bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimized Placement of Frost-Measuring Sensors in Heat Exchangers via Image Processing of Frost Formation Pattern
Authors: Aguiar Martim , Gaspar Pedro Dinis , Silva Pedro Dinho
Published: June 2023

Heat exchangers (HXs) play a critical role in maintaining human thermal comfort and ensuring product safety and quality in various industries. However, the formation of frost on HX surfaces during cooling operations can significantly impact their performance and energy efficiency. Traditional defrosting methods primarily rely on time-based control of heaters or HX operation, overlooking the actual frost formation pattern across the surface. This pattern is influenced by ambient air conditions (humidity and temperature) and surface temperature variations. To address this issue, frost formation sensors can be strategically placed within the HX. However, the non-uniform frost pattern poses challenges in sensor placement. This study proposes an optimized sensor placement approach using computer vision and image processing techniques to analyze the frost formation pattern. Through creating a frost formation map and evaluating various sensor locations, frost detection can be optimized to control defrosting operations with higher accuracy, thereby enhancing the thermal performance and energy efficiency of HXs. The results demonstrate the effectiveness of the proposed method in accurately detecting and monitoring frost formation, providing valuable insights for sensor placement optimization. This approach presents significant potential in enhancing the overall performance and sustainability of the operation of HXs.
A Quantitative Evaluation of the Performance of the Low-Cost AudioMoth Acoustic Recording Unit
Authors: Lapp Sam , Stahlman Nickolus , Kitzes Justin
Published: June 2023

The AudioMoth is a popular autonomous recording unit (ARU) that is widely used to record vocalizing species in the field. Despite its growing use, there have been few quantitative tests on the performance of this recorder. Such information is needed to design effective field surveys and to appropriately analyze recordings made by this device. Here, we report the results of two tests designed to evaluate the performance characteristics of the AudioMoth recorder. First, we performed indoor and outdoor pink noise playback experiments to evaluate how different device settings, orientations, mounting conditions, and housing options affect frequency response patterns. We found little variation in acoustic performance between devices and relatively little effect of placing recorders in a plastic bag for weather protection. The AudioMoth has a mostly flat on-axis response with a boost above 3 kHz, with a generally omnidirectional response that suffers from attenuation behind the recorder, an effect that is accentuated when it is mounted on a tree. Second, we performed battery life tests under a variety of recording frequencies, gain settings, environmental temperatures, and battery types. We found that standard alkaline batteries last for an average of 189 h at room temperature using a 32 kHz sample rate, and that lithium batteries can last for twice as long at freezing temperatures compared to alkaline batteries. This information will aid researchers in both collecting and analyzing recordings generated by the AudioMoth recorder.
BBSF: Blockchain-Based Secure Weather Forecasting Information through Routing Protocol in Vanet
Authors: Sohail Hamza , Hassan Mahmood ul , Elmagzoub M. A. , Rajab Adel , Rajab Khairan , Ahmed Adeel , Shaikh Asadullah , Ali Abid , Jamil Harun
Published: June 2023

A vehicular ad hoc network (VANET) is a technique that uses vehicles with the ability to sense data from the environment and use it for their safety measures. Flooding is a commonly used term used for sending network packets. VANET may cause redundancy, delay, collision, and the incorrect receipt of the messages to their destination. Weather information is one of the most important types of information used for network control and provides an enhanced version of the network simulation environments. The network traffic delay and packet losses are the main problems identified inside the network. In this research, we propose a routing protocol which can transmit the weather forecasting information on demand based on source vehicle to destination vehicles, with the minimum number of hop counts, and provide significant control over network performance parameters. We propose a BBSF-based routing approach. The proposed technique effectively enhances the routing information and provides the secure and reliable service delivery of the network performance. The results taken from the network are based on hop count, network latency, network overhead, and packet delivery ratio. The results effectively show that the proposed technique is reliable in reducing the network latency, and that the hop count is minimized when transferring the weather information.
A Novel Smart CFRP Cable Based on Optical Electrical Co-Sensing for Full-Process Prestress Monitoring of Structures
Authors: Yang Huanyu , Shao Lian , Ou Jinping , Zhou Zhi
Published: June 2023

Carbon-fiber-reinforced polymer (CFRP) is a type of composite material with many superior performances, such as high tensile strength, light weight, corrosion resistance, good fatigue, and creep performance. As a result, CFRP cables have great potential to replace steel cables in prestressed concrete structures. However, the technology to monitor the stress state in real-time throughout the entire life cycle is very important in the application of CFRP cables. Therefore, an optical–electrical co-sensing CFRP cable (OECSCFRP cable) was designed and manufactured in this paper. Firstly, a brief description is outlined for the production technology of the CFRP-DOFS bar, CFRP-CCFPI bar, and CFRP cable anchorage technology. Subsequently, the sensing and mechanical properties of the OECS-CFRP cable were characterized by serious experiments. Finally, the OECS-CFRP cable was used for the prestress monitoring of an unbonded prestressed RC beam to verify the feasibility of the actual structure. The results show that the main static performance indexes of DOFS and CCFPI meet the requirements of civil engineering. In the loading test of the prestressed beam, the OECS-CFRP cable can effectively monitor the cable force and the midspan defection of the beam so as to obtain the stiffness degradation of the prestressed beam under different loads.
New Water-Soluble Poly(propylene imine) Dendrimer Modified with 4-Sulfo-1,8-naphthalimide Units: Sensing Properties and Logic Gates Mimicking
Authors: Said Awad I. , Staneva Desislava , Grabchev Ivo
Published: June 2023

