bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Spatio-Temporal Pattern Evolution and the Coupling Coordination Relationship of Land-Use Benefit from a Low-Carbon Perspective: A Case Study of Fujian Province
Authors: Li Daichao , Fan Kunkun , Lu Jiaqi , Wu Sheng , Xie Xiaowei
Published: September 2022

To accelerate the ecological civilization in the new era and coordinate the region’s ecological economic growth, land-use benefit pre-evaluations and coordination analyses must be carried out. These should be based on a land-use structure layout that is low-carbon oriented to ensure the land is utilized efficiently and sustainably. This paper studies Fujian Province, the national ecological civilization test area, and constructs a framework for land-use benefit evaluation and coupling coordination relationship analysis based on land-use structure from the low-carbon perspective. Based on land-use status data from 2000 to 2020, land-use simulation data under two development scenarios in 2030, and accounting for the different types of main functional areas, this paper establishes the land-use benefit evaluation model. The model uses aspects of carbon emission benefit, economic benefit, and ecological benefit to calculate the land-use benefit of counties (cities and districts) in Fujian Province from 2000 to 2030 by combining with the grey prediction model. The coupling coordination degree model is used to explore the coordination relationship between the above three types of benefits in different districts and counties in 2030 and to identify the main factors restricting the improvement of coupling coordination relationships in different regions in the future. The following results are found: (1) From the perspective of land-use efficiency, the coupling and coordination of land-use efficiency and benefits of counties (cities and districts) in Fujian Province continued to rise from 2000 to 2030 under the low-carbon development scenario, and the spatial agglomeration characteristics were obvious. By 2030, the coupling and coordination relationship of regional land-use efficiency was gradually optimized, and the development pattern with the Fuzhou metropolitan area and Xiamen-Zhangquan metropolitan area as the core was formed. (2) From the perspective of restrictive factors of land-use efficiency coupling coordination, the improvement of land-use efficiency coupling coordination relationship in each county (city and district) is affected by multiple factors. The influence degree is economic benefit > ecological benefit > carbon emissions. These results will help to promote the efficient and sustainable use of land resources and realize the comprehensive and coordinated development of a low-carbon economy and society.
Barriers and Strategies of Intercultural Manadonese and Japanese Communication in Japan
Authors: Diner Lispridona , Zulaeha Ida , Subyantoro Subyantoro , Supriatnaningsih Rina
Published: September 2022

A strategy is often needed in the communication process to support smooth interaction. Therefore, this study aimed to evaluate the barriers and strategies of intercultural Manadonese and Japanese communication in Japan. An open questionnaire model was used to obtain data for both natives, as 182 respondents submitted complete results with an age range between 20 and 60 years old. The data instrument also contained five questions on the barriers and implementation of intercultural communication strategies. However, the strategies of the Japanese and Manadonese natives had obstacles in their implementation. Because of cultural and social differences, the methods by which different levels of understanding are utilized were considered. The results showed that this communication strategy had a significant high-level cultural difference, according to the Manadonese native perspective. Meanwhile, the Japanese focused on the parties subject to the application of the strategy, which subsequently showed high respect for the interlocutor.
The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective
Authors: Cao Junwei , Liu Dong , Zhang Guihua , Shang Meng
Published: September 2022

During the COVID-19 pandemic, many countries have used digital contact tracing apps (DCTAs) to implement contact tracing. Although the use of DCTAs has contributed to the prevention and control of COVID-19, there are doubts in academia about their actual effectiveness. In this study, the role of DCTAs in the prevention of COVID-19 was analyzed in terms of both the responsibility and inconvenience to life in a large-scale DCTA overuse environment, based on the normative activation model. The findings suggest that the overuse of a DCTA activates people’s personal norms by triggering awareness of the consequences and ascription of responsibility, leading people to consistently cooperate with the government to prevent COVID-19. However, the inconvenience of living with DCTA overuse weakens the effect of the awareness of consequences and ascription of responsibility and the role of the ascription of responsibility in influencing personal norms. These effects may bear on people’s willingness to consistently cooperate with the government to prevent COVID-19. The results of this study confirm the effectiveness of DCTA in counteracting pandemics from a social responsibility perspective in a large-scale environment where DCTA is used, enriching the literature on DCTA research in the COVID-19 pandemic. The results of this study can also help governments develop and improve policies to prevent COVID-19, as well as improve the DCTAs’ operating patterns.
Stochastic Inoculum, Biotic Filtering and Species-Specific Seed Transmission Shape the Rare Microbiome of Plants
Authors: Johnston-Monje David , Gutiérrez Janneth P. , Becerra Lopez-Lavalle Luis Augusto
Published: September 2022

