bluuebunny/crossref_metadata_2025 huggingface dataset:
Achieving Learning Outcomes of Emergency Remote Learning to Sustain Higher Education during Crises: An Empirical Study of Malaysian Undergraduates
Authors: Looi Kim Hoe , Wye Chung-Khain , Abdul Bahri Elya Nabila
Published: January 2022

The sudden switch to emergency remote learning during the COVID-19 pandemic posed many challenges for learners, but it also provided the opportunity to research these challenges. This study empirically examines the relationships of the contextual challenges of emergency remote learning with future preference for e-learning, as well as moderating effects of learning outcomes on future preference for e-learning of undergraduates during the closure of Higher Education Institutions. Participants were drawn from two universities in Malaysia practising emergency remote learning during the survey period. Underpinned by the literature, the challenges of emergency remote learning and future preference for e-learning were operationalised into items reflective of each factor. In total, 352 valid responses were collected via a self-administered questionnaire hosted on Google Forms, and responses were analysed with Eviews statistical software. In this study, the significant challenges associated with future preference for e-learning, in descending order, were disadvantages (negative), learning outcomes, and advantages. Additionally, the interaction between learning outcomes and disadvantages has a positive relationship, reversing the original negative relationship of disadvantages with future preference for e-learning. Sustainability of higher education in times of crisis is critical. This study provides valuable insights concerning the importance of achieving learning outcomes in order to support sustainable higher education using emergency remote learning during similar future crises.
Economic Valuation of Improving Environmental Degradations in Korea Using Choice Experiment
Authors: Kim Hyun-ju , Lee Yoon
Published: January 2022

This study aims to quantitatively identify the economic value of the comprehensive improvement of environmental degradations caused by climate change. The research method applied to that is the choice experiment. Fine particulate matter, algae bloom, and heat waves were selected as individual attributes constituting environmental problems. It was found that the willingness to pay could not be induced for any level of improvement in algal bloom. It was concluded that if heat waves improved to the medium level where the number of heat-related illnesses and estimated deaths decreased by 50% compared to the current level, there would be a loss in value by USD 13.33. The value of improving environmental problems is USD 7.69 per household per year, and the improvement of fine particulate matter was the highest value attributed by consumers. This study is significant in that it comprehensively evaluates severe environmental problems, reflects their priorities and importance, and assesses the value for each level. It provides important foundational data for establishing effective budget input strategies to maximize consumer benefits and aids in the preparation of effective policies by establishing more detailed goals to achieve net-zero carbon emissions and the Sustainable Development Goals.
Oil Spill Governance: Evidence from Bintan Island, Indonesia
Authors: Purnaweni Hartuti , Saputra Jumadil , Roziqin Ali , Kismartini Kismartini , Djumiarti Titik , Seitz Thomas
Published: January 2022

Issues of oil spills in various locations worldwide have been widely published in several studies. However, studies on policy management and strategies for handling cases related to oil spills are still limited. As one of the largest oil-producing countries with international shipping traffic, Indonesia is vulnerable to oil spills. Therefore, by drawing upon evidence from Bintan Island, this study aims to provide recommendations for stakeholders concerning governance and policy to address the oil spill case, which has had adverse social, economic, and environmental impacts. Data were collected from semi-structured interviews, focus group discussion, observation, actual online news, and official government reports using a case study approach. The result indicates that the local government is slow in responding to Bintan Island’s reoccurring yearly oil spillage. Policy responses are still focused on repressive and conventional methods. Hence, preventive and multi-stakeholder governance is required to handle oil spills. Furthermore, this study provides an overview of the oil spill problem and its management strategy in developing countries, especially Indonesia.
Detection of the Seasonally Activated Rural Areas
Authors: Drobnjaković Marija , Panić Milena , Stanojević Gorica , Doljak Dejan , Kokotović Kanazir Vlasta
Published: January 2022

Rural areas have been usually observed through agriculture; however, today, it is broadened with various activities. In Serbia, it has been characterized by unbalanced development, which has led to a declining vitality and depopulation. The main goal of this research is detection of seasonally activated rural areas in Serbia, expressed through the population fluctuation, temporary settlement, or occasional use of residential and economic facilities, and identification of spatial patterns of seasonal use. This research applied an innovative proxy—nighttime lights (NTL)—as a complementary tool to statistical analyses, which are conducted in the GIS environment. The calculation encompassed two seasonality coefficients: one based on the NTL and the second based on statistical data on tourist turnover. The spatial frame applies settlement level and micro level (pixels), while temporal includes monthly values for the period 2015–2019. The obtained results highlight tourist activity as the main cause of seasonal activation of rural areas. The largest seasonal fluctuations were registered in mountain areas and spa resorts. For mountain areas, the highest seasonality is in the winter months (peak—January/February), and lowest is in the summer season. The seasonal character of spa centers indicates the similar trend, generally less pronounced (peak—January), however, with higher seasonality during the summer.
Towards a Sustainable Bioeconomy through Industrial Symbiosis: Current Situation and Perspectives
Authors: Bijon Nicolas , Wassenaar Tom , Junqua Guillaume , Dechesne Magali
Published: January 2022

