bluuebunny/crossref_metadata_2025 huggingface dataset:
Distribution and Species Richness of Benthic Polychaeta and Sipuncula in the Northwestern Pacific
Authors: Kohlenbach Katharina , Knauber Henry , Brandt Angelika , Saeedi Hanieh
Published: April 2023

Polychaeta and Sipuncula are abundant inhabitants of benthic marine habitats and have been increasingly sampled in the Northwest Pacific (NWP). However, polychaete and sipunculan species richness, composition, and distribution patterns still require further investigation, despite previous studies due to increasing deep-sea data flow. Using occurrence records for Polychaeta and Sipuncula from the Ocean Biodiversity Information System (OBIS) and the Global Biodiversity Information Facility (GBIF), we analyzed sampling effort (the number of distribution records), alpha (the number of species per 700,000 km2 hexagon cells) and gamma (the number of species per 5° latitudinal band) species diversity, and estimated species richness along latitudinal and bathymetric gradients. The species richness estimations were also correlated with multiple environmental and topographic variables, including depth, temperature, dissolved oxygen, chlorophyll, primary production, phytoplankton, current velocity, light, iron, nitrate, phosphate, silicate, and salinity. The dataset included over 30,000 distribution records belonging to polychaete (31,114 records, 98%) and sipunculan (690 records, 2%) species. Half of the distribution records were reported at a species level. The area around the island of Hainan and South Korea showed the highest alpha species richness (the number of species per 700,000 km2 hexagon cell), yet the estimated species richness (ES50) indicated that there might be many unknown, unsampled, or non-digitized species throughout the whole NWP. Correspondingly, most distribution records (sampling effort) and gamma species richness were found between latitudes 20 and 40° and decreased towards higher latitudes. Sipuncula were reported relatively more frequently from the deep sea than Polychaeta (62.8% vs. 12%). Overall, the number of species and records decreased with increasing depth, with a peak at about 5000 m. The alpha species richness had the strongest positive correlations with temperature, chlorophyll, primary production, and phytoplankton concentration. Here, we provide an overview of the species richness and distribution of Polychaeta in comparison with Sipuncula in the NWP, in both shallow and deep environments. This study demonstrates where further sampling efforts are needed to fill our knowledge gaps on annelids’ distribution and diversity along the NWP. This could improve the analyses of the distribution and diversity of annelids to better understand the current environmental drivers of biodiversity, as well as predicting potential future drivers. The outcome of the environmental correlation provides thus valuable knowledge for predicting the future impacts of global warming on potential distribution shifts of annelids into new environments such as the Arctic Sea, possibly resulting in biological invasions.
VisionICE: Air–Ground Integrated Intelligent Cognition Visual Enhancement System Based on a UAV
Authors: Li Qingge , Yang Xiaogang , Lu Ruitao , Fan Jiwei , Wang Siyu , Qin Zhen
Published: April 2023

Post-disaster search and rescue is critical to disaster response and recovery efforts and is often conducted in hazardous and challenging environments. However, the existing post-disaster search and rescue operations have problems such as low efficiency, limited search range, difficulty in identifying the nature of the target, and wrong target location. Therefore, this study develops an air–ground integrated intelligent cognition visual enhancement system based on a UAV (VisionICE). The technique combines a portable AR display device, a camera-equipped helmet, and a quadcopter UAV for efficient patrols over a wide area. First, the system utilizes wireless image sensors on the UAV and helmet to capture images from the air and ground views. Using the YOLOv7 algorithm, the cloud server calculates and analyzes these visual data to accurately identify and detect targets. Lastly, the AR display device obtains real-time intelligent cognitive results. The system allows personnel to simultaneously acquire air and ground dual views and achieve brilliant cognitive results and immersive visual experiences in real time. The findings indicate that the system demonstrates significant recognition accuracy and mobility. In contrast to conventional post-disaster search and rescue operations, the system can autonomously identify and track targets of interest, addressing the difficulty of a person needing help to conduct field inspections in particular environments. At the same time, the system can issue potential threat or anomaly alerts to searchers, significantly enhancing their situational awareness capabilities.
A Dually Flat Embedding of Spacetime
Authors: Naudts Jan
Published: April 2023

A model of spacetime is presented. It has an extension to five dimensions, and in five dimensions the geometry is the dual of the Euclidean geometry w.r.t. an arbitrary positive-definite metric. Dually flat geometries are well-known in the context of information geometry. The present work explores their role in describing the geometry of spacetime. It is shown that the positive-definite metric with its flat 5-d connection can coexist with a pseudometric for which the connection is that of Levi–Civita. The 4-d geodesics are characterized by five conserved quantities, one of which can be chosen freely and is taken equal to zero in the present work. An explicit expression for the parallel transport operators is obtained. It is used to construct a pseudometric for spacetime by choosing an arbitrary possibly degenerate inner product in the tangent space of a reference point, for instance, that of Minkowski. By parallel transport, one obtains a pseudometric for spacetime, the metric connection of which extends to a 5-d connection with vanishing curvature tensor. The de Sitter space is considered as an example.
Semantic Representation of Robot Manipulation with Knowledge Graph
Authors: Miao Runqing , Jia Qingxuan , Sun Fuchun , Chen Gang , Huang Haiming , Miao Shengyi
Published: April 2023

