bluuebunny/crossref_metadata_2025 huggingface dataset:
3D-DIoU: 3D Distance Intersection over Union for Multi-Object Tracking in Point Cloud
Authors: Mohammed Sazan Ali Kamal , Razak Mohd Zulhakimi Ab , Rahman Abdul Hadi Abd
Published: March 2023

Multi-object tracking (MOT) is a prominent and important study in point cloud processing and computer vision. The main objective of MOT is to predict full tracklets of several objects in point cloud. Occlusion and similar objects are two common problems that reduce the algorithm’s performance throughout the tracking phase. The tracking performance of current MOT techniques, which adopt the ‘tracking-by-detection’ paradigm, is degrading, as evidenced by increasing numbers of identification (ID) switch and tracking drifts because it is difficult to perfectly predict the location of objects in complex scenes that are unable to track. Since the occluded object may have been visible in former frames, we manipulated the speed and location position of the object in the previous frames in order to guess where the occluded object might have been. In this paper, we employed a unique intersection over union (IoU) method in three-dimension (3D) planes, namely a distance IoU non-maximum suppression (DIoU-NMS) to accurately detect objects, and consequently we use 3D-DIoU for an object association process in order to increase tracking robustness and speed. By using a hybrid 3D DIoU-NMS and 3D-DIoU method, the tracking speed improved significantly. Experimental findings on the Waymo Open Dataset and nuScenes dataset, demonstrate that our multistage data association and tracking technique has clear benefits over previously developed algorithms in terms of tracking accuracy. In comparison with other 3D MOT tracking methods, our proposed approach demonstrates significant enhancement in tracking performances.
Static Hand Gesture Recognition Using Capacitive Sensing and Machine Learning
Authors: Noble Frazer , Xu Muqing , Alam Fakhrul
Published: March 2023

Automated hand gesture recognition is a key enabler of Human-to-Machine Interfaces (HMIs) and smart living. This paper reports the development and testing of a static hand gesture recognition system using capacitive sensing. Our system consists of a 6×18 array of capacitive sensors that captured five gestures—Palm, Fist, Middle, OK, and Index—of five participants to create a dataset of gesture images. The dataset was used to train Decision Tree, Naïve Bayes, Multi-Layer Perceptron (MLP) neural network, and Convolutional Neural Network (CNN) classifiers. Each classifier was trained five times; each time, the classifier was trained using four different participants’ gestures and tested with one different participant’s gestures. The MLP classifier performed the best, achieving an average accuracy of 96.87% and an average F1 score of 92.16%. This demonstrates that the proposed system can accurately recognize hand gestures and that capacitive sensing is a viable method for implementing a non-contact, static hand gesture recognition system.
Scalable Lightweight Protocol for Interoperable Public Blockchain-Based Supply Chain Ownership Management
Authors: Khor Jing Huey , Sidorov Michail , Zulqarnain Seri Aathira Balqis
Published: March 2023

Scalability prevents public blockchains from being widely adopted for Internet of Things (IoT) applications such as supply chain management. Several existing solutions focus on increasing the transaction count, but none of them address scalability challenges introduced by resource-constrained IoT device integration with these blockchains, especially for the purpose of supply chain ownership management. Thus, this paper solves the issue by proposing a scalable public blockchain-based protocol for the interoperable ownership transfer of tagged goods, suitable for use with resource-constrained IoT devices such as widely used Radio Frequency Identification (RFID) tags. The use of a public blockchain is crucial for the proposed solution as it is essential to enable transparent ownership data transfer, guarantee data integrity, and provide on-chain data required for the protocol. A decentralized web application developed using the Ethereum blockchain and an InterPlanetary File System is used to prove the validity of the proposed lightweight protocol. A detailed security analysis is conducted to verify that the proposed lightweight protocol is secure from key disclosure, replay, man-in-the-middle, de-synchronization, and tracking attacks. The proposed scalable protocol is proven to support secure data transfer among resource-constrained RFID tags while being cost-effective at the same time.
Beamforming Techniques for Passive Radar: An Overview
Authors: Núñez-Ortuño José M. , González-Coma José P. , Nocelo López Rubén , Troncoso-Pastoriza Francisco , Álvarez-Hernández María
Published: March 2023

Passive radar is an interesting approach in the context of non-cooperative target detection. Because the signal source takes advantage of the so-called illuminator of opportunity (IoO), the deployed system is silent, allowing the operator cheap, portable, and practically undetectable deployments. These systems match perfectly with the use of antenna arrays to take advantage of the additional gains provided by the coherent combination of the signals received at each element. To obtain these benefits, linear processing methods are required to enhance the system’s performance. In this work, we summarize the main beamforming methods in the literature to provide a clear picture of the current state of the art. Next, we perform an analysis of the benefits and drawbacks and explore the chance of increasing the number of antenna elements. Finally, we identify the major challenges to be addressed by researchers in the future.
Deep Neural Network Analysis on Uplift Resistance of Plastic Greenhouses for Sustainable Agriculture
Authors: Kim Myeong-Hwan , Song Chul-Min
Published: March 2023