A plant’s health and productivity is influenced by its associated microbes. Although the common/core microbiome is often thought to be the most influential, significant numbers of rare or uncommon microbes (e.g., specialized endosymbionts) may also play an important role in the health and productivity of certain plants in certain environments. To help identify rare/specialized bacteria and fungi in the most important angiosperm plants, we contrasted microbiomes of the seeds, spermospheres, shoots, roots and rhizospheres of Arabidopsis, Brachypodium, maize, wheat, sugarcane, rice, tomato, coffee, common bean, cassava, soybean, switchgrass, sunflower, Brachiaria, barley, sorghum and pea. Plants were grown inside sealed jars on sterile sand or farm soil. Seeds and spermospheres contained some uncommon bacteria and many fungi, suggesting at least some of the rare microbiome is vertically transmitted. About 95% and 86% of fungal and bacterial diversity inside plants was uncommon; however, judging by read abundance, uncommon fungal cells are about half of the mycobiome, while uncommon bacterial cells make up less than 11% of the microbiome. Uncommon-seed-transmitted microbiomes consisted mostly of Proteobacteria, Firmicutes, Bacteriodetes, Ascomycetes and Basidiomycetes, which most heavily colonized shoots, to a lesser extent roots, and least of all, rhizospheres. Soil served as a more diverse source of rare microbes than seeds, replacing or excluding the majority of the uncommon-seed-transmitted microbiome. With the rarest microbes, their colonization pattern could either be the result of stringent biotic filtering by most plants, or uneven/stochastic inoculum distribution in seeds or soil. Several strong plant–microbe associations were observed, such as seed transmission to shoots, roots and/or rhizospheres of Sarocladium zeae (maize), Penicillium (pea and Phaseolus), and Curvularia (sugarcane), while robust bacterial colonization from cassava field soil occurred with the cyanobacteria Leptolyngbya into Arabidopsis and Panicum roots, and Streptomyces into cassava roots. Some abundant microbes such as Sakaguchia in rice shoots or Vermispora in Arabidopsis roots appeared in no other samples, suggesting that they were infrequent, stochastically deposited propagules from either soil or seed (impossible to know based on the available data). Future experiments with culturing and cross-inoculation of these microbes between plants may help us better understand host preferences and their role in plant productivity, perhaps leading to their use in crop microbiome engineering and enhancement of agricultural production.
Rolling Circles as a Means of Encoding Genes in the RNA World
Authors: Rivera-Madrinan Felipe , Di Iorio Katherine , Higgs Paul G.
Published: September 2022

The rolling circle mechanism found in viroids and some RNA viruses is a likely way that replication could have begun in the RNA World. Here, we consider simulations of populations of protocells, each containing multiple copies of rolling circle RNAs that can replicate non-enzymatically. The mechanism requires the presence of short self-cleaving ribozymes such as hammerheads, which can cleave and re-circularize RNA strands. A rolling circle must encode a hammerhead and the complement of a hammerhead, so that both plus and minus strands can cleave. Thus, the minimal functional length is twice the length of the hammerhead sequence. Selection for speed of replication will tend to reduce circles to this minimum length. However, if sequence errors occur when copying the hammerhead sequence, this prevents cleavage at one point, but still allows cleavage on the next passage around the rolling circle. Thus, there is a natural doubling mechanism that creates strands that are multiple times the length of the minimal sequence. This can provide space for the origin of new genes with beneficial functions. We show that if a beneficial gene appears in this new space, the longer sequence with the beneficial function can be selected, even though it replicates more slowly. This provides a route for the evolution of longer circles encoding multiple genes.
Behavioral and Molecular Effects of Thapsigargin-Induced Brain ER- Stress: Encompassing Inflammation, MAPK, and Insulin Signaling Pathway
Authors: Askari Sahar , Javadpour Pegah , Rashidi Fatemeh Sadat , Dargahi Leila , Kashfi Khosrow , Ghasemi Rasoul
Published: September 2022

Accumulation of misfolded proteins, known as endoplasmic reticulum (ER) stress, is known to participate in Alzheimer’s disease (AD). AD is also correlated with impaired central insulin signaling. However, few studies have probed the relationship between memory, central ER stress, inflammation, hippocampal mitogen-activated protein kinase (MAPK) activity and insulin resistance. The present study aimed to investigate the causative role and underlying mechanisms of brain ER stress in memory impairment and develop a reliable animal model for ER-mediated memory loss. Thapsigargin (TG), a known ER stress activator, was centrally administered. The cognitive function of animals was evaluated by the Morris Water Maze (MWM). To verify the induction of central ER stress, we investigated the mRNA expression of UPR markers in the hippocampus. In addition, the activation of ER stress markers, including Bip, CHOP, and some related apoptosis and pro-inflammatory proteins, such as caspase-3, Bax, Bcl-2, TNF-α, MAPK, and insulin signaling markers, were assessed by Western-blots. The results demonstrated that TG impairs spatial cognition and hippocampal insulin signaling. Meanwhile, molecular results showed a concurrent increment of hippocampal UPR markers, apoptosis, P38 activity, and TNF-α. This study introduced TG-induced ER stress as a pharmacological model for memory impairment in rats and revealed some underlying mechanisms.
Rose Bengal-Modified Upconverting Nanoparticles: Synthesis, Characterization, and Biological Evaluation
Authors: Nahorniak Mykhailo , Pop-Georgievski Ognen , Velychkivska Nadiia , Filipová Marcela , Rydvalová Eliška , Gunár Kristýna , Matouš Petr , Kostiv Uliana , Horák Daniel
Published: September 2022