Autonomous indoor service robots are affected by multiple factors when they are directly involved in manipulation tasks in daily life, such as scenes, objects, and actions. It is of self-evident importance to properly parse these factors and interpret intentions according to human cognition and semantics. In this study, the design of a semantic representation framework based on a knowledge graph is presented, including (1) a multi-layer knowledge-representation model, (2) a multi-module knowledge-representation system, and (3) a method to extract manipulation knowledge from multiple sources of information. Moreover, with the aim of generating semantic representations of entities and relations in the knowledge base, a knowledge-graph-embedding method based on graph convolutional neural networks is proposed in order to provide high-precision predictions of factors in manipulation tasks. Through the prediction of action sequences via this embedding method, robots in real-world environments can be effectively guided by the knowledge framework to complete task planning and object-oriented transfer.
Structured Cluster Detection from Local Feature Learning for Text Region Extraction
Authors: Lin Huei-Yung , Hsu Chin-Yu
Published: April 2023

The detection of regions of interest is commonly considered as an early stage of information extraction from images. It is used to provide the contents meaningful to human perception for machine vision applications. In this work, a new technique for structured region detection based on the distillation of local image features with clustering analysis is proposed. Different from the existing methods, our approach takes the application-specific reference images for feature learning and extraction. It is able to identify text clusters under the sparsity of feature points derived from the characters. For the localization of structured regions, the cluster with high feature density is calculated and serves as a candidate for region expansion. An iterative adjustment is then performed to enlarge the ROI for complete text coverage. The experiments carried out for text region detection of invoice and banknote demonstrate the effectiveness of the proposed technique.
Social and Emotional Learning and Early Literacy Skills: A Quasi-Experimental Study of RULER
Authors: Bailey Craig S. , Martinez Olivia , DiDomizio Elizabeth
Published: April 2023

RULER is a pre-K–12 systemic approach to social and emotional learning (SEL) that supports educators in cultivating emotion skills and provides them with pedagogical principles and tools to help them explicitly teach social and emotional skills to students. The current study tests whether preschool-level access to RULER was associated with growth in early literacy skills using a sample of 1051 preschoolers in 95 classrooms across 19 community-based centers in a small urban northeastern US community. The Preschool Early Literacy Indicators were collected three times over an academic year by district staff. Multi-level growth modeling with inverse probability weighting revealed that children in preschools with access to RULER grew significantly more in their early literacy skills than children without access to RULER—an end-of-year difference equivalent to 0.25 standard deviations, 95% CI [0.14, 0.40]. The current study demonstrates that RULER may promote young children’s early literacy skills.
Improving Dynamic Security in Islanded Power Systems: Quantification of Minimum Synchronous Inertia Considering Fault-Induced Frequency Deviations
Authors: Gouveia José , Moreira Carlos L. , Peças Lopes João A.
Published: April 2023

In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia.
Comparison of the Power Extraction Performance of an Oscillating Hydrofoil Turbine with Different Deflector Designs
Authors: Shanmugam Arun Raj , Park Ki Sun , Sohn Chang Hyun
Published: April 2023

The unsteady RANS equations for a two-dimensional hydrofoil were solved using ANSYS Fluent to model and simulate the hydrofoil at a constant Reynolds number, Re, of 2 × 105 and a fixed reduced frequency, f*, of 0.14. The simulations were performed by varying parameters, such as the number of deflectors N, tilt angle of the deflectors β, and vertical spacing of the deflectors J* = J/c, to determine the effect of the upstream deflector’s position on the hydrofoil’s performance. The results demonstrated that the deflector was effective at redirecting the separated flow away from the edges, which was then amplified downstream before colliding with the leading edge of the oscillating hydrofoil to increase power extraction. The performance of the oscillating hydrofoil was highly reliant on all three studied parameters. The hydrofoil with two deflectors (N = 2) displayed marginally superior power extraction capability compared to the hydrofoil with a single deflector (N = 1). Furthermore, the hydrofoil with the rightward inclined deflector at a low tilt angle (−5° ≥ β ≥ −10°) exhibited relatively better power extraction performance than the others. The best deflector design increased the hydrofoil’s cycle-averaged power coefficient by approximately 32% compared to a hydrofoil without a deflector. The vortex structures revealed that the flow evolution and power extraction performance were dependent on the size, robustness, and growth rate of the leading edge vortex (LEV) as well as the timing of LEV separation. The power extraction efficiency of an oscillating hydrofoil increased in the mid downstroke and upstroke due to the formation of a more robust LEV when the hydrofoil–deflector interaction was advantageous, but it dropped in the wing reversal due to the early separation of the LEV when the hydrofoil–deflector interaction was counterproductive.
Research on Model Predictive Control of a 130 t/h Biomass Circulating Fluidized Bed Boiler Combustion System Based on Subspace Identification
Authors: Wei Heng , Liu Shanjian , He Jianjie , Liu Yinjiao , Zhang Guanshuai
Published: April 2023

