Miracle-dz/UniFAR-FTUs huggingface dataset:
The Correlation between the Financial Cycle and Business Cycle: Evidence from China at Different Event Periods

This paper uses EMD method to construct the structural components of the financial cycle and business cycle and analyzes their lead-lag relationships and dynamic correlation mechanism at three specific periods (2008Q3, 2012Q3, and 2017Q3). We find that during the period of the financial crisis, financial cyclical fluctuations precede business cyclical fluctuations; during the period of the new normal of the economy, the peaks and valleys of the financial cycle and the business cycle are the same; during the period of strong financial supervision, the business cycle precedes the financial cycle. Furthermore, compared with the other two periods, the negative effects of financial shocks during the period of strong financial supervision are largest, the spillover effect of the financial cycle on the business cycle is strongest.
A Survey on Information-Centric Networking with Cloud Internet of Things and Artificial Intelligence

The Internet is evolving, and data is a critical component of today’s Internet. People are more interested in data than data location. An information-centric network (ICN) uses this idea and makes data, instead of host addresses, an integral component. Another essential topic in the contemporary period is cloud or edge computing, as well as the Internet of Things (IoT) and Artificial Intelligence (AI), which becomes even more critical when combined with ICN. We initially rate the configuration of ICN with cloud or edge IoT and AI (ICN-CIoT-AI) in this study so that readers may learn about the latest trends and merging of ICN-CIoT-AI. As data rates rise and the Internet becomes a requirement for any technology, we require IoT settings in which data can be cached locally, which is possible when ICN collaborates with cloud or edge computing. To make this arrangement more intelligent, we require AI, and machine learning algorithms can help to overcome many obstacles. In this paper, we first discuss ICN, its deployment, and its unique features that distinguish it from its archrival TCP/IP. We then present the most recent research on ICN-CIoT-AI and provide a comprehensive analysis of this domain in terms of technology, AI/ML domain, IoT, and cloud technology. The study framework, simulation software, and results achieved by the researchers are also listed. Finally, we explore three broad categories of open issues and challenges raised by the researchers: security, performance, and in-network caching. We also exhibit the technologies that were employed in the study.
Curing Effect and Resistivity Evolution of Zinc-Contaminated Red Clay Cured by Phosphate-Based Binder

Curing agent is often used in the in situ remediation of industrial contaminated sites. The reaction between curing agent and contaminated soil has a great impact on the conductivity of soil. Quantitative analysis of the resistivity evolution of cured contaminated soil is an important prerequisite for the accurate evaluation of the in situ remediation effect of heavy metal contaminated sites. In this paper, the pH value, unconfined compressive strength, and resistivity evolution of Zn-contaminated red clay cured with new phosphate-based binder (KMP) at different curing ages were tested, and the internal relationship between the KMP content and the metal ion content and the pH value, unconfined compressive strength, and resistivity evolution were analyzed. The curing effect of KMP, Zn2+ concentration, and curing age on contaminated soil was further evaluated. The results show that the unconfined compressive strength of red clay is weakened with the increase of Zn2+ concentration. The curing effect of KMP on zinc-contaminated red clay is obvious. The pH control of KMP curing agent on zinc-contaminated red clay is effective, and the pH value within 10.5 can effectively stabilize metal ion leaching. There is a good linear relationship between KMP content and curing age and resistivity. Under uniaxial compression, the resistivity decreases with the increase of stress at different Zn2+ concentrations, and the minimum value of the resistivity corresponds to the peak value of uniaxial compression. It provides possibility for the application of resistivity method in the study of mechanical strength properties of red clay.
InteliRank: A Four-Pronged Agent for the Intelligent Ranking of Cloud Services Based on End-Users’ Feedback

Cloud Computing (CC) provides a combination of technologies that allows the user to use the most resources in the least amount of time and with the least amount of money. CC semantics play a critical role in ranking heterogeneous data by using the properties of different cloud services and then achieving the optimal cloud service. Regardless of the efforts made to enable simple access to this CC innovation, in the presence of various organizations delivering comparative services at varying cost and execution levels, it is far more difficult to identify the ideal cloud service based on the user’s requirements. In this research, we propose a Cloud-Services-Ranking Agent (CSRA) for analyzing cloud services using end-users’ feedback, including Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and Software as a Service (SaaS), based on ontology mapping and selecting the optimal service. The proposed CSRA possesses Machine-Learning (ML) techniques for ranking cloud services using parameters such as availability, security, reliability, and cost. Here, the Quality of Web Service (QWS) dataset is used, which has seven major cloud services categories, ranked from 0–6, to extract the required persuasive features through Sequential Minimal Optimization Regression (SMOreg). The classification outcomes through SMOreg are capable and demonstrate a general accuracy of around 98.71% in identifying optimum cloud services through the identified parameters. The main advantage of SMOreg is that the amount of memory required for SMO is linear. The findings show that our improved model in terms of precision outperforms prevailing techniques such as Multilayer Perceptron (MLP) and Linear Regression (LR).
Determining High-Frequency Conductivity Based on Shielding Effectiveness Measurement Using Rectangular Waveguides

