Ji
Published: February 2024

In this study, an optimization method using various multi-output regression models as model proxies within the NSGA-II framework was applied to determine the geometric parameters (P, W, D) of L-shaped twisted tape inserts for achieving the optimal overall heat transfer performance in a circular heat exchange tube. Herein, 4 multi-output regression models, namely, MOLR, MOSVR, MOGPR, and BPNN, were selected as proxy models and trained on a dataset containing 74 groups of data. The training results indicated that the MOGPR model, balancing high accuracy and low error conditions, exhibited moderate training times among the four algorithms. BPNN showed a comparatively lower comprehensive training effect, obtaining training accuracy close to that of the MOGPR algorithm but with approximately twice the training time. The worst fitting performance was gained with the MOSVR algorithm. Due to its fitting performance, the MOSVR algorithm was excluded from the subsequent NSGA-II model proxy. Through multi-objective optimization with NSGA-II, the optimal structural dimensions for three sets of L-shaped twisted tape inserts were obtained to achieve the best overall heat transfer efficiency within the tube.
Effects of Near-Critical Condensation and Cavitation on the Performance of S-CO2 Compressor
Authors: Xie Wenlin , Tian Yong , Jiang Peng , Wang Bo , Xu Xiang
Published: February 2024

The supercritical carbon dioxide (S-CO2) Brayton cycle efficiency increases as the compressor inlet condition approaches the critical point. However, the thermodynamic properties of CO2 vary dramatically near the critical point, and phase change is most likely to happen. Both cavitation and condensation bring about significant adverse effects on the performance of compressors. In this paper, the quantitative effects of nonequilibrium condensation and cavitation on the performance of an S-CO2 centrifugal compressor with different inlet-relative entropy values are investigated. The properties of CO2 were provided by the real-gas property table, and the nonequilibrium phase-change model was adopted. The numerical simulation method with the nonequilibrium phase-change model was validated in the Lettieri nozzle and Sandia compressor. Furthermore, simulations were carried out in a two-stage centrifugal compressor under conditions of various inlet-relative entropy values. The type of nonequilibrium phase change can be distinguished by inlet-relative entropy. Cavitation makes the choke mass flow rate decrease due to the drop in the speed of sound. Condensation mainly occurs on the leading edge of the main blade at a large mass flow rate, but cavitation occurs on the splitter. The condensation is more evenly distributed on the main blade, but the cavitation is mainly centered on the leading edge.
Improving the Indoor Air Quality of Office Buildings in the Post-Pandemic Era—Impact on Energy Consumption and Costs
Authors: D’Agostino Diana , Minelli Federico , Minichiello Francesco , Musella Maddalena
Published: February 2024

Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope.
Improvement of Laser-Induced Damage on High-Efficiency Solar Cells via Top-Hat Beam Ablation
Authors: Qian Feng , Shen Honglie , Huang Guoping , Liu Biao , Hong Juan
Published: February 2024

An important challenge in industrial laser ablation is laser-induced damage. In this study, reduced damage was achieved through the transition of the laser distribution from a Gaussian beam to a top-hat beam using diffractive optical elements (DOE), which overcome inhomogeneous irradiation. The higher peak fluence of a Gaussian beam far exceeded the ablation threshold and led to severely melted silicon at a higher depth covering the polished texture. The top-hat beam, with uniform irradiation, had a superior ablation characteristic and created a uniform square opening with the shallow melted silicon in the lift-off process. Thus, its effective minor carrier lifetime was 15.35% less at an ablated area fraction of 2% after re-passivation because of the decreased damage. After optimizing the ablation pattern with a top-hat beam, the local contacts improved the average open-circuit voltage (Voc) and short-circuit current (Isc) values of the cells due to the decreased damage and the uniform openings, but the damage induced by a Gaussian beam was too deep and can be partly restored under back surface field (BSF) formation. The overall increment in Isc and Voc enhanced the average efficiency by 0.05% of the absolute value for the PERC cells and 0.03% of the absolute value for bi-facial PERC cells.
Pore Structure Characteristics of Shale Oil Reservoirs with Different Lithofacies and Their Effects on Mobility of Movable Fluids: A Case Study of the Chang 7 Member in the Ordos Basin, China
Authors: Xiao Yufang , Ye Zhengqin , Wang Hongliang , Yang Hailong , Mu Nana , Ji Xinyuan , Zhao He
Published: February 2024