In this study, we attempted to find an alternative method to identify and efficiently predict the interaction between the soil and basic structure of plastic greenhouses for sustainable agriculture. The interaction between the foundation structure of the plastic greenhouse and the soil appears as uplift resistance. We first measured the uplift resistance by using various artificial neural networks. The data required by the model were obtained through laboratory experiments, and a deep neural network (DNN) was employed to improve the model performance. We proposed a new deep learning structure called DNN-T that has the advantage of stabilizing neural circuits by suppressing feedback by using the concept of biological interneurons. The DNN-T was trained using driving data for four scenarios. The upward resistance of the DNN-T according to the training conditions showed a high correlation (r = 0.90), and the error decreased when the input conditions of the training data were varied. DNN-Ts mimicking interneurons can contribute to solving various nonlinear problems in geotechnical engineering. We believe that our DNN-T model can be used to determine the uplift resistance of solid and continuous pipe foundations, effectively reducing the need for time-consuming and extensive testing.
Experimental and Numerical Investigation of the Flexural Behavior of Mortar Beams Strengthened with Recycled Plastic Mesh
Authors: Ghanem Hassan , Chahal Safwan , Khatib Jamal , Elkordi Adel
Published: March 2023

The generation of plastic waste is increasing all over the world at an alarming rate, therefore raising concerns related to its disposal. As space for landfilling is becoming scarce and as incinerating the plastic waste leads to the release of toxic elements into the environment, recycling becomes a viable and an attractive option in pursuit of sustainable development. This paper investigates the flexural behavior of mortar beams reinforced with recycled plastic mesh. To achieve this objective, 27 mortar beams were prepared, with 24 of them containing waste plastic mesh with different void ratios and effective widths. All beams were cured for 28 days and then tested using a three-point bending test. Mid-span deflection was measured for each increment of load to obtain the load deflection curve. Moreover, a numerical simulation was performed on all mortar specimens using finite element software ABAQUS and a comparison was made with the experimental analysis. Test results showed that the addition of plastic mesh increased the flexural toughness and ductility of mortar beams. Furthermore, it was noticed that as the effective width ratio increased from 0 to 0.58, the ultimate capacity and flexural toughness increased. Beyond this level, a decrease was observed. On the other hand, the ductility index was proportional to the flexural toughness for all mesh effective width ratios. Comparing the ultimate capacity, flexural toughness and ductility index between the experimental and numerical data, there was a difference of up to 7%. This indicates that the numerical output can be a good predictor of the performance of plastic inside the mortar. Hence, using recycled plastic mesh could be recommended for improving the flexural performance of mortar beams, creating a sustainable composite.
Systematic Literature Review on Robust Optimization in Solving Sustainable Development Goals (SDGs) Problems during the COVID-19 Pandemic
Authors: Chaerani Diah , Shuib Adibah , Perdana Tomy , Irmansyah Athaya Zahrani
Published: March 2023

Handling uncertainty is important in decision making, especially for SDGs problems. Robust Optimization (RO) is an applied optimization method that can be employed to handle optimization under uncertain data. With SDGs problems, many uncertain data have been considered in decision making. With RO, the data uncertainties are assumed to lay within a compact, convex continuous set. There are three special sets that can be used to represent the data, i.e., box, ellipsoidal, or polyhedral uncertainty sets. These special sets lead the SDGs problems to a computationally tractable optimization model, such that the global optimal solution is attained. However, literature reviews on the application of RO in SDGs decision-making is sparse, especially during the COVID-19 pandemic period. This paper examines the following topics: (1) the purposes of studies of RO and SDGs during the COVID-19 pandemic, (2) the state-of-the-art in RO-SDGs to determine the research objectives, and (3) the SDGs type of problems that have been modeled using RO. A systematic literature review is conducted in this paper, wherein discussion is based on a PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) flowchart. To this end, the database reference searching conducted on the Scopus, Science Direct, and SAGE databases, is completed using the help RStudio software. The analysis was carried out on two datasets, assisted by the output visualization using RStudio software with the “bibliometrix” package, and using the ‘biblioshiny()’ command to create a link to the “shiny web interface”. In this paper, the research gap on application of RO to SDGs problems is analyzed in order to identify the research objectives, methods, and specific RO-SDGs problems. As a result, the application of RO to SDGs problems is rare; this finding provides a motivation to conduct a further study of RO and SDGs during the COVID-19 pandemic. An expansion is presented using the key phrase “Operations Research and Optimization Modeling”, or “OROM”. SDGs in Indonesia may be referenced as an example of the capacity building available through RO/OROM.
Sleep Duration and Risk of Depression: Empirical Evidence from Chinese Middle-Aged and Older Adults
Authors: Yu Weijie , Gong Yijia , Lai Xiaozhen , Liu Jianping , Rong Hongguo
Published: March 2023

