bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Terrestrial Inputs on Mesozooplankton Community Structure in Bohai Bay, China
Authors: Li Danyang , Wen Yujian , Zhang Guodong , Zhang Guicheng , Sun Jun , Xu Wenzhe
Published: May 2022

Zooplankton play a pivotal role in connecting primary producers and high trophic levels, and changes in their temporal and spatial distribution may affect the entire marine ecosystem. The spatial and seasonal taxonomic composition patterns of mesozooplankton in Bohai Bay were investigated in relation to a number of water parameters. Bohai Bay is a eutrophic semi-enclosed bay with dynamic physico-chemical conditions influenced by terrestrial inputs and seawater intrusion. The results showed that under the condition of terrigenous input, the diversity of mesozooplankton species near the eutrophic Haihe River Estuary and Jiyun River Estuary was lower than that in the central Bohai Bay, with gelatinous Oikopleura dioica as the dominant species. The mesozooplankton diversity was highest in the bay mouth affected by seawater intrusion, and the dominant oceanic species, mainly copepods Corycaeus affinis, Calanus sinicus, and Oithona similis, entered the inner bay from the bay mouth. Meanwhile, the abundance of mesozooplankton in summer was significantly higher than that in autumn. Compared with historical data, the dominant species in Bohai Bay has evolved from arrow worm Sagitta crassa to copepod Paracalanus parvus, probably due to global warming, indicating the effects of human activities on the succession of mesozooplankton community.
Sclerosing Microcystic Adenocarcinoma Arising from the Tongue: A Case Report and Literature Review
Authors: Lee Yi-Ying , Hwang Tzer-Zen , Jin Ying-Tai , Chen Chien-Chin
Published: May 2022

Sclerosing microcystic adenocarcinoma is a rare and recently characterized cancer that affects the mucosal surfaces of the head and neck without adnexal involvement. Histologically, microcystic adnexal carcinoma of the skin resembles it. It does, however, contain unique characteristics that merit our attention for potential diagnostic errors. Therefore, we present a 48-year-old male with sclerosing microcystic adenocarcinoma of the tongue, along with a full discussion and a brief review of pertinent literature.
Task Offloading Strategy Based on Mobile Edge Computing in UAV Network
Authors: Qi Wei , Sun Hao , Yu Lichen , Xiao Shuo , Jiang Haifeng
Published: May 2022

When an unmanned aerial vehicle (UAV) performs tasks such as power patrol inspection, water quality detection, field scientific observation, etc., due to the limitations of the computing capacity and battery power, it cannot complete the tasks efficiently. Therefore, an effective method is to deploy edge servers near the UAV. The UAV can offload some of the computationally intensive and real-time tasks to edge servers. In this paper, a mobile edge computing offloading strategy based on reinforcement learning is proposed. Firstly, the Stackelberg game model is introduced to model the UAV and edge nodes in the network, and the utility function is used to calculate the maximization of offloading revenue. Secondly, as the problem is a mixed-integer non-linear programming (MINLP) problem, we introduce the multi-agent deep deterministic policy gradient (MADDPG) to solve it. Finally, the effects of the number of UAVs and the summation of computing resources on the total revenue of the UAVs were simulated through simulation experiments. The experimental results show that compared with other algorithms, the algorithm proposed in this paper can more effectively improve the total benefit of UAVs.
Family Experiences with the Upbringing and Education of a Child with Congenital Malformations, Focusing on the Conditions of an Inclusive School Environment
Authors: Sedláčková Dagmar , Kantor Jiří
Published: May 2022

The birth of a child with congenital malformation and serious illness impacts the experiences of all family members and the educational process, but there are only rare descriptions of such cases in the literature. The aim of this study is to understand better the lived experiences of a Czech family who have a child with congenital malformations with a focus on his education in an inclusive environment. The study is based on van Manen’s methodology and autobiographic (or semi-structured) interviews with Karl (19), his mother (46), and his father (49). Data were analyzed for every participant separately: the mother—repeated challenges associated with increasing new health complications, discomfort of son, school support, the future, optimism, and gratefulness; the father—comprehensive support of the son, including all family; Karl—concealment of disability, difficulties associated with disability, participation, school support, relationship with peers, and the future. Based on the results of this case study, for the education of students with congenital malformation and illness, we recommend including parents, healthcare professionals, and school staff in the mutual teamwork; adapting the timetables and spatial arrangements at school; and coordinating the educational process with necessary interventions.
Self-Efficacy in a 3-Dimensional Virtual Reality Classroom—Initial Teacher Education Students’ Experiences
Authors: Pendergast Donna , O’Brien Mia , Prestridge Sarah , Exley Beryl
Published: May 2022