Determining the high-frequency conductivity of a material is one of the critical steps in material characterization. In this paper, we introduce a new technique for determining the conductivity which is based on shielding effectiveness measurement in a rectangular waveguide. The proposed method has been validated using the simulation and measurement. The proposed method has shown a very good accuracy for determining the conductivity and has significant advantages over traditional techniques, such as simple setup/postprocessing, no need for vector measurement, high repeatability, and being capable of measuring high conductivities precisely. Besides these advantages, the proposed method has some limitation such as being suitable for good and/or thick conductors.
An Improved A-Star Algorithm Considering Water Current, Traffic Separation and Berthing for Vessel Path Planning

A traditional A-Star (A*) algorithm generates an optimal path by minimizing the path cost. For a vessel, factors of path length, obstacle collision risk, traffic separation rule and manoeuvrability restriction should be all taken into account for path planning. Meanwhile, the water current also plays an important role in voyaging and berthing for vessels. In consideration of these defects of the traditional A-Star algorithm when it is used for vessel path planning, an improved A-Star algorithm has been proposed. To be specific, the risk models of obstacles (bridge pier, moored or anchored ship, port, shore, etc.) considering currents, traffic separation, berthing, manoeuvrability restriction have been built firstly. Then, the normal path generation and the berthing path generation with the proposed improved A-Star algorithm have been represented, respectively. Moreover, the problem of combining the normal path and the berthing path has been also solved. To verify the effectiveness of the proposed A-Star path planning methods, four cases have been studied in simulation and real scenarios. The results of experiments show that the proposed A-Star path planning methods can deal with the problems denoted in this article well, and realize the trade-off between the path length and the navigation safety.
Identifying New Knowledge Areas to Strengthen the Project Management Institute (PMI) Framework

Abstract In an increasingly volatile, uncertain, complex and ambiguous (VUCA) world, managers of capital projects are under relentless pressure to consistently meet their performance expectations. At the execution stage, managers have to constantly orchestrate competing demands on scare resources and, simultaneously, manage project operations to meet time, costs and quality compliances. This calls for simple methods to distinguish factors that could cause execution stage delays and prioritise their remedial actions. The objective, therefore, was to propose and test a methodology through empirical evidence, which could be useful for managers to focus on the distinguishing factors (rather than on all factors) to achieve execution excellence. We used a three-stage methodology leveraging the existing Project Management Institute (PMI) framework to define variables and then tested the methodology using case data generated from projects adopting a grounded theory approach. A set-theoretic, multi-value qualitative comparative analysis (QCA) tool helped appropriately configure this empirical case data and a subsequent Boolean minimisation technique then identified the distinguishing factor(s) that explained superior project schedule performance. The results corroborated literature findings. Two contributions emerged from this study: (a) our methodology enabled a richer analysis of the case than what would have been possible by adopting a more conventional approach; and (b) there is a potential for a domain-specific extension of the PMI framework to cover technology transfer projects having their unique knowledge areas.
Is Avoidable Hospitalization Experienced Prior to Infection Associated With COVID-19-Related Deaths?

Objectives: This study aimed to determine the effect of the presence or absence of avoidable hospitalization before acquiring coronavirus disease (COVID-19) on COVID-19-related deaths. Methods: This study used the total NHIS-COVID-19 dataset comprising domestic COVID-19 patients, provided by the National Health Insurance Service (NHIS) in South Korea. We conducted logistic regression and double robust estimation (DRE) to confirm the effect of avoidable hospitalization on COVID-19-related deaths. Results: Logistic regression analysis confirmed that the odds ratio (OR) of death due to COVID-19 was high in the group that experienced avoidable hospitalization. DRE analysis showed a higher OR of death due to COVID-19 in the group that experienced avoidable hospitalization compared to the group that did not experience avoidable hospitalization, except in the subgroup aged ≤69 years. Conclusion: The effect of avoidable hospitalization on COVID-19-related deaths was confirmed. Therefore, continued health care, preventive medicine, and public health management are essential for reducing avoidable hospitalizations despite the COVID-19 pandemic. Clinicians need to be informed about the importance of continuous disease management.
Generative Oversampling Method for Imbalanced Data on Bearing Fault Detection and Diagnosis