A new water-soluble poly(propylene imine) dendrimer (PPI) modified with 4-sulfo-1,8-naphthalimid units (SNID) and its related structure monomer analog (SNIM) has been prepared by a simple synthesis. The aqueous solution of the monomer exhibited aggregation-induced emission (AIE) at 395 nm, while the dendrimer emitted at 470 nm due to an excimer formation beside the AIE at 395 nm. Fluorescence emission of the aqueous solution of either SNIM or SNID was significantly affected by traces of different miscible organic solvents, and the limits of detection were found to be less than 0.05% (v/v). Moreover, SNID exhibited the function to execute molecular size-based logic gates where it mimics XNOR and INHIBIT logic gates using water and ethanol as inputs and the AIE/excimer emissions as outputs. Hence, the concomitant execution of both XNOR and INHIBIT enables SNID to mimic digital comparators.
Optical Systems Identification through Rayleigh Backscattering
Authors: Nadimi Goki Pantea , Mulugeta Thomas Teferi , Caldelli Roberto , Potì Luca
Published: June 2023

We introduce a technique to generate and read the digital signature of the networks, channels, and optical devices that possess the fiber-optic pigtails to enhance physical layer security (PLS). Attributing a signature to the networks or devices eases the identification and authentication of networks and systems thus reducing their vulnerability to physical and digital attacks. The signatures are generated using an optical physical unclonable function (OPUF). Considering that OPUFs are established as the most potent anti-counterfeiting tool, the created signatures are robust against malicious attacks such as tampering and cyber attacks. We investigate Rayleigh backscattering signal (RBS) as a strong OPUF to generate reliable signatures. Contrary to other OPUFs that must be fabricated, the RBS-based OPUF is an inherent feature of fibers and can be easily obtained using optical frequency domain reflectometry (OFDR). We evaluate the security of the generated signatures in terms of their robustness against prediction and cloning. We demonstrate the robustness of signatures against digital and physical attacks confirming the unpredictability and unclonability features of the generated signatures. We explore signature cyber security by considering the random structure of the produced signatures. To demonstrate signature reproducibility through repeated measurements, we simulate the signature of a system by adding a random Gaussian white noise to the signal. This model is proposed to address services including security, authentication, identification, and monitoring.
Fine-Tuned Temporal Dense Sampling with 1D Convolutional Neural Network for Human Action Recognition
Authors: Lim Kian Ming , Lee Chin Poo , Tan Kok Seang , Alqahtani Ali , Ali Mohammed
Published: June 2023

Human action recognition is a constantly evolving field that is driven by numerous applications. In recent years, significant progress has been made in this area due to the development of advanced representation learning techniques. Despite this progress, human action recognition still poses significant challenges, particularly due to the unpredictable variations in the visual appearance of an image sequence. To address these challenges, we propose the fine-tuned temporal dense sampling with 1D convolutional neural network (FTDS-1DConvNet). Our method involves the use of temporal segmentation and temporal dense sampling, which help to capture the most important features of a human action video. First, the human action video is partitioned into segments through temporal segmentation. Each segment is then processed through a fine-tuned Inception-ResNet-V2 model, where max pooling is performed along the temporal axis to encode the most significant features as a fixed-length representation. This representation is then fed into a 1DConvNet for further representation learning and classification. The experiments on UCF101 and HMDB51 demonstrate that the proposed FTDS-1DConvNet outperforms the state-of-the-art methods, with a classification accuracy of 88.43% on the UCF101 dataset and 56.23% on the HMDB51 dataset.
Quantification of Extramyocellular Lipids and Intramuscular Fat from Muscle Echo Intensity in Lower Limb Muscles: A Comparison of Four Ultrasound Devices against Magnetic Resonance Spectroscopy
Authors: Piponnier Enzo , Ishikawa Masaki , Kunimasa Yoko , Sano Kanae , Jagot Kévin , Boisseau Nathalie , Kurihara Toshiyuki , Martin Vincent
Published: June 2023