This study explores initial teacher education (ITE) university students’ experiences of work-integrated-learning (WiL) placements in a virtual reality environment. The COVID-19 pandemic was the catalyst for this study when schools around the world were inaccessible to ITE students. Undertaking WiL, which is typically a mandated component of ITE programs, became challenging, if not impossible. In this uncertain environment and the broader context of a nation-wide teacher shortage in Australia, the need to pivot and consider alternatives became a high priority. This study reports on a simulated experimental space as an alternative WiL for ITE students in a virtual classroom environment, exploring the impact on the self-efficacy of the participants. The ITE students explored the platform as a teaching space, designing, delivering and participating in lessons. Data about their experiences were collected utilising a multi-methods design comprised of self-efficacy surveys and self-reflections. The findings reveal: (i) an increase in self-efficacy upon completion of the experience, with a small decline post program; and (ii) reported development of technological and pedagogical confidence. These findings contribute to the field as low teacher self-efficacy is identified as one of the inhibitors for the integration of technology in teacher education. This study provides an insight into the transformative potential of enhancing ITE students’ self-efficacy in simulated, virtual environments.
A General Math Anxiety Measure
Authors: Kelly Stephanie , Croucher Stephen M. , Kim Kyung Yong , Permyakova Tatiana , Turdubaeva Elira , Rocker Kenneth T. , Eskiçorapçı Nadirabegim , Stanalieva Gulzada , Orunbekov Bakyt , Rimkeeratikul Sucharat
Published: May 2022

Math anxiety is a psychological burden that can hinder individuals across their lifetimes. However, the current literature lacks a valid measure of math anxiety that can be used across instructional modalities and among non-student populations. As such, it is difficult to assess math anxiety in virtual learning environments, track math anxiety across lifetimes, or determine the utility of math anxiety inoculations for non-student populations. This study presents a validity portfolio for a generalized math anxiety measure that can be used across teaching modalities, across lifetimes, and is simple enough to be used cross-culturally. The measure yielded evidence of validity when used in all tested samples: the United States (student and non-student samples), New Zealand (student and non-student samples), Kyrgyzstan (non-student sample), Turkey (non-student sample), Russia (non-student sample), and Thailand (non-student sample). The data support the use of the new math anxiety measure free of context.
Sentiment Analysis of Users’ Reactions on Social Media during the Pandemic
Authors: Abdukhamidov Eldor , Juraev Firuz , Abuhamad Mohammed , El-Sappagh Shaker , AbuHmed Tamer
Published: May 2022

During the outbreak of the COVID-19 pandemic, social networks became the preeminent medium for communication, social discussion, and entertainment. Social network users are regularly expressing their opinions about the impacts of the coronavirus pandemic. Therefore, social networks serve as a reliable source for studying the topics, emotions, and attitudes of users that have been discussed during the pandemic. In this paper, we investigate the reactions and attitudes of people towards topics raised on social media platforms. We collected data of two large-scale COVID-19 datasets from Twitter and Instagram for six and three months, respectively. This paper analyzes the reaction of social network users in terms of different aspects including sentiment analysis, topic detection, emotions, and the geo-temporal characteristics of our dataset. We show that the dominant sentiment reactions on social media are neutral, while the most discussed topics by social network users are about health issues. This paper examines the countries that attracted a higher number of posts and reactions from people, as well as the distribution of health-related topics discussed in the most mentioned countries. We shed light on the temporal shift of topics over countries. Our results show that posts from the top-mentioned countries influence and attract more reactions worldwide than posts from other parts of the world.
Administrators and Students on E-Learning: The Benefits and Impacts of Proper Implementation in Nigeria
Authors: Sucuoğlu Esen , Andrew Azubike Umunze
Published: May 2022

The quest for better education and knowledge acquisition has triggered the introduction, acceptance and incorporation of e-learning into Nigerian learning. The introduction of the concept of e-learning to Nigerian learning can be dated back to the 1980s, when reputable Nigerians enrolled in several universities in London. In addition, the introduction of e-learning to a premier university in Nigeria, rooted in the college of Ibadan, led to greater interest, causing locals to seek extramural work and other studies at Oxford University. This study examines the impacts that proper educational administration, policy making and implementation, as well as the adoption of e-learning, can have to fix the dilapidated Nigerian educational structure. A quantitative method of data collection was used, through well-structured questionnaires for both administrators and students issued to the four universities sampled in this study. A total of 240 questionnaires were issued to respondents, with 60 each to the different universities and with 30 each for both students and administrators. A total of 180 were retrieved, and descriptive analysis was carried out with SPSS (23). Internal consistency was determined with Cronbach’s alpha, having an internal consistency of 0.78. The findings show that all the administrators were graduates with a minimum of a Bachelor’s degree. It was revealed that 32 (17.8%) of the students possessed smartphones as gadgets for e-learning and that administrators contributed to the enhancement of student performance, hence creating impacts in their examination grades, with a mean of 2.66, being rated ‘Good’ for their performance. Unfavorable government policies and unprofessionalism of administrators in e-learning implementations were the major constraints, with a mean of 4.6. The cost of the procurement of the needed resources (data) for e-learning also impacts e-learning. Internet resources used by the students contributed to huge success in e-learning for 28 (24.6%) and 24 (21.9%) students. Although the constraints limit the effectiveness of e-learning in Nigeria, it also impacts student advancement compared with the face-to-face learning process. The government’s proactive measures will improve e-learning.
An Exploratory Study of Cognitive Sciences Applied to Cybersecurity
Authors: Andrade Roberto O. , Fuertes Walter , Cazares María , Ortiz-Garcés Iván , Navas Gustavo
Published: May 2022