In this study, we developed a novel data-driven fault detection and diagnosis (FDD) method for bearing faults in induction motors where the fault condition data are imbalanced. First, we propose a bearing fault detector based on convolutional neural networks (CNN), in which the vibration signals from a test bench are used as inputs after an image transformation procedure. Experimental results demonstrate that the proposed classifier for FDD performs well (accuracy of 88% to 99%) even when the volume of normal and fault condition data is imbalanced (imbalance ratio varies from 20:1 to 200:1). Additionally, our generative model reduces the level of data imbalance by oversampling. The results improve the accuracy of FDD (by up to 99%) when a severe imbalance ratio (200:1) is assumed.
Effect of Mixed Substrates with Rice Straw on Cultivation of Pleurotus ostreatus

This study was carried out to investigate the effect of several agro-industrial wastes and mixed substrates with rice straw (w/w) on production of ( Pleurotus ostreatus ). Mixed substrates with rice straw at rate 1:1 by weight showed higher effect on the first stage, second and third stages. Data indicated that the time for production ranged from 12 25.5, from 22 52.25 and from 25 55 days respectively. When mixed substrates with rice straw the results were found within the period ranged from 11.75 18.5, from 22.5 -28.5 and from 26.5 32 days respectively. Mixed substrates with rice straw reduce the first stage time of oyster compare with the control substrates. Therefore, reduce pinheads and fruiting bodies formation period. The mixed substrates rice straw with waste paper (RS+WP) gave the maximum of oyster mushroom produced per 1 kg dry ~ 578.50 g and gave the maximum biological efficiency 57.85 %. Finally, mixed substrates with rice straw increase in biological efficiency of P. ostreatus over control substrates.
Modeling and analysis of centralized demand response with two‐way communication in a microgrid

Real‐time imbalance between demand and supply due to either consumers' unforeseen activities or wide penetration of renewable energy resource has become one of the critical factors to our daily power quality. To address the real‐time imbalance challenge, demand response (DR) management is imperative in a smart grid, as it can effectively shape the total load from the demand side. We have presented a concept of a new DR architecture, which is characterized by controlling DR clients in each home with two‐way communication for demand management, while in a conventional way DR clients are controlled by a central server with specific signals differing from one device to another. The proposed architecture offers the advantages of high adjustment capability, less communication overhead, improved scalability, and universality. In this article, we model the proposed DR architecture in detail from the viewpoint of DR clients and server, and analyze the feasibility of it by conducting extensive simulations. The results demonstrate that the proposed DR architecture is efficient and effective in stabilizing power quality in terms of the change rate of total load and power frequency. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Characterizing Adolescents' Dietary Intake by Taste: Results From the UK National Diet and Nutrition Survey

The taste of foods is a key factor for adolescents' food choices and intakes, yet, exploring taste characteristics of adolescents' diet is limited. Using food records for 284 adolescents (10–19 years old) from the National Diet and Nutrition Survey (NDNS), year 9 (2016–2017), we classified diets according to taste. Tastes for each food consumed were generated from a previous survey that asked participants to allocate one main taste to each food. Responses from that survey were processed and included in a Hierarchical Cluster Analysis (HCA) to identify taste clusters. The resulting tastes were then applied to the adolescents' food records in the NDNS. For each individual, the total weight of food per day for each taste was calculated. A linear regression model was used to explore dietary intakes from each taste. Findings reveal that adolescents' daily energy intake was highest (34%) from foods that taste sweet. Sweet foods were the main calorie contributors at breakfast and daytime snacking, while energy intake from neutral-tasting foods was higher at lunch and dinner. Sweet food intake was significantly positively associated with higher energy, sugar, and fat intakes. For each percentage increase in sweet foods, energy increased by 10 kcal/d (95% CI 6, 15; P < 0.01). Savory food intake was lower in carbohydrates and sugars; with neutral food consumption inversely associated with energy, carbohydrate, sugars, saturated and total fat. Higher salty food intake was linked to higher saturated fat as well as sodium consumption. Sweet and neutral foods dominate the UK adolescent diet, followed by savory tastes. Balancing the contributions of different tasting foods could assist in improving adolescent diet quality.
Molecular Characterization of Bacillus sp. with Inter- Simple Sequence Repeat (ISSR) Markers

R.E. EL-Kholy(*) Abstract : Interspecific crosses between some mutants by EMS belonging to both two species (B. subtilis NRRL B3411 and B. licheniformis 11945 BT3) gave some hybrids produced 1.5 folds α-amylase enzyme comparing with parental strains. Inter-simple sequence repeat (ISSR) markers were used to investigate genetic diversity among of isolates of Bacillus and Genetic variations of thirteen Bacillus species were evaluated using random amplified polymorphic DNA. The amplified products varied in size from 1502537 bp. The SDS-PAGE protein banding pattern of these hybrids was performed and compared with protein banding pattern of their parental strains. Furthermore determination of the α-amylase produced by the thirteen selected strains. African Stud. Rev. Vol. ( 41 ) ( 2017 ) : 1 20
Determinants of Credit Risk in Ethiopian Banking Industry: Does Political Stability Matter?