High-quality upconverting NaYF4:Yb3+,Er3+ nanoparticles (UCNPs; 26 nm in diameter) based on lanthanides were synthesized by a high-temperature coprecipitation method. The particles were modified by bisphosphonate-terminated poly(ethylene glycol) (PEG) and Rose Bengal (RB) photosensitizer. The particles were thoroughly characterized using transmission electron microscopy, dynamic light scattering, thermogravimetric analysis, FTIR, and X-ray photoelectron and upconversion luminescence spectroscopy in terms of morphology, hydrodynamic size, composition, and energy transfer to the photosensitizer. Moreover, the singlet oxygen generation from RB-containing UCNPs was investigated using 9,10-diphenylanthracene probe under 980 nm excitation. The cytotoxicity of UCNPs before and after conjugation with RB was evaluated on highly sensitive rat mesenchymal stem cells (rMSCs) and significant differences were found. Correspondingly, consi-derable variations in viability were revealed between the irradiated and non-irradiated rat glioma cell line (C6) exposed to RB-conjugated UCNPs. While the viability of rMSCs was not affected by the presence of UCNPs themselves, the cancer C6 cells were killed after the irradiation at 980 nm due to the reactive oxygen species (ROS) production, thus suggesting the potential of RB-conjugated PEG-modified UCNPs for applications in photodynamic therapy of cancer.
Ivermectin: A Controversial Focal Point during the COVID-19 Pandemic
Authors: Castillejos-López Manuel , Torres-Espíndola Luz Maria , Huerta-Cruz Juan Carlos , Flores-Soto Edgar , Romero-Martinez Bianca S. , Velázquez-Cruz Rafael , Higuera-Iglesias Anjarath , Camarena Ángel , Torres-Soria Ana Karen , Salinas-Lara Citlaltepetl , Fernández-Plata Rosario , Alvarado-Vásquez Noé , Solís-Chagoyán Héctor , Ruiz Víctor , Aquino-Gálvez Arnoldo
Published: September 2022

The SARS-CoV-2 pandemic has confirmed the apocalyptic predictions that virologists have been making for several decades. The challenge the world is facing is that of trying to find a possible treatment, and a viable and expedient option for addressing this challenge is the repurposing of drugs. However, in some cases, although these drugs are approved for use in humans, the mechanisms of action involved are unknown. In this sense, to justify its therapeutic application to a new disease, it is ideal, but not necessary, to know the basic mechanisms of action involved in a drug’s biological effects. This review compiled the available information regarding the various effects attributed to Ivermectin. The controversy over its use for the treatment of COVID-19 is demonstrated by this report that considers the proposal unfeasible because the therapeutic doses proposed to achieve this effect cannot be achieved. However, due to the urgent need to find a treatment, an exhaustive and impartial review is necessary in order to integrate the knowledge that exists, to date, of the possible mechanisms through which the treatment may be helpful in defining safe doses and schedules of Ivermectin.
Urinary Collectrin (TMEM27) as Novel Marker for Acute Kidney Injury
Authors: Pajenda Sahra , Wagner Ludwig , Gerges Daniela , Herkner Harald , Tevdoradze Tamar , Mechtler Karl , Schmidt Alice , Winnicki Wolfgang
Published: September 2022

Acute kidney injury (AKI) is a leading complication in hospitalized patients of different disciplines due to various aetiologies and is associated with the risk of chronic kidney disease, the need for dialysis and death. Since nephrons are not supplied with pain signals, kidney injury is mostly diagnosed by serum creatinine with a time delay. Recent work has shown that certain urinary biomarkers are available for early detection of AKI. In total, 155 subjects, including 102 patients with AKI at various stages and 53 subjects without AKI, were enrolled, and their course and laboratory data were recorded. Urinary collectrin (TMEM27) was measured by a commercially available ELISA assay. Changes in serum creatinine were used to determine AKI stage. Patients with AKI presented with significantly lower levels of urinary collectrin compared to patients without AKI (1597 ± 1827 pg/mL vs. 2855 ± 2073; p = 0.001). Collectrin was found to inversely correlate with serum creatinine and stages of AKI. Collectrin levels were lowest in AKI stage III (1576 ± 1686 pg/mL; p = 0.001) and also significantly lower in stage II (1616 ± 2148 pg/mL; p = 0.021) and stage I (1630 ± 1956 pg/mL; p = 0.019) compared to subjects without AKI. An optimal minimum collectrin cut-off value of 1606 [95% CI 1258 to 1954] pg/mL was determined to detect AKI. In conclusion, urinary collectrin represents an indicator of AKI that, unlike all other established AKI biomarkers, decreases with stage of AKI and thus may be associated with a novel pathogenic pathway.
Spontaneous Bacterial Peritonitis in Decompensated Liver Cirrhosis—A Literature Review
Authors: Huang Chien-Hao , Lee Chen-Hung , Chang Ching
Published: September 2022