The Chang 7 member of the Triassic Yanchang Formation in the Ordos Basin is a significant continent shale oil reservoir in China. Therefore, conducting an in-depth investigation into the pore structure and fluid mobility characteristics of the Chang 7 shale oil reservoir holds immense importance for advancing shale oil exploration. This study conducts a detailed analysis of the pore structures and their impact on fluid mobility of the Chang 7 shale oil reservoir using multiple methodologies, i.e., a cast thin section, scanning electron microscopy (SEM), X-ray diffraction (XRD), high-pressure mercury injection (HPMI), low-temperature nitrogen adsorption (LTNA), and nuclear magnetic resonance (NMR). The results show that the sandstone in the Yanwumao area of the Chang 7 shale oil reservoir consists mainly of lithic arkose and feldspathic litharenite, which can be classified into three lithofacies (massive fine-grained sandstone (Sfm), silt-fine sandstone with graded bedding (Sfgb), and silt-fine sandstone with parallel bedding (Sfp)). Moreover, three pore structures (Type I, II, and III), and four pore spaces (nanopores, micropores, mesopores, and macropores) can be characterized. Pore structure Type I, characterized by large pores, exhibits bimodal pore diameter curves, resulting in the highest levels of movable fluid saturation (MFS) and movable fluid porosity (MFP). Pore structure Type II demonstrates unimodal pore structures, indicating robust connectivity, and higher MFS and MFP. Pore structure Type III primarily consists of dissolved and intercrystalline pores with smaller pore radii, a weaker pore configuration relationship, and the least fluid mobility. Furthermore, a correlation analysis suggests that the pore structure significantly impacts the fluid flowability in the reservoir. Favorable petrophysical properties and large pores enhance fluid flowability. Micropores and mesopores with high fractal dimensions have a greater impact on reservoir fluid mobility compared to macropores and nanopores. Mesopores mainly control MFS and MFP, while micropores govern the shift from bound fluid to movable fluid states. Among the lithofacies types, the Sfm lithofacies exhibit the highest fluid mobility due to their significant proportion of macropores and mesopores, whereas the Sfgb lithofacies have lower values because they contain an abundance of micropores. The Sfp lithofacies also dominate macropores and mesopores, resulting in medium fluid mobility levels. This study combines lithofacies types, micro-reservoir pore structure characteristics, and mobile fluid occurrence characteristics to better understand the dominant reservoir distribution characteristics of the Chang 7 shale oil reservoirs in the Ordos Basin and provide theoretical information for further optimization of production strategies.
Optimization of Financial Indicators in Shale-Gas Wells Combining Numerical Decline Curve Analysis and Economic Data Analysis
Authors: Soage Andres , Juanes Ruben , Colominas Ignasi , Cueto-Felgueroso Luis
Published: February 2024