Cognitive security is the interception between cognitive science and artificial intelligence techniques used to protect institutions against cyberattacks. However, this field has not been addressed deeply in research. This study aims to define a Cognitive Cybersecurity Model by exploring fundamental concepts for applying cognitive sciences in cybersecurity. For achieving this, we developed exploratory research based on two steps: (1) a text mining process to identify main interest areas of research in the cybersecurity field and (2) a valuable review of the papers chosen in a systematic literature review that was carried out using PRISMA methodology. The model we propose tries to fill the gap in automatizing cognitive science without taking into account the users’ learning processes. Its definition is supported by the main findings of the literature review, as it leads to more in-depth future studies in this area.
DeepRare: Generic Unsupervised Visual Attention Models
Authors: Kong Phutphalla , Mancas Matei , Gosselin Bernard , Po Kimtho
Published: May 2022

Visual attention selects data considered as “interesting” by humans, and it is modeled in the field of engineering by feature-engineered methods finding contrasted/surprising/unusual image data. Deep learning drastically improved the models efficiency on the main benchmark datasets. However, Deep Neural Networks-based (DNN-based) models are counterintuitive: surprising or unusual data are by definition difficult to learn because of their low occurrence probability. In reality, DNN-based models mainly learn top-down features such as faces, text, people, or animals which usually attract human attention, but they have low efficiency in extracting surprising or unusual data in the images. In this article, we propose a new family of visual attention models called DeepRare and especially DeepRare2021 (DR21), which uses the power of DNNs’ feature extraction and the genericity of feature-engineered algorithms. This algorithm is an evolution of a previous version called DeepRare2019 (DR19) based on this common framework. DR21 (1) does not need any additional training other than the default ImageNet training, (2) is fast even on CPU, (3) is tested on four very different eye-tracking datasets showing that DR21 is generic and is always within the top models on all datasets and metrics while no other model exhibits such a regularity and genericity. Finally, DR21 (4) is tested with several network architectures such as VGG16 (V16), VGG19 (V19), and MobileNetV2 (MN2), and (5) it provides explanation and transparency on which parts of the image are the most surprising at different levels despite the use of a DNN-based feature extractor.
Threat Matrix: A Fast Algorithm for Human–Machine Chinese Ludo Gaming
Authors: Han Fuji , Zhou Man
Published: May 2022

Chinese Ludo, also known as Aeroplan Chess, has been a very popular board game for several decades. However, there is no mature algorithm existing for human–machine gambling. The major challenge is the high randomness of the dice rolls, where the algorithm must ensure that the machine is smarter than a human in order to guarantee that the owner of the game machines makes a profit. This paper presents a fast Chinese Ludo algorithm (named “Threat Matrix”) that we have recently developed. Unlike from most chess programs, which rely on high performance computing machines, the evaluation function in our program is only a linear sum of four factors. For fast and low-cost computation, we innovatively construct the concept of the threat matrix, by which we can easily obtain the threat between any two dice on any two positions. The threat matrix approach greatly reduces the required amount of calculations, enabling the program to run on a 32-bit 80 × 86 SCM with a 100 MHz CPU while supporting a recursive algorithms to search plies. Statistics compiled from matches against human game players show that our threat matrix has an average win rate of 92% with no time limit, 95% with a time limit of 10 s, and 98% with a time limit of 5 s. Furthermore, the threat matrix can reduce the computation cost by nearly 90% compared to real-time computing; memory consumption drops and is stable, which increases the evaluation speed by 58% compared to real-time computing.
The Role of Crypto Trading in the Economy, Renewable Energy Consumption and Ecological Degradation
Authors: Miśkiewicz Radosław , Matan Krzysztof , Karnowski Jakub
Published: May 2022

The rapid growth of information technology and industrial revolutions provoked digital transformation of all sectors, from the government to households. Moreover, digital transformations led to the development of cryptocurrency. However, crypto trading provokes a dilemma loop. On the one hand, crypto trading led to economic development, which allowed attracting additional resources to extending smart and green technologies for de-carbonising the economic growth. On the other hand, crypto trading led to intensifying energy sources, which provoked an increase in greenhouse gas emissions and environmental degradation. The paper aims to analyse the connections between crypto trading, economic development of the country, renewable energy consumption, and environmental degradation. The data for analysis were obtained from: Our World in Data, World Data Bank, Eurostat, Ukrstat, Crystal Blockchain, and KOF Globalisation Index. To check the hypothesis, the paper applied the Pedroni and Kao panel cointegration tests, FMOLS and DOLS panel cointegration models, and Vector Error Correction Models. The findings concluded that the increasing crypto trading led to enhanced GDP, real gross fixed capital formation, and globalisation. However, in the long run, the relationship between crypto trading and the share of renewable energies in total energy consumption was not confirmed by the empirical results. For further directions, it is necessary to analyse the impact of crypto trading on land and water pollution.
CFD Modeling of Thermoacoustic Energy Conversion: A Review
Authors: Di Meglio Armando , Massarotti Nicola
Published: May 2022