Background: Spontaneous bacterial peritonitis (SBP) is defined as a bacterial infection of the ascitic fluid without a surgically treatable intra-abdominal infection source. SBP is a common, severe complication in cirrhosis patients with ascites, and if left untreated, in-hospital mortality may exceed 90%. However, the incidence of SBP has been lowered to approx. 20% through early diagnosis and antibiotic therapy. Clinical awareness, prompt diagnosis, and immediate treatment are advised when caring for these patients to reduce mortality and morbidity. Aim: To discuss important issues comprising types of SBP, pathogenesis, bacteriology, including the emergence of multidrug-resistant (MDR) microorganisms, prompt diagnosis, risk factors, prognosis, treatment strategies, as well as recurrence prevention through antibiotic prophylaxis until liver transplantation and future trends in treating and preventing SBP in detail. Methods: This article is a literature review and appraisal of guidelines, randomized controlled trials, meta-analyses, and other review articles found on PubMed from between 1977 and 2022. Results: There are three types of SBP. Bacterial translocation from GI tract is the most common source of SBP. Therefore, two thirds of SBP cases were caused by Gram-negative bacilli, of which Escherichia coli is the most frequently isolated pathogen. However, a trend of Gram-positive cocci associated SBP has been demonstrated in recent years, possibly related to more invasive procedures and long-term quinolone prophylaxis. A diagnostic paracentesis should be performed in all patients with cirrhosis and ascites who require emergency room care or hospitalization, who demonstrate or report consistent signs/symptoms in order to confirm evidence of SBP. Distinguishing SBP from secondary bacterial peritonitis is essential because the conditions require different therapeutic strategies. The standard treatment for SBP is prompt broad-spectrum antibiotic administration and should be tailored according to community-acquired SBP, healthcare-associated or nosocomial SBP infections and local resistance profile. Albumin supplementation, especially in patients with renal impairment, is also beneficial. Selective intestinal decontamination is associated with a reduced risk of bacterial infection and mortality in high-risk group. Conclusions: The standard treatment for SBP is prompt broad-spectrum antibiotic administration and should be tailored according to community-acquired SBP, healthcare-associated or nosocomial SBP infections and local resistance profile. Since the one-year overall mortality rates for SBP range from 53.9 to 78%, liver transplantation should be seriously considered for SBP survivors who are good candidates for transplantation. Further development of non-antibiotic strategies based on pathogenic mechanisms are also urgently needed.
Thermal Dynamic Exploration of Full-Ceramic Ball Bearings under the Self-Lubrication Condition
Authors: Tian Junxing , Wu Yuhou , Sun Jian , Xia Zhongxian , Ren Kexuan , Wang He , Li Songhua , Yao Jinmei
Published: September 2022

A silicon nitride ceramic bearing has good self-lubricating characteristics. It still has a good operational status under the condition of a lack of oil. However, the temperature distribution of a silicon nitride ceramic bearing during its operation is unclear. To clarify the thermal distribution of a full-ceramic ball silicon nitride ceramic bearing under self-lubricating conditions, the changing trend of the rolling friction temperature between the rolling elements and channels with different accuracies is analyzed using the friction testing machine. The bearing heat generation model based on the silicon nitride material coefficient is established, and the life test machine measures the temperature of the bearing to verify the accuracy of the simulation model. The results show that the friction temperature between the ceramic ball and channel decreases with the increase in ceramic ball level. With an increase in the ceramic ball pressure and temperature, the friction temperature rises. Under self-lubrication, when the bearing bears a heavy load, the influence of the rotating speed on temperature rise tends to decrease. Under the condition of high speed, with the increase in load, the change range of temperature rise shows an upward trend. The important relationship between the bearing’s heat and bearing’s load and speed is revealed. It provides some theoretical guidance for the thermal analysis of a silicon nitride ceramic ball bearing under the self-lubricating condition to improve the service life and reliability of full-ceramic ball bearings.
Improving the Shipbuilding Sales Process by Selected Lean Management Tool
Authors: Kunkera Zoran , Tošanović Nataša , Štefanić Nedeljko
Published: September 2022

Market positioning, i.e., the competitiveness of European shipyards, depends a lot on the measures of continuously improving the business processes, therefore meeting the criteria of environmental protection and sustainable energy. Lean management enables ongoing improvements of all system processes by recognizing and removing the unnecessary costs of the same, i.e., those activities which do not contribute to the added value for the customer. In this paper, the authors research the magnitude of improvements in the shipbuilding sales process achieved by applying the Lean tool “Value Stream Mapping” (VSM). The example of analysing the informational stream of the studied European shipyard’s existing sales process, performed by implementing the VSM, has defined the measures to decrease the losses in the process, with an emphasis on waiting time in internal and external communication. Upon VSM of the future state, measuring improvements realised by applying key performance indicators began. Significant cost savings in the sales process and the simultaneous increase of productivity of the employees participating in those process activities have been noted, as well as the substantial growth in sales and the shipyard’s income.
Investigation on the Cage Whirl State of Cylindrical Roller Bearings under High Speed and Light Load
Authors: Zhang Jiaming , Qiu Ming , Dong Yanfang , Pang Xiaoxu , Li Junxing , Yang Chuanmeng
Published: September 2022