We present a methodology to determine optimal financial parameters in shale-gas production, combining numerical simulation of decline curves and stochastic modeling of the gas price. The mathematical model of gas production considers free gas in the pore and the gas adsorbed in kerogen. The dependence of gas production on petrophysical parameters and stimulated permeability is quantified by solving the model equations in a 3D geometry representing a typical fractured shale well. We use Monte Carlo simulation to characterize the statistical properties of various common financial indicators of the investment in shale-gas. The analysis combines many realizations of the physical model, which explores the variability of porosity, induced permeability, and fracture geometry, with thousands of realizations of gas price trajectories. The evolution of gas prices is modeled using the bootstrapping statistical resampling technique to obtain a probability density function of the initial price, the drift, and the volatility of a geometric Brownian motion for the time evolution of gas price. We analyze the Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback Period (DPP) indicators. By computing the probability density function of each indicator, we characterize the statistical percentile of each value of the indicator. Alternatively, we can infer the value of the indicator for a given statistical percentile. By mapping these parametric combinations for different indicators, we can determine the parameters that maximize or minimize each of them. We show that, to achieve a profitable investment in shale-gas with high certainty, it is necessary to place the wells in extremely good locations in terms of geological parameters (porosity) and to have exceptional fracturing technology (geometry) and fracture permeability. These high demands in terms of petrophysical properties and hydrofracture engineering may explain the industry observation of “sweet spots”, that is, specific areas within shale-gas plays that tend to yield more profitable wells and where many operators concentrate their production. We shed light on the rational origin of this phenomenon: while shale formations are abundant, areas prone to having a multi-parameter combination that renders the well profitable are less common.
Interannual Variation in Gas Exchange and Leaf Anatomy in Cenostigma pyramidale Is Exacerbated through El Niño and La Niña Climate Events
Authors: Pompelli Marcelo F. , Jarma-Orozco Alfredo , Jaraba-Navas Juan de Dios , Pineda-Rodriguez Yirlis Yadeth , Rodríguez-Páez Luis Alfonso
Published: February 2024

This study sheds light on the remarkable physiological adaptations that the Cenostigma pyramidale makes, particularly during periods of extreme water scarcity, and their remarkable ability to rebound when a new rainy season arrives. C. pyramidale employs a survival strategy to mitigate the adverse effects of water shortage and then endures challenging environmental conditions and sustaining vital functions. Previously, this species was classified as deciduous since it retained at least 40% of its leaves to sustain basal gas exchange rates. The discrepancy in classification arises from differences in study methodologies, with this research being conducted in the field under natural conditions. This study demonstrates a negative correlation between rainfall and specific leaf area (SLA), highlighting that plants with smaller SLA are more drought-tolerant. Changes in leaf anatomy, including an increase in palisade parenchyma and reduction in spongy tissue, serve as adaptive strategies to enhance photosynthesis under water stress conditions. Hydraulic conductance plays a crucial role in plant adaptation to water scarcity. An intricate interplay between leaf anatomy and hydraulic conductance is observed, with adjustments in xylem characteristics influencing leaf gas exchange. The phenotypic plasticity is high in C. pyramidale, demonstrating the species’ ability to adapt to changing environmental conditions. In summary, this study illuminates the multifaceted strategies employed by plants to cope with water scarcity, from leaf shedding to anatomical and physiological adaptations, highlighting the resilience of native species in arid environments. These findings offer valuable insights into plant responses to environmental stress and their ability to thrive in challenging conditions.
Investigating Water Storage Dynamics in the Litter Layer: The Impact of Mixing and Decay of Pine Needles and Oak Leaves
Authors: Ilek Anna , Błońska Ewa , Miszewski Kamil , Kasztelan Adrian , Zborowska Magdalena
Published: February 2024

Little is known about how the degree of mixing various forest-forming species affects forest floor hydrology. We evaluated the water storage capacity of the resulting litter layer by mixing the litterfall of Scots pine and sessile oak and studying their decomposition time. We prepared 90 artificial samples containing pure pine litter, pure oak litter, and mixed pine–oak litter with varying shares of pine needles. These samples were subjected to 15 months of decomposition in soil. After every three months of decay, some samples were removed from the soil, and their water storage capacity, bulk density, and C:N ratio were evaluated. Our findings indicate that samples with the greatest water storage capacity had a low C:N ratio and a predominant share of oak leaves. Conversely, samples with a high C:N ratio and a predominant share of pine needles had the lowest water storage capacity. After 12 and 15 months of decomposition, the water storage capacity increased by more than 52% compared to the initial water capacity of the samples. The highest increase in water storage capacity (>40%) was observed in samples with a predominant share of oak leaves, while the lowest (approximately 28%) was recorded in samples with 80 and 100% of pine needles. Our findings suggest that introducing mixed-species stands, with deciduous species as the predominant component, can yield several ecological benefits, such as an increased ability to store water in forest floor.
Nutrient Variations and Their Use Efficiency of Pinus massoniana Seedling Tissues in Response to Low Phosphorus Conditions
Authors: Xu Jin , Jian Zunji , Zhang Yuanzheng , Deng Xiuxiu , Lei Lei , Zeng Lixiong , Xiao Wenfa , Ni Yanyan
Published: February 2024