In this article, a comprehensive review of the computational fluid dynamics (CFD)-based modeling approach for thermoacoustic energy conversion devices is proposed. Although thermoacoustic phenomena were discovered two centuries ago, only in recent decades have such thermoacoustic devices been spreading for energy conversion. The limited understanding of thermoacoustic nonlinearities is one of the reasons limiting their diffusion. CFD is a powerful tool that allows taking into consideration all the nonlinear phenomena neglected by linear theory, on which standard designs are based, to develop energy devices that are increasingly efficient. Starting from a description of all possible numerical models to highlight the difference from a full CFD method, the nonlinearities (dynamic, fluid dynamic and acoustic) are discussed from a physical and modeling point of view. The articles found in the literature were analyzed according to their setup, with either a single thermoacoustic core (TAC) or a full device. With regard to the full devices, a further distinction was made between those models solved at the microscopic scale and those involving a macroscopic porous media approach to model the thermoacoustic core. This review shows that there is no nonlinear porous media model that can be applied to the stack, regenerator and heat exchangers of all thermoacoustic devices in oscillating flows for each frequency, and that the eventual choice of turbulence model requires further studies.
In-Depth Assessment and Optimized Actuation Method of a Novel Solar-Driven Thermomechanical Actuator via Shape Memory Alloy
Authors: Almadani Ibrahim Khalil , Osman Ibrahim Sufian , Hariri Nasir Ghazi
Published: May 2022

Currently, energy demand is more significant than ever due to population growth and advances in recent technologies. In order to supply more energy while maintaining a healthy environment, renewable energy resources are employed. This paper proposes a novel solar-driven shape memory alloy thermomechanical actuator as an eco-friendly solution for solar thermal applications. The proposed actuator was assessed numerically and experimentally. The numerical tests showed that the designed actuation mechanism’s inner temperature has a minimum variation per day of about 14 °C and a temperature variation of 19 °C for most days of the year, which allows for proper activation and deactivation of the actuator. As for the experimental tests, the presented actuation mechanism achieved a bi-directional force of over 150 N, where the inner temperatures of the actuator were recorded at about 70.5 °C while pushing forces and 28.9 °C while pulling forces. Additionally, a displacement of about 127 mm was achieved as the internal temperature of the actuator reached 70.4 °C. The work presented adds to the body of knowledge of a novel solar-based self-driven actuation mechanism that facilitates various applications for solar thermal systems.
A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks
Authors: Kothona Despoina , Bouhouras Aggelos
Published: May 2022

The topic of power loss reduction in distribution systems has gained significant attention over recent years. Despite the efforts of the European Union towards the minimization of power losses, the decarbonization of the transport sector has raised several concerns, since charging overlaps of Electric Vehicles (EVs) can cause extensive power losses and power quality issues. Considering these, the present paper proposes a two-stage EV charging planning and Network Reconfiguration (NR) methodology, addressing the problem of power loss minimization in both Low-Voltage (LV) and Medium-Voltage (MV) Distribution Networks (DNs), respectively. In the first stage, considering the key role of the aggregator, the EV charging planning is applied to LV DN. In the second stage, the NR technique is applied to the MV DN, by taking into account the hourly power demand of LV DNs as obtained by the aggregators. The proposed methodology has been applied on a benchmarked MV network for which each node is represented by a real LV network. The results indicate that the proposed methodology could yield up to a 63.64% power loss reduction, in respect to the base scenario, i.e., no charging planning and no NR are applied.
Impact of COVID-19 Response Measures on Electricity Sector in Jordan
Authors: Malkawi Salaheddin , Kiwan Suhil , Alzghoul Sajedah
Published: May 2022

With the wide spread of new variants of coronavirus that cause the infectious disease COVID-19, governments around the world typically respond by imposing restrictions on people’s activities that range from partial to full lockdowns. This has severe implications on all economic activities, which is manifested by the changes in energy demand. In this study, the impact of COVID-19 on the electricity sector in Jordan is analysed through quantifying the strictness of the government response measures to contain the spread of the pandemic, as calculated by the stringency index, with the electricity demand by the different sectors. Results showed that the minimum peak load in 2020 decreased by 13% as compared to that of 2019. The most affected sectors were the domestic sector, whose share in consumption increased by 8%, and the commercial and hotel sector, whose share decreased by 19%. The concept of an energy-weighted stringency index was introduced to account for the impact of government response measures on the different sectors. The analysis was applied for all Jordan as well as for the three electricity distribution regions. Results also showed that despite measures taken to contain spread of the pandemic, the share of electricity generation by renewables increased from 15% in 2019 to 24% in 2020.
Experimental and Numerical Research on Temperature Evolution during the Fast-Filling Process of a Type III Hydrogen Tank
Authors: Zhao Bin , Wei Huan , Peng Xueyuan , Feng Jianmei , Jia Xiaohan
Published: May 2022