The structure of large biomass circulating fluidized bed (BCFB) boilers is complex, and control schemes for coal-fired boilers cannot be simply applied to biomass boilers. Multivariable coupling and operational disturbances are also common issues. In this study, a state space model of a 130 t/h BCFB boiler was established under different operating conditions. Using the 100% operating point as an example, a model predictive controller was designed and tested under output disturbance and input disturbance conditions. The results show that the predictive control system designed in this study has a fast response speed and good stability.
Drop-In Replacement of R134a in a Household Refrigerator with Low-GWP Refrigerants R513A, R516A, and R1234ze(E)
Authors: Belman-Flores Juan M. , Heredia-Aricapa Yonathan , García-Pabón Juan J. , Pérez-García Vicente , Pérez-Reguera César G.
Published: April 2023

This study proposes the experimental evaluation of alternative refrigerants with low global warming potentials (GWPs) such as R1234ze(E), R513A, and the mixture R516A as a drop-in replacement for R134a in a domestic refrigerator with a volumetric capacity of 513 L. Initially, the optimal charge for each refrigerant was defined based on the minimum energy consumption of the refrigerator, then the thermal and energy performance of the refrigerator was evaluated. Finally, a total equivalent warming impact analysis (TEWI) was performed. The main results indicated that the optimal charge of the alternative refrigerants was below that corresponding to R134a (105 g), of which R516A (86 g) presented the greatest charge reduction. Regarding the average temperature of the refrigerator compartments, very adequate thermal conditions were observed; thus, the alternative refrigerants showed very similar conditions to R134a. For the coefficient of performance (COP) and considering R134a as a reference, it was observed that R513A presented the greatest reduction of around 28%, while R1234ze(E) showed an increase of 13% in relation to R134a. Finally, the TEWI analysis showed R1234ze(E) as the refrigerant with the least impact.
Fault Detection and Identification in MMCs Based on DSCNNs
Authors: Cheng Guanyuan , Song Shaojian
Published: April 2023

Fault detection and location is one of the critical issues in engineering applications of modular multilevel converters (MMCs). At present, MMC fault diagnosis based on neural networks can only locate the open-circuit fault of a single submodule. To solve this problem, this paper proposes a fault detection and localization strategy based on a depthwise separable convolutional (DSC) neural network. By inputting the bridge arm circulating current and the submodule capacitor voltage into two serially connected neural networks, not only can this method achieve the classification of submodule open-circuit faults, submodule block short-circuit faults, and bridge arm inductance faults in MMCs, but it can also locate the switch where open-circuit faults occur. The simulation experimental results show that the proposed method achieves fault classification and locates multiple submodule open-circuit faults in the same bridge arm. This method achieves accuracies of ≥99% and 87.7% for the single-point and multi-point open-circuit fault localization in MMCs, respectively, which is better than some benchmark achievements in the current literature in terms of detection accuracy, and speed, and it has fewer model parameters and better real-time performance.
A Comprehensive Review of Fracture Characterization and Its Impact on Oil Production in Naturally Fractured Reservoirs
Authors: Kharrat Riyaz , Ott Holger
Published: April 2023

Naturally fractured reservoirs are indescribable systems to characterize and difficult to produce and forecast. For the development of such reservoirs, the role of naturally forming fractures in the different development stages needs to be recognized, especially for the pressure maintenance and enhanced oil recovery stages. Recent development in the field of naturally carbonate fractured aimed at fracture characterization, fracture modeling, and fracture network impact of fracture networks on oil recovery were reviewed. Consequently, fracture identification and characterization played pivotal roles in understanding production mechanisms by integrating multiple geosciences sources and reservoir engineering data. In addition, a realistic fracture modeling approach, such as a hybrid, can provide a more accurate representation of the behavior of the fracture and, hence, a more realistic reservoir model for reservoir production and management. In this respect, the influence of different fracture types present in the reservoir, such as major, medium, minor, and hairline fractures networks, and their orientations were found to have different rules and impacts on oil production in the primary, secondary, and EOR stages. In addition, any simplification or homogenization of the fracture types might end in over or underestimating the oil recovery. Improved fracture network modeling requires numerous considerations, such as data collection, facture characterization, reservoir simulation, model calibration, and model updating based on newly acquired field data are essential for improved fracture network description. Hence, integrating multiple techniques and data sources is recommended for obtaining a reliable reservoir model for optimizing the primary and enhanced oil recovery methods.
State of the Art of Oil and Gas Pipeline Vulnerability Assessments
Authors: Zhang Han , Feng Qingshan , Yan Bingchuan , Zheng Xianbin , Yang Yue , Chen Jian , Zhang Hong , Liu Xiaoben
Published: April 2023