This study aimed to compare different ultrasound devices with magnetic resonance spectroscopy (MRS) to quantify muscle lipid content from echo intensity (EI). Four different ultrasound devices were used to measure muscle EI and subcutaneous fat thickness in four lower-limb muscles. Intramuscular fat (IMF), intramyocellular (IMCL) and extramyocellular lipids (EMCL) were measured using MRS. Linear regression was used to compare raw and subcutaneous fat thickness-corrected EI values to IMCL, EMCL and IMF. IMCL had a poor correlation with muscle EI (r = 0.17–0.32, NS), while EMCL (r = 0.41–0.84, p < 0.05–p < 0.001) and IMF (r = 0.49–0.84, p < 0.01–p < 0.001) had moderate to strong correlation with raw EI. All relationships were improved when considering the effect of subcutaneous fat thickness on muscle EI measurements. The slopes of the relationships were similar across devices, but there were some differences in the y-intercepts when raw EI values were used. These differences disappeared when subcutaneous fat thickness-corrected EI values were considered, allowing for the creation of generic prediction equations (r = 0.41–0.68, p < 0.001). These equations can be used to quantify IMF and EMCL within lower limb muscles from corrected-EI values in non-obese subjects, regardless of the ultrasound device used.
Determination of Sugars and Acids in Grape Must Using Miniaturized Near-Infrared Spectroscopy
Authors: Cornehl Lucie , Krause Julius , Zheng Xiaorong , Gauweiler Pascal , Schwander Florian , Töpfer Reinhard , Gruna Robin , Kicherer Anna
Published: June 2023

An automatic determination of grape must ingredients during the harvesting process would support cellar logistics and enables an early termination of the harvest if quality parameters are not met. One of the most important quality-determining characteristics of grape must is its sugar and acid content. Among others, the sugars in particular determine the quality of the must and wine. Chiefly in wine cooperatives, in which a third of all German winegrowers are organized, these quality characteristics serve as the basis for payment. They are acquired upon delivery at the cellar of the cooperative or the winery and result in the acceptance or rejection of grapes and must. The whole process is very time-consuming and expensive, and sometimes grapes that do not meet the quality requirements for sweetness, acidity, or healthiness are destroyed or not used at all, which leads to economic loss. Near-infrared spectroscopy is now a widely used technique to detect a wide variety of ingredients in biological samples. In this study, a miniaturized semi-automated prototype apparatus with a near-infrared sensor and a flow cell was used to acquire spectra (1100 nm to 1350 nm) of grape must at defined temperatures. Data of must samples from four different red and white Vitis vinifera (L.) varieties were recorded throughout the whole growing season of 2021 in Rhineland Palatinate, Germany. Each sample consisted of 100 randomly sampled berries from the entire vineyard. The contents of the main sugars (glucose and fructose) and acids (malic acid and tartaric acid) were determined with high-performance liquid chromatography. Chemometric methods, using partial least-square regression and leave-one-out cross-validation, provided good estimates of both sugars (RMSEP = 6.06 g/L, R2 = 89.26%), as well as malic acid (RMSEP = 1.22 g/L, R2 = 91.10%). The coefficient of determination (R2) was comparable for glucose and fructose with 89.45% compared to 89.08%, respectively. Although tartaric acid was predictable for only two of the four varieties using near-infrared spectroscopy, calibration and validation for malic acid were accurate for all varieties in an equal extent like the sugars. These high prediction accuracies for the main quality determining grape must ingredients using this miniaturized prototype apparatus might enable an installation on a grape harvester in the future.
Recent Developments in Inertial and Centrifugal Microfluidic Systems along with the Involved Forces for Cancer Cell Separation: A Review
Authors: Farahinia Alireza , Zhang Wenjun , Badea Ildiko
Published: June 2023

The treatment of cancers is a significant challenge in the healthcare context today. Spreading circulating tumor cells (CTCs) throughout the body will eventually lead to cancer metastasis and produce new tumors near the healthy tissues. Therefore, separating these invading cells and extracting cues from them is extremely important for determining the rate of cancer progression inside the body and for the development of individualized treatments, especially at the beginning of the metastasis process. The continuous and fast separation of CTCs has recently been achieved using numerous separation techniques, some of which involve multiple high-level operational protocols. Although a simple blood test can detect the presence of CTCs in the blood circulation system, the detection is still restricted due to the scarcity and heterogeneity of CTCs. The development of more reliable and effective techniques is thus highly desired. The technology of microfluidic devices is promising among many other bio-chemical and bio-physical technologies. This paper reviews recent developments in the two types of microfluidic devices, which are based on the size and/or density of cells, for separating cancer cells. The goal of this review is to identify knowledge or technology gaps and to suggest future works.
AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity
Authors: Gao Xueyuan , Feng Hua
Published: June 2023

Artificial intelligence is profoundly influencing various facets of our lives, indicating its potential to significantly impact sustainability. Nevertheless, capturing the productivity gains stemming from artificial intelligence in macro-level data poses challenges, leading to the question of whether artificial intelligence is reminiscent of the “Solow paradox”. This study employs micro-level manufacturing data to investigate the impact of artificial intelligence on firms’ productivity. The study finds that every 1% increase in artificial intelligence penetration can lead to a 14.2% increase in total factor productivity. This conclusion remains robust even after conducting endogeneity analysis and a series of robustness tests. The study identifies that the positive impact of artificial intelligence on productivity is primarily achieved through the value-added enhancement effect, skill-biased enhancement effect, and technology upgrading effect. Furthermore, the study reveals that the effects of artificial intelligence on productivity vary across different property rights and industry concentration contexts. Additionally, the structure of factor endowments within firms can also influence the productivity gains from artificial intelligence. Our study presents compelling evidence demonstrating the role of artificial intelligence in fostering economic sustainability within the framework of Industry 4.0.
COVID-19 Pandemic Learning: The Uprising of Remote Detailing in Pharmaceutical Sector Using Sales Force Automation and Its Sustainable Impact on Continuing Medical Education
Authors: Yılmaz Altuntaş Elgiz , Yalçın Esin Cumhur
Published: June 2023