The temperature rises hydrogen tanks during the fast-filling process could threaten the safety of the hydrogen fuel cell vehicle. In this paper, a 2D axisymmetric model of a type III hydrogen for the bus was built to investigate the temperature evolution during the fast-filling process. A test rig was carried out to validate the numerical model with air. It was found significant temperature rise occurred during the filling process, despite the temperature of the filling air being cooled down due to the throttling effect. After verification, the 2D model of the hydrogen tank was employed to study the temperature distribution and evolution of hydrogen during the fast-filling process. Thermal stratification was observed along the axial direction of the tank. Then, the effects of filling parameters were examined, and a formula was fitted to predict the final temperature based on the simulated results. At last, an effort was paid on trying the improve the temperature distribution by increasing the injector length of the hydrogen tank. The results showed the maximal temperature and mass averaged temperature decreased by 2 K and 3.4 K with the length of the injector increased from 50 mm to 250 mm.
Reservoir Interpretation of Intrusive Rock Buried-Hill with Mud-Logging Data while Drilling—Taking the Y Area in the Qiongdongnan Basin of the South China Sea as an Example
Authors: Qu Xuejiao , Zhu Chaobin , Chen Xianjun , Chen Pei , Tan Bing , Xiong Yixue , Guo Shusheng , Jiang Nan
Published: May 2022

The intrusive rock buried-hill reservoir is one of the main targets for oil and gas exploration in the offshore sedimentary basins of China. In order to discover the reservoir as early as possible for decision-making to save costs, reservoir interpretation with mud-logging data needs to be studied. Previous studies have showed that the homogeneity rocks reservoir can be well interpreted with mud-logging data u the Kb (mechanical specific energy ratio) method and the WL (tangential power)-WH (vertical power) intersection method. However, reservoir interpretation with mud-logging data for intrusive rock buried-hill has not been reported. The key steps or parameters of these two kinds of methods used for reservoir interpretation need to be modified for the vertical variation of intrusive rock buried-hill. Furthermore, confirming the interpretation of these two kinds of methods has not been reported. Taking the Y area in the Qiongdongnan Basin of the South China Sea as an example, the intrusive rock buried-hill can be divided into four zones based on its characteristics and genesis in descending order: the sand–gravel weathering zone, the weathering fracture zone, the inner fracture zone, and the base rock zone. The reservoir can be well interpreted when taking the MSE (mechanical specific energy) geometrical mean of the base rock zone as a basic value to calculate Kb. The reservoir will also be well interpreted when WH ranges from 0 to 4.5 MPa and WL ranges from 0 to 99 MPa in the column while intersecting. The layers of the reservoir can be interpreted as Kb < 1 in the sand–gravel weathering zone and the weathering fracture zone. The Kb < 1 and effective intersection of WL-WH layers at the same time could be interpreted as a reservoir in the inner fracture zone and the base rock zone. After combining the Kb method with the WL-WH intersection method, the reservoir of intrusive rock buried-hill can be well interpreted. The total thickness of the uninterpretable reservoir ratio is less than 20% compared to reservoir interpretation with well-logging for each well.
Decentralized Coordination Dispatch Model Based on Chaotic Mutation Harris Hawks Optimization Algorithm
Authors: Wang Yuanyuan , Yu Zexu , Dou Zhenhai , Qiao Mengmeng , Zhao Ye , Xie Ruishuo , Liu Lianxin
Published: May 2022

Aiming at the economic dispatch problem for an interconnected system with wind power integration, and in order to realize the goals of system economy and improvement of the cross-regional consumption level of wind energy, a decentralized coordination dispatch model is established in this paper. In this model, a DC tie-line is cut by the branch cutting method and used as a coupling variable. A virtual upper-level dispatch center is established, and the economic dispatch problem to be solved is decomposed into a master optimization problem for the upper-level dispatch center and subsidiary optimization problems for the lower-level dispatch centers. For solving this model, an improved Harris hawks optimization (HHO) algorithm called the chaotic mutation Harris hawks optimization (CMHHO) algorithm is proposed. In the CMHHO algorithm, tent mapping and the “DE/pbad-to-pbest/1” strategy are introduced, and a new nonlinear escape energy factor adjustment is proposed. Through an algorithm comparison experiment and a simulation experiment with two examples, the superiority of the CMHHO algorithm, the effectiveness of the proposed model and the applicability of the CMHHO algorithm to the proposed model are verified. The model proposed is of great significance for solving the economic dispatch problem for an interconnected system with wind power integration.
Heritable and Climatic Sources of Variation in Juvenile Tree Growth in an Austrian Common Garden Experiment of Central European Norway Spruce Populations
Authors: Morales Laura , Swarts Kelly
Published: May 2022