In recent years, the safety of oil and gas pipelines has become a primary concern for the pipeline industry. This paper presents a comprehensive study of the vulnerability concepts that may be used to measure the safety status of pipeline systems. The origins of the vulnerability concepts are identified, the development and evolution of the vulnerability concepts are described, and the main connotations of the four levels of vulnerability concepts applied in different fields at this stage are summarized. Qualitative and quantitative methods of vulnerability assessment are comprehensively investigated, and the advantages and disadvantages, scope of application and key issues faced are compared and summarized. The research and analysis show that the vulnerability assessment of oil and gas pipelines is at a preliminary stage, and there is an urgent demand to establish a unified vulnerability concept and assessment system for oil and gas pipeline systems. The current qualitative or semi-quantitative assessment of pipeline vulnerability research lacks reasonable and scientific standards and bases for the classification of indicators and the determination of indicator scores, and it needs to focus on the establishment and improvement of quantitative assessment models.
Artificial Intelligence for Energy Processes and Systems: Applications and Perspectives
Authors: Skrobek Dorian , Krzywanski Jaroslaw , Sosnowski Marcin , Uddin Ghulam Moeen , Ashraf Waqar Muhammad , Grabowska Karolina , Zylka Anna , Kulakowska Anna , Nowak Wojciech
Published: April 2023

In recent years, artificial intelligence has become increasingly popular and is more often used by scientists and entrepreneurs. The rapid development of electronics and computer science is conducive to developing this field of science. Man needs intelligent machines to create and discover new relationships in the world, so AI is beginning to reach various areas of science, such as medicine, economics, management, and the power industry. Artificial intelligence is one of the most exciting directions in the development of computer science, which absorbs a considerable amount of human enthusiasm and the latest achievements in computer technology. This article was dedicated to the practical use of artificial neural networks. The article discusses the development of neural networks in the years 1940–2022, presenting the most important publications from these years and discussing the latest achievements in the use of artificial intelligence. One of the chapters focuses on the use of artificial intelligence in energy processes and systems. The article also discusses the possible directions for the future development of neural networks.
Experimental Evaluation of a Photovoltaic/Thermal Air Heater with Metal Mesh-Integrated Thermal Energy Storage System
Authors: Tuncer Azim Doğuş , Gürbüz Emine Yağız , Keçebaş Ali , Georgiev Aleksandar G.
Published: April 2023

The objective of this study is to improve the performance of a hybrid photovoltaic/thermal (PV/T) air heater incorporating a thermal energy storage system (TESS) that uses paraffin and has metallic mesh layers. In the experimental part of the research, three different pilot-scale PV/Ts have been designed, manufactured, and experimentally investigated. The first system was structured as a conventional PV/T, while the second (PVT/TESS) was modified with a paraffin-based TESS. The efficiency of a hybrid PV/T air heater was improved by integrating a paraffin-based thermal energy storage system (TESS) with metallic mesh layers (PV/T-MTESS). The performance of the modified PV/T-MTESS system was compared to two other PV/T systems under the same weather conditions and air flow rate. The results of the experiment demonstrated that the integration of mesh layers into the TESS led to substantial improvements in the system’s thermal and electrical performance, as well as its overall exergy efficiency. The improvements were 33.17%, 14.82%, and 58.15%, respectively, when compared to the unaltered (conventional) PV/T setup. Moreover, an enviro-economic analysis has been performed on the developed and tested PV/Ts. Using TESS with only paraffin and with mesh layer-added paraffin reduced the payback time of the system by 2.54% and 9.85%, respectively. Moreover, the annual carbon dioxide saving was improved from 0.079 tons/year to 0.103 tons/year using a mesh layer-integrated TESS in the PV/T air heater.
Interpretation of Sand Body Architecture in Complex Fault Block Area of Craton Basin: Case Study of TIII in Sangtamu Area, Tarim Basin
Authors: Wang Chao , Yan Chunjing , Zhu Zhengjun , Li Shaohua , Lv Duanchuan , Wang Xixin , Liu Dawang
Published: April 2023

The complex fault block oilfields in the craton basin contain vast reserves of oil and gas resources. During the development of an oilfield, the flow of oil, gas, and water, is controlled by faults and configuration boundaries. The distribution of remaining oil and gas depends on the interpretation of the reservoir’s architecture. However, recognizing the faults and the architecture boundary remains a challenge, hindering the efficient development of these resources. This study proposes a new idea for interpreting the configuration of thick sand bodies. This study was conducted in order to interpret the fine architecture of thick sand bodies in the Sangtamu area, using core samples, well logging, and production data, guided by sedimentation patterns from ancient to modern times. Results indicate that the Sangtamu area is a braided river delta front sedimentary system, dominated by the backbone underwater distributary channel and branch-type underwater distributary channels. The backbone channel is larger in scale, with a relatively large rock grain size and a box-shaped logging curve, whereas the smaller-scale branch channels have a bell-shaped logging curve resulting from the gradual weakening of water energy. Sandstone bodies from different types of underwater distributary channels are spatially overlapped, forming thick plate-like sandstones. The architecture interface between channels can be used as the fluid seepage boundary and can help prevent bottom water intrusion to a certain extent. The remaining oil is primarily concentrated in the architecture boundary area, which presents the next potential tapping area.
An Application of Machine Learning Algorithms by Synergetic Use of SAR and Optical Data for Monitoring Historic Clusters in Cypriot Cities
Authors: Tzima Maria Spyridoula , Agapiou Athos , Lysandrou Vasiliki , Artopoulos Georgios , Fokaides Paris , Chrysostomou Charalambos
Published: April 2023