Investigating the mechanisms by which plants adapt to low phosphorus content in ecosystems is crucial for nutrient dynamics division. Our study investigated the growth adaptation strategies of Pinus massoniana seedlings to low phosphorus conditions, including nutrient and non-structural carbohydrate (NSC) allocation, nutrient stoichiometry, and changes in nutrient resorption efficiency along a fact-based gradient. Our results showed that the total biomass and aboveground biomass proportion increased with substrate phosphorus content, reaching maximum biomass in the one-time phosphorus treatment. The nutrient concentration of components remained relatively stable, with the allocating preference to roots and needles under low phosphorus conditions. NSC was allocated as starch in fine roots and as soluble sugar in needles. Seedlings did not show signs of phosphorus limitation, even in the non-phosphorus group. The nitrogen resorption efficiency to phosphorus resorption efficiency ratio (NRE: PRE) of needles significantly varied between the high and low phosphorus treatments. In response to phosphorus deficiency, seedlings demonstrated homeostatic adjustments to maintain the relative stability of nutrient concentration. Fine roots and needles were prioritized to ensure nutrient uptake and photosynthetic product production. Additionally, it was necessary to differentiate the indicative function of nitrogen/phosphorus for various species and components, and NRE: PRE potentially provides a sensitive indicator of nutrient limitation status.
The Dynamics of Stand Structure Development and Natural Regeneration of Common Beech (Fagus sylvatica L.) in Plitvice Lakes National Park
Authors: Dubravac Tomislav , Barčić Damir , Rosavec Roman , Španjol Željko , Vojniković Sead
Published: February 2024

The authors investigate the structural characteristics, regeneration processes, growth, development, and survival of a young generation of common beech (Fagus sylvatica L.) based on three periodic measurements (1998, 2009, and 2018). The studied forest community (Lamio orvale-Fagetum sylvaticae (Ht. 1938) Bohridi 1963) is situated within a forest reserve in Plitvice Lakes National Park, Croatia. Monitoring was carried out according to UN/ECE (2000) for systematic and repeated research. The basic structural indicators, structural canopy elements, and appearance of the young generation were measured as the basic conditions of natural restoration in repeated phytocenological surveys (1980, 1988, 2004). The distribution of the number of trees of the first two measurements (1998–2009) indicates a distribution with pronounced right asymmetry. The structural dynamics observed during the surveys and alongside vegetation surveys indicate the dynamics of the growth and development of beech. The results show that the main drivers of development dynamics in protected forest ecosystems are structural breaks (gaps) that occur in stands due to the action of abiotic and biotic factors. The passive management model in effect in the national park should be replaced with a more active approach to facilitate natural processes with the aim of preserving and renewing the forest ecosystem.
Different Protein Hydrolysates Can Be Used in the Penaeus vannamei (Boone, 1934) Diet as a Partial Replacement for Fish Meal during the Grow-Out Phase
Authors: Negrini Celma , do Nascimento Ferreira Caio Henrique , Kracizy Rafael Ortiz , Ferreira Rosane Lopes , dos Santos Luana Cardoso , Retcheski Milena Cia , Mauerwerk Marlise Teresinha , Cazarolli Luisa Helena , Boscolo Wilson Rogério , Cupertino Ballester Eduardo Luis
Published: February 2024