The concepts of industrial symbiosis (IS) and bioeconomy (BE) both focus on ways to reduce dependence on non-renewable resources. However, these two frames of reference have rarely been considered as part of a joint strategy to achieve sustainability. Here, we describe how they inter-operate, in well documented IS case studies, to identify current synergy patterns of organic by-products, their limits, and promising pathways towards integrated initiatives that pursue the respective goals of each framework. We first evaluated the nature of synergies in current practices, and how they contribute to sustainability. Second, we focused on the role of agriculture in these symbioses, due to its fundamental role in circular bioeconomy. We used three main dimensions to analyze our case studies: IS emergence, governance of synergies, and actor serendipity. We identified three main patterns of organic matter use within IS, which we termed metabolic resources, metabolic biorefinery, and global biorefinery. Our observations suggest that synergies with agriculture are undervalued, by both internal and external practitioners. We conclude that while the combination of BE and IS can bolster sustainability, it requires a dedicated implementation strategy that has yet to be conceived.
Women’s Perceptions and Attitudes to Household Air Pollution Exposure and Capability to Change Cooking Behaviours in Urban Rwanda
Authors: Woolley Katherine E. , Bartington Suzanne E. , Thomas G. Neil , Pope Francis D. , Muhizi Aldo , Mugabe Claude , Ahishakiye Omar , Kabera Telesphore , Greenfield Sheila M.
Published: January 2022

Household air pollution (HAP) from cooking on biomass fuel presents significant health, environmental and socioeconomic consequences worldwide. However, there is a lack of understanding of the factors influencing cooking behaviours that affect HAP exposure in Rwanda (e.g., cooking location, removing children from the cooking area). Sixteen qualitative in-depth interviews were undertaken with women living in an underprivileged neighbourhood in Kigali, Rwanda. Deductive thematic analysis was carried out using the Behaviour Change Wheel (Capability—ability to engage with chosen activity, Opportunity—factors which are beyond the individual’s control and Motivation—brain processes which direct behaviour: COM-B) to determine the thoughts and perceptions around cooking location and removing children from the cooking area. Facilitators and barriers were subsequently identified within the COM-B framework for the following HAP mitigation interventions: outdoor cooking, removing children from the cooking area and Liquid Petroleum Gas (LPG) use. Of the 16 interviewed, 12 cooked outdoors (75%), two (12.5%) cooked indoors (in the main home) and two (12.5%) in a separate kitchen. Despite the majority cooking outdoors, this was reported not to be a favourable cooking location. Levels of awareness of HAP sources and knowledge of the health effects of air pollution were observed to be limited, reducing women’s capability to change, along with stated barriers of cost, housing constraints and safety. Factors out of the individuals’ control (opportunities) included weather, socio-economic and educational factors. Preconceived beliefs, experiencing smoke reduction and the briefly described short-term health effects, directed motivation. Furthermore, participants identified a need for community-based education as a facilitator to changing their behaviour. Despite a high level of observed motivation towards reducing HAP exposure, many women lacked the capability and opportunity to change their behaviour. There are research and policy implications concerning development of community-based interventions which involved end-users and relevant stakeholders in the development process.
Short-Term Effects of Reclamation of Aquaculture Ponds to Paddy Fields on Soil Chemical Properties and Bacterial Communities in Eastern China Coastal Zone
Authors: Hu Anyong , Lv Min , Jiang Shumiao , Xu Lingyi , Guo Shiyang , Zhao Na , Zheng Manman , Liu Bo , Li Jinbiao
Published: January 2022

Large areas of tidal flats were previously developed into aquaculture ponds and were recently encouraged to be converted into paddy fields to fulfill food and economic needs in China. However, the influences of short-term rice cultivation at the reclaimed aquaculture ponds on soil chemical properties and bacterial communities are poorly understood. To address this issue, we collected mineral soil samples at 0–20 and 20–40 cm depths from non-cultivated soils and paddy fields after being reclaimed from aquaculture ponds in Nantong, China, and identified soil bacterial communities using high-throughput sequencing. The results suggested that rice cultivation significantly increased the accumulation of total soil carbon (TC) and dissolved organic carbon (WSOC). The pH, ammonium (NH4+), nitrate (NO3−) and available phosphorus (AP) varied with the reclamation duration but did not show a unanimous tendency. Proteobacteria, Acidobacteria, Bacteroidetes, Chloroflexi and Planctomycetes dominated the bacterial community in both non-cultivated and cultivated soils after reclamation regardless of cultivation ages and soil depth. The variations in the diversity and composition of the soil microbial community were mainly associated with electrical conductivity (EC), WSOC, TC, NH4+ and NO3− in non-cultivated and cultivated lands. Here, we found that short-term rice cultivation at the reclaimed aquaculture ponds strongly influenced soil bacterial communities and chemical properties, especially in the 0–20 cm depth, in the coastal regions.
6+: A Novel Approach for Building Extraction from a Medium Resolution Multi-Spectral Satellite
Authors: Dixit Mayank , Chaurasia Kuldeep , Mishra Vipul Kumar , Singh Dilbag , Lee Heung-No
Published: January 2022