The availability of resources is vital when rapid changes and updated medical information in the provision of care are needed, such as in the fight against COVID-19, which is not a conventional disease. Continuing medical education plays an essential role in preparing for and responding to such emergencies. Workflow has improved based on the virtual meetings, online trainings, and remote detailing conducted by medical representatives in order to deliver educational content instantly through digital tools, such as salesforce automation (SFA), webinars, etc. In terms of its regulatory barriers, the pharmaceutical industry mainly targets healthcare professionals, unlike most businesses that reach end users directly. Medical representatives are equipped with an SFA to enhance customer relationship management (CRM) and closed loop marketing (CLM) capabilities in pharmaceutical companies. This study aimed to fill a gap in the literature by investigating the use of SFA in work patterns, such as health professionals’ loyalty and involvement in their medical knowledge in Turkey, and how it allows for differentiating training from marketing. This study intended to compare the data on internists and medical products gathered from a well-known pharmaceutical company’s SFA. The data covered the first three months of the year 2020, when medical representatives had a normal daily routine, and that of 2021, when Turkey experienced the most powerful surge of the COVID-19 pandemic. The analysis was based on simple correspondence analysis (SCA) and multiple correspondence analysis (MCA) for 11 variables. Monitoring product, physician’s segment, and medical representatives’ behaviors with SFA had a significant influence on the pharma-physician relationship strategy, as expected. The findings supported the view that SFA technologies can be deployed to advance the medical knowledge of physicians, in addition to managing and designing superior CRM and CLM capabilities.
Application of Machine Learning Techniques to Predict Visitors to the Tourist Attractions of the Moche Route in Peru
Authors: Bravo Jessie , Alarcón Roger , Valdivia Carlos , Serquén Oscar
Published: June 2023

Due to the COVID-19 pandemic, the tourism sector has been one of the most affected sectors and requires management entities to develop urgent measures to reactivate and achieve digital transformation using emerging disruptive technologies. The objective of this research is to apply machine learning techniques to predict visitors to tourist attractions on the Moche Route in northern Peru, for which a methodology based on four main stages was applied: (1) data collection, (2) model analysis, (3) model development, and (4) model evaluation. Public data from official sources and internet data (TripAdvisor and Google Trends) during the period from January 2011 to May 2022 are used. Four algorithms are evaluated: linear regression, KNN regression, decision tree, and random forest. In conclusion, for both the prediction of national and foreign tourists, the best algorithm is linear regression, and the results allow for taking the necessary actions to achieve the digital transformation to promote the Moche Route and, thus, reactivate tourism and the economy in the north of Peru.
Improvement of Environmental, Social, and Cultural Attributes in the Slum Settlements on the Riverbanks of Yogyakarta City under the Sultan’s Rule
Authors: Hawa Nada Ismita , Antriyandarti Ernoiz , Martono Dwi Nowo , Maulana Rifqi Aji
Published: June 2023

A riverbank revitalization program is being carried out to overcome the problem of slum areas and restore the role of the river. Many local governments in Indonesia are working to revitalize riverbanks, with Yogyakarta being one of them. As a special region in Indonesia, the Yogyakarta government has implemented the Mundur, Munggah, Madhep Kali (M3K) program, under Government Regulation (PP) No. 38 of 2011, to manage the conservation, development, and control of the destructive power of river water. This study aimed to ascertain how changes to the riverbanks affect both people’s quality of life and the river itself. The factors that influenced the changes in the environment, society, and culture of the community after the M3K program were also determined in this study. This study used a descriptive method with qualitative and quantitative data analyses. The statistical analysis method used was logistic regression. The findings obtained show that the M3K program has transformed people’s mindsets and habits toward keeping the environment clean, particularly the river area. According to the findings of the logistic regression analysis, the variables that determine the changes in the social and cultural environment of the community affected by M3K are age, education, employment opportunities, and income.
Comprehensive Laboratory Evaluation of Crack Resistance for an Asphalt Rubber Stress-Absorbing Membrane Interlayer (AR-SAMI)
Authors: Li Ping , Peng Wenju , Tian Shuaituan , Liu Zhaohui , Liu Junbin , Liu Shende
Published: June 2023

