bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Crystal Anisotropy on the Characteristics of Solitary Waves in the Nonlinear Supratransmission Effect: Molecular Dynamic Modeling
Authors: Zakharov Pavel V. , Korznikova Elena A. , Izosimov Artem A. , Kochkin Andrey S.
Published: October 2023

This study examines the mechanism of nonlinear supratransmission (NST), which involves the transfer of disturbance to discrete media at frequencies not supported by the structure. We considered a model crystal with A3B stoichiometry. The investigation was carried out using atomistic modeling through molecular dynamics. The interatomic interaction was determined by a potential obtained through the embedded atom method, which approximates the properties of the Pt3Al crystal. The effect of NST is an important property of many discrete structures. Its existence requires the discreteness and nonlinearity of the medium, as well as the presence of a forbidden zone in its spectrum. This work focuses on the differences in the NST effect due to the anisotropy of crystallographic directions. Three planes along which the disturbance caused by NST propagated were considered: (100), (110), and (111). It was found that the intensity of the disturbance along the (100) plane is an order of magnitude lower than for more densely packed directions. Differences in the shape of solitary waves depending on the propagation direction were shown. Moreover, all waves can be described by a single equation, being a solution of the discrete variational equations of macroscopic and microscopic displacements, with different parameters, emphasizing the unified nature of the waves and the contribution of crystal anisotropy to their properties. Studying the NST phenomenon is essential due to numerous applications of the latter, such as implications in information transmission and signal processing. Understanding how disturbances propagate in discrete media could lead to advancements in communication technologies, data storage, and signal amplification where the earlier mentioned ability to describe it with analytical equations is of particular importance.
Exploring the Potential of Distributed Computing Continuum Systems
Authors: Donta Praveen Kumar , Murturi Ilir , Casamayor Pujol Victor , Sedlak Boris , Dustdar Schahram
Published: October 2023

Computing paradigms have evolved significantly in recent decades, moving from large room-sized resources (processors and memory) to incredibly small computing nodes. Recently, the power of computing has attracted almost all current application fields. Currently, distributed computing continuum systems (DCCSs) are unleashing the era of a computing paradigm that unifies various computing resources, including cloud, fog/edge computing, the Internet of Things (IoT), and mobile devices into a seamless and integrated continuum. Its seamless infrastructure efficiently manages diverse processing loads and ensures a consistent user experience. Furthermore, it provides a holistic solution to meet modern computing needs. In this context, this paper presents a deeper understanding of DCCSs’ potential in today’s computing environment. First, we discuss the evolution of computing paradigms up to DCCS. The general architectures, components, and various computing devices are discussed, and the benefits and limitations of each computing paradigm are analyzed. After that, our discussion continues into various computing devices that constitute part of DCCS to achieve computational goals in current and futuristic applications. In addition, we delve into the key features and benefits of DCCS from the perspective of current computing needs. Furthermore, we provide a comprehensive overview of emerging applications (with a case study analysis) that desperately need DCCS architectures to perform their tasks. Finally, we describe the open challenges and possible developments that need to be made to DCCS to unleash its widespread potential for the majority of applications.
Towards Data Storage, Scalability, and Availability in Blockchain Systems: A Bibliometric Analysis
Authors: Kandpal Meenakshi , Goswami Veena , Priyadarshini Rojalina , Barik Rabindra Kumar
Published: October 2023

In recent years, blockchain research has drawn attention from all across the world. It is a decentralized competence that is spread out and uncertain. Several nations and scholars have already successfully applied blockchain in numerous arenas. Blockchain is essential in delicate situations because it secures data and keeps it from being altered or forged. In addition, the market’s increased demand for data is driving demand for data scaling across all industries. Researchers from many nations have used blockchain in various sectors over time, thus bringing extreme focus to this newly escalating blockchain domain. Every research project begins with in-depth knowledge about the working domain, and new interest information about blockchain is quite scattered. This study analyzes academic literature on blockchain technology, emphasizing three key aspects: blockchain storage, scalability, and availability. These are critical areas within the broader field of blockchain technology. This study employs CiteSpace and VOSviewer to understand the current state of research in these areas comprehensively. These are bibliometric analysis tools commonly used in academic research to examine patterns and relationships within scientific literature. Thus, to visualize a way to store data with scalability and availability while keeping the security of the blockchain in sync, the required research has been performed on the storage, scalability, and availability of data in the blockchain environment. The ultimate goal is to contribute to developing secure and efficient data storage solutions within blockchain technology.
Analytical Validation of an Immunohistochemical 7-Biomarker Prognostic Assay (immunoprint®) for Early-Stage Cutaneous Melanoma in Archival Tissue of Patients with AJCC v8 T2–T3 Disease
Authors: Ziemer Mirjana , Weidenthaler-Barth Beate , Gussek Philipp , Pfeiffer Maja , Kleemann Johannes , Bankov Katrin , Wild Peter J. , Seibold Silke , Sureshkumar Priyavathi , Nickel Patricia , Strobel Anton , Werner Markus , Grabbe Stephan
Published: October 2023