This paper explores the cage whirl state under different operating conditions based on the cylindrical roller bearing dynamics model. The stability and whirl characteristics of the cage whirl are evaluated by considering the rotation and force of the cage and roller. The results demonstrate that the cage whirl state is divided into three types according to the cage whirl orbit: disordered whirl, local periodic whirl and regular circular whirl. With disordered whirl, the whirl speed and whirl radius of the cage are unpredictable, and the force of the cage changes frequently. With local periodic whirl, the rotation speed, whirl speed and the force on the cage change periodically or stay constant. In the case of a regular circular whirl, the force on the cage should be considered to evaluate the stability of the cage whirl. In addition, the collision force between the roller and cage determines whether the cage whirl speed is stable or not, and the bearing slipping has no obvious effect on cage whirl stability.
Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse
Authors: Zhou Li , Liu Huwei , Zhao Junhui , Wang Fan , Yang Jianglong
Published: September 2022

The routing strategy for order picking is an important factor in the efficiency of warehouse picking, and improvements to the warehouse layout provide more routing options for picking. The number of storage locations to be visited during the picking operation also has an impact on the selection of routing strategies. In order to achieve an effective improvement in the efficiency of picking operations in warehouse distribution centers, this paper focuses on the leaf warehouse layout based on the previous single-command operation strategy and extends it to study the multi-command operation strategy, in which three heuristic routing strategies, the S-shape, the return, and the composite, are introduced to solve the walking distance problem of picking operations, with the study of the selection of the routing strategy for different numbers of storage locations to be visited. Based on the distance equation between any two storage locations to be visited in the leaf layout warehouse, travel distance models corresponding to the three routing strategies in the picking operation are constructed, and the cuckoo search algorithm is introduced to solve and calculate the travel distance of the composite strategies for the experiments. In addition, the computational experiments of the three path strategies are carried out according to the different numbers of storage locations to be visited in the picking operation. By analyzing the numerical results, we find that the composite strategy has the best overall results among the three routing strategies, with the average values of optimization rates exceeding 30% (the S-shape) and 40% (the return), respectively. At the same time, the return strategy outperforms the S-shape strategy when the number of locations to be visited is less than seven. As the number of locations to be visited increases, the S-shape strategy gradually outperforms the return strategy. From a managerial and practical perspective, compared to the single-command operation strategy that is the focus of the current research, the multi-command operation strategy we studied is more relevant to the actual situation of order merging picking in warehouses and can effectively improve the efficiency of picking operations, the competitiveness of enterprises, and customer satisfaction of e-commerce enterprises.
Numerical Research of Dynamical Behavior in Engineering Applications by Using E–E Method
Authors: Wu Tiecheng , Li Yulong , Jiang Dapeng , Zhang Yuxin
Published: September 2022

In this research, a general numerical setting has been developed by finite volume approaching for the Eulerian–Eulerian method under OpenFOAM to provide an efficient reference for industrial bubbly flows having various geometrical characteristics under different conditions. Nine different test cases were selected from chemical, nuclear, bio-processing and metallurgical engineering. We compared the predicted results with experimental findings, and the comparison proved that our implementation is correct. The numerical result has good agreement with the experimental result in most testing cases. From the analysis, we found that turbulent dispersion and drag forces were of critical importance and had to be considered in simulations. The turbulent dispersion took into account the turbulence effect, and the drag forces considered two-way coupling and ensured the good position of the Eulerian–Eulerian equations. Wall lubrication and lift forces had to be considered to solve phase fraction accumulation near walls, especially for aspect ratio pipe flows. Under other conditions, lateral forces could be neglected without any problem.
Efficient Estimation of Two-Parameter Xgamma Distribution Parameters Using Ranked Set Sampling Design
Authors: Al-Omari Amer Ibrahim , Benchiha SidAhmed , Almanjahie Ibrahim M.
Published: September 2022

An efficient method such as ranked set sampling is used for estimating the population parameters when the actual observation measurement is expensive and complicated. In this paper, we consider the problem of estimating the two-parameter xgamma (TPXG) distribution parameters under the ranked set sampling as well as the simple random sampling design. Various estimation methods, including the weighted least-square estimator, maximum likelihood estimators, least-square estimator, Cramer–von Mises, the maximum product of spacings estimators, and Anderson–Darling estimators, are considered. A comparison between the ranked set sampling and simple random sampling estimators, with the same number of measurement units, is conducted using a simulation study in terms of the bias, mean squared errors, and efficiency of estimators. The merit of the ranked set sampling estimators is examined using real data of bank customers. The results indicate that estimations using the ranked set sampling method are more efficient than the simple random sampling competitor considered in this study.
A Mutual Information-Based Network Autoregressive Model for Crude Oil Price Forecasting Using Open-High-Low-Close Prices
Authors: Sioofy Khoojine Arash , Shadabfar Mahboubeh , Edrisi Tabriz Yousef
Published: September 2022