In an era of rapid technological improvements, state-of-the-art methodologies and tools dedicated to protecting and promoting our cultural heritage should be developed and extensively employed in the contemporary built environment and lifestyle. At the same time, sustainability principles underline the importance of the continuous use of historic or vernacular buildings as part of the building stock of our society. Adopting a holistic, integrated, multi-disciplinary strategy can link technological innovation with the conservation and restoration of heritage buildings. This paper presents the ongoing research and results of the application of Machine Learning methods for the remote monitoring of the built environment of the historic cluster in Cypriot cities. This study is part of an integrated, multi-scale, and multi-disciplinary study of heritage buildings, with the end goal of creating an online HBIM platform for urban monitoring.
The Rising Threat of Atmospheric CO2: A Review on the Causes, Impacts, and Mitigation Strategies
Authors: Nunes Leonel J. R.
Published: April 2023

The increasing levels of carbon dioxide (CO2) in the atmosphere have become a major environmental challenge due to their contribution to global warming. The primary drivers of the increase in atmospheric CO2 concentrations are the combustion of fossil fuels, deforestation, agricultural practices, or the production of cement, which play a significant role in the increase of CO2 concentration in the atmosphere. However, efforts are being made to mitigate the negative effects of CO2 emissions, including carbon capture and storage (CCS) technologies that aim to capture CO2 from industrial processes and store it in underground geological formations. Methane, another potent greenhouse gas, is another major contributor to climate change and is mainly produced by agricultural activities such as livestock farming and rice cultivation. To address this, sustainable agricultural practices, such as reducing meat consumption and adopting climate-smart farming techniques, are crucial. Ultimately, a sustainable future can be secured for the planet and future generations by implementing effective measures, such as the use of sustainable energy sources, improvements in energy efficiency, responsible land use practices, and reducing the emissions of both CO2 and methane.
Barriers to the Utilization of Primary Health Centers (PHCs) in Iraq
Authors: Al Janabi Taysir
Published: April 2023

Primary care has been viewed as a means to ensure equitable access to care, enhance efficiency within healthcare systems, and improve health service quality. In recent decades, Iraq has transformed its compromised health system, shifting the healthcare model from hospital-based to primary care through primary health centers (PHCs) and referral mechanisms. Based on an extensive literature review, this qualitative paper explores the healthcare utilization of PHCs in different regions of Iraq. It also identifies some barriers to PHC use and recommends evidence-based approaches for improving PHCs’ performance. Some reported challenges to better utilizing PHCs were the poor quality of services, patient dissatisfaction, long walking distance to a health center, and limited availability and affordability of the medications. If Iraq is to use primary care as a tool in achieving sustainable development goals (SDGs), collaborative efforts addressing the facility-related factors should be a priority.
Plant Traits of Tilia tomentosa Moench, Fraxinus excelsior L., and Pinus nigra J.F.Arnold as a Proxy of Urbanization
Authors: Petrova Slaveya , Petkova Mariana
Published: April 2023

Linden, ash, and pine are ubiquitous ornamental trees due to their ability to adapt to the urban environment. They have been key species in urban green infrastructure from more than hundreds of years and play an active role in maintaining ecosystem services. The urbanization rate in recent decades, combined with global climate change, has led to dynamic changes in the environmental factors which pose new challenges to urban vegetation. Hence, the aims of this study were as follows: (i) to track changes in the content of some elements in plant leaves after transplanting them into an urban environment; (ii) to investigate the relationship between urbanization intensity with plant traits (leaf injuries, photosynthetic activity, transpiration, stomatal conductance, and molecular changes); and (iii) to provide recommendations for improving the management and ecological functions of urban trees. To address these aims, data on urbanization intensity (according to the percentage of built-up area and traffic volume), plant performance, and intraspecific variations of silver linden (Tilia tomentosa), European ash (Fraxinus excelsior), and European black pine (Pinus nigra) were collected at four experimental plots in the city of Plovdiv (Bulgaria) during 2015–2020. The initial concentrations of some potentially toxic elements (As, Cd, Cr, Cu, Mn, Pb, V, and Zn) in the tree leaves at the beginning (prior to planting into the urban environment) and at the end of the experiment were also measured. We illustrate that the growth of urbanization intensity increased the concentrations of potentially toxic elements in tree leaves, caused leaf injuries, and enhanced the maximum photosynthetic rate but decreased the transpiration rate and stomatal conductance. At the molecular level, the percentage of polymorphic bands was also found to depend on urbanization intensity. High similarity was observed between the trees in the first three experimental plots (subjected to urbanization load), with the lowest similarity in the control plot. These findings are of high practical value for urban planners regarding how to build a new green infrastructure and how to preserve plant diversity in urban areas across urbanization gradients.
Study on the Effect of Flattening Modification on Bamboo Cutting Board and Corresponding Carbon Footprint Evaluation
Authors: Zhao Yihan , Ma Yan , Lou Zhichao , Li Yanjun
Published: April 2023