Objective: To investigate the relationships between sleep duration and depression among middle-aged and older adults in China. Methods: This study used the data of 17,744 respondents from the 2018 China Health and Retirement Longitudinal Study (CHARLS), an ongoing national longitudinal survey of Chinese adults aged 45 years and above. Self-reported sleep duration per night was obtained from face-to-face interviews. Depression was evaluated using the 10-item Center for Epidemiological Studies-Depression scale (CES-D 10). The multivariable generalized linear model (GLM) was adopted to estimate the associations between sleep duration and depression. Results: Of the 17,744 respondents, 8425 (47.5%) were men. The mean (SD) age was 62.6 (10.0) years old. Respondents with short (≤4, 5 h per night) sleep duration had a higher risk of depression [odds ratio (OR): 2.77, 95% confidence interval (CI): 2.35–3.27), p < 0.001; OR: 1.65, 95% CI: 1.38–1.98, p < 0.001] compared with those slept for 7 h per night after adjusting for covariates. Long sleep duration (8, 9, ≥10) had no significant risk for depression. Restricted cubic splines analysis suggested that when sleep duration fell below 9 h, increased sleep duration was associated with a significantly lower risk of depression (OR: 0.82, 95% CI: 0.79–0.84, p < 0.001). When sleep duration exceeded 9 h, the risk of depression (OR: 1.03, 95% CI: 0.94–1.14, p = 0.512) would not increase significantly facing prolonged sleep duration. Conclusions: Short sleep duration was associated with depressive symptoms among middle-aged and older adults in China. Future studies are needed to focus on examining the cause-effect relationship between sleep duration and depression.
A New Hybrid White Shark and Whale Optimization Approach for Estimating the Li-Ion Battery Model Parameters
Authors: Fathy Ahmed , Yousri Dalia , Alharbi Abdullah G. , Abdelkareem Mohammad Ali
Published: March 2023

Constructing a reliable equivalent circuit of Li-Ion batteries using real operating conditions by estimating optimal parameters is mandatory for many engineering applications, as it controls the energy management of the battery in a hybrid system. However, model parameters can vary according to the electrochemical nature of the battery, so improving the accuracy of the battery model parameters is essential to obtain reliable and accurate equivalent circuits. Therefore, this paper proposes a new efficient hybrid optimization approach for determining the proper parameters of Li-ion battery Shepherd model equivalent circuits. The proposed algorithm comprises a white shark optimizer (WSO) and the whale optimization approach (WOA) for modifying the stochastic behavior of the WSO while searching for food sources. Minimizing the root mean square error between the estimated and measured battery voltages is the objective function considered in this work. The hybrid variant of the WSO (HWSO) was examined with two different types of batteries. Moreover, the proposed HWSO was validated versus a set of recent meta-heuristic approaches including the sea horse optimizer (SHO), artificial gorilla troops optimizer (GTO), coyote optimization algorithm (COA), and the basic version of the WSO. Furthermore, statistical analyses, mean convergence, and fitting curves were conducted for the comparisons. The proposed HWSO succeeded in achieving the least fitness values of 2.6172 × 10−4 and 5.6118 × 10−5 with standard deviations of 9.3861 × 10−5 and 3.2854 × 10−4 for battery 1 and battery 2, respectively. On the other hand, the worst fitness values were 6.5230 × 10−2 and 6.6197 × 10−5 via SHO and WSO for both considered batteries. The proposed HWSO results prove the efficiency of the proposed approach in providing highly accurate battery model parameters with high consistency and a unique convergence curve compared to the other methods.
Improving Sustainability of Learning Outcomes: An Empirical Study of Medical Students’ Autonomous Learning
Authors: Zhao Lei , Zhu Ruijie , Cai Xu , Zhang Junchao
Published: March 2023

Achieving sustainable learning outcomes for medical students requires the assessment of their engagement in autonomous learning, and the development of sustainable autonomous learning skills. This study examined the relationship among autonomous learning, academic support, school satisfaction, and learning outcomes. It used structural equation modeling to analyze data from 725 medical students studying at Huazhong University of Science and Technology, Wuhan. The findings showed that autonomous learning was positively related to academic support, school satisfaction, and learning outcomes. Furthermore, both school satisfaction and learning outcomes were positively correlated with academic support. Similarly, school satisfaction was positively correlated with learning outcomes. Academic support and school satisfaction mediated and serially mediated the relationship between autonomous learning and learning outcomes, respectively. Additionally, autonomous learning had positive direct and indirect effects on learning outcomes through the serial mediation of academic support and school satisfaction. The serial mediating effects of academic support and school satisfaction were significant. Thus, autonomous learning was considered to be an important aspect of sustainable learning outcomes; educational administrators could systematically encourage students’ autonomous learning to increase their invested time and effort, and help students improve their learning outcomes.
Air Quality Modeling of Cooking Stove Emissions and Exposure Assessment in Rural Areas
Authors: He Yucheng , Nishandar Sanika Ravindra , Edwards Rufus David , Princevac Marko
Published: March 2023

Cooking stoves produce significant emissions of PM2.5 in homes, causing major health impacts in rural communities. The installation of chimneys in cooking stoves has been documented to substantially reduce indoor emissions compared to those of traditional open fires. Majority of the emissions pass through chimneys to the outdoors, while some fraction of the emissions leak directly into the indoor air, which is defined as fugitive emission. Indoor PM2.5 concentrations are then the result of such fugitive emissions and the infiltration of outdoor neighborhood pollutants. This study uses a combination of the one-contaminant box model and dispersion models to estimate the indoor PM2.5 household concentration. The results show that the contributions of outdoor infiltration to indoor PM2.5 concentrations increase with higher packing densities and ventilation rates. For a case study, under WHO recommended ventilation conditions, the 24 h average mass concentration is ~21 μg/m3, with fugitive concentration accounting for ~90% of the total exposure for highly packed communities. These results help to identify the potential benefits of intervention strategies in regions that use chimney stoves.
The Future Direction of Halal Food Additive and Ingredient Research in Economics and Business: A Bibliometric Analysis
Authors: Nazaruddin La Ode , Gyenge Balázs , Fekete-Farkas Maria , Lakner Zoltán
Published: March 2023