We leveraged publicly available data on juvenile tree height of 299 Central European Norway spruce populations grown in a common garden experiment across 24 diverse trial locations in Austria and weather data from the trial locations and population provenances to parse the heritable and climatic components of juvenile tree height variation. Principal component analysis of geospatial and weather variables demonstrated high interannual variation among trial environments, largely driven by differences in precipitation, and separation of population provenances based on altitude, temperature, and snowfall. Tree height was highly heritable and modeling the covariance between populations and trial environments based on climatic data led to more stable estimation of heritability and population × environment variance. Climatic similarity among population provenances was highly predictive of population × environment estimates for tree height.
The Influence of the Provenance and Spatial Structure on the Growth of European Silver Fir (Abies alba Mill.) of Autochthonous Origin in a Forest Plantation in the Białowieża Forest
Authors: Marozau Aleh , Kotszan Uladzimir , Nowakowska Justyna , Berezovska Daria , Moser Warren Keith , Hsiang Tom , Oszako Tomasz
Published: May 2022

Currently, a change in the species composition of the Białowieża Forest, eastern Poland, is occurring. Parallel to the dying of spruce (Picea abies L. Karst.), caused by Ips typographus (L.), there is a spread of deciduous tree species, among which hornbeam (Carpinus betulus L.) is the most active. Against the background of climate change, it is of interest to consider the possibility of reintroducing relict species in areas occupied until recently by spruce. One of these is silver fir (Abies alba Mill.), which is biologically and ecologically very similar to spruce. The Tisovik tract (the Belarusian part of the Białowieża Forest) is the most northeastern and the only preserved refuge of autochthonous silver fir in the region. Therefore, it is the most suitable source of propagation of this species outside the mountainous part of its range. The target area of our study was a 26-year old artificial stand included in the information system of forest genetic resources conserved in Europe. It was created in 1996 in the Polish part of the Białowieża Forest in the Hajnówka Forest District (Forestry Wilczy Jar) from 10 half-sib families originating from seeds collected in the Tisovik tract. The goal of the study was to assess the influence of provenance factors and spatial structure on productivity and phenotypic variation as measured by diameter (DBH). The study’s initial results showed that the provenance factor’s influence at the pole wood stage manifests itself more clearly than spatial structure. Even within the framework of individual half-sibs, there was a clear differentiation of diameters between investigated trees. Interpretation of the obtained results allowed us to conclude that there is a “threshold value” of the distance between trees in a stand of a given age, which determines the point when its increase no longer contributes to an increase in DBH. The most promising phenotypes were selected for further research and practical actions to reproduce silver fir further.
The Response and Survival Mechanisms of Staphylococcus aureus under High Salinity Stress in Salted Foods
Authors: Feng Ying , Ming Tinghong , Zhou Jun , Lu Chenyang , Wang Rixin , Su Xiurong
Published: May 2022

Staphylococcus aureus (S. aureus) has a strong tolerance to high salt stress. It is a major reason as to why the contamination of S. aureus in salted food cannot be eradicated. To elucidate its response and survival mechanisms, changes in the morphology, biofilm formation, virulence, transcriptome, and metabolome of S. aureus were investigated. IsaA positively regulates and participates in the formation of biofilm. Virulence was downregulated to reduce the depletion of nonessential cellular functions. Inositol phosphate metabolism was downregulated to reduce the conversion of functional molecules. The MtsABC transport system was downregulated to reduce ion transport and signaling. Aminoacyl-tRNA biosynthesis was upregulated to improve cellular homeostasis. The betaine biosynthesis pathway was upregulated to protect the active structure of proteins and nucleic acids. Within a 10% NaCl concentration, the L-proline content was upregulated to increase osmotic stability. In addition, 20 hub genes were identified through an interaction analysis. The findings provide theoretical support for the prevention and control of salt-tolerant bacteria in salted foods.
Astragalin and Isoquercitrin Isolated from Aster scaber Suppress LPS-Induced Neuroinflammatory Responses in Microglia and Mice
Authors: Kim Eun Hae , Shim Youn Young , Lee Hye In , Lee Sanghyun , Reaney Martin J. T. , Chung Mi Ja
Published: May 2022

The current study investigated the anti-neuroinflammatory effects and mechanisms of astragalin (Ast) and isoquercitrin (Que) isolated from chamchwi (Aster scaber Thunb.) in the lipopolysaccharide (LPS)-activated microglia and hippocampus of LPS induced mice. LPS induced increased cytotoxicity, nitric oxide (NO) production, antioxidant activity, reactive oxygen species (ROS), inducible nitric oxide synthase (iNOS) expression, the release of pro-inflammatory cytokines, protein kinase B phosphorylation, and mitogen-activated protein kinases (MAPK) phosphorylation in LPS-treated microglial cells. Intraperitoneal injection of LPS also induced neuroinflammatory effects in the murine hippocampus. Ast and Que significantly reduced LPS-induced production of NO, iNOS, and pro-inflammatory cytokines in the microglia and hippocampus of mice. Therefore, anti-inflammatory effects on MAPK signaling pathways mediate microglial cell and hippocampus inflammation. In LPS-activated microglia and hippocampus of LPS-induced mice, Ast or Que inhibited MAPK kinase phosphorylation by extracellular signal-regulated kinase, c-Jun N-terminal kinase, and p38 signaling proteins. Ast and Que inhibited LPS-induced ROS generation in microglia and increased 1,1-diphenyl-2-picrylhydrazyl radical scavenging. In addition, LPS treatment increased the heme oxygenase-1 level, which was further elevated after Ast or Que treatments. Ast and Que exert anti-neuroinflammatory activity by down-regulation of MAPKs signaling pathways in LPS-activated microglia and hippocampus of mice.
Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy
Authors: Klein Daniel , Breuch René , Reinmüller Jessica , Engelhard Carsten , Kaul Peter
Published: May 2022