Bamboo, as a renewable biomass material, has received wide public attention. However, due to the thin-walled and hollow structure of bamboo, the mainstream processing method is complex and requires splitting the bamboo into narrow strips and then gluing them together for further manufacturing products. In addition, the surface glue residue makes the safety of indoor applications a concern, especially for cutting boards that come into contact with food. In response to the above problems, this paper introduces a bamboo flattening technology, which can flatten and unfold the pre-treated bamboo into a large-size flattened bamboo board (FBB). The results show that, compared to untreated bamboo, the dimensional stability of the FBB was improved and the flexural strength and elastic modulus of the FBB were increased by about 8.0%. The flattened bamboo cutting board was manufactured with the FBB as the surface layer and had a moisture content and hardness value of 9.2% and 5080 N, respectively, and the accumulated dip peel length of any glue layer was less than 25 mm. The flattened bamboo cutting board is proved to be a carbon-neutral product with a carbon footprint value of −42.92 kg CO2/t. This work provides a theoretical basis for the fabrication of large-size unspliced bamboo boards and provides new ideas for the scenario-specific application of FBBs. Using a FBB to make cutting boards can avoid contact between food and adhesives, making them more hygienic. The findings of this research can be used to make bamboo cutting boards more hygienic, environmentally friendly and possess excellent physical and mechanical properties.
An Experimental Study on the Transportation Characteristics of Perfluoro(2-methyl-3-pentanone) in a Straight Pipe
Authors: Ni Xiaomin , Chen Ye , Huang Qiurui , Zhao Chenxi , Li Songyang , Huang Jiahui , Wang Jian
Published: April 2023

Gaseous fire suppressants are usually stored in a vessel via pressurization, and then discharged out through pipelines. The flow behaviors of the agents in pipes greatly affect its dispersion in space, as well as the fire extinguishing results. Here, an experimental study was carried out on the transportation characteristics of perfluoro(2-methyl-3-pentanone) (C6F12O) in a horizontal straight pipe with the temperature and pressure recorded synchronously. At a filling pressure of 1800 kPa and a filling density of 517 kg·m−3, the agent release was completed in 2.0 s with the pipeline pressure peak of 1145 kPa and the pipeline temperature nadir of −10.6 °C. In comparison to that of bromotrifluoromethane (CF3Br) under the same conditions, the temperature and pressure curves of C6F12O exhibited similar varying trajectories but a much smaller amplitude, which could be ascribed to their different thermophysical properties. When keeping the other conditions unchanged, raising the filling pressure C6F12O reduces the discharge duration and the pipeline temperatures. Increasing the filling density extends the discharge duration, but shows little influence on the pipeline temperatures. The results were expected to provide useful information for the model validation and engineering design of a C6F12O fire-suppressing system with a predictable performance.
Phylogenetic Relationships of the Pseudogobionini Group (Teleostei: Cyprinidae) with Selection Pressure Analyses to Genes of Mitochondrial Genome
Authors: Chen Lin , Zhang Xiaoyu , Liu Huanzhang
Published: April 2023

We newly sequenced complete mitochondrial genomes (mitogenome) of two gudgeon species Saurogobio dabryi and S. punctatus, and we downloaded 49 gudgeon mitogenomes from GenBank to investigate the phylogeny of the Pseudogobionini group and analyze selection pressure of the genes. With genera Gobio, Acanthogobio, and Romanogobio as outgroups, the phylogeny of the Pseudogobionini group was revealed as ((Xenophysogobio + Gobiobotia) + (Saurogobio + (Abbottina + (Pseudogobio + Biwia complex)))) based on the concatenated nucleotide sequences of 13 protein-coding genes (PCGs). Based on the molecular phylogeny and morphological or osteological characters, we proposed a classification system of the Pseudogobionini group. Moreover, five pairs of sister taxa were selected for gene selection pressure analyses to explore the link of mitochondrial gene evolution to group differentiation and adaptations. We detected significantly different dN/dS values in 11 out of 13 (excluding ND3 and ND4L) PCGs in five pairs of clades, significantly different mean dN/dS, dN, and/or dS values in 8 out of 13 PCGs (excluding ND2, ATP8, ND3, ND4L, and ND6) in three pairs of sub-clades and seven positively selected sites in another three pairs of sub-clades. These results indicated that mitochondrial gene evolution might have contributed to group differentiation and adaptations especially for river or lake environments.
An Approximate Analytical Model of a Jet Flow with Mach Reflection and Pulsed Energy Supply at the Main Shock
Authors: Chernyshov Mikhail V. , Savelova Karina E.
Published: April 2023