Reflective cracking is a common distress of semi-rigid base asphalt pavements and overlay pavement projects. An asphalt rubber stress-absorbing membrane interlayer (AR-SAMI) prepared by waste tires is an effective engineering solution for treating reflective cracking. This method can also reduce black pollution. However, there is no unified test method and index for crack resistance evaluation. In this work, AR-SAMIs with different air voids and gradations were investigated. A small beam bending test (BBT) at −10 °C and 15 °C, crack expansion SCB (CE-SCB) test, low-temperature SCB (LT-SCB) test, and Overlay Test (OT) were performed to evaluate the crack resistance of AR-SAMI comprehensively. Statistical analysis was also performed. Results showed that the crack resistance of AR-SAMI improved as the air voids decreased. The crack resistance of 10-A gradation with more fine aggregate was excellent. However, the AR-SAMI with more coarse aggregate had better crack extension resistance under the condition of pre-existing cracks. There are differences in the evaluation results of different test methods due to the various evaluation focus. The −10 °C BBT, CE-SCB, and OT were recommended to evaluate the crack resistance comprehensively. Research results can guide the evaluation method or index selection of crack resistance and the optimization of AR-SAMI mixture design under different working conditions.
Psychometric Performance of the Fear of COVID-19 Scale (FCV-19S) and Its Validation in Czechia
Authors: Remr Jiri
Published: June 2023

The COVID-19 pandemic has brought significant changes to people’s lives, causing high levels of anxiety, distress, and fear. In response, the “Fear of COVID-19” scale (FCV-19S) was developed in 2020 to measure the severity of fears related to COVID-19. This study assessed the psychometric properties of the Czech version of the FCV-19S, which was administered to a representative sample of 1372 participants, and confirmatory factor analysis (CFA) was conducted. The sample reflects the structure of a theoretical population aged 15–74 years and is composed of 50% males and 50% females. Moreover, univariate statistics were calculated, internal consistency was tested, and uni-dimensionality based on principal component analysis was performed. In addition, univariate statistical analyses were performed, internal consistency was tested, and univariate consistency was also assessed using principal component analysis. CFA indicated that the scale demonstrated very good standard indices; FCV-19S showed a high level of internal consistency, and it adequately differentiated the levels of fear among diverse subpopulations. The findings suggest that the Czech version of the FCV-19S is a valid and reliable instrument that has robust psychometric properties and can, therefore, be recommended for use in research. The availability of the Czech version of the FCV-19S will contribute to assessments of the impact of the COVID-19 pandemic on the Czech population, providing valuable information in guiding interventions aimed at reducing the negative psychological impacts of the pandemic.
Research on the Mechanism of Transfer Payment Policy on Resource Dependence of Resource-Depleted Cities
Authors: Wu Zhengyuan , Gu Qifeng , Zeng Jianqiu
Published: June 2023

The objective of this study is to clarify the impact and mechanism of transfer payment policies on the resource dependence of resource-depleted cities. Based on the panel data of 113 prefecture-level resource-based cities from 2006 to 2017, this study uses a multi-period difference-in-differences model to conduct an empirical study on the impact and mechanism of transfer payment policies on resource-depleted cities. The results are as follows: Firstly, the transfer payment policy can reduce the resource dependence of resource-depleted cities. Secondly, there is a significant difference between the eastern region and the central and western regions in terms of the effects of policy implementation. Thirdly, transfer payment policies reduce local dependence on resources, mainly through upgrading industrial structures and enhancing infrastructure construction and technological progress. The research indicates that providing financial policy support for the transformation of resource-depleted cities, exploring ways to reduce resource dependence in the eastern region, playing an exemplary role, and expanding the intensity of urban industrial transformation are of reference significance for the sustainable development of resource-depleted cities. This study also contributes to the coordinated development of the regional economy and the policy formulation of the sustainable development of resource-depleted cities.
Automated Optimum Design of Light Steel Frame Structures in Chinese Rural Areas Using Building Information Modeling and Simulated Annealing Algorithm
Authors: Zhou Ting , Sun Kezhao , Chen Zhihua , Yang Zhexi , Liu Hongbo
Published: June 2023

Many manual calculations and repeated modeling are required during the traditional structural design process. However, due to the high cost, rural buildings in China cannot be professionally designed and verified by designers as urban buildings, and their safety and economy cannot easily meet the requirements. Building Information Modeling (BIM) technology and intelligent optimization algorithms can effectively improve the structural design process and reduce design costs, but their applications in the field of rural residential buildings in China are limited. Therefore, this paper presents an innovative framework that realizes the structural design of rural light steel frame structures on the BIMBase platform (widely used BIM software in China, BIMBase 2023R1.3). Based on the parametric library of structural components built on standardized component coding, the framework completes the rapid modeling of rural light steel frame structures and the interaction between the BIMBase platform and structural analysis software, SATWE. The improved two-stage simulated annealing (SA) algorithm is applied to the structural design of rural buildings to obtain a design scheme that meets the design requirements and reduces the material consumption as much as possible. Two prefabricated rural light steel frame structures were analyzed to evaluate the efficiency of the proposed framework. The results show the feasibility of the proposed framework. Compared with traditional manual design methods, the design period can be reduced by six times while maintaining comparable levels of material consumption and structural design indicators.
Oil and Non-Oil Determinants of Saudi Arabia’s International Competitiveness: Historical Analysis and Policy Simulations
Authors: Hasanov Fakhri J. , Razek Noha
Published: June 2023