Selected patients with early-stage melanoma have a “hidden high risk” of poor oncologic outcomes. They might benefit from clinical trials, and ultimately, if warranted by trial results, judicious everyday use of adjuvant therapy. A promising tool to identify these individuals is the immunoprint® assay. This immunohistochemical 7-biomarker prognostic test was clinically validated in three independent cohorts (N = 762) to classify early-stage patients as high-risk or low-risk regarding melanoma recurrence and mortality. Using College of American Pathologists (CAP) recommendations, we analytically validated this assay in primary melanoma specimens (N = 20 patients). We assessed assay precision by determining consistency of risk classification under repeated identical conditions (repeatability) or across varying conditions (reproducibility), involving separate assay runs, operators (laboratory scientists), and/or observers (e.g., dermatopathologists). Reference classification was followed by five analytical validation phases: intra-run/intra-operator, intra-observer, inter-run, inter-operator, and inter-observer. Concordance of classifications in each phase was assessed via Fleiss’ kappa (primary endpoint) and percent agreement (secondary endpoint). Seven-marker signature classification demonstrated high consistency across validation categories (Fleiss’ kappa 0.864–1.000; overall percent agreement 95–100%), in 9/10 cases, exceeding, and in 1/10 cases, closely approaching, CAP’s recommended 0.9 level. The 7-marker assay has now been verified to provide excellent repeatability, reproducibility, and precision, besides having been clinically validated.
From Nonalcoholic Steatohepatits to Steatotic Liver Disease: A Long Way
Authors: Cotrim Helma
Published: October 2023

In 1980, Ludwig et al [...]
Deep Learning to Predict the Cell Proliferation and Prognosis of Non-Small Cell Lung Cancer Based on FDG-PET/CT Images
Authors: Hu Dehua , Li Xiang , Lin Chao , Wu Yonggang , Jiang Hao
Published: October 2023

(1) Background: Cell proliferation (Ki-67) has important clinical value in the treatment and prognosis of non-small cell lung cancer (NSCLC). However, current detection methods for Ki-67 are invasive and can lead to incorrect results. This study aimed to explore a deep learning classification model for the prediction of Ki-67 and the prognosis of NSCLC based on FDG-PET/CT images. (2) Methods: The FDG-PET/CT scan results of 159 patients with NSCLC confirmed via pathology were analyzed retrospectively, and the prediction models for the Ki-67 expression level based on PET images, CT images and PET/CT combined images were constructed using Densenet201. Based on a Ki-67 high expression score (HES) obtained from the prediction model, the survival rate of patients with NSCLC was analyzed using Kaplan–Meier and univariate Cox regression. (3) Results: The statistical analysis showed that Ki-67 expression was significantly correlated with clinical features of NSCLC, including age, gender, differentiation state and histopathological type. After a comparison of the three models (i.e., the PET model, the CT model, and the FDG-PET/CT combined model), the combined model was found to have the greatest advantage in Ki-67 prediction in terms of AUC (0.891), accuracy (0.822), precision (0.776) and specificity (0.902). Meanwhile, our results indicated that HES was a risk factor for prognosis and could be used for the survival prediction of NSCLC patients. (4) Conclusions: The deep-learning-based FDG-PET/CT radiomics classifier provided a novel non-invasive strategy with which to evaluate the malignancy and prognosis of NSCLC.
Unexplained and Unexpected Pediatric Deaths: Forensic Review and New Perspectives
Authors: Aquila Isabella , Sacco Matteo Antonio , Gorniak Jan , Rouse Melanie , Gualtieri Saverio , Cordasco Fabrizio , Tarallo Alessandro Pasquale , Raffaele Roberto , Ricci Pietrantonio
Published: October 2023

Unexplained and unexpected pediatric deaths are a major challenge in global healthcare. The role of the forensic pathologist is crucial in determining the cause and manner of death in these cases, although to date, there are many limitations in post-mortem diagnosis. The role of the autopsy and related forensic investigations become a fundamental tool to investigate and give an explanation for an unacceptable event, considering the young age of the victims. From this point of view, even today, it is necessary that this phenomenon is correctly recorded through standardized systems and universally accepted methods. Furthermore, it is essential that scientific research on this topic is increased through the implementation of universally accepted operating protocols recognizing real risk factors in order to prevent such events. The purpose of the study is to offer a review of the state of the art about unexplained pediatric death and, above all, to propose an international reporting platform, extending proper investigations not only to judicial cases but also to all the other cases of unexpected pediatric death.
Efficient YOLOv7-Drone: An Enhanced Object Detection Approach for Drone Aerial Imagery
Authors: Fu Xiaofeng , Wei Guoting , Yuan Xia , Liang Yongshun , Bo Yuming
Published: October 2023