The supersonic flow of a reactive gas mixture with Mach reflection of oblique shocks and pulsed energy supply at the Mach stem is considered within the framework of the Chapman–Jouguet theory. An approximate analytical model is proposed that quickly determines the shape and size of the shock-wave structure as well as the flow parameters in various flow regions. As an example of the application of the proposed analytical model, the “first barrel” of a highly overexpanded jet flow of an air-methane mixture with a high supersonic velocity, is studied. Flows of hydrogen–air and hydrogen–oxygen mixtures were also considered for comparison with preceding numerical results. The height of the triple point of the Mach reflection is determined in the presence of a change in the chemical composition of the mixture and an isobaric pulsed energy supply at the main shock.
Identification of Antibacterial Components and Modes in the Methanol-Phase Extract from a Herbal Plant Potentilla kleiniana Wight et Arn
Authors: Tang Yingping , Yu Pan , Chen Lanming
Published: April 2023

The increase in bacterial resistance and the decline in the effectiveness of antimicrobial agents are challenging issues for the control of infectious diseases. Traditional Chinese herbal plants are potential sources of new or alternative medicine. Here, we identified antimicrobial components and action modes of the methanol-phase extract from an edible herb Potentilla kleiniana Wight et Arn, which had a 68.18% inhibition rate against 22 species of common pathogenic bacteria. The extract was purified using preparative high-performance liquid chromatography (Prep-HPLC), and three separated fragments (Fragments 1–3) were obtained. Fragment 1 significantly elevated cell surface hydrophobicity and membrane permeability but reduced membrane fluidity, disrupting the cell integrity of the Gram-negative and Gram-positive pathogens tested (p < 0.05). Sixty-six compounds in Fragment 1 were identified using Ultra-HPLC and mass spectrometry (UHPLC-MS). The identified oxymorphone (6.29%) and rutin (6.29%) were predominant in Fragment 1. Multiple cellular metabolic pathways were altered by Fragment 1, such as the repressed ABC transporters, protein translation, and energy supply in two representative Gram-negative and Gram-positive strains (p < 0.05). Overall, this study demonstrates that Fragment 1 from P. kleiniana Wight et Arn is a promising candidate for antibacterial medicine and food preservatives.
Recent Advances in the Incorporation of Polysaccharides with Antioxidant and Antibacterial Functions to Preserve the Quality and Shelf Life of Meat Products
Authors: Ben Akacha Boutheina , Michalak Monika , Najar Basma , Venturi Francesca , Taglieri Isabella , Kačániová Miroslava , Ben Saad Rania , Mnif Wissem , Garzoli Stefania , Ben Hsouna Anis
Published: April 2023

Meat and meat products are susceptible to various types of natural processes such as oxidative degradation due to their high content of protein and essential amino acids. However, finding solutions to maintain the nutritional and sensory quality of meat and meat products is unavoidable. Hence, there is a pressing need to investigate alternatives to synthetic preservatives, focusing on active biomolecules of natural provenance. Polysaccharides are natural polymers of various sources that exhibit antibacterial and antioxidant properties via a variety of mechanisms, owing to their diversity and structural variation. For this reason, these biomolecules are widely studied in order to improve texture, inhibit the growth of pathogens, and improve the oxidative stability and sensory characteristics of meat products. However, the literature has not addressed their biological activity in meat and meat products. This review summarizes the various sources of polysaccharides, their antioxidant and antibacterial activities (mainly against pathogenic food strains), and their use as natural preservatives to replace synthetic additives in meat and meat products. Special attention is given to the use of polysaccharides to improve the nutritional value of meat, resulting in more nutrient-rich meat products with higher polysaccharide content and less salt, nitrites/nitrates, and cholesterol.
Ethyl Vanillin Rapid Crystallization from Carboxymethyl Chitosan Ion-Switchable Hydrogels
Authors: Huang Chenghong , Tang Hong , Huang Xiaorong , Chen Hongjie , Yang Kang , Yin Qi , Zhang Lin , Li Xia , Mou Xue , Chen Shuangkou , Zhang Yuchan , Hu Yan
Published: April 2023

Polymer gels are usually used for crystal growth as the recovered crystals have better properties. Fast crystallization under nanoscale confinement holds great benefits, especially in polymer microgels as its tunable microstructures. This study demonstrated that ethyl vanillin can be quickly crystallized from carboxymethyl chitosan/ethyl vanillin co-mixture gels via classical swift cooling method and supersaturation. It found that EVA appeared with bulk filament crystals accelerated by a large quantity of nanoconfinement microregions resulted from space-formatted hydrogen network between EVA and CMCS when their concentration exceeds 1:1.4 and may occasionally arise when the concentration less than 1:0.8. It was observed that EVA crystal growth has two models involving hang-wall growth at the air-liquid interface at the contact line, as well as extrude-bubble growth at any sites on the liquid surface. Further investigations found that EVA crystals can be recovered from as-prepared ion-switchable CMCS gels by 0.1 M hydrochloric acid or acetic acid without defects. Consequently, the proposed method may offer an available scheme for a large-scale preparation of API analogs.
Whole Mitochondrial Genome Detection and Analysis of Two- to Four-Generation Maternal Pedigrees Using a New Massively Parallel Sequencing Panel
Authors: Peng Dan , Geng Jiaojiao , Yang Jingyi , Liu Jiajun , Wang Nana , Wu Riga , Sun Hongyu
Published: April 2023