To achieve sustainable economic growth, Saudi Vision 2030’s target is to improve Saudi Arabia’s ranking on the Global Competitiveness Index from 25 in 2015–2016 to within the top 10 by 2030. Saudi Arabia also aims to increase the share of non-oil exports in the non-oil GDP from 16% in 2016 to 50% by 2030. For policymakers to make informed decisions to achieve these goals, they need to understand the driving forces of Saudi Arabia’s competitiveness. To this end, we consider the real effective exchange rate (REER) as a measure of external price competitiveness, as it captures domestic and global price changes. We then examine the REER using a two-stage modeling framework. First, we estimate the REER equation, which allows us to assess the impacts of the determinants and evaluate currency misalignments as a competitiveness indicator. Second, we extend the KAPSARC Global Energy Macroeconometric Model (KGEMM) with the estimated equation, which provides a framework for simulating the competitiveness impacts of the theoretically formulated determinants and other variables relevant to policymakers. The framework also allows us to account for feedback loops. We conduct a policy scenario analysis to quantify the competitiveness effects of the Public Investment Fund’s (PIF) new strategy for 2021–2025. We derive the following policy insights. Authorities may wish to implement initiatives boosting future productivity and, thus, competitiveness, such as PIF investments. Policymakers should be regularly informed about currency misalignment. Government consumption and public investment projects should consider substituting imports with locally produced goods and services. Local content development would also help to diversify the Saudi economy. Finally, attracting more foreign investment and other assets from the rest of the world may lead to technological development and improvement in the economic, financial, and social infrastructure and business environment, all enhancing competitiveness.
AI Carbon Footprint Management with Multi-Agent Participation: A Tripartite Evolutionary Game Analysis Based on a Case in China
Authors: Wang Xuwei , Ji Kaiwen , Xie Tongping
Published: June 2023

AI is playing an important role in promoting sustainable development, but the carbon footprint caused by AI is scaling quickly and may partly offset the effort to reduce carbon emissions. However, recommendations for limiting the AI carbon footprint are lacking. In order to address this gap in the literature, this paper first constructs a tripartite evolutionary game model by taking governments, AI industry alliances, and consumers into consideration, and then exploring the impacts of key factors on these three players’ strategy selection based on the case of smart air conditioner consumption in China. The results show that the behavior of governments has an important influence on the behavior of AI industry alliances and consumers. The ideal consequence is that governments adopt an unregulated strategy, AI industry alliances adopt a green development strategy, and consumers adopt a green purchase strategy. Regulation by governments is indispensable for limiting the AI carbon footprint during an early stage but becomes dispensable when the system reaches an optimal state. Although a tendency toward green consumption, image benefit, regulatory cost, carbon price, and the subsidies given to consumers and AI industry alliances can largely influence the strategy selection of governments, governments are most sensitive to carbon prices and the subsidies given to consumers. AI industry alliances are not sensitive to subsidies, reputation improvement, and reputation loss but are most sensitive to carbon prices. Consumers are most sensitive to green consumption tendencies, self-satisfaction, and utility but are not sensitive to subsidies.
A Backstepping Control Strategy for Power System Stability Enhancement
Authors: Bahloul Wissem , Zdiri Mohamed Ali , Marouani Ismail , Alqunun Khalid , Alshammari Badr M. , Alturki Mansoor , Guesmi Tawfik , Hadj Abdallah Hsan , Tlijani Kamel
Published: June 2023

Secure power system operation relies extensively on the analysis of transient stability and control. The dynamics involved in power system control are often complex and nonlinear. Most of the currently existing works approach these frequent problems with nonlinear control techniques, leading to a requirement for specific controller parameter adjustments. In these veins, this paper proposes a new method for stabilizing electric power systems, using nonlinear backstepping control by optimizing the controller’s parameters. The Jaya algorithm and Genetic algorithm are utilized as a powerful meta-heuristic optimization technique to search parameters of an optimal controller. Improvement in system damping, transient stability, and voltage regulation has been achieved by minimizing the integral time absolute error (ITAE) as the objective function. Numerical simulations on an SMIB power system under different fault conditions showed that the proposed method outperforms classical power system stabilizer (PSS) methods, reducing overshoots and settling times and eliminating steady-state errors. These findings highlight the effectiveness of the proposed approach and its potential contribution to the development of advanced nonlinear control techniques for electric power systems. The suggested optimization methods demonstrate superior performance, compared to classical methods, and achieve a reduction of 27.5% in overshoot and 87% in transient time in addition to complete elimination of static error.
Does Stronger Environmental Regulation Promote Firms’ Export Sophistication? A Quasi-Natural Experiment Based on Sewage Charges Standard Reform in China
Authors: Zhang Weihao , Xu Helian , Xu Yuanyuan
Published: June 2023