The continued political instability in Ethiopia’s Tigray Region has made it tough for bankers to recover loan repayments, triggering banks’ nonperforming assets to rise. Beyond the bank industry-specific and macroeconomic determinants, the article aims to understand the relationship between political stability and credit risk. The article focuses on 16 Ethiopian banks to understand the mentioned relationship in developing countries. From 2010 to 2020, data are obtained from the World Governance Indicators, World Development Indicators database and Ethiopia’s National Bank. Based on a two-step dynamic panel estimator, the results suggest that political stability is negatively correlated with credit risk, while political instability does have a positive impact on bank credit risk. Credit risk was inversely related to increased operating efficiency, diversified earnings and national currency appreciation. In contrast, greater bank size, rising inflation and economic expansion all contribute to a high level of credit risk. The loan-to-asset ratio and profitability were shown to have a minor influence on nonperforming loans (NPLs). Thus, this study provides a better understanding of the effects of political stability on the factors that determine levels of NPLs in developing economies.
Implementation of Building Information Modeling (BIM) in Pakistan Construction Industry

This paper examines the implementation of building information modeling (BIM) in construction industry. Various initiatives and approaches are used in different countries to promote the BIM implementation in their construction industries. The real implementation and use of BIM remains a major concern of the construction industry. This study investigates the implantation of BIM globally, in developed countries and the percentage of implementation of BIM in constriction industry of Sindh, Pakistan. This research demonstrates 131 responses from BIM users regarding BIM implementation whose collaboration aspects produce the highest positive impact. The adopted methodology is an online questionnaire survey and literature review which was conducted to find out the implementation of BIM in construction industries of developed countries. This research reveals that BIM implementation is increasing continuously over the past few years. A Number of developed countries are emerging successful BIM implementation strategies, United States, United Kingdom, Germany, France are generally leading the way. However, according to our study findings, only 11% of industries have implemented BIM in Sindh, Pakistan.
Propulsive performance of a twin-rectangular-foil propulsor in a counterphase oscillation

Analysis of propulsive thrust and efficiency of a finite aspect ratio, twin-foil counterphase wing-in-ground (WIG) effect propulsor configuration is made using a time-domain panel method. Comparisons were made for the effects of number of foils (single versus double), aspect ratio, variable distance between two foils with fixed heave amplitude-that is, influence of interaction, and heave amplitude with fixed distance. In addition to the apparent advantage of propulsor dynamics equilibrium due to the cancellation of the side and vertical forces, results show that each foil of the twin-foil configuration, when close to each other to generate the WIG effect, has substantially higher thrust contribution than the single-foil propulsor under moderate to heavy load conditions (reduced frequency greater than 0.5). Due to the interaction of foils on each other, increase of thrust also produced a higher efficiency over the whole range of reduced frequencies examined. Findings also include the tendency of the thrust and efficiency due to both the fixed heave amplitude with varied distance between foil equilibrium position and fixed distance with varied heave amplitude. Twin-foil counterphase oscillating propulsors show an aerodynamic and hydrodynamic advantage for micro air vehicles (MAV) and autonomous underwater vehicles (AUV) over the single-foil configuration.
HVDC Transmission Technology of Wind Power System with Multi-Phase PMSG

The high voltage DC (HVDC) transmission technology of wind power system, with multi-phase permanent magnetic synchronous generator (PMSG) is proposed in this paper. Each set of three-phase winding of the multi-phase PMSG was connected to a diode rectifier. The output of the diode rectifier was connected by several parallel isolated DC–DC converters. Each DC–DC converter was connected to a sub-module (SM). All SMs and two inductors were connected in a series. The proposed wind power system has several advantages including, transformerless operation, low cost, low voltage stress, and high fault tolerance. The maximum power point tracking (MPPT) and energy balance of the DC–DC converters were achieved by controlling the duty cycles of the DC–DC converters. The HVDC transmission was achieved by the nearest level control (NLC) with voltage sorting. The simulation model with 18-phase PMSG was established. Experimental results were also studied based on RT-Lab.