For smart, sustainable cities and urban planning, building extraction through satellite images becomes a crucial activity. It is challenging in the medium spatial resolution. This work proposes a novel methodology named ‘6+’ for improving building extraction in 10 m medium spatial resolution multispectral satellite images. Data resources used are Sentinel-2A satellite images and OpenStreetMap (OSM). The proposed methodology merges the available high-resolution bands, super-resolved Short-Wave InfraRed (SWIR) bands, and an Enhanced Normalized Difference Impervious Surface Index (ENDISI) built-up index-based image to produce enhanced multispectral satellite images that contain additional information on impervious surfaces for improving building extraction results. The proposed methodology produces a novel building extraction dataset named ‘6+’. Another dataset named ‘6 band’ is also prepared for comparison by merging super-resolved bands 11 and 12 along with all the highest spatial resolution bands. The building ground truths are prepared using OSM shapefiles. The models specific for extracting buildings, i.e., BRRNet, JointNet, SegUnet, Dilated-ResUnet, and other Unet based encoder-decoder models with a backbone of various state-of-art image segmentation algorithms, are applied on both datasets. The comparative analyses of all models applied to the ‘6+’ dataset achieve a better performance in terms of F1-Score and Intersection over Union (IoU) than the ‘6 band’ dataset.
Exploring the Evolution and Determinants of Open Innovation: A Perspective from Patent Citations
Authors: Ji Yakun , Yu Xiang , Sun Minghan , Zhang Ben
Published: January 2022

The research of open innovation (OI) has developed considerably in recent years. In this article, a new perspective based on the patent citation network is provided to explore the dynamic evolution and mode of OI. In our framework of the OI network, enterprises are represented as nodes, and patent citations represent cross-organizational knowledge flow, which are ties in the network. The Driver Assistance System (DAS) was selected as the research case. Time-sliced patent citation networks are constructed, and then an exponential random graph model is employed to identify the formation mechanism of OI networks. The results show that the OI network of DAS is still partially open and at a low level. The inherent dominance of automakers may have been weakened, and new models and relationships in innovation activities are developing. In addition, heterogeneity in type and geographic proximity which significantly promote the formation of the open network was prevented, but the larger scale of the enterprise inhibited the OI network. R&D investment has no obvious impact. This research provides a new perspective to observe open innovation and helps stakeholders to better understand industry trends.
Three-Level Reduced Switch AC/DC/AC Power Conversion System for High Voltage Electric Vehicles
Authors: Sadeghi Zahra , Shahparasti Mahdi , Rajaei Amirhossein , Laaksonen Hannu
Published: January 2022

Two of the main challenges of recent electric vehicles (EVs) are the charging time and high initial cost. To solve the problem associated with long charging time, the car manufacturers are moving from 400 V battery EV (BEV) to 800 V BEV, which enables the utilization of multi-level converters in EV applications. This paper presents a power conversion system consisting of a Vienna rectifier and a two/three level hybrid inverter as a machine-side inverter to drive a permanent-magnet synchronous motor (PMSM). The Vienna rectifier improves the quality of the grid-side current and provides a regulated DC-link voltage. The proposed inverter, known as a 10-switch inverter, offers high output current quality with a lower number of active switches, making it compact and cost-effective. The field-oriented control (FOC), along with the SPWM modulation, is implemented to control the system. A reliable and cost-effective PMSM drive system demands sensorless control; therefore, a sliding mode observer (SMO) is used to estimate the rotor position and velocity. The accuracy of the proposed system was proved through the simulation results from MATLAB/Simulink.
Deformation and Mechanical Characteristics of Existing Foundation Pit and Tunnel Itself Caused by Shield Tunnel Undercrossing
Authors: Lou Ping , Li Yonghe , Lu Shide , Xiao Hongbo , Zhang Zhengang
Published: January 2022

This paper establishes a three-dimensional symmetrical shield model to investigate the influence of a double-line shield tunnel undercrossing an existing foundation pit and of changed grouting pressure on the deformation and mechanical characteristics of both the foundation pit and the tunnel itself, and it proposes a method of symmetrical segmented pressure, in which different grouting pressure is applied in different sections of the tunnel. The monitoring data are used to verify the reliability of the model, and the maximum relative error is 5.44%. The numerical results show that the maximum subsidence of the retaining pile and anchor are 3.76 mm and 10.33 mm, respectively, and the maximum tensile stress of the anchor is increased by 32.4%. The subsidence shape of the foundation pit raft is an arch with four corners warping upward and the maximum subsidence difference is 3.17 mm. Uneven subsidence of the tunnel occurs along the longitudinal direction, and large and small subsidences are located at the outside and underpart of the foundation pit, respectively, and the maximum and minimum values are 11.15 mm and 2.13 mm, respectively, and the maximum subsidence difference is 9.02 mm. The deformation and mechanical characteristics of both the foundation pit and the tunnel are significantly decreased by appropriately increasing the grouting pressure, and it is recommended that the grouting pressure should not exceed 300 kPa. The proposed method of segmented pressure can reduce the differential subsidence by 47.2% and the maximum tensile stress by 27.2%, so it can significantly reduce the uneven subsidence of the tunnel and improve the tunnel stress condition. The research results can provide a theoretical basis for the safe construction of shield tunnels under the existing foundation pit.
Acknowledgment to Reviewers of Symmetry in 2021
Authors:   Symmetry Editorial Office
Published: January 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Inhomogeneous Phases in the Chirally Imbalanced 2 + 1-Dimensional Gross-Neveu Model and Their Absence in the Continuum Limit
Authors: Pannullo Laurin , Wagner Marc , Winstel Marc
Published: January 2022