In recent years, the rise of low-cost mini rotary-wing drone technology across diverse sectors has emphasized the crucial role of object detection within drone aerial imagery. Low-cost mini rotary-wing drones come with intrinsic limitations, especially in computational power. Drones come with intrinsic limitations, especially in resource availability. This context underscores an urgent need for solutions that synergize low latency, high precision, and computational efficiency. Previous methodologies have primarily depended on high-resolution images, leading to considerable computational burdens. To enhance the efficiency and accuracy of object detection in drone aerial images, and building on the YOLOv7, we propose the Efficient YOLOv7-Drone. Recognizing the common presence of small objects in aerial imagery, we eliminated the less efficient P5 detection head and incorporated the P2 detection head for increased precision in small object detection. To ensure efficient feature relay from the Backbone to the Neck, channels within the CBS module were optimized. To focus the model more on the foreground and reduce redundant computations, the TGM-CESC module was introduced, achieving the generation of pixel-level constrained sparse convolution masks. Furthermore, to mitigate potential data losses from sparse convolution, we embedded the head context-enhanced method (HCEM). Comprehensive evaluation using the VisDrone and UAVDT datasets demonstrated our model’s efficacy and practical applicability. The Efficient Yolov7-Drone achieved state-of-the-art scores while ensuring real-time detection performance.
Transforming Great Salt Lake from Afterthought to Asset
Authors: Sowby Robert B.
Published: October 2023

In a 36-year period that coincides with my lifetime, Great Salt Lake, one of the world’s largest terminal lakes and a critical ecosystem in the Western Hemisphere, went from its largest to its smallest recorded size. In this opinion piece, I argue that the fundamental problem is that we Utahns and other stakeholders have treated Great Salt Lake as an afterthought instead of an asset. I describe the conditions that led to this point, some transformations now taking place, and the new hope that the lake will recover.
Higher Education in Public Health as a Tool to Reduce Disparities: Findings from an Exploratory Study among the Bedouin Community in Israel
Authors: Bashkin Osnat , Suisa Avia , Levi Sharon
Published: October 2023

The Bedouin community is a minority disadvantaged population in Israel that suffers from a variety of health and socioeconomic disparities and limited access to higher education. The current study aimed to examine perceptions, successes, and challenges experienced by Bedouin students during their studies and to assess an internship program developed on the principles of a community-based participatory research approach to public health. In-depth interviews were conducted with 34 Bedouin students studying in the public health academic track between January and April 2023. Grounded Theory was used to analyze the data. Three main themes emerged from the analysis: (1) facilitators for the decision to pursue higher education in public health, (2) challenges and coping strategies, and (3) experiences of success. The internship program included eleven Bedouin students who conducted six community intervention projects covering a range of topics with different target Bedouin populations. Higher education is crucial for empowering minorities, producing leadership, and reducing socioeconomic and health gaps. The field internship enabled the necessary alignment between academia and public health practice. It is important to further reflect on the integration of minority groups in public health studies and its role in decreasing health inequity.
A Double-Edge-Triggered Digital LDO with Built-In Adaptive VCO Clock for Fast Transient Response and Low Power Consumption
Authors: Xin Xin , Wei Dongdong , Tong Xingyuan
Published: October 2023

A double-edge-triggered digital low dropout regulator (DLDO) is proposed with a built-in adaptive voltage-controlled oscillator (VCO) clock (AVC) for a system-on-chip (SoC) application. To achieve a fast transient response, the main comparator generates the comparison result at the rising edge of the AVC, and this result is sampled by the coarse or fine bidirectional shifter register at the falling edge of the AVC. Furthermore, the clock frequency can be boosted from 8 MHz at the steady state to 50 MHz by the AVC when the output current suffers from a sudden change, and it can also be adjusted in real-time according to the output voltage, which avoids the oscillation phenomenon and decreases the power consumption during the recovery process. To further lower the power consumption, the self-clock comparator replaces the conventional static comparator in the transient detector. The post-simulation results show that the proposed DLDO consumes a quiescent current of 95.13 μA in the steady state, and drives a maximum load current of 25 mA at the supply power of 0.6 V with an active area of 0.053-mm2 in a 180 nm CMOS process. When the load current jumps from 0.5 mA to 25 mA at the edge of 100 ps, the undershoot voltage and overshoot voltage are only 335 mV with the recovery time of 2.7 μs and 47.6 mV with the recovery time of 2.1 μs at the total on-chip capacitor of 50 pF, respectively, resulting in two competitive figures of merits (FoMs) than the previous works.
Battery-Assisted Battery Charger with Maximum Power Point Tracking for Thermoelectric Generator: Concept and Experimental Proof
Authors: Tanabe Shunsuke , Tanzawa Toru
Published: October 2023

This paper proposes a concept of battery-assisted battery charger with maximum power point tracking for DC energy transducer such as thermoelectric generator and photo voltaic generator, and shows experimental results to prove the concept. The DC energy transducer is connected in series with a battery to increase the voltage. The plus terminal for the DC energy transducer is connected with the input terminal of a DC-DC buck converter, whereas the battery is connected with the output terminal of the converter. Thus, the current is boosted from the input to the output. When the net current to the battery is positive, the system works as a battery charger. To extract the as much power from the DC energy transducer as possible for high charging efficiency, maximum power point tracking is introduced. The converter was designed in 180 nm 3V CMOS with a silicon area of 1.05 mm2. The concept was experimentally proven by varying the reference voltages to control the input voltage. An all-solid-state battery was charged up from 2.2 V to 2.3 V in two hours by the converter with a flexible thermoelectric generator which had an open-circuit voltage of 0.6 V.
Flow-Based Joint Programming of Time Sensitive Task and Network
Authors: Chi Yingying , Zhang Huayu , Liu Yong , Chen Ning , Zheng Zhe , Zhu Hailong , Zhang Peiying , Zhan Haotian
Published: October 2023