Based on the quasi-natural experiment of sewage charges standard reform, this paper adopts a staggered difference-in-difference model to empirically investigate the effect of environmental regulation on firms’ export sophistication and the mechanism of the effect, using the matched data from the Chinese Annual Survey of Industrial Firms and Chinese Custom Trade databases from 2004 to 2013. The results show that (1) the environmental regulation policy of sewage charges standard reform significantly promotes the upgrading of firms’ export sophistication; (2) the impact of sewage charges standard reform on firms’ export sophistication is heterogeneous, in that the promotion effect of sewage charges standard reform on firms’ export sophistication is mainly manifested in simultaneous import and export firms, large-sized firms, and local firms; and (3) the sewage charges standard reform mainly through the mechanisms of innovation compensation effect and product switching effect to promote firms’ export sophistication. This paper provides empirical evidence and policy insights for governments to formulate and implement environmental protection policies appropriately.
Adjusting pH of the Secondary Composting Materials to Further Enhance the Lignocellulose Degradation and Promote the Humification Process
Authors: Zhao Bing , Wang Yuyun , Li Lan , Ma Liting , Deng Yaqin , Xu Zhi
Published: June 2023

Straw waste has a large amount of lignocellulose, which shows a strong resistance to biodegradation in the composting process and hinders the formation of humic substances. Therefore, the effects of pH adjustment and inoculation of degradation bacteria on the composting process, lignocellulose degradation and humus formation in secondary fermentation were explored through aerobic composting experiments. The experiment was designed with four treatment groups: CK (conventional composting), T1 (adjusting pH), T2 (inoculating P. chrysosporium), and T3 (adjusting pH and inoculating P. chrysosporium), respectively. Results showed that except for treatment CK, all other treatments met the maturation standards at the end of composting. Adjustment of the pH value and the inoculation of Phanerochaete chrysosporium (P. chrysosporium) can significantly shorten the fermentation time. Among them, the lignin content of treatment T3 was reduced significantly by 14.28% compared to treatment T2; the content of humic acid in T3 increased significantly by 51.32% and 14.04% compared with T1 (adjusting pH) and T2 (p < 0.05), respectively. In terms of key enzyme activity and precursor substance changes, the pH adjustment treatment was superior to other treatments after composting. This study confirmed that the change of pH conditions is an important environmental factor for microorganisms to enhance the humification process; degrading enzymes were used as a “bridge” to enhance the continuous degradation of lignocellulose by microorganisms and increase the supplementation of precursors and the synthesis of humic acid, which is the mechanism to enhance the humification process. Our findings provided a new method to enhance the humification process, which is a valuable and economical technical approach to improve organic fertilizer quality.
Ecoenzymatic Stoichiometry Reveals Microbial Carbon and Phosphorus Limitations under Elevated CO2, Warming and Drought at Different Winter Wheat Growth Stages
Authors: Wang Jing , Wang Xuesong , Zheng Fenli , Wei Hanmei , Zhao Miaomiao , Jiao Jianyu
Published: June 2023

The use of microbial metabolic limitation techniques has the potential to provide insights into carbon and nutrient cycling in an ecosystem under the influence of climate change. This study aimed to determine the characteristics and potential mechanisms of microbial metabolic limitation at the different growth stages of winter wheat (Triticum aestivum L.) in response to elevated CO2 concentrations, warming and drought. Winter wheat plants were grown in artificial climate chambers, and a set of treatments were employed, including two levels of CO2 concentration (400 and 800 μmol·mol−1), a temperature regime (the current ambient temperature and a temperature increase of 4 °C) and water conditions (80% and 60% of the field water capacity). The results showed that the soil microbes were mainly limited by C and P. Microbial C limitation significantly decreased by 26.7% and 36.9% at the jointing stage and significantly increased by 47.6% and 42.6% at the grain filling stage in response to elevated CO2 and warming, respectively. The microbial P limitation significantly decreased by 10.9–13.0% under elevated CO2 at the anthesis and grain filling stages, while it was not affected by warming. Both microbial C and P limitations were unaffected by drought. The growth stage, soil dissolved organic carbon (DOC) and available phosphorus (AP) were the key factors affecting microbial C limitation, and microbial P limitation was mainly affected by the soil microbial biomass carbon (MBC), phosphorus (MBP) and microbial C:P ratio. Thus, the soil microbial C and P limitations differed with growth stages and were primarily indirectly affected by the available nutrients in the soil and the properties of the microbial biomass, respectively. These findings are important for understanding the mechanisms underlying microbe-mediated C and nutrient cycles. Overall, this study provides guidance for soil nutrient management in an agroecosystem experiencing climate change.
Simulation Techniques for Strength Component Partially Accelerated to Analyze Stress–Strength Model
Authors: Yousef Manal M. , Fayomi Aisha , Almetwally Ehab M.
Published: June 2023