As the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but they are exposed to a variety of stress factors, such as temperature differences, there is a demand for a method that can take these stress factors and the associated reactions of the bacteria into account. Therefore, bacterial stress reactions to lifetime conditions (regular treatment, 25 °C, HCl, 2-propanol, NaOH) and sampling conditions (cold sampling, desiccation, heat drying) were induced to explore the effects on Raman spectra in order to improve the chemometric models. As a result, in this study nine food-relevant bacteria were exposed to seven stress conditions in addition to routine cultivation as a control. Spectral alterations in lipids, polysaccharides, nucleic acids, and proteins were observed when compared to normal growth circumstances without stresses. Regardless of the involvement of several stress factors and storage times, a model for differentiating the analyzed microorganisms from genus down to strain level was developed. Classification of the independent training dataset at genus and species level for Escherichia coli and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%.
Dispersive Liquid-Liquid Microextraction Followed by HS-SPME for the Determination of Flavor Enhancers in Seafood Using GC-MS
Authors: Luo Xiaolin , Wang Xiaoyuan , Du Ming , Xu Xianbing
Published: May 2022

The determination of flavor compounds using headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–mass spectrometry (GC-MS) can be severely interfered with by complex food matrices in food systems, especially solid samples. In this study, dispersive liquid-liquid microextraction (DLLME) was applied prior to HS-SPME to efficiently reduce the matrix effect in solid seafood samples. The method had high sensitivity (the quantification limits of maltol and ethyl maltol were 15 and 5 μg/kg, respectively), an excellent linear relationship (R2 ≥ 0.996), and the sample recovery rate was 89.0–118.6%. The relative standard deviation (RSD %) values for maltol and ethyl maltol were lower than 10%. Maltol (from 0.7 to 2.2 μg/g) and ethyl maltol (from 0.9 to 34.7 μg/g) in seafood were detected in the selected samples by the developed method. Finally, DLLME coupled with HS-SPME effectively removed the influence of sample matrix and improved the sensitivity of the method. The developed method was applicable in the analysis of flavor enhancers in complex matrix foods.
Analysis of Related Metabolites Affecting Taste Values in Rice under Different Nitrogen Fertilizer Amounts and Planting Densities
Authors: Xiong Qiangqiang , Sun Changhui , Shi Hong , Cai Shuo , Xie Hengwang , Liu Fangping , Zhu Jinyan
Published: May 2022

The aim of this study was to explore the differences in metabolites related to rice quality formation under different nitrogen (N) fertilizers and planting densities. In this study, Yangnongxiang 28 was used as the experimental material with the following conditions: high nitrogen and low density (HNLD; high nitrogen: 360 kg·hm−2, low density: the row spacing of rice plants was 16 cm × 30 cm), medium nitrogen and medium density (MNMD; medium nitrogen: 270 kg·hm−2, medium density: the row spacing of rice plants was 13 cm × 30 cm), and low nitrogen and high density (LNHD; low nitrogen: 270 kg·hm−2, high density: the row spacing of rice plants was 10 cm × 30 cm). The rice quality indexes, including the processing quality, amylose content, and taste value, were compared under different treatments, and we analyzed their relationship with the metabolites. The results show that the milled rice rate of HNLD was 13.85% and was 1.89% higher than that of LNHD and MNMD, respectively. The head milled rice rate of HNLD was 32.45% and 6.39% higher than that of LNHD and MNMD, respectively. The milled rice rate and head milled rice rate of HNLD and MNMD were significantly higher than those of LNHD. This study identified 22 differential metabolites (DMs) in HNLD and LNHD, 38 DMs in HNLD and MNMD, and 23 DMs in LNHD and MNMD. Most of the identified differential metabolites were lipid metabolites, which were mainly enriched in the lipid metabolic pathways and amino acid metabolic pathways. The correlation analysis showed that the lipid metabolite physapubescin was significantly negatively correlated with the taste value. The lipid metabolites 2-undecen-1-ol, lucidenic acid F, and 8-deoxy-11,13-dihydroxygrosheimin were significantly positively correlated with the taste value. Lipids may be important substances that lead to differences in taste under different nitrogen fertilizer and density treatments.
Ensemble FARIMA Prediction with Stable Infinite Variance Innovations for Supermarket Energy Consumption
Authors: Wang Jing , Liu Yi , Wu Haiyan , Lu Shan , Zhou Meng
Published: May 2022