Mitochondrial DNA (mtDNA) is an effective genetic marker in forensic practice, especially for aged bones and hair shafts. Detection of the whole mitochondrial genome (mtGenome) using traditional Sanger-type sequencing is laborious and time-consuming. Additionally, its ability to distinguish point heteroplasmy (PHP) and length heteroplasmy (LHP) is limited. The application of massively parallel sequencing in mtDNA detection helps researchers to study the mtGenome in-depth. The ForenSeq mtDNA Whole Genome Kit, which contains a total of 245 short amplicons, is one of the multiplex library preparation kits for the mtGenome. We used this system to detect the mtGenome in the blood samples and hair shafts of thirty-three individuals from eight two-generation pedigrees, one three-generation pedigree, and one four-generation pedigree. High-quality sequencing results were obtained. Ten unique mtGenome haplotypes were observed in the mothers from the ten pedigrees. A total of 26 PHPs were observed using the interpretation threshold of 6%. Eleven types of LHPs in six regions were evaluated in detail. When considering homoplasmic variants only, consistent mtGenome haplotypes were observed between the twice-sequenced libraries and between the blood and hair shafts from the same individual and among maternal relatives in the pedigrees. Four inherited PHPs were observed, and the remainder were de novo/disappearing PHPs in the pedigrees. Our results demonstrate the effective capability of the ForenSeq mtDNA Whole Genome Kit to generate the complete mtGenome in blood and hair shafts, as well as the complexity of mtDNA haplotype comparisons between different types of maternal relatives when heteroplasmy is considered.
The Classification of Cultural Heritage Buildings in Athens Using Deep Learning Techniques
Authors: Siountri Konstantina , Anagnostopoulos Christos-Nikolaos
Published: April 2023

Architectural structures, the basic elements of the urban web, are an aggregation of buildings that have been built at different times, with different materials, and in different styles. Through research, they can be divided into groups that present common morphological attributes and refer to different historical periods with particular social, economic, and cultural characteristics. The identification of these common repeating elements and organizational construction structures leads to the identification of the “type” of the building, which until now has required specialized knowledge, time, and customized proof checking. Recent developments in the field of artificial intelligence (AI) and, more specifically, in deep learning (DL) appear to contribute gradually to the study of the typological evolution of buildings, especially those of cultural heritage (CH). In this paper, we present a deep-learning-based method for the classification of modern Athenian architecture (since 1830) using the YOLO algorithm. This research work can contribute to the digital management of the existing urban building stock, the autonomous large-scale categorization of data that are available from street view images, and the enhancement of the tangible CH.
Rapid and Efficient In Vitro Propagation Protocol of Endangered Wild Prickly Pear Growing in Eastern Morocco
Authors: Marhri Ahmed , Tikent Aziz , Garros Laurine , Merah Othmane , Elamrani Ahmed , Hano Christophe , Abid Malika , Addi Mohamed
Published: April 2023

The Opuntia genus is widely recognized as a significant member of the Cactaceae family. The eastern Moroccan prickly pear’s wild ecotype is renowned for its production of fruits of superior quality, which are in high demand. Nonetheless, the white cochineal (Dactylopius opuntiae) has emerged as a significant hazard to the persistence of the indigenous wild prickly pear population in the majority of the country’s territories. Conventional plant propagation techniques may facilitate the transmission of pathogens to successive generations and thus fail to satisfy market requirements. Therefore, the primary goal of this study was to develop a rapid and efficient protocol for large-scale production of the eastern Moroccan wild ecotype using axillary buds as the starting material. Sterilization of the starting material is a crucial but challenging step in this species, as the meristem is located just beneath the spine. The protocol developed for this study produced moderately satisfactory results, with 20 to 30% contamination in each experiment. The obtained shoots were incubated on Murashige and Skoog medium supplemented with varying concentrations of BAP (0, 1.5, 3, 5, and 7.5 mg/L). The treatment with BAP at 5 mg/L exhibited a statistically significant increase in the average number of regenerated shoots per explant (19.42). The effect of kinetin on the rooting of prickly pear was evaluated by transferring the shoots to a MS medium supplemented with varying concentrations of kinetin (0, 0.5, 1, 1.5, 2, and 2.5 mg/L). The use of kinetin increased the number and length of roots while also shortening the root development period from 21 days to 10 days. The best results were obtained at a concentration of 1.5 mg/L of kinetin. Furthermore, satisfactory acclimatization of plants was achieved by using plastic containers with a gradually increasing opening of the lids. The outcomes of this experimentation have significant potential to facilitate the preservation of this botanical variety, reduce the risk of white cochineal infestation, and address the need for superior quality fruit supply in the market.