Based on independent progressive type-II censored samples from two-parameter Burr-type XII distributions, various point and interval estimators of δ=P(Y<X) were proposed when the strength variable was subjected to the step–stress partially accelerated life test. The point estimators computed were maximum likelihood and Bayesian under various symmetric and asymmetric loss functions. The interval estimations constructed were approximate, bootstrap-P, and bootstrap-T confidence intervals, and a Bayesian credible interval. A Markov Chain Monte Carlo approach using Gibbs sampling was designed to derive the Bayesian estimate of δ. Based on the mean square error, bias, confidence interval length, and coverage probability, the results of the numerical analysis of the performance of the maximum likelihood and Bayesian estimates using Monte Carlo simulations were quite satisfactory. To support the theoretical component, an empirical investigation based on two actual data sets was carried out.
The Conchoidal Twisted Surfaces Constructed by Anti-Symmetric Rotation Matrix in Euclidean 3-Space
Authors: Çelik Serkan , Karadağ Hacı Bayram , Kuşak Samancı Hatice
Published: June 2023

A twisted surface is a type of mathematical surface that has a nontrivial topology, meaning that it cannot be smoothly deformed into a flat surface without tearing or cutting. Twisted surfaces are often described as having a twisted or Möbius-like structure, which gives them their name. Twisted surfaces have many interesting mathematical properties and applications, and are studied in fields such as topology, geometry, and physics. In this study, a conchoidal twisted surface is formed by the synchronized anti-symmetric rotation matrix of a planar conchoidal curve in its support plane and this support plane is about an axis in Euclidean 3-space. In addition, some examples of the conchoidal twisted surface are given and the graphs of the surfaces are presented. The Gaussian and mean curvatures of this conchoidal twisted surface are calculated. Afterward, the conchoidal twisted surface formed by an involute curve and the conchoidal twisted surface formed by a Bertrand curve pair are given. Thanks to the results obtained in our study, we have added a new type of surface to the literature.
Certain Subclasses of Analytic and Bi-Univalent Functions Governed by the Gegenbauer Polynomials Linked with q-Derivative
Authors: Kazımoğlu Sercan , Deniz Erhan , Cotîrlă Luminiţa-Ioana
Published: June 2023

In this paper, we introduce and investigate two new subclasses of analytic and bi-univalent functions using the q-derivative operator Dq0<q<1 and the Gegenbauer polynomials in a symmetric domain, which is the open unit disc Λ=℘:℘∈Cand℘<1. For these subclasses of analytic and bi-univalent functions, the coefficient estimates and Fekete–Szegö inequalities are solved. Some special cases of the main results are also linked to those in several previous studies. The symmetric nature of quantum calculus itself motivates our investigation of the applications of such quantum (or q-) extensions in this paper.
Classical and Bayesian Inference for the Kavya–Manoharan Generalized Exponential Distribution under Generalized Progressively Hybrid Censored Data
Authors: Abdelwahab Mahmoud M. , Ghorbal Anis Ben , Hassan Amal S. , Elgarhy Mohammed , Almetwally Ehab M. , Hashem Atef F.
Published: June 2023

This manuscript focuses on the statistical inference of the Kavya–Manoharan generalized exponential distribution under the generalized type-I progressive hybrid censoring sample (GTI-PHCS). Different classical approaches of estimation, such as maximum likelihood, the maximum product of spacing, least squares (LS), weighted LS, and percentiles under GTI-PHCS, are investigated. Based on the squared error and linear exponential loss functions, the Bayes estimates for the unknown parameters utilizing separate gamma priors under GTI-PHCS have been derived. Point and interval estimates of unknown parameters are developed. We carry out a simulation using the Monte Carlo algorithm to show the performance of the inferential procedures. Finally, real-world data collection is examined for illustration purposes.
Review of Chaotic Intermittency
Authors: Elaskar Sergio , del Río Ezequiel
Published: June 2023

Chaotic intermittency is characterized by a signal that alternates aleatory between long regular (pseudo-laminar) phases and irregular bursts (pseudo-turbulent or chaotic phases). This phenomenon has been found in physics, chemistry, engineering, medicine, neuroscience, economy, etc. As a control parameter increases, the number of chaotic phases also increases. Therefore, intermittency presents a continuous route from regular behavior to chaotic motion. In this paper, a review of different types of intermittency is carried out. In addition, the description of two recent formulations to evaluate the reinjection processes is developed. The new theoretical formulations have allowed us to explain several tests previously called pathological. The theoretical background also includes the noise effects in the reinjection mechanism.
The Power of Symmetries in Nuclear Structure and Some of Its Problems
Authors: Hess Peter O.
Published: June 2023

A review of several classical, algebraic models in nuclear structure physics, which use symmetries as an important tool, are presented. After a conceptual introduction to group theory, a selection of models is chosen to illustrate the methods and the power of the usage of symmetries. This enables us to describe very involved systems in a greatly simplified manner. Some problems are also discussed, when ignoring basic principles of nature, such as the Pauli exclusion principle. We also show that occasionally one can rescue these omissions. In a couple of representative models, applications of symmetries are explicitly applied in order to illustrate how extremely complicated systems can be treated. This contribution is meant as a review of the use of algebraic models in nuclear physics, leading to a better understanding of the articles in the same special volume.