We studied the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing was found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We showed that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.
Symmetry in Functional Equations and Analytic Inequalities II
Authors: Lupas Alina Alb
Published: January 2022

The field of functional equations is an ever-growing branch of mathematics with far-reaching applications; it is increasingly used to investigate problems in mathematical analysis, combinatorics, biology, information theory, statistics, physics, the behavioral sciences, and engineering [...]
Improving the Statistical Qualities of Pseudo Random Number Generators
Authors: Álvarez Rafael , Martínez Francisco , Zamora Antonio
Published: January 2022

Pseudo random and true random sequence generators are important components in many scientific and technical fields, playing a fundamental role in the application of the Monte Carlo methods and stochastic simulation. Unfortunately, the quality of the sequences produced by these generators are not always ideal in terms of randomness for many applications. We present a new nonlinear filter design that improves the output sequences of common pseudo random generators in terms of statistical randomness. Taking inspiration from techniques employed in symmetric ciphers, it is based on four seed-dependent substitution boxes, an evolving internal state register, and the combination of different types of operations with the aim of diffusing nonrandom patterns in the input sequence. For statistical analysis we employ a custom initial battery of tests and well-regarded comprehensive packages such as TestU01 and PractRand. Analysis results show that our proposal achieves excellent randomness characteristics and can even transform nonrandom sources (such as a simple counter generator) into perfectly usable pseudo random sequences. Furthermore, performance is excellent while storage consumption is moderate, enabling its implementation in embedded or low power computational platforms.
The Quest for the Astrophysical Gravitational-Wave Background with Terrestrial Detectors
Authors: Regimbau Tania
Published: January 2022

We present the gravitational-wave background and its properties focusing on the background from compact binary coalescences in terrestrial detectors. We also introduce the standard data analysis method used to search for this background and discuss its detectability with second and third generation networks of detectors. To illustrate, we first use simple models and then discuss more realistic models based on simulations.
Particle Dark Matter Density and Entropy Production in the Early Universe
Authors: Chaudhuri Arnab , Khlopov Maxim Yu. , Porey Shiladitya
Published: January 2022

Dark Matter (DM) density is reduced if entropy production takes place after DM particles abundance is frozen out in the early universe. We study a possibility of such reduction due to entropy production in the electroweak phase transition (EWPT). We compare scenarios of entropy production in the standard model (SM) and its simplest extension, the two-Higgs doublet model (2HDM). Assuming the EWPT is of second order in the SM scenario and the first order in the 2HDM, we calculate the entropy release in these scenarios and the corresponding dilution of preexisting DM density in the early universe. We find the effect of dilution in EWPT significant for confrontation with observations of any form of possible DM (including primordial black holes (PBHs)), which is frozen out, decoupled, frozen in, or formed before EWPT.
A Lévy Distribution Based Searching Scheme for the Discrete Targets in Vast Region
Authors: Lian Zhigang , Luo Dan , Dai Bingrong , Chen Yangquan
Published: January 2022

This paper investigates the Discrete Targets Search Problem, (DTSP), which aims to quickly search for discrete objects scattered in a vast symmetry region. Different from continuous function extremal value search, the discrete points search cannot make use of the properties of regular functions, such as function analytic, single/multiple extreme, and monotonicity. Thus, in this paper a new search scheme based on Lévy random distribution is investigated. In comparison with the TraditionalCarpet search or Random search based on other distributions, DTSP can provide much faster search speed which is demonstrated by simulation with different scales problems for the selected scenarios. The simulations experiment proves that DTSP is faster for searching for a discrete single target or multiple targets in a wide area. It provides a new method for solving the discrete target search problem.
Toward Data Integrity Architecture for Cloud-Based AI Systems
Authors: Witanto Elizabeth Nathania , Oktian Yustus Eko , Lee Sang-Gon
Published: January 2022

AI has been implemented in many sectors such as security, health, finance, national defense, etc. However, together with AI’s groundbreaking improvement, some people exploit AI to do harmful things. In parallel, there is rapid development in cloud computing technology, introducing a cloud-based AI system. Unfortunately, the vulnerabilities in cloud computing will also affect the security of AI services. We observe that compromising the training data integrity means compromising the results in the AI system itself. From this background, we argue that it is essential to keep the data integrity in AI systems. To achieve our goal, we build a data integrity architecture by following the National Institute of Standards and Technology (NIST) cybersecurity framework guidance. We also utilize blockchain technology and smart contracts as a suitable solution to overcome the integrity issue because of its shared and decentralized ledger. Smart contracts are used to automate policy enforcement, keep track of data integrity, and prevent data forgery. First, we analyze the possible vulnerabilities and attacks in AI and cloud environments. Then we draw out our architecture requirements. The final result is that we present five modules in our proposed architecture that fulfilled NIST framework guidance to ensure continuous data integrity provisioning towards secure AI environments.
New Acoustic Features for Synthetic and Replay Spoofing Attack Detection
Authors: Wei Linqiang , Long Yanhua , Wei Haoran , Li Yijie
Published: January 2022

