bluuebunny/crossref_metadata_2025 huggingface dataset:
The Extraction, Characterization and Biological Activity of Natural Products
Authors: Yan Linlin , Kljakić Aleksandra Cvetanović
Published: September 2023

The aim of this Special Issue, entitled “The Extraction, Characterization and Biological Activity of Natural Products”, is to expand our knowledge and promote a better understanding of the latest scientific advances in the field of the extraction, isolation and characterization of biologically active compounds of natural plants [...]
Salvia officinalis L. and Salvia sclarea Essential Oils: Chemical Composition, Biological Activities and Preservative Effects against Listeria monocytogenes Inoculated into Minced Beef Meat
Authors: Ben Akacha Boutheina , Ben Hsouna Anis , Generalić Mekinić Ivana , Ben Belgacem Améni , Ben Saad Rania , Mnif Wissem , Kačániová Miroslava , Garzoli Stefania
Published: September 2023

In this study, Salvia officinalis L. and Salvia sclarea essential oils (EOs) were investigated using gas chromatography-mass spectrometry (GC-MS) to describe their chemical composition. The obtained results show, for both EOs, a profile rich in terpene metabolites, with monoterpenes predominating sesquiterpenes but with significant qualitative and quantitative differences. The main compound found in the Salvia officinalis EO (SOEO) was camphor (19.0%), while in Salvia sclarea EO (SCEO), it was linalyl acetate (59.3%). Subsequently, the in vitro antimicrobial activity of the EOs against eight pathogenic strains was evaluated. The disc diffusion method showed a significant lysis zone against Gram-positive bacteria. The minimum inhibitory concentrations (MICs) ranged from 3.7 mg/mL to 11.2 mg/mL, indicating that each EO has specific antimicrobial activity. Both EOs also showed significant antiradical activity against DPPH radicals and total antioxidant activity. In addition, the preservative effect of SOEO (9.2%) and SCEO (9.2%), alone or in combination, was tested in ground beef, and the inhibitory effect against Listeria monocytogenes inoculated into the raw ground beef during cold storage was evaluated. Although the effect of each individual EO improved the biochemical, microbiological, and sensory parameters of the samples, their combination was more effective and showed complete inhibition of L. monocytogenes after 7 days of storage at 4 °C. The results show that both EOs could be used as safe and natural preservatives in various food and/or pharmaceutical products.
The Impact of Tillage and Crop Residue Incorporation Systems on Agrophysical Soil Properties
Authors: Steponavičienė Vaida , Rudinskienė Aušra , Žiūraitis Giedrius , Bogužas Vaclovas
Published: September 