Owning to the application of artificial intelligence and big data analysis in industry, automobiles, aerospace, and other fields, the high-bandwidth candidate, time-sensitive networking (TSN), is introduced into the data communication network. Apart from keeping the safety-critical and real-time requirements, it faces challenges to satisfy large traffic transmission, such as sampled video for computer vision. In this paper, we consider task scheduling and time-sensitive network together and formalize them into a first-order-constraints satisfy module theory (SMT) problem. Based on the result of the solver, we build flow-level scheduling based on IEEE 802.1 Qbv. By splitting the flow properly, it can reduce the constraint inequality as the traffic grows more than the traditional frame-based programming model and achieve near 100% utilization. It can be a general model for the deterministic task and network scheduling design.
Global Individual Interaction Network Based on Consistency for Group Activity Recognition
Authors: Huang Cheng , Zhang Dong , Li Bing , Xian Yun , Lee Dah-Jye
Published: October 2023

Modeling the interactions among individuals in a group is essential for group activity recognition (GAR). Various graph neural networks (GNNs) are regarded as popular modeling methods for GAR, as they can characterize the interaction among individuals at a low computational cost. The performance of the current GNN-based modeling methods is affected by two factors. Firstly, their local receptive field in the mapping layer limits their ability to characterize the global interactions among individuals in spatial–temporal dimensions. Secondly, GNN-based GAR methods do not have an efficient mechanism to use global activity consistency and individual action consistency. In this paper, we argue that the global interactions among individuals, as well as the constraints of global activity and individual action consistencies, are critical to group activity recognition. We propose new convolutional operations to capture the interactions among individuals from a global perspective. We use contrastive learning to maximize the global activity consistency and individual action consistency for more efficient recognition. Comprehensive experiments show that our method achieved better GAR performance than the state-of-the-art methods on two popular GAR benchmark datasets.
Robust Blind Image Watermarking Using Coefficient Differences of Medium Frequency between Inter-Blocks
Authors: Zhu Bingbing , Fan Xuefeng , Zhang Tianshuo , Zhou Xiaoyi
Published: October 2023

The existing discrete cosine transform (DCT) differential quantization robust watermarking has poor robustness against JPEG compression, cropping, and combined attacks. To improve such issues, a pair of adjacent block coefficients are selected to reduce the offset and improve the robustness of the watermarking. Firstly, at adjacent positions of neighboring blocks, the differences of medium frequency coefficients are calculated, and then the differences are used to divide regions. Experimental results show that this method is more robust to various attacks than the existing DCT differential quantization robust watermarking. The accuracy of watermark extraction under a JPEG compression attack increased by 2%, while the error rates of watermark extraction under a cropping attack and a combination attack decreased by 4.4% and 9%.
Graph U-Shaped Network with Mapping-Aware Local Enhancement for Single-Frame 3D Human Pose Estimation
Authors: Yu Bing , Huang Yan , Cheng Guang , Huang Dongjin , Ding Youdong
Published: October 2023

The development of 2D-to-3D approaches for 3D monocular single-frame human pose estimation faces challenges related to noisy input and failure to capture long-range joint correlations, leading to unreasonable predictions. To this end, we propose a straightforward, but effective U-shaped network called the mapping-aware U-shaped graph convolutional network (M-UGCN) for single-frame applications. This network applies skeletal pooling/unpooling operations to expand the limited convolutional receptive field. For noisy inputs, as local nodes have direct access to the subtle discrepancies between poses, we define an additional mapping-aware local-enhancement mechanism to focus on local node interactions across multiple scales. We evaluated our proposed method on the benchmark datasets Human3.6M and MPI-INF-3DHP, and the experimental results demonstrated the robustness of the M-UGCN against noisy inputs. Notably, the average error in the proposed method was found to be 4.1% lower when compared to state-of-the-art methods adopting similar multi-scale learning approaches.
Bellman–Genetic Hybrid Algorithm Optimization in Rural Area Microgrids
Authors: Zahraoui Fatima Zahra , Et-taoussi Mehdi , Chakir Houssam Eddine , Ouadi Hamid , Elbhiri Brahim
Published: October 2023

Incorporating renewable Distributed Energy Resources (DER) into the main grid is crucial for achieving a sustainable transition from fossil fuels. However, this generation system is complicated by the fluctuating behavior of renewable resources and the variable load demand, making it less reliable without a suitable energy storage system (ESS). This study proposes an Optimal Power Flow Management (OPFM) strategy for a grid-connected hybrid Micro Grid (MG) comprising a wind turbine (WT), a photovoltaic (PV) field, a storage battery, and a Micro Gas turbine (MGT). This proposed strategy includes (i) minimizing the MG’s daily energy cost, (ii) decreasing CO2 emissions by considering the variable load, weather forecast, and main grid fees to optimize the battery charging/discharging strategy, and (iii) optimizing the decision-making process for power purchase/sell from/to the main grid. The suggested OPFM approach is implemented using a Genetic Algorithm and compared with the Bellman Algorithm and a restricted management system via several simulations under the Matlab environment. Furthermore, the hybridization of the Bellman Algorithm and the Genetic Algorithm is proposed to enhance the OPFMC strategy’s efficiency by leveraging both algorithms’ strengths. The simulation results demonstrate the effectiveness of the proposed strategy in lowering energy costs and CO2 emissions and enhancing reliability. Additionally, the comparison of the hybridized GA algorithm reveals a cost 16% higher than the Bellman Algorithm; however, the use of the hybridized GA algorithm leads to a reduction in GHG emissions by 31.4%. These findings underscore the trade-off between cost and environmental impact in the context of algorithmic optimization for microgrid energy management.
Application of Machine Learning to Classify the Technical Condition of Marine Engine Injectors Based on Experimental Vibration Displacement Parameters
Authors: Monieta Jan , Kasyk Lech
Published: October 2023