With the rapid development of intelligent speech technologies, automatic speaker verification (ASV) has become one of the most natural and convenient biometric speaker recognition approaches. However, most state-of-the-art ASV systems are vulnerable to spoofing attack techniques, such as speech synthesis, voice conversion, and replay speech. Due to the symmetry distribution characteristic between the genuine (true) speech and spoof (fake) speech pair, the spoofing attack detection is challenging. Many recent research works have been focusing on the ASV anti-spoofing solutions. This work investigates two types of new acoustic features to improve the performance of spoofing attacks. The first features consist of two cepstral coefficients and one LogSpec feature, which are extracted from the linear prediction (LP) residual signals. The second feature is a harmonic and noise subband ratio feature, which can reflect the interaction movement difference of the vocal tract and glottal airflow of the genuine and spoofing speech. The significance of these new features has been investigated in both the t-stochastic neighborhood embedding space and the binary classification modeling space. Experiments on the ASVspoof 2019 database show that the proposed residual features can achieve from 7% to 51.7% relative equal error rate (EER) reduction on the development and evaluation set over the best single system baseline. Furthermore, more than 31.2% relative EER reduction on both the development and evaluation set shows that the proposed new features contain large information complementary to the source acoustic features.
Application of Particle Swarm Optimization with Simulated Annealing in MIT Regularization Image Reconstruction
Authors: Yang Dan , Xu Bin , Xu Bin , Lu Tian , Wang Xu
Published: January 2022

Background and Objectives: Due to the soft-field effect of the electromagnetic field and the limit of detection, image reconstruction of magnetic induction tomography has to recover more complex electrical characteristics from very few signals. These cause a problem which have underdetermination, nonlinearity, and ill-posed characteristics, and therefore lead to many difficulties in finding its solution. Although many regularization image reconstruction methods exist, they are not suitable for MIT applications due to regularization parameter selection. The purpose of this paper is to study the principle of particle swarm optimization with simulated annealing, and to propose a regularization method for reconstruction, which will provide a new way to solve the MIT image problems. Methods and Models: Firstly, the regularization principle of image reconstruction of MIT will be analyzed. Then the hybrid regularization algorithm, including Tikhonov and NOSER regularization, will be developed, using the dimension of the Hessian matrix as a penalty term respecting the prior knowledge. PSO-SA algorithm will be applied to obtain an optimal solution for regularization parameters. Finally, six typical numerical models and approximately symmetrical cerebral hemorrhage models by COMSOL will be carried out, and the voltage signals obtained from the simulation will be used to verify the proposed reconstruction method. Results: Through the simulation results, the proposed imaging method has the average CC values of 0.9932, 0.8286 and the average RE values of 0.4982, 0.8320 for simple and complex models, respectively. Moreover, when the SNR changes from 55 dB to 35 dB, the CC value of the cerebral hemorrhage model reduced by 0.1034. The results demonstrate the effectiveness and high theoretical feasibility of the proposed method in MIT image reconstruction. Conclusions: This study indicates the potential application of PSO-SA algorithm in regularization imaging problem. Compared with traditional regularization imaging methods, the proposed method has the advantages of better accuracy, robustness and noise resistance, showing the certain application value in other similar ill-ness imaging problems.
A Comparison of Bivariate Zero-Inflated Poisson Inverse Gaussian Regression Models with and without Exposure Variables
Authors: Ermawati Ermawati , Purhadi Purhadi , Rahayu Santi Puteri
Published: January 2022

In this paper, we focus on the comparison of the bivariate zero-inflated Poisson inverse Gaussian regression (BZIPIGR) type II model in two cases: with and without exposure variables. The BZIPIGR type II model is applied to analyze the occurrence of maternal and early neonatal mortality in South Sulawesi Province, Indonesia using 2019 data, which contain many zero values and have the issue of overdispersion in the response variable. Furthermore, to analyze the number of deaths in various areas, the exposure variable is considered. The maximum likelihood estimation (MLE) is used in parameter estimation, which involves numerical iteration and application of the Berndt–Hall–Hall–Hausman (BHHH) algorithm. Sum square error (SSE) serves as the criterion of model selection when exposure variables are included. The existence of exposure variables strongly affects the model’s accuracy, especially using the BZIPIGR type II model. According to the SSE and RMSE values, the BZIPIGR type II model with exposure variables performs better than the model without exposure variables in estimating parameter values. All predictors with exposure variables in this study had a significant influence on the number of maternal and early neonatal mortalities.
Variance and Semi-Variances of Regular Interval Type-2 Fuzzy Variables
Authors: Tang Wenjing , Chen Yitao
Published: January 2022