The global financial markets are greatly affected by crude oil price movements, indicating the necessity of forecasting their fluctuation and volatility. Crude oil prices, however, are a complex and fundamental macroeconomic variable to estimate due to their nonlinearity, nonstationary, and volatility. The state-of-the-art research in this field demonstrates that conventional methods are incapable of addressing the nonlinear trend of price changes. Additionally, many parameters are involved in this problem, which adds to the complexity of such a prediction. To overcome these obstacles, a Mutual Information-Based Network Autoregressive (MINAR) model is developed to forecast the West Texas Intermediate (WTI) close crude oil price. To this end, open, high, low, and close (OHLC) prices of crude oil are collected from 1 January 2020 to 20 July 2022. Afterwards, the Mutual Information-based distance is utilized to establish the network of OHLC prices. The MINAR model provides a basis to consider the joint effects of the OHLC network interactions, the autoregressive impact, and the independent noise and establishes an intelligent tool to estimate the future fluctuations in a complex, multivariate, and noisy environment. To measure the accuracy and performance of the model, three validation measures, namely, RMSE, MAPE, and UMBRAE, are applied. The results demonstrate that the proposed MINAR model outperforms the benchmark ARIMA model.
Micropolar Nanofluid Flow in a Stagnation Region of a Shrinking Sheet with Fe3O4 Nanoparticles
Authors: Waini Iskandar , Ishak Anuar , Lok Yian Yian , Pop Ioan
Published: September 2022

Conventional liquids have poor thermal conductivity, thus limiting their use in engineering. Therefore, scientists and researchers have created nanofluids, which consist of nanoparticles dispersed in a base fluid, to improve heat transfer properties in various fields, such as electronics, medicine, and molten metals. In this study, we examine the micropolar nanofluid flow in a stagnation region of a stretching/shrinking sheet by employing the modified Buongiorno nanofluid model. The nanofluid consists of magnetite (Fe3O4) nanoparticles. The similarity equations are solved numerically using MATLAB software. The solution is unique for the shrinking strength λ≥−1. Two solutions are found for the limited range of λ when λc<λ<−1. The solutions terminate at λ=λc in the shrinking region. The rise in micropolar parameter K contributes to the increment in the skin friction coefficient Rex1/2Cf and the couple stress RexMw, but the Nusselt number Rex−1/2Nux and the Sherwood number Rex−1/2Shx decrease. These physical quantities intensify with the rise in the magnetic parameter M. Finally, we investigated the stability of the solutions over time. This work contributes to the dual solution and time stability analysis of the current problem. In addition, critical values of the main physical parameters are also presented. These critical values are usually known as the separation values from laminar to turbulent boundary layer flows. In this case, once the critical value is achieved, the process for the specific product can be planned according to the desired output to optimize the productivity.
A Framework for Project Delivery Systems via Hybrid Fuzzy Risk Analysis: Application and Extension in ICT
Authors: Bidel Mohammad Javad , Safari Hossein , Amoozad Mahdiraji Hannan , Zavadskas Edmundas Kazimieras , Antucheviciene Jurgita
Published: September 2022

One of the essential factors of project success is selecting the proper delivery method. This study aimed to provide a new hybrid decision-making framework to assist project stakeholders in evaluating and selecting the most appropriate Project Delivery System (PDS) and documenting the decision process. For this purpose, the selection factors of PDSs were obtained from a literature review, and critical selection factors were screened based on the fuzzy Delphi method, whereby expert feedback was on Information and Communication Technology (ICT) projects was obtained. Subsequently, the ICT project risks were identified and categorized into six competitive constraints, including time, cost, quality, reputation, value, and scope, and the risk factors were prioritized in each area. Then, the effect of project risks on the decision criteria was investigated using a fuzzy cognitive map (FCM). Finally, the PDSs were ranked through Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). This article researched a novel multi-layer decision system combining the FCM and FTOPSIS techniques. The decision criteria received their weights from the evaluation of the causal relationships between PDS selection factors and project risks. Thus, PDSs were ranked based on different project characteristics, the opinions of stakeholders, and the effect of project risks on the decision-making process; this increased the likelihood of project success. The results showed that the impact of the most critical project risks on the selection factors was so severe that they changed the weight of the criteria in the decision matrix and, subsequently, changed the ranking of decision options.
The Synergy of Double Neural Networks for Bridge Bidding
Authors: Zhang Xiaoyu , Lin Rongheng , Bo Yuchang , Yang Fangchun
Published: September 2022