The article presents the possibility of using machine learning (ML) in artificial intelligence to classify the technical state of marine engine injectors. The technical condition of the internal combustion engine and injection apparatus significantly determines the composition of the outlet gases. For this purpose, an analytical package using modern technology assigns experimental test scores to appropriate classes. The graded changes in the value of diagnostic parameters were measured on the injection subsystem bench outside the engine. The influence of the operating conditions of the fuel injection subsystem and injector condition features on the injector needle vibration displacement waveforms was subjected to a neural network (NN) ML process and then tested. Diagnostic parameters analyzed in the amplitude, frequency, and time–frequency domains were subjected after a learning process to recognize simulated various regulatory and technical states of suitability and unfitness with single and complex damage of new and worn injector nozzles. Classification results were satisfactory in testing single damage and multiple changes in technical state characteristics for unfitness states with random wear injectors. Testing quality reached above 90% using selected NNs of Statistica 13.3 and MATLAB R2022a environments.
A Study on the Permeability and Damage Characteristics of Limestone under Stress–Seepage Coupling Conditions
Authors: Wang Lu , Liu Jianfeng , Liao Yilin , Yang Shuyu , He An , Xu Huining
Published: October 2023

With the increase in energy demand, energy engineering has gradually developed to go deeper, accompanied by a complex geological environment, such as the coupling of stress and seepage. Limestone is widely found in underground rock engineering, and its stress–seepage coupling characteristics have a great influence on the safety and stability of related engineering projects. In order to study the permeability characteristics and damage evolution of limestone during the deformation and failure process under stress–seepage coupling conditions, permeability and acoustic emission tests on limestone were performed in this paper. The results showed that: the stress–strain curve demonstrated periodicity, as did the permeability change. The change in permeability in different deformation stages of axial strain and lateral strain was similar, but it was more appropriate to reflect the permeability evolution in terms of lateral strain. The permeability of the limestone slightly decreased in the volumetric compression stage, and tended to saturate after a sudden increase in the expansion stage. The presence of the confining pressure reduced the permeability of the rock. In the process of limestone deformation and failure, the level of acoustic emission activity can reflect the degree of fracture development. The permeability characteristics and acoustic emission characteristics had a good corresponding relationship. The greater the confining pressure, the higher the acoustic emission activity. The deformation and damage process of limestone experienced three stages: damage stable growth, damage acceleration development, and damage saturation.
Bioenergy Generation from Different Types of Waste by Anaerobic Digestion
Authors: Pilarska Agnieszka A. , Pilarski Krzysztof
Published: October 2023

One of the problems of the modern world is the generation of increasing amounts of waste by agriculture and various industries [...]
Numerical Simulation of the Effects of Blade–Arm Connection Gap on Vertical–Axis Wind Turbine Performance
Authors: Hara Yutaka , Miyashita Ayato , Yoshida Shigeo
Published: October 2023

Many vertical-axis wind turbines (VAWTs) require arms, which generally provide aerodynamic resistance, to connect the main blades to the rotating shaft. Three–dimensional numerical simulations were conducted to clarify the effects of a gap placed at the blade–arm connection portion on VAWT performance. A VAWT with two straight blades (diameter: 0.75 m, height: 0.5 m) was used as the calculation model. Two horizontal arms were assumed to be connected to the blade of the model with or without a gap. A cylindrical rod with a diameter of 1 or 5 mm was installed in the gap, and its length varied from 10 to 30 mm. The arm cross section has the same airfoil shape (NACA 0018) as the main blade; however, the chord length is half (0.04 m) that of the blade. The simulation shows that the power of the VAWT with gaps is higher than that of the gapless VAWT. The longer gap length tends to decrease the power, and increasing the diameter of the connecting rod amplifies this decreasing tendency. Providing a short gap at the blade–arm connection and decreasing the cross–sectional area of the connecting member is effective in increasing VAWT power.
Experimental Studies of the Pressure Drop in the Flow of a Microencapsulated Phase-Change Material Slurry in the Range of the Critical Reynolds Number
Authors: Dutkowski Krzysztof , Kruzel Marcin , Kochanowska Martyna
Published: October 2023