In this paper, we define the variance and semi-variances of regular interval type-2 fuzzy variables (RIT2-FVs) as well as derive a calculation formula of them based on the credibility distribution. Following the relationship between the variance and the semi-variances of the regular symmetric triangular interval type-2 fuzzy variables (RSTIT2-FVs), a special type of interval type-2 fuzzy variable is discovered and proved. Furthermore, for applying the two measures, we propose the operational law for the variance and semi-variances of the linear function of mutually independent RSTIT2-FVs. Some numerical examples are illustrated. The consequences of examples prove that the formulas we proposed can be effectively applied to the calculation of the variance of RSTIT2-FVs. The results indicate that they play a great role in the application of variance of type-2 fuzzy sets in various fields.
An Alternative Low-Cost Embedded NILM System for Household Energy Conservation with a Low Sampling Rate
Authors: Biansoongnern Somchai , Plangklang Boonyang
Published: January 2022

The measurement of the energy consumption of electrical appliances, where the meter is installed at a single point on the main input circuit of the building, is called non-intrusive load monitoring (NILM). The NILM method can distinguish the loads that are currently active and break down how the loads consume electricity. A microcontroller with embedded software was selected to read the data into the NILM method process at a low sampling rate every 1 s or 1 Hz. The measured data and the data obtained by the NILM algorithm were displayed via an internet platform. This article presents an alternative low-cost embedded NILM system for household energy conservation with a low sampling rate, which could identify electrical appliances such as an air conditioner, refrigerator, television, electric kettle, electric iron, microwave oven, rice cooker, and washing machine. Four features of symmetry pattern were extracted, containing information on the value of active power change, the value of reactive power change, the number of intersection points between the active power data and the reference line, and an estimation of an equation for the starting characteristics of the electrical equipment. The proposed NILM system was tested in a selected test house that used a single-phase power system. A typical meter was also installed to compare the results with the proposed NILM. The validity of the tests was checked for 1 month in 3 houses to analyze the results. The proposed method was able to detect 91.3% of total events. The accuracy of the average ability of the system to disaggregate devices was 0.897. The accuracy value for total power consumption was 0.927. The continuous data recording of the NILM method provides information on the behavior of electrical appliances that can be used for maintenance and warnings.
j-Dimensional Integral Involving the Logarithmic and Exponential Functions: Derivation and Evaluation
Authors: Reynolds Robert , Stauffer Allan
Published: January 2022

In the fields of science and engineering, tasks involving repeated integrals appear on occasion. The authors’ study on repeated integrals of a class of exponential and logarithmic functions is presented in this publication. The paper includes several examples that demonstrate the evaluation of the analytical parts of the multi-dimensional integral derived. All the results in this work are new.
Acknowledgment to Reviewers of Tomography in 2021
Authors:   Tomography Editorial Office
Published: January 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
The Effect of Low Doses of Zearalenone (ZEN) on the Bone Marrow Microenvironment and Haematological Parameters of Blood Plasma in Pre-Pubertal Gilts
Authors: Mróz Magdalena , Gajęcka Magdalena , Przybyłowicz Katarzyna E. , Sawicki Tomasz , Lisieska-Żołnierczyk Sylwia , Zielonka Łukasz , Gajęcki Maciej Tadeusz
Published: January 2022

The aim of this study was to determine whether low doses of zearalenone (ZEN) influence the carry-over of ZEN and its metabolites to the bone marrow microenvironment and, consequently, haematological parameters. Pre-pubertal gilts (with a body weight of up to 14.5 kg) were exposed to daily ZEN doses of 5 μg/kg BW (group ZEN5, n = 15), 10 μg/kg BW (group ZEN10, n = 15), 15 μg/kg BW (group ZEN15, n = 15), or were administered a placebo (group C, n = 15) throughout the entire experiment. Bone marrow was sampled on three dates (exposure dates 7, 21, and 42—after slaughter) and blood for haematological analyses was sampled on 10 dates. Significant differences in the analysed haematological parameters (WBC White Blood Cells, MONO—Monocytes, NEUT—Neutrophils, LYMPH—Lymphocytes, LUC—Large Unstained Cells, RBC—Red Blood Cells, HGB—Haemoglobin, HCT—Haematocrit, MCH—Mean Corpuscular Volume, MCHC—Mean Corpuscular Haemoglobin Concentrations, PLT—Platelet Count and MPV—Mean Platelet Volume) were observed between groups. The results of the experiment suggest that exposure to low ZEN doses triggered compensatory and adaptive mechanisms, stimulated the local immune system, promoted eryptosis, intensified mycotoxin biotransformation processes in the liver, and produced negative correlations between mycotoxin concentrations and selected haematological parameters.
Acknowledgment to Reviewers of Universe in 2021
Authors:   Universe Editorial Office
Published: January 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Mapping the Galactic Metallicity Gradient with Open Clusters: The State-of-the-Art and Future Challenges
Authors: Spina Lorenzo , Magrini Laura , Cunha Katia
Published: January 2022