This study evaluated the inclusion of protein hydrolysates and a commercial product as a partial replacement for fish meals in the diet of Pacific white shrimp (Penaeus vannamei) during the grow-out phase. A recirculation system with 24 experimental units and a biological filter was used. The experimental design was completely randomized with six treatments: control; chicken protein hydrolysate (CPH); enzymatic hydrolysate of chicken feathers; Aquabite®; CPH + maltodextrin; CPH + yeast; and four replicates. After 50 days, the zootechnical performance and animal welfare parameters, centesimal carcass composition, digestive enzyme activity, and hemocyte count were evaluated. The treatments did not affect the zootechnical performance and total hemocyte count of the animals (p > 0.05). The evaluation of the antenna length indicated that all animals were in good health. The antenna length in treatment T5 was significantly greater (p > 0.05) than that in T4 and similar to that in treatments T3 and T6, demonstrating a positive influence of dietary protein hydrolysates. Concerning animal welfare, dietary protein hydrolysates influenced the length of the antenna (p < 0.05). The antenna length associated with different treatments indicated that the animals were in good welfare conditions in the production environment. With respect to body chemical composition, dry matter, ether extract, and ash were affected by the treatments (p < 0.05). Regarding the analysis of digestive enzymes, the treatments influenced the activities of amylase and trypsin (p < 0.05). The performance of the animals was satisfactory under all treatments, including enzymatic activity, demonstrating the possibility of using hydrolysates.
Relatively Low Lecithin Inclusion Improved Gelling Characteristics and Oxidative Stability of Single-Washed Mackerel (Auxis thazard) Surimi
Authors: Panpipat Worawan , Chumin Thinnaphop , Thongkam Porntip , Pinthong Pattaraporn , Shetty Kalidas , Chaijan Manat
Published: February 2024

The effect of lecithin addition on the gelling characteristics and oxidative stability of single-washed mackerel (Auxis thazard) surimi was investigated in this study. Surimi was chopped in the presence of 2.5% (w/w) NaCl with different concentrations of lecithin (0, 0.1, 0.5, 1, and 1.5 g/100 g surimi). The rheological behavior, gel-forming ability, microstructure, and lipid oxidation of lecithin-added surimi varied significantly depending on lecithin content. When compared to the control, lecithin at 0.1, 0.5, and 1 g/100 g improved the breaking force of the gel (p < 0.05). The breaking force of the gel decreased significantly as lecithin concentration increased (up to 1.5 g/100 g) (p < 0.05). Deformation, on the other hand, reacted differently to the lecithin than it did to the breaking force. At a lecithin level of 0.1 g/100 g, the surimi gel displayed improved deformation (p < 0.05). Nonetheless, at higher doses (0.5–1.5 g/100 g), lecithin considerably reduced surimi gel deformation (p < 0.05), and the gel containing lecithin at 1.5 g/100 g showed significantly decreased deformation. Surimi with 0.1 g/100 g lecithin had the lowest expressible drip (p < 0.05). In general, lecithin at concentrations ranging from 0.1 to 1 g/100 g reduced expressible drip (p < 0.05), but not at 1.5 g/100 g, which was equivalent to the control (p > 0.05). Adding lecithin to mackerel surimi improved its whiteness slightly, regardless of concentration. Lecithin impacted the microstructures of surimi gel in a concentration-dependent manner. Lecithin at a concentration of 0.1 g/100 g produced a densely packed network with small, jointed clusters and minimal holes within the gel. Joined clusters in the gel were reduced by 0.5–1.5 g/100 g lecithin, and continuous aggregates predominated. Surprisingly, at higher doses of lecithin, notably 1.5 g/100 g, porous structures with continuous voids were perceived. Surimi gels treated with various lecithin doses had lower thiobarbituric acid reactive substances (TBARS) levels than the control (p < 0.05). Overall, lecithin at a low concentration of 0.1 g/100 g was most effective at improving the texture, increasing water-holding capacity, lightening the color, and delaying lipid oxidation of single-washed mackerel surimi.
Modeling and Optimization of Herb-Fortified Fresh Kombucha Cheese: An Artificial Neural Network Approach for Enhancing Quality Characteristics
Authors: Lončar Biljana , Pezo Lato , Iličić Mirela , Kanurić Katarina , Vukić Dajana , Degenek Jovana , Vukić Vladimir
Published: February 2024

In this study, an Artificial Neural Network (ANN) model is used to solve the complex task of producing fresh cheese with the desired quality parameters. The study focuses on kombucha fresh cheese samples fortified with ground wild thyme, supercritical fluid extract of wild thyme, ground sage and supercritical fluid extract of sage and optimizes the parameters of chemical composition, antioxidant potential and microbiological profile. The ANN models demonstrate robust generalization capabilities and accurately predict the observed results based on the input parameters. The optimal neural network model (MLP 6-10-16) with 10 neurons provides high r2 values (0.993 for training, 0.992 for testing, and 0.992 for validation cycles). The ANN model identified the optimal sample, a supercritical fluid extract of sage, on the 20th day of storage, showcasing specific favorable process parameters. These parameters encompass dry matter, fat, ash, proteins, water activity, pH, antioxidant potential (TP, DPPH, ABTS, FRAP), and microbiological profile. These findings offer valuable insights into producing fresh cheese efficiently with the desired quality attributes. Moreover, they highlight the effectiveness of the ANN model in optimizing diverse parameters for enhanced product development in the dairy industry.
Production, Composition and Nutritional Properties of Organic Milk: A Critical Review
Authors: Linehan Kevin , Patangia Dhrati , Ross Reynolds , Stanton Catherine
Published: February 2024

Milk is one of the most valuable products in the food industry with most milk production throughout the world being carried out using conventional management, which includes intensive and traditional systems. The intensive use of fertilizers, antibiotics, pesticides and concerns regarding animal health and the environment have given increasing importance to organic dairy and dairy products in the last two decades. This review aims to compare the production, nutritional, and compositional properties of milk produced by conventional and organic dairy management systems. We also shed light on the health benefits of milk and the worldwide scenario of the organic dairy production system. Most reports suggest milk has beneficial health effects with very few, if any, adverse effects reported. Organic milk is reported to confer additional benefits due to its lower omega-6–omega-3 ratio, which is due to the difference in feeding practices, with organic cows predominantly pasture fed. Despite the testified animal, host, and environmental benefits, organic milk production is difficult in several regions due to the cost-intensive process and geographical conditions. Finally, we offer perspectives for a better future and highlight knowledge gaps in the organic dairy management system.
Multi-Spectral Food Classification and Caloric Estimation Using Predicted Images
Authors: Lee Ki-Seung
Published: February 2024

In nutrition science, methods that accomplish continuous recognition of ingested foods with minimal user intervention have great utility. Our recent study showed that using images taken at a variety of wavelengths, including ultraviolet (UV) and near-infrared (NIR) bands, improves the accuracy of food classification and caloric estimation. With this approach, however, analysis time increases as the number of wavelengths increases, and there are practical implementation issues associated with a large number of light sources. To alleviate these problems, we proposed a method that used only standard red-green-blue (RGB) images to achieve performance that approximates the use of multi-wavelength images. This method used RGB images to predict the images at each wavelength (including UV and NIR bands), instead of using the images actually acquired with a camera. Deep neural networks (DNN) were used to predict the images at each wavelength from the RGB images. To validate the effectiveness of the proposed method, feasibility tests were carried out on 101 foods. The experimental results showed maximum recognition rates of 99.45 and 98.24% using the actual and predicted images, respectively. Those rates were significantly higher than using only the RGB images, which returned a recognition rate of only 86.3%. For caloric estimation, the minimum values for mean absolute percentage error (MAPE) were 11.67 and 12.13 when using the actual and predicted images, respectively. These results confirmed that the use of RGB images alone achieves performance that is similar to multi-wavelength imaging techniques.