Phase-change materials (PCMs) are attractive materials for storing thermal energy thanks to the energy supplied/returned during the change in matter state. The encapsulation of PCMs prevent them from connecting into large clusters, prevents the chemical interaction of the PCM with the walls of the tank and the exchanger material, and allows the phase change to be initiated in parallel in each capsule. The microencapsulation of PCMs (mPCMs) and the nanoencapsulation of PCMs (nPCMs) entail that these particles added to the base liquid can act as a slurry used in heat exchange systems. PCM micro-/nanocapsules or mPCM (nPCM) slurry are subjected to numerous physical, mechanical, and rheological tests. However, flow tests of mPCM (nPCM) slurries are significantly limited. This paper describes the results of detailed adiabatic flow tests of mPCM slurry in a tube with an internal diameter of d = 4 mm and a length of L = 400 mm. The tests were conducted during laminar, transient, and turbulent flows (Re < 11,250) of mPCM aqueous slurries with concentrations of 4.30%, 6.45%, 8.60%, 10.75%, 12.90%, 15.05%, and 17.20%. The mPCM slurry had a temperature of T = 7 °C (the microcapsule PCM was a solid), T = 24 °C (the microcapsule PCM was undergoing a phase change), and T = 44 °C (the microcapsule PCM was a liquid). This work aims to fill the research gap on the effect of the mPCM slurry concentration on the critical Reynolds number. It was found that the concentration of the mPCM has a significant effect on the critical Reynolds number, and the higher the concentration of mPCM in the base liquid, the more difficult it was to keep the laminar flow. Additionally, it was observed that, as yet unknown in the literature, the temperature of the slurry (and perhaps the physical state of the PCM in the microcapsule) may affect the critical Reynolds number.
How Does the Urban Forest Environment Affect the Psychological Restoration of Residents? A Natural Experiment in Environmental Perception from Beijing
Authors: Li Sixian , Chen Tianyu , Chen Feiying , Mi Feng
Published: October 2023

The urban forest is not only an essential part of maintaining the security of the urban ecosystem but also an important restorative environmental site that benefits the physical and mental health of residents. In this research, a natural experiment was designed in Beijing in order to evaluate the urban forest environment in terms of visual, auditory, and olfactory senses, and the effects of psychosocial restoration in urban forest environments were tested. On this basis, a Partial Least Squares-Structural Equation Model was structured to verify the “environment-perception-restoration mechanism”. The findings showed that the urban forest environment was the main cause of the differences in residents’ psychological restoration and the natural environment perception, while the natural environment perception directly impacted residents’ psychological restoration and mediated the relationship between the urban forest environment and psychological restoration. Therefore, Beijing needs to further optimize the landscape, sound, smell, and other environmental elements of urban forests and create a peaceful and spacious urban forest open space, considering the environmental perception preferences of urban residents, to improve the psychological restoration effect of urban forests.
Enhancing Acetic Acid Production in In Vitro Rumen Cultures by Addition of a Homoacetogenic Consortia from a Kangaroo: Unravelling the Impact of Inhibition of Methanogens and Effect of Almond Biochar on Rumen Fermentations
Authors: Stefanini Lopes Renan , Ahring Birgitte
Published: October 2023

A homoacetogenic consortium was cultivated from feces from a nursing joey red kangaroo and inoculated into an in vitro ruminal culture. The in vitro ruminal culture was treated with methanogenic inhibitor 2-bromoethanesulfonate (BES), followed by two different homoacetogenic inoculation strategies. Initial observations showed inhibitory effects of BES, with stabilization of the acetic acid concentrations without any increase in concentration, even with the homoacetogenic inoculation. When homoacetogenic bacterial culture was added after the BES addition had ceased, acetic acid production was increased 2.5-fold. Next-generation sequencing showed an increased population of Bacteroidetes after inoculation with the homoacetogenic consortia, along with a slight decrease in diversity. An Almond Shell biochar (AS) addition resulted in a 28% increase in acetic acid concentration if tested directly on the homoacetogenic kangaroo consortia. However, when applied to the rumen culture, it did not enhance acetate production but further promoted other reductive pathways such as methanogenesis and propiogenesis, resulting in increased concentrations of methane and propionic acid, respectively. These findings demonstrate that bioaugmentation with homoacetogenic bacteria can improve acetic acid production of an in vitro rumen culture when methanogenesis has been eliminated. Such advancements can potentially contribute to the optimization of rumen fermentation processes and may have practical implications for improved livestock feed efficiency and methane mitigation strategies.
Changes in the Quality and Nontargeted Metabolites of Salt-Fermented Shrimp (Saeu-jeot) Based on Fermentation Time
Authors: Park Sunhyun , Kim Keono , Jang Mi , Lee Heeyoung , Sung Jeehye , Kim Jong-Chan
Published: October 2023

Saeu-jeot is a widely consumed variety of jeotgal, a South Korean salt-fermented food. However, there is a lack of existing studies conducting nontargeted metabolomic analyses of saeu-jeot during fermentation. To evaluate the changes in saeu-jeot during fermentation, saeu-jeot samples were fermented for 360 days under controlled conditions. Samples collected at different time points were subjected to physicochemical (including nontargeted metabolomic analysis) and microbial analyses. As fermentation progressed, the pH decreased and acidity increased, whereas total nitrogen, amino-nitrogen, and specific amino acid concentrations increased. Nontargeted metabolite analysis supports these results. Metabolite profiling classified changes in saeu-jeot during fermentation into those occurring in the early (15–45 days), middle (60–180 days), and late (270–360 days) stages. Pathogenic bacteria were not detected, and biogenic amine levels were not elevated, suggesting that saeu-jeot is safe to consume. Overall, pH, amino-nitrogen, and pathogenic bacteria, according to the fermentation stage of saeu-jeot, can be useful parameters for evaluating the quality of salted shrimp.
MSEN: A Multi-Scale Evolutionary Network for Modeling the Evolution of Temporal Knowledge Graphs
Authors: Yu Yong , Chen Shudong , Du Rong , Tong Da , Xu Hao , Chen Shuai
Published: October 2023