In this paper, we make use of data collected for open cluster members by high-resolution spectroscopic surveys and programmes (i.e., APOGEE, Gaia-ESO, GALAH, OCCASO, and SPA). These data have been homogenised and then analysed as a whole. The resulting catalogue contains [Fe/H] and orbital parameters for 251 Galactic open clusters. The slope of the radial metallicity gradient obtained through 175 open clusters with high-quality metallicity determinations is −0.064 ± 0.007 dex kpc−1. The radial metallicity distribution traced by open clusters flattens beyond RGal = 12.1 ± 1.1 kpc. The slope traced by open clusters in the [Fe/H]-Lz diagram is −0.31 ± 0.02 × 103 dex km−1 kpc−1 s, but it flattens beyond Lz = 2769 ± 177 km kpc s−1. In this paper, we also review some high-priority practical challenges around the study of open clusters that will significantly push our understanding beyond the state-of-the-art. Finally, we compare the shape of the galactic radial metallicity gradient to those of other spiral galaxies.
Statistical Tools for Imaging Atmospheric Cherenkov Telescopes
Authors: D’Amico Giacomo
Published: January 2022

The development of Imaging Atmospheric Cherenkov Telescopes (IACTs) unveiled the sky in the teraelectronvolt regime, initiating the so-called “TeV revolution”, at the beginning of the new millennium. This revolution was also facilitated by the implementation and adaptation of statistical tools for analyzing the shower images collected by these telescopes and inferring the properties of the astrophysical sources that produce such events. Image reconstruction techniques, background discrimination, and signal-detection analyses are just a few of the pioneering studies applied in recent decades in the analysis of IACTs data. This (succinct) review has the intent of summarizing the most common statistical tools that are used for analyzing data collected with IACTs, focusing on their application in the full analysis chain, including references to existing literature for a deeper examination.
A Polyvalent Broad-Spectrum Escherichia Phage Tequatrovirus EP01 Capable of Controlling Salmonella and Escherichia coli Contamination in Foods
Authors: Zhou Yuqing , Li Lei , Han Kaiou , Wang Leping , Cao Yajie , Ma Dongxin , Wang Xiaoye
Published: January 2022

Salmonella and Escherichia coli (E. coli) food contamination could lead to serious foodborne diseases. The gradual increase in the incidence of foodborne disease invokes new and efficient methods to limit food pathogenic microorganism contamination. In this study, a polyvalent broad-spectrum Escherichia phage named Tequatrovirus EP01 was isolated from pig farm sewage. It could lyse both Salmonella Enteritidis (S. Enteritidis) and E. coli and exhibited broad host range. EP01 possessed a short latent period (10 min), a large burst size (80 PFU/cell), and moderate pH stability (4–10) and appropriate thermal tolerance (30–80 °C). Electron microscopy and genome sequence revealed that EP01 belonged to T4-like viruses genus, Myoviridae family. EP01 harbored 12 CDSs associated with receptor-binding proteins and lacked virulence genes and drug resistance genes. We tested the inhibitory effect of EP01 on S. Enteritidis, E. coli O157:H7, E. coli O114:K90 (B90), and E. coli O142:K86 (B) in liquid broth medium (LB). EP01 could significantly reduce the counts of all tested strains compared with phage-free groups. We further examined the effectiveness of EP01 in controlling bacterial contamination in two kinds of foods (meat and milk) contaminated with S. Enteritidis, E. coli O157:H7, E. coli O114:K90 (B90), and E. coli O142:K86 (B), respectively. EP01 significantly reduced the viable counts of all the tested bacteria (2.18–6.55 log10 CFU/sample, p < 0.05). A significant reduction of 6.55 log10 CFU/cm2 (p < 0.001) in bacterial counts on the surface of meat was observed with EP01 treatment. Addition of EP01 at MOI of 1 decreased the counts of bacteria by 4.3 log10 CFU/mL (p < 0.001) in milk. Generally, the inhibitory effect exhibited more stable at 4 °C than that at 28 °C, whereas the opposite results were observed in milk. The antibacterial effects were better at MOI of 1 than that at MOI of 0.001. These results suggests that phage EP01-based method is a promising strategy of controlling Salmonella and Escherichia coli pathogens to limit microbial food contamination.
Visualization of Marek’s Disease Virus Genomes in Living Cells during Lytic Replication and Latency
Authors: Vychodil Tereza , Wight Darren J. , Nascimento Mariana , Jolmes Fabian , Korte Thomas , Herrmann Andreas , Kaufer Benedikt B.
Published: January 2022

Visualization of the herpesvirus genomes during lytic replication and latency is mainly achieved by fluorescence in situ hybridization (FISH). Unfortunately, this technique cannot be used for the real-time detection of viral genome in living cells. To facilitate the visualization of the Marek’s disease virus (MDV) genome during all stages of the virus lifecycle, we took advantage of the well-established tetracycline operator/repressor (TetO/TetR) system. This system consists of a fluorescently labeled TetR (TetR-GFP) that specifically binds to an array of tetO sequences. This tetO repeat array was first inserted into the MDV genome (vTetO). Subsequently, we fused TetR-GFP via a P2a self-cleaving peptide to the C-terminus of the viral interleukin 8 (vIL8), which is expressed during lytic replication and latency. Upon reconstitution of this vTetO-TetR virus, fluorescently labeled replication compartments were detected in the nucleus during lytic replication. After validating the specificity of the observed signal, we used the system to visualize the genesis and mobility of the viral replication compartments. In addition, we assessed the infection of nuclei in syncytia as well as lytic replication and latency in T cells. Taken together, we established a system allowing us to track the MDV genome in living cells that can be applied to many other DNA viruses.
Stephen Oroszlan and Retroviral Proteins
Authors: Rein Alan
Published: January 2022