The increasing growth trend of the global Muslim population implies an increase in the consumption of halal products. The importance of the halal market attracts much attention from many stakeholders, including academia/researchers. Many scholars have conducted studies on halal topics. However, these studies cover broad topics, such as ICT potential in the halal sector, the halal supply chain, Islamic Law, and other halal studies related to natural sciences. This study aims to study the research gap and future trends of halal food additive and ingredient research in business and economics using bibliometric analysis. The data were obtained from the Scopus database from 1999 to 2022. The authors analyzed the keyword “Halal Consumption and Production” by using the general keyword “Halal or Haram Additive and Ingredient”. The dataset was uploaded on VOSviewer and R language (Bibliometrix) software. This study found a deficit of studies on halal food additives and ingredients in business and economics. The co-occurrence network output demonstrated that future studies on halal food additives and ingredients should consider clusters that have lower density and central positions, such as production–consumption and the supply chain, healthy foods, and the logistics market and health effects. The Bibliometrix strategic diagram of the 2020–2022 thematic evolution demonstrates a research gap in three out of four quadrants (i.e., emerging or declining, basic, and motor themes). This study suggests potential research areas in the field of halal food additives and ingredients, such as ethical and sustainable sourcing, responsible consumption, consumer sovereignty, international trade, economic modeling, food security, green/sustainable supply chain, and halal regulation and product safety.
Enhancing Digital Presence for Maximizing Customer Value in Fast-Food Restaurants
Authors: Daradkeh Fathi Mohamed , Hassan Thowayeb H. , Palei Tatiana , Helal Mohamed Y. , Mabrouk Sanaa , Saleh Mahmoud I. , Salem Amany E. , Elshawarbi Nabila N.
Published: March 2023

Digital transformation has altered the way customers interact with restaurants. As a result, digital transformation has had an enormous impact, changing restaurant customer value. Therefore, this research aims to develop a dynamic and sustainable method for creating customer value in digital transformation. This study suggested digital dynamic capabilities and digital customer orientation as a process model (i.e., sensing, seizing, transforming, and refining) to develop digital transformation and create a dynamic customer value. We chose fast-food restaurants in Egypt to examine the proposed model using a qualitative approach of semi-structured interviews with fast-food managers and hospitality experts. The findings indicated that fast-food restaurants’ different digital transformation capabilities and tools (e.g., value innovation, SWOT analysis, artificial intelligence, new technology selection criteria, digital maturity, building several digital platforms, and gathering and analyzing customers’ online reviews) help them create customer value. However, interviewees highlighted how well-suited the suggested digital dynamic capabilities are to serve as drivers of digital transformation in fast-food restaurants and create a dynamic customer value. This research expands the dynamic capabilities theory by adding digital customer orientation (i.e., proactive and reactive to customer feedback) to develop digital transformation and create customer value in fast-food restaurants. This research provides fast-food restaurant managers with an in-depth explanation of how to implement the digital dynamic capabilities model for executing digital transformation and developing a new dynamic customer value.
Improving Psychological Well-Being in Urban University Districts through Biophilic Design: Two Cases in Mexico
Authors: Cobreros Carlos , Medoza-Ruvalcaba Neyda , Flores-García Mariana , Roggema Rob
Published: March 2023

Since 2007, more than half of the population has lived in cities, and an increase of 60 percent is expected by 2030. The city can bring many benefits to citizens, but it also brings a series of problems, such as a loss of psychological well-being and the breakdown of social cohesion and several aspects of mental health. University districts, usually concentrated in specific parts of cities, suffer particularly from these negative effects. Nature can be used to alleviate these problems and provide the benefits of a connected urban life. The university community’s well-being depends on contact with nature. In this sense, biophilic design improves the built environment. The purpose of this article is to analyze the relationship between connectedness to nature and psychological well-being in university communities to contrast the effect that nature has on people’s psychological well-being and to identify possible biophilic design patterns that could improve connectedness to nature, validating the urgent need to design and implement biophilic design in current cities and university urban districts.
Research on Time to Market and Pricing of Platform Products in a Competitive Environment
Authors: Zhou Lei , Qi Yue , You Xinshang
Published: March 2023

Platforms are gradually becoming important business organization models, and platforms with bilateral market characteristics such as payment platforms and online shopping platforms are gradually penetrating people’s lives. Freemium content mostly exists in particular platforms such as online video platforms, etc. Platforms need to balance upstream and downstream markets when formulating strategies. This paper is the first to explore the time-to-market and pricing strategies of products in bilateral markets. By connecting upstream and downstream markets through cross-network externalities, we construct a system dynamics model of the problem, simulate the diffusion process of new product launches, and solve the problem of the optimal time to market and optimal pricing of the product. The simulation analyzes the effects of different parameters on the optimal time-to-market and pricing strategies, and comparing the diffusion in a unilateral market, we find that in a competitive market environment, the time-to-market and pricing of products are influenced by exogenous variables such as network externalities, and firms can promote their products more efficiently by changing the marketing mix strategy of platform product benefits and quality reputation. Meanwhile, the results obtained by considering bilateral markets when developing strategies for platform-based companies can lead to higher returns.
Causes, Types and Consequences of Municipal Waste Landfill Fires—Literature Review
Authors: Dabrowska Dominika , Rykala Wojciech , Nourani Vahid
Published: March 2023