This paper concerns a fractional modeling and prediction method directly oriented toward an industrial time series with obvious non-Gaussian features. The hidden long-range dependence and the multifractal property are extracted to determine the fractional order. A fractional autoregressive integrated moving average model (FARIMA) is then proposed considering innovations with stable infinite variance. The existence and convergence of the model solutions are discussed in depth. Ensemble learning with an autoregressive moving average model (ARMA) is used to further improve upon accuracy and generalization. The proposed method is used to predict the energy consumption in a real cooling system, and superior prediction results are obtained.
A Bi-Geometric Fractional Model for the Treatment of Cancer Using Radiotherapy
Authors: Momenzadeh Mohammad , Obi Olivia Ada , Hincal Evren
Published: May 2022

Our study is based on the modification of a well-known predator-prey equation, or the Lotka–Volterra competition model. That is, a system of differential equations was established for the population of healthy and cancerous cells within the tumor tissue of a patient struggling with cancer. Besides, fractional differentiation remedies the situation by obtaining a meticulous model with more flexible parameters. Furthermore, a specific type of non-Newtonian calculus, bi-geometric calculus, can describe the model in terms of proportions and implies the alternative aspect of a dynamic system. Moreover, fractional operators in bi-geometric calculus are formulated in terms of Hadamard fractional operators. In this article, the development of fractional operators in non-Newtonian calculus was investigated. The model was extended in these criteria, and the existence and uniqueness of the model were considered and guaranteed in the first step by applying the Arzelà–Ascoli. The bi-geometric analogue of the numerical method provided a suitable tool to solve the model approximately. In the end, the visual graphs were obtained by using the MATLAB program.
A High-Quality Genome Assembly of Striped Catfish (Pangasianodon hypophthalmus) Based on Highly Accurate Long-Read HiFi Sequencing Data
Authors: Hai Dao Minh , Yen Duong Thuy , Liem Pham Thanh , Tam Bui Minh , Huong Do Thi Thanh , Hang Bui Thi Bich , Hieu Dang Quang , Garigliany Mutien-Marie , Coppieters Wouter , Kestemont Patrick , Phuong Nguyen Thanh , Farnir Frédéric
Published: May 2022

The HiFi sequencing technology yields highly accurate long-read data with accuracies greater than 99.9% that can be used to improve results for complex applications such as genome assembly. Our study presents a high-quality chromosome-scale genome assembly of striped catfish (Pangasianodon hypophthalmus), a commercially important species cultured mainly in Vietnam, integrating HiFi reads and Hi-C data. A 788.4 Mb genome containing 381 scaffolds with an N50 length of 21.8 Mb has been obtained from HiFi reads. These scaffolds have been further ordered and clustered into 30 chromosome groups, ranging from 1.4 to 57.6 Mb, based on Hi-C data. The present updated assembly has a contig N50 of 14.7 Mb, representing a 245-fold and 4.2-fold improvement over the previous Illumina and Illumina-Nanopore-Hi-C based version, respectively. In addition, the proportion of repeat elements and BUSCO genes identified in our genome is remarkably higher than in the two previously released striped catfish genomes. These results highlight the power of using HiFi reads to assemble the highly repetitive regions and to improve the quality of genome assembly. The updated, high-quality genome assembled in this work will provide a valuable genomic resource for future population genetics, conservation biology and selective breeding studies of striped catfish.
The Impact of SKP2 Gene Expression in Chronic Myeloid Leukemia
Authors: Hodeib Hossam , Abd EL Hai Dina , Tawfik Mohamed A. , Allam Alzahraa A. , Selim Ahmed F. , Sarhan Mohamed E. , Selim Amal , Sabry Nesreen M. , Mansour Wael , Youssef Amira
Published: May 2022

Introduction: The prognosis of chronic myeloid leukemia (CML) patients has been dramatically improved with the introduction of imatinib (IM), the first tyrosine kinase inhibitor (TKI). TKI resistance is a serious problem in IM-based therapy. The human S-phase kinase-associated protein 2 (SKP2) gene may play an essential role in the genesis and progression of CML. Aim of the study: We try to explore the diagnostic/prognostic impact of SKP2 gene expression to predict treatment response in first-line IM-treated CML patients at an early response stage. Patients and methods: The gene expression and protein levels of SKP2 were determined using quantitative RT-PCR and ELISA in 100 newly diagnosed CML patients and 100 healthy subjects. Results: SKP2 gene expression and SKP2 protein levels were significantly upregulated in CML patients compared to the control group. The receiver operating characteristic (ROC) analysis for the SKP2 gene expression level, which that differentiated the CML patients from the healthy subjects, yielded a sensitivity of 86.0% and a specificity of 82.0%, with an area under the curve (AUC) of 0.958 (p < 0.001). The ROC analysis for the SKP2 gene expression level, which differentiated optimally from the warning/failure responses, yielded a sensitivity of 70.59% and a specificity of 71.21%, with an AUC of 0.815 (p < 0.001). Conclusion: The SKP2 gene could be an additional diagnostic and an independent prognostic marker for predicting treatment responses in first-line IM-treated CML patients at an early time point (3 months).