Artificial intelligence (AI) has made many breakthroughs in the perfect information game. Nevertheless, Bridge, a multiplayer imperfect information game, is still quite challenging. Bridge consists of two parts: bidding and playing. Bidding accounts for about 75% of the game and playing for about 25%. Expert-level teams are generally indistinguishable at the playing level, so bidding is the more decisive factor in winning or losing. The two teams can communicate using different systems during the bidding phase. However, existing bridge bidding models focus on at most one bidding system, which does not conform to the real game rules. This paper proposes a deep reinforcement learning model that supports multiple bidding systems, which can compete with players using different bidding systems and exchange hand information normally. The model mainly comprises two deep neural networks: a bid selection network and a state evaluation network. The bid selection network can predict the probabilities of all bids, and the state evaluation network can directly evaluate the optional bids and make decisions based on the evaluation results. Experiments show that the bidding model is not limited by a single bidding system and has superior bidding performance.
Analysis of a Non-Discriminating Criterion in Simple Additive Weighting Deep Hierarchy
Authors: Çakır Ozan , Gürler İbrahim , Gündüzyeli Bora
Published: September 2022

In the current account, we present an analysis of a non-discriminating criterion under simple additive weighting synthesis, considering a deep decision hierarchy. A non-discriminating criterion describes a criterion where all decision alternatives under consideration perform equally. We question eliminating such a criterion from the decision hierarchy in search of simpler problem representation and computational efficiency. Yet, we prove such an approach may result in order misrepresentations between decision alternatives. This analysis is performed in the form of four research questions that relate to the detection of certain conditions under which such distortions in the order integrity of decision alternatives will occur, calculating the change in their final performances, distinguishing the alternatives whose performances are consistent, and examining the role of the normalization procedure adopted in averting such distortions when the non-discriminating criterion is ignored. Along these lines, this study provides clear inferences which are of interest to researchers and decision makers, using simple additive weighting and similar methods that rely on additive synthesis.
A New Regression Model on the Unit Interval: Properties, Estimation, and Application
Authors: Benites Yury R. , Cancho Vicente G. , Ortega Edwin M. M. , Vila Roberto , Cordeiro Gauss M.
Published: September 2022

A new and flexible distribution is introduced for modeling proportional data based on the quantile of the generalized extreme value distribution. We obtain explicit expressions for the moments, quantiles, and other structural properties. An extended regression model is constructed as an alternative to compete with the beta regression. Some simulations from the Bayesian perspectives are developed, and an illustrative application to real data involving the comparison of models and influence diagnostics is also addressed.
Generalized Johnson Distributions and Risk Functionals
Authors: Floros Christos , Gkillas Konstantinos , Kountzakis Christos
Published: September 2022

In this paper, we study the generalized Johnson distributions’ class and its applications in finance and risk theory. The recent literature on Johnson distributions displays a better gooodness of fitting for data coming from financial markets, such as portfolio returns. However, a gereral question in risk theory and finance is the following: Which class of distributions is more appropriate in order to determine the behaviour of data coming from financial markets and insurance claims? Another question is the following one: Is ther any class of distributions that is appropriate for calculations related to any kind of risk faced by financial isntitutions and insurance companies? The answer proposed to these questions is the use of generalized Johnson’s distributions. The parameters of such distributions are estimated by the order statistics of a single or more samples. Risk functionals represent a unified approach comprising every kind of risk metric. Risk functionals include value-at-risk and expected shortfall, coherent risk measures, and endpoints and thresholds. We deduce that the risk functionals sastisfy convexity—like properties with respect to finitely-mixed distributions. We also prove in detail that the empirical distribution is a reasonable way for the estimation of the above risk functionals. In the Appendix, we provide two numerical examples for fitting samples of portfolio returns under the Johnson’s transformation.
Analysis of Jet Wall Flow and Heat Transfer Conveying ZnO-SAE50 Nano Lubricants Saturated in Darcy-Brinkman Porous Medium
Authors: Khan Umair , Zaib Aurang , Ishak Anuar , Waini Iskandar , M. Sherif El-Sayed , Pop Ioan
Published: September 2022

The problem of 2D (two-dimensional) wall jet flow, along with heat transfer incorporated by nanofluid in a Darcy-Brinkman medium, while recognizing the requirement for efficient heating and cooling systems. Following the use of similarity variables, the resultant system of ODEs (ordinary differential equations) is solved using the well-known and efficient bvp4c (boundary-value problem of the 4th order) technique. The significance of physical quantities for the under-consideration parameters is illustrated and explained. The findings show that the nanoparticle volume fraction and porosity parameters decrease the velocity, but increase the temperature. In addition, the temperature uplifts in the presence of radiation effect. The suction parameter initially decreases and then increases the velocity near the surface, while the temperature declines.
Fuzzy Logic and Soft Computing—Dedicated to the Centenary of the Birth of Lotfi A. Zadeh (1921–2017)
Authors: Nădăban Sorin
Published: September 2022