Stephen Oroszlan received his early education in Hungary, graduating in 1950 from the Technical University in Budapest with a degree in chemical engineering [...]
Transcriptomic Profiling of Mouse Mast Cells upon Pathogenic Avian H5N1 and Pandemic H1N1 Influenza a Virus Infection
Authors: Tang Yuling , Wu Hongping , Huo Caiyun , Zou Shumei , Hu Yanxin , Yang Hanchun
Published: January 2022

Mast cells, widely residing in connective tissues and on mucosal surfaces, play significant roles in battling against influenza A viruses. To gain further insights into the host cellular responses of mouse mast cells with influenza A virus infection, such as the highly pathogenic avian influenza A virus H5N1 and the human pandemic influenza A H1N1, we employed high-throughput RNA sequencing to identify differentially expressed genes (DEGs) and related signaling pathways. Our data revealed that H1N1-infected mouse mast P815 cells presented more up- and down-regulated genes compared with H5N1-infected cells. Gene ontology analysis showed that the up-regulated genes in H1N1 infection were enriched for more degranulation-related cellular component terms and immune recognition-related molecular functions terms, while the up-regulated genes in H5N1 infection were enriched for more immune-response-related biological processes. Network enrichment of the KEGG pathway analysis showed that DEGs in H1N1 infection were specifically enriched for the FoxO and autophagy pathways. In contrast, DEGs in H5N1 infection were specifically enriched for the NF-κB and necroptosis pathways. Interestingly, we found that Nbeal2 could be preferentially activated in H5N1-infected P815 cells, where the level of Nbeal2 increased dramatically but decreased in HIN1-infected P815 cells. Nbeal2 knockdown facilitated inflammatory cytokine release in both H1N1- and H5N1-infected P815 cells and aggravated the apoptosis of pulmonary epithelial cells. In summary, our data described a transcriptomic profile and bioinformatic characterization of H1N-1 or H5N1-infected mast cells and, for the first time, established the crucial role of Nbeal2 during influenza A virus infection.
The Ongoing Journey of a Shigella Bioconjugate Vaccine
Authors: Martin Patricia , Alaimo Cristina
Published: January 2022

Shigellosis is a serious disease with a major impact, especially in low-income countries where mortality and morbidity are high. In addition, shigellosis among travelers and military personnel is a cause of significant morbidity and contributes to the increase in antimicrobial resistance. The World Health Organization (WHO) considers the development of a Shigella vaccine a priority for public health. Over the past 60 years, several efforts to develop a Shigella vaccine have been pursued, without success. The principle of preventing shigellosis with a conjugate vaccine was demonstrated in the 1990′s, but this vaccine was not further developed. Bioconjugation is an innovative technology that allows the production of conjugate vaccines in a biological environment to preserve native immunogenic structures. In this review, we describe the journey of the bioconjugate Shigella vaccine, one of the most advanced clinical programs for a Shigella vaccine.
Molecular Genetic Investigation of Digital Melanoma in Dogs
Authors: Conrad David , Kehl Alexandra , Beitzinger Christoph , Metzler Thomas , Steiger Katja , Pfarr Nicole , Fischer Konrad , Klopfleisch Robert , Aupperle-Lellbach Heike
Published: January 2022

Canine digital melanoma, in contrast to canine oral melanoma, is still largely unexplored at the molecular genetic level. The aim of this study was to detect mutant genes in digital melanoma. Paraffin-embedded samples from 86 canine digital melanomas were examined for the BRAF V595E variant by digital droplet PCR (ddPCR), and for exon 11 mutations in c-kit. Furthermore, exons 2 and 3 of KRAS and NRAS were analysed by Sanger sequencing. Copy number variations (CNV) of KITLG in genomic DNA were analysed from nine dogs. The BRAF V595E variant was absent and in c-kit, a single nucleotide polymorphism was found in 16/70 tumours (23%). The number of copies of KITLG varied between 4 and 6. KRAS exon 2 codons 12 and 13 were mutated in 22/86 (25.6%) of the melanomas examined. Other mutually exclusive RAS mutations were found within the hotspot loci, i.e., KRAS exon 3 codon 61: 2/55 (3.6%); NRAS exon 2 codons 12 and 13: 2/83 (2.4%); and NRAS exon 3 codon 61: 9/86 (10.5%). However, no correlation could be established between histological malignancy criteria, survival times and the presence of RAS mutations. In summary, canine digital melanoma differs from molecular genetic data of canine oral melanoma and human melanoma, especially regarding the proportion of RAS mutations.