The amount of municipal waste produced worldwide has seen a significant increase in recent years. The need to store waste is a significant problem in the context of environmental threats and spatial development. Due to the fact that the easiest way to reduce the amount of waste is to incinerate it, and despite the fact that waste incineration plants have existed since the late 1800s, the amount of illegal waste burning and landfills has also increased. Subsurface landfill fires are particularly dangerous, as they can affect the structure of the landfill. Methane also plays an important role in fires as it is flammable and contributes to the spread of fire. In addition, the leachate from incinerated waste is much more dangerous than the leachate from waste in its natural state. The effluents from incinerated waste include heavy metals and persistent organic pollutants, as well as sulphates, chlorides, and polycyclic aromatic hydrocarbons. Other pollutants also end up in the atmosphere. The aim of this article is to present the problem of landfill fires and their impact on air, soil, and water, based on a review of the selected documented fires as well as indicators of fires in the areas in which the authors of this article conducted their research. The article presents an overview of methods and tests, such as dynamic leaching tests, monitoring tests, and lysimetric tests, all of which can be implemented to prevent fires as well as for research purposes after a fire has occurred, so that this article can be utilitarian not only for researchers, but also for decision makers.
Can the Low-Carbon Transition Impact the Urban–Rural Income Gap? Empirical Evidence from the Low-Carbon City Pilot Policy
Authors: Chen Tingwei , Zhang Zongbin
Published: March 2023

Environmental transformation is a broad and profound economic and social systemic change, which will certainly influence a number of the economic system fields. In particular, does China’s continued low-carbon transition widen the urban–rural income gap while achieving energy conservation and emission reduction targets? This research investigates the effects of low-carbon city pilot (LCCP) programs on urban-rural income gaps and associated mechanisms using a panel of 282 prefecture-level cities from 2007 to 2021. The analysis finds that: (1) LCCP policies exacerbate the urban-rural income disparity in general. In pilot cities, policy implementation widens the urban-rural income difference by roughly 0.5% on average when compared to non-pilot cities. (2) LCCP policies have a direct U-shaped association with employment structure and have a favorable influence on employment structure. (3) The LCCP policies have an inverted U-shaped association with regional innovation capacity, and the LCCP policies have a positive influence on regional innovation capacity. (4) The effects of LCCP policies on urban-rural income disparities vary dramatically between cities based on geography, city size, and resource endowment. The Chinese government should break down market segmentation and encourage urban-rural integration in order to foster technical advancement and scientific and technology innovation, therefore closing the urban-rural income gap and attaining high-quality economic growth in China.
Teaching Design Model of Bridge Aesthetics Course Facing Ecological Landscape Sustainable Development
Authors: Dong Fenghui , Ruan Sihan , Zhao Yuting , Wei Yang
Published: March 2023

In recent years, ecological building of bridges has gradually begun to appear in cities, and this trend is conducive to the sustainable development of urban bridges and an ecological environment, promoting the development of emerging industries around cities and driving the development of the urban economy. Bridges’ ecological aesthetic design cannot be separated from ecological aesthetics, and the relationship between these two factors is complementary and inseparable. This paper focuses on the relationship between the teaching of a bridge aesthetic design course and ecological landscape sustainable development. Based on a visual impression hierarchy deep learning model and a statistical analysis of a questionnaire, including reliability and validity analyses, a teaching model for the design of landscape bridge structure systems was constructed. Landscape bridge structure systems combine the dimensions of function, form, mechanics, and culture, and the teaching design model of landscape bridges must include non-professional students, undergraduate students, graduate students, and graduates working in enterprises. Investigations were performed of the urban block landscape, water environment landscape, urban garden landscape, and landscape bridges within natural mountain landscapes. The results showed that: (1) the influence and role of landscape aesthetics related to the water environment and urban garden landscapes are the most important; (2) in the teaching of a bridge aesthetics course, sustainable ecological development must consider the aesthetic value of landscape bridges while ensuring function and safety; and (3) for students at different learning stages, the focus in terms of bridge aesthetic system elements is different. Both the bridge structural landscape configuration and the ecological aesthetics must be considered together during the teaching of bridge aesthetics design courses. To achieve such a goal, students at different levels must have a good understanding of ecologically sustainable development and bridge aesthetics.
Applications of Gegenbauer Polynomials for Subfamilies of Bi-Univalent Functions Involving a Borel Distribution-Type Mittag-Leffler Function
Authors: Alatawi Abdullah , Darus Maslina , Alamri Badriah
Published: March 2023