In 1965, Lotfi A. Zadeh published “Fuzzy Sets”, his pioneering and controversialpaper, which has now reached over 115,000 citations [...]
SemG-TS: Abstractive Arabic Text Summarization Using Semantic Graph Embedding
Authors: Etaiwi Wael , Awajan Arafat
Published: September 2022

This study proposes a novel semantic graph embedding-based abstractive text summarization technique for the Arabic language, namely SemG-TS. SemG-TS employs a deep neural network to produce the abstractive summary. A set of experiments were conducted to evaluate the performance of SemG-TS and to compare the results to those of a popular baseline word embedding technique called word2vec. A new dataset was collected for the experiments. Two evaluation methodologies were followed in the experiments: automatic and human evaluations. The Rouge evaluation measure was used for the automatic evaluation, while for the human evaluation, Arabic native speakers were tasked to evaluate the relevancy, similarity, readability, and overall satisfaction of the generated summaries. The obtained results prove the superiority of SemG-TS.
Neural Network-Based Modeling for Risk Evaluation and Early Warning for Large-Scale Sports Events
Authors: Zhong Chenghao , Lou Wengao , Wang Chuting
Published: September 2022

[Problem] The risks of hosting large-scale sports events are very difficult to evaluate and often directly affected by natural environment risks, events management risks, and social environment risks. Before hosting the events, accurately assessing these risks can effectively minimize the occurrence of risks and reduce the subsequent losses. [Aim] In this article, we advocate the use of a back propagation neural network (BPNN) model for risk evaluation and early warning of large-scale sports events. [Methods] We first use expert surveys to assess the risks of 28 large-scale sports events using 12 indicators associated with climate conditions, events management, and natural disasters. We then apply the BPNN model to evaluate the risks of 28 large-scale sports events with sufficient samples by adding white noise with mean zero and small variance to the small actual samples. We provide a general rule to establish a BPNN model with insufficient and small samples. [Results] Our research results show that the recognition accuracy of the established BPNN model is 86.7% for the 15 simulation samples and 100% for the 28 actual samples. Based on this BPNN model, we determined and ranked the risk level of the events and the importance of each indicator. Thus, sample S8 had the highest risk and the second highest was sample S14, and indicator nine was the most important and indicator one the least important. [Conclusions] We can apply the established BPNN model to conveniently evaluate the risk of hosting a large-scale sports event. By analyzing the nonlinear relationship between each indicator and the risk of the sports event, and applying the established BPNN model, we can propose more targeted and effective measures and suggestions for eliminating and decreasing the risks of hosting a large-scale sports event, and ensure large-scale sports events can be successfully hosted.
Relationship between Mental Health and Socio-Economic, Demographic and Environmental Factors in the COVID-19 Lockdown Period—A Multivariate Regression Analysis
Authors: Bonnini Stefano , Borghesi Michela
Published: September 2022

Amongst the several consequences of the COVID-19 pandemic, we should include psychological effects on the population. The mental health consequences of lockdown are affected by several factors. The most important are: the duration of the social isolation period, the characteristics of the living space, the number of online (virtual) and offline (physical) contacts and perceived contacts’ closeness, individual characteristics, and the spread of infection in the geographical area of residence. In this paper, we investigate the possible effects of environmental, social and individual characteristics (predictors) on mental health (response) during the COVID-19 lockdown period. The relationship between mental health and predictors can be studied with a multivariate linear regression model, because “mental health” is a multidimensional concept. This work provides a contribution to the debate about the factors affecting mental health in the period of the COVID-19 lockdown, with the application of an innovative approach based on a multivariate regression analysis and a combined permutation test on data collected in a survey conducted in Italy in 2020.
Analysis of a Class of Predation-Predation Model Dynamics with Random Perturbations
Authors: Tan Xuewen , Liu Pengpeng , Luo Wenhui , Chen Hui
Published: September 2022

In this paper, we study a class of predation–prey biological models with random perturbation. Firstly, the existence and uniqueness of systematic solutions can be proven according to Lipschitz conditions, and then we prove that the systematic solution exists globally. Moreover, the article discusses the long-term dynamical behavior of the model, which studies the stationary distribution and gradual properties of the system. Next, we use two different methods to give the conditions of population extinction. From what has been discussed above, we can safely draw the conclusion that our results are reasonable by using numerical simulation.
Numerical Simulation for Brinkman System with Varied Permeability Tensor
Authors: El Ouadefli Lahcen , El Akkad Abdeslam , El Moutea Omar , Moustabchir Hassan , Elkhalfi Ahmed , Luminița Scutaru Maria , Muntean Radu
Published: September 2022

The aim of this paper is to study a stationary Brinkman problem in an anisotropic porous medium by using a mini-element method with a general boundary condition. One of the important aspects of the P1−Bubble/P1 method is satisfying the inf-sup condition, which allows us the existence and the uniqueness of the weak solution to our problem. To go further in this theoretical study, an a priori error estimate is established. To see the importance of this method in reality, we applied this method to a real problem. The numerical simulation studies support our results and demonstrate the effectiveness of this method.