Temporal knowledge graphs play an increasingly prominent role in scenarios such as social networks, finance, and smart cities. As such, research on temporal knowledge graphs continues to deepen. In particular, research on temporal knowledge graph reasoning holds great significance, as it can provide abundant knowledge for downstream tasks such as question answering and recommendation systems. Current reasoning research focuses primarily on interpolation and extrapolation. Extrapolation research aims to predict the likelihood of events occurring in future timestamps. Historical events are crucial for predicting future events. However, existing models struggle to fully capture the evolutionary characteristics of historical knowledge graphs. This paper proposes a multi-scale evolutionary network (MSEN) model that leverages Hierarchical Transfer aware Graph Neural Network (HT-GNN) in a local memory encoder to aggregate rich structural semantics from each timestamp’s knowledge graph. It also utilizes Time Related Graph Neural Network (TR-GNN) in a global memory encoder to model temporal-semantic dependencies of entities across the global knowledge graph, mining global evolutionary patterns. The model integrates information from both encoders to generate entity embeddings for predicting future events. The proposed MSEN model demonstrates strong performance compared to several baselines on typical benchmark datasets. Results show MSEN achieves the highest prediction accuracy.
A Cold Climate Wooden Home and Conflagration Danger Index: Justification and Practicability for Norwegian Conditions
Authors: Strand Ruben Dobler , Log Torgrim
Published: October 2023

The vast majority of fire-related deaths occur in residential buildings. Until recently, the fire risk for these buildings was only considered through static risk assessments or period-based assessments applying to certain periods of the year, e.g., Christmas holidays. However, for homes with indoor wooden panelling, especially in the ceiling, a dynamic fire danger indicator can be predicted for cold climate regions. Recognising the effect of fuel moisture content (FMC) of indoor wooden panelling on the enclosure fire development allows for the prediction of a wooden home fire danger indicator. In the present study, dry wood fire dynamics are analysed and experimental observations are reported to support in-home wooden panel FMC as a suitable wooden home fire danger indicator. Then, from previous work, the main equation for modelling in-home FMC is considered and a generic enclosure for FMC modelling is justified based on literature data and supported through a sensitivity study for Norwegian wooden homes. Further, ten years of weather data for three selected locations in Norway, i.e., a coastal town, an inland fjord town and a mountain town, were analysed using a three-dimensional risk matrix to assess the usability of the fire risk modelling results. Finally, a cold climate wooden home fire danger index was introduced to demonstrate how the risk concept can be communicated in an intuitive way using similar gradings as the existing national forest fire index. Based on the generic enclosure, the findings support FMC as a fire risk indicator for homes with interior wooden panelling (walls and ceiling). Large differences in the number of days with arid in-home conditions were identified for the selected towns. The number of days with combined strong wind and dry wooden homes appears to depend more on the number of days with strong wind than days of in-home drought. Thus, the coastal town was more susceptible to conflagrations than the drier inland towns. This aligns well with the most significant fire disasters in Norway since 1900. In addition, it was demonstrated that the number of high-risk periods is manageable and can be addressed by local fire departments through proactive measures. In turn, the fire risk modelling and associated index respond well to the recent changes in Norwegian regulations, requiring the fire departments to have systems for detecting increased risk levels. Testing the modelling for a severe winter fire in the USA indicates that the presented approach may be of value elsewhere as well.
Appropriateness Evaluation of Releasing Area for Four Marine Organisms in Stock Enhancement: A Fatty Acid Approach
Authors: Wang Zichen , Lv Zehua , Zhang Junbo
Published: October 2023