In this research, a novel linear operator involving the Borel distribution and Mittag-Leffler functions is introduced using Hadamard products or convolutions. This operator is utilized to develop new subfamilies of bi-univalent functions via the principle of subordination with Gegenbauer orthogonal polynomials. The investigation also focuses on the estimation of the coefficients |aℓ|(ℓ=2,3) and the Fekete–Szegö inequality for functions belonging to these subfamilies of bi-univalent functions. Several corollaries and implications of the findings are discussed. Overall, this study presents a new approach for constructing bi-univalent functions and provides valuable insights for further research in this area.
On Some Topological and Geometric Properties of Some q-Cesáro Sequence Spaces
Authors: Yılmaz Yılmaz , Akdemir Ahmet Ocak
Published: March 2023

Mathematical concepts are aesthetic tools that are useful to create methods or solutions to real-world problems in theory and practice, and that sometimes contain symmetrical and asymmetrical structures due to the nature of the problems. In this study, we investigate whether the sequence spaces Xpq, 0≤p<∞, and X∞, which are constructed by q-Cesáro matrix, satisfy some of the further properties described with respect to the bounded linear operators on them. More specifically, we answer to the question: “Which of these spaces have the Approximation, Dunford-Pettis, Radon–Riesz and Hahn–Banach extension properties?”. Furthermore, we try to investigate some geometric properties such as rotundity and smootness of these spaces.
Confidence Interval Estimation for the Ratio of the Percentiles of Two Delta-Lognormal Distributions with Application to Rainfall Data
Authors: Thangjai Warisa , Niwitpong Sa-Aat , Niwitpong Suparat , Smithpreecha Narudee
Published: March 2023

The log-normal distribution (skewed distribution or asymmetry distribution) is used to describe random variables comprising positive real values. It is well known that the logarithm values of these are normally distributed (symmetry distribution). Positively right-skewed data applicable to the log-normal distribution are frequently observed in the fields of environmental studies, biology, and medicine. The number of zero observations follows a binomial distribution. However, problems can arise in the analysis of data containing zero observations along with log-normally distributed data, for which the delta-lognormal distribution is often referred to for using the analysis of the data. In statistics, the percentile provides the relative standing of a numerical data point when compared to all of the others in a distribution with reference to the observations at or below it. In this study, estimates for the confidence interval for the ratio of the percentiles of two delta-lognormal distributions are constructed using fiducial generalized confidence interval approaches based on the fiducial quantity and the optimal generalized fiducial quantity, the Bayesian approach, and the parametric bootstrap method. As assessed by Monte Carlo simulations using the RStudio programming in terms of the coverage probability and the average length, the Bayesian approach performed quite well by providing adequate coverage probabilities along with the shortest average lengths in all of the scenarios tested. Daily rainfall data contain both zero and positive values. The daily rainfall data can usually be fitted to the delta-lognormal distribution. Their application to rainfall data is also provided to illustrate their efficacies with real data. The efficacy of the approach is used to compare two rainfall dispersion populations.
Combination Antiretroviral Therapy and Immunophenotype of Feline Immunodeficiency Virus
Authors: Kim Jeffrey , Behzadi Elisa S. , Nehring Mary , Carver Scott , Cowan Shannon R. , Conry Megan K. , Rawlinson Jennifer E. , VandeWoude Sue , Miller Craig A.
Published: March 2023

Feline Immunodeficiency Virus (FIV) causes progressive immune dysfunction in cats similar to human immunodeficiency virus (HIV) in humans. Although combination antiretroviral therapy (cART) is effective against HIV, there is no definitive therapy to improve clinical outcomes in cats with FIV. This study therefore evaluated pharmacokinetics and clinical outcomes of cART (2.5 mg/kg Dolutegravir; 20 mg/kg Tenofovir; 40 mg/kg Emtricitabine) in FIV-infected domestic cats. Specific pathogen free cats were experimentally infected with FIV and administered either cART or placebo treatments (n = 6 each) for 18 weeks, while n = 6 naïve uninfected cats served as controls. Blood, saliva, and fine needle aspirates from mandibular lymph nodes were collected to quantify viral and proviral loads via digital droplet PCR and to assess lymphocyte immunophenotypes by flow cytometry. cART improved blood dyscrasias in FIV-infected cats, which normalized by week 16, while placebo cats remained neutropenic, although no significant difference in viremia was observed in the blood or saliva. cART-treated cats exhibited a Th2 immunophenotype with increasing proportions of CD4+CCR4+ cells compared to placebo cats, and cART restored Th17 cells compared to placebo-treated cats. Of the cART drugs, dolutegravir was the most stable and long-lasting. These findings provide a critical insight into novel cART formulations in FIV-infected cats and highlight their role as a potential animal model to evaluate the impact of cART on lentiviral infection and immune dysregulation.
Inhibition of Rab1B Impairs Trafficking and Maturation of SARS-CoV-2 Spike Protein
Authors: Veeck Christopher , Biedenkopf Nadine , Rohde Cornelius , Becker Stephan , Halwe Sandro
Published: March 2023

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) utilizes cellular trafficking pathways to process its structural proteins and move them to the site of assembly. Nevertheless, the exact process of assembly and subcellular trafficking of SARS-CoV-2 proteins remains largely unknown. Here, we have identified and characterized Rab1B as an important host factor for the trafficking and maturation of the spike protein (S) after synthesis at the endoplasmic reticulum (ER). Using confocal microscopy, we showed that S and Rab1B substantially colocalized in compartments of the early secretory pathway. Co-expression of dominant-negative (DN) Rab1B N121I leads to an aberrant distribution of S into perinuclear spots after ectopic expression and in SARS-CoV-2-infected cells caused by either structural rearrangement of the ERGIC or Golgi or missing interaction between Rab1B and S. Western blot analyses revealed a complete loss of the mature, cleaved S2 subunit in cell lysates and culture supernatants upon co-expression of DN Rab1B N121I. In sum, our studies indicate that Rab1B is an important regulator of trafficking and maturation of SARS-CoV-2 S, which not only improves our understanding of the coronavirus replication cycle but also may have implications for the development of antiviral strategies.
Oncolytic Efficacy of a Recombinant Vaccinia Virus Strain Expressing Bacterial Flagellin in Solid Tumor Models
Authors: Shakiba Yasmin , Vorobyev Pavel O. , Naumenko Victor A. , Kochetkov Dmitry V. , Zajtseva Ksenia V. , Valikhov Marat P. , Yusubalieva Gaukhar M. , Gumennaya Yana D. , Emelyanov Egor A. , Semkina Alevtina S. , Baklaushev Vladimir P. , Chumakov Peter M. , Lipatova Anastasia V.
Published: March 2023

Oncolytic viral therapy is a promising novel approach to cancer treatment. Oncolytic viruses cause tumor regression through direct cytolysis on the one hand and recruiting and activating immune cells on the other. In this study, to enhance the antitumor efficacy of the thymidine kinase-deficient vaccinia virus (VV, Lister strain), recombinant variants encoding bacterial flagellin (subunit B) of Vibrio vulnificus (LIVP-FlaB-RFP), firefly luciferase (LIVP-Fluc-RFP) or red fluorescent protein (LIVP-RFP) were developed. The LIVP-FLuc-RFP strain demonstrated exceptional onco-specificity in tumor-bearing mice, detected by the in vivo imaging system (IVIS). The antitumor efficacy of these variants was explored in syngeneic murine tumor models (B16 melanoma, CT26 colon cancer and 4T1 breast cancer). After intravenous treatment with LIVP-FlaB-RFP or LIVP-RFP, all mice tumor models exhibited tumor regression, with a prolonged survival rate in comparison with the control mice. However, superior oncolytic activity was observed in the B16 melanoma models treated with LIVP-FlaB-RFP. Tumor-infiltrated lymphocytes and the cytokine analysis of the serum and tumor samples from the melanoma-xenografted mice treated with these virus variants demonstrated activation of the host’s immune response. Thus, the expression of bacterial flagellin by VV can enhance its oncolytic efficacy against immunosuppressive solid tumors.
Concomitant Campylobacteriosis in a Puppy and in Its Caregiver: A One Health Perspective Paradigm in Human-Pet Relationship
Authors: Candellone Alessia , Badino Paola , Girolami Flavia , Cerquetella Matteo , Nebbia Patrizia , Aresu Luca , Zoppi Simona , Bergero Domenico , Odore Rosangela
Published: March 2023

We report a case of laboratory-confirmed Campylobacter (C). jejuni and C. upsaliensis symptomatic infection in a puppy, a French Bouledogue, female, 6 months of age, fed a raw, unbalanced, poultry-based diet (RPD), (48.1 CP, 33% EE, 0.3% Ca, 0.5% Phos, 0.5 Ca/P, on a dry-matter basis), and in its owner. Soon after adoption, the pet and the caregiver showed severe gastrointestinal signs and needed hospitalization. Fecal PCR assays, selective cultures, and antibiotic susceptibility testing were performed, and multi-drug resistant C. jejuni and C. upsaliensis were isolated from the feces of both. The same bacteria were also identified by FISH in the dog colonic biopsies collected during endoscopy. The puppy was prescribed a complete commercial diet for growing dogs, (30.00% CP, 21.00% EE, 1.2% Ca; 1% Phos; as fed) and treated with ciprofloxacin. The dog and the man healed uneventfully and tested negative for further fecal PCR analyses. This report focuses on dog nutritional management and explores the potential routes of exposure, with emphasis on emerging outbreaks related to current pet food fads. Our data support the One Health approach, where veterinarians, physicians, and owners are challenged to build effective stewardship to prevent the spread of zoonoses.
Effect of a Ketogenic Medium Chain Triglyceride-Enriched Diet on the Fecal Microbiota in Canine Idiopathic Epilepsy: A Pilot Study
Authors: García-Belenguer Sylvia , Grasa Laura , Palacio Jorge , Moral Jon , Rosado Belén
Published: March 2023

Ketogenic diets have been successfully used in people and dogs with idiopathic epilepsy. This study examined the effect of a ketogenic medium chain triglycerides (MCT)- enriched diet administered for one month on the fecal microbiota of epileptic (n = 11) (six with drug-sensitive epilepsy, DSE; five with drug-refractory epilepsy, DRE) and non-epileptic beagle dogs (n = 12). A significant reduction after diet in the relative abundance of bacteria from the Actinobacteria phylum was observed in all dogs. Epileptic dogs showed a higher relative abundance of Lactobacillus compared with non-epileptic dogs at baseline but these differences disappeared after diet. Epileptic dogs also showed a significantly higher abundance of Negativicutes and Selenomonadales after dietary intervention. Baseline microbiota patterns were similar in non-epileptic beagles and dogs with DSE but significantly different from dogs with DRE. In non-epileptic and DSE groups, the MCT diet decreased the relative abundance of Firmicutes and increased that of Bacteroidetes and Fusobacteria, but the opposite effect was observed in dogs with DRE. These results suggest that the MCT diet effect would depend on individual baseline microbiota patterns and that ketogenic diets could help reduce gut microbiota differences between dogs with DRE and DSE.
Drivers of Spatial and Temporal Dynamics in Water Turbidity of China Yangtze River Basin
Authors: Li Jian , Xia Chunlin
Published: March 2023

The sustainable development of the water environment in the Yangtze River basin has become a critical issue in China. Turbidity is a comprehensive element for water quality monitoring. In this study, the baseline of water turbidity in the Yangtze River was constructed using 36 years of Landsat images from 1986 to 2021. The spatial and temporal dynamics of turbidity and its driving factors were explored. The results show that (i) the proposed Landsat-based turbidity model performs well, with a correlation coefficient (R2) of 0.68 and a Root Mean Square Error (RMSE) of 7.83 NTU for the whole basin. (ii) The turbidity level in the Yangtze River basin is spatially high in the upper reaches (41.7 NTU), low in the middle reaches (30.9 NTU), and higher in the lower reaches (37.6 NTU). The river turbidity level (60.1 NTU) is higher than the turbidity in lakes and reservoirs (29.6 NTU). The turbidity in the Yangtze River basin shows a decreasing trend from 1986 to 2021, with the most significant decrease in the mainstream of the Yangtze River. Seasonally, the mean turbidity in the Yangtze River basin shows a “low in summer and high in winter” trend, but opposite trends were revealed for the first time in rivers and lakes, such as Dongting Lake, Poyang Lake, and Taihu Lake, etc. (iii) Natural factors, including precipitation and natural vegetation cover (woodlands, grasslands, and shrubs) could explain 58% of the turbidity variations, while human activities including impervious surfaces, cropland, and barren land are lower impact. Annual precipitation was negatively correlated with water turbidity, while cropland and barren land showed a significant positive correlation. The study is of great practical value for the sustainable development of the water environment in the Yangtze River basin and provides a reference for remote sensing monitoring of the water environment in inland water bodies.
The Impact of Water Utilization on the Dynamic Total Efficiency of China’s Agricultural Production
Authors: Feng Ying , Lin I-Fang , Lu Ching-Cheng , Lin Hsiu-Hsiu
Published: March 2023

Water resources are very important to agricultural production. In recent years, the change rate of agricultural cultivated land area in China has been very low, so it is not easy to increase its area and improve production capacity. To measure the impact of China’s water resources on agricultural efficiency from 2012 to 2016, this research applies the dynamic SBM model, conceives agricultural water as an external input, and uses the cultivated land area as an immutable intertemporal variable. The empirical results show that (1) the agricultural efficiency of Beijing, Heilongjiang, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Sichuan, Qinghai, and Xinjiang are not affected by agricultural water. (2) The average value of China’s overall agricultural efficiency increased from 0.834 to 0.910, indicating that agricultural water is a positive efficiency factor. (3) Jilin, Chongqing, Inner Mongolia, Shaanxi, and Hubei are the five administrative regions with the most improvement in agricultural efficiency. (4) Insufficient agricultural productivity is the main factor affecting agricultural efficiency.
Magnetic Natural Coagulants for Plastic Recycling Industry Wastewater Treatability
Authors: Ribeiro Thais , Ladeia Janz Fellipe Jhordã , Vizibelli Dandley , Borges Julio Cesar Ângelo , Borssoi Joelmir André , Fukumoto Amanda Alcaide Francisco , Bergamasco Rosângela , Ueda Yamaguchi Natália , Pereira Edilaine Regina
Published: March 2023

The plastic recycling industry generates a high volume of wastewaters. In this study, an unprecedented use of Moringa oleifera and tannin (Acacia mearnsii bark) associated with magnetite was proposed for the treatment of these wastewaters. The response surface method (RSM) and central composite rotational design (CCRD) methodology was applied to optimize the influence of operational variables (pH, temperature, electrical conductivity, turbidity, apparent color, chemical oxygen demand (COD), and total solids) on the performance of the magnetic natural coagulants on coagulation, flocculation, and sedimentation process. The results indicated that temperature, pH, electrical conductivity, and total solids did not generate significant differences in treatments when magnetite was added to natural coagulants. Similarly, the parameters apparent color, turbidity, and COD also did not present significant differences in treatments with Moringa oleifera and magnetite association, although achieving high efficiencies. Finally, the addition of magnetite significantly improved tannin efficiency removal for turbidity, apparent color, and COD with the optimized treatment (21.55 mg L−1 of tannin concentration and 28 min of sedimentation). Thus, natural coagulants associated with magnetite are potential alternatives for the treatment of plastic recycling wastewater and could be used as an environmentally friendly coagulant.