In light of the ongoing depletion of global fishery resources, there has been a growing trend towards increasing the scope of stock enhancement activities. The objective of these efforts is to replenish the diminishing fishery resources and restore the ecological balance within marine biological communities. Nevertheless, the efficacy of the stock enhancement project has been hindered by the differential growth and environmental adaptability of released species, which can be attributed to the influence of abundant food resources. As a consequence, the project has not yielded the anticipated outcomes. One useful strategy for enhancing the efficacy of stock enhancement is the deliberate allocation of appropriate habitats for diverse released organisms. Fatty acids were extracted by the Folch method and the composition and content of muscle fatty acids were determined by gas chromatography mass spectrometry. This study examines the fatty acid composition of four commercially important species, namely, little yellow croaker (Larimichthys polyactis), red sea bream (Pagrus major), swimming crab (Portunus trituberculatus), and ridgetail white prawn (Exopalaemon carinicauda). The sum of available docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) is employed as an indicator to assess the appropriateness of the marine environment for releasing these species (DE). The red sea bream exhibited the lowest DE value of 13.69% in the northern coastal water of the Bohai Sea, and the little yellow croaker displayed the lowest DE value of 10.91% in the southern coastal water of the Shandong Peninsula. Conversely, the DE values of other seas were comparable, averaging 20.16%. The range of the DE value of the swimming crab across various coastal waters was observed to be between 33.59% and 45.21%. The ridgetail white prawn had a DE value of 21.10% in the coastal water of Yancheng City, Jiangsu Province, as well as the southern coastal water of the Shandong Peninsula, and a DE value of 31.75% in the southern and central coastal waters of Zhejiang Province. The findings of the study indicate that the Bohai Sea and the northern region of the Yellow Sea are the appropriate stock enhancement areas for red sea bream. Similarly, the Yellow Sea and the northern part of the East China Sea are identified as suitable habitats for the little yellow croaker. The swimming crab, on the other hand, is adapted to be released in the Yellow Sea, the Bohai Sea, and the East China Sea. The north of the central part of the East China Sea is an appropriate release area for the ridgetail white prawn.
Molecular Identification and Expression Analysis of an Intelectin Gene in the Yellow Catfish Pelteobagrus fulvidraco (Siluriformes: Bagridae)
Authors: Jiang Senhao , Lei Yuting , Li Yanxuan , Sun Wanyan , Wang Ti , Ma Ruiting , Liu Qiuning , Tang Boping
Published: October 2023

Intelectins (ITLNs) are a family of calcium-dependent lectins with carbohydrate-binding capacity, are distributed across various vertebrates, and play an important role in the innate immune response against pathogen infection. The yellow catfish Pelteobagrus fulvidraco (Siluriformes: Bagridae) is an economically important fish in China. The aim of this study was to quantify the gene expression of ITLN in response to pathogen-associated molecular patterns (PAMPs) stimulation. Here, the ITLN gene of P. fulvidraco was characterized and named PfITLN. The full-length cDNA of PfITLN was 1132 bp, including a 5’-untranslated region (UTR) of 140 bp, a 3’-UTR of 110 bp, and an open reading frame (ORF) of 882 bp encoding a polypeptide of 293 amino acids, which contains a signal peptide and two fibrinogen-related domains (FReDs). PfITLN had a molecular weight of 32.39 kDa with a theoretical pI of 5.03. The deduced PfITLN amino acid sequence had 81%, 64%, and 55% homology with Ictalurus furcatus, Danio rerio, and Homo sapiens, respectively. Moreover, the predicted tertiary protein structure of PfITLN was highly similar to that of other animals, and phylogenetic analysis showed that the PfITLN protein was close to those of other Teleostei. Real-time quantitative reverse transcription-PCR (qRT-PCR) analysis showed PfITLN expression in all examined tissues, with the highest abundance seen in the liver, followed by the head kidney, spleen, trunk kidney, and muscle. After PAMP infection with lipopolysaccharide (LPS) and polyriboinosinic polyribocytidylic acid (poly I:C), the expression levels of PfITLN were significantly upregulated at different time points. These results suggested that PfITLN might be involved in innate immunity.
Phenotypic and Genotypic Characteristics of Non-Hemolytic L. monocytogenes Isolated from Food and Processing Environments
Authors: Szymczak Barbara
Published: October 2023

Increasingly, Listeria monocytogenes (LM) with atypical phenotypic and genotypic characteristics are being isolated from food, causing problems with their classification and testing. From 2495 soil, food, and swab samples from the food industry, 262 LM isolates were found. A total of 30 isolates were isolated, mainly from soil and plant food, and were classified as atypical LM (aLM) because they lacked the ability to move (30/11.4%) and perform hemolysis (25/9.5%). The isolation environment affected aLM incidence, cell size, sugar fermentation capacity, antibiotic sensitivity, and the number of virulence genes. Therefore, despite several characteristics differentiating all aLMs/non-hemolytic isolates from reference LMs, the remaining phenotypic characteristics were specific to each aLM isolate (like a fingerprint). The aLM/non-hemolytic isolates, particularly those from the soil and meat industries, showed more variability in their sugar fermentation capacity and were less sensitive to antibiotics than LMs. As many as 11 (36.7%) aLM isolates had resistance to four different antibiotics or simultaneously to two antibiotics. The aLM isolates possessed 3–7 of the 12 virulence genes: prfA and hly in all aLMs, while iap was not present. Only five (16.7%) isolates were classified into serogroups 1/2c-3c or 4a-4c. The aLM/non-hemolytic isolates differed by many traits from L. immobilis and atypical L. innocua. The reference method of reviving and isolating LM required optimization of aLM. Statistical analyses of clustering, correlation, and PCA showed similarities and differences between LM and aLM/non-hemolytic isolates due to individual phenotypic traits and genes. Correlations were found between biochemical traits, antibiotic resistance, and virulence genes. The increase in the incidence of atypical non-hemolytic LM may pose a risk to humans, as they may not be detected by ISO methods and have greater antibiotic resistance than LM. aLM from LM can be distinguished based on lack of hemolysis, motility, growth at 4 °C, ability to ferment D-arabitol, and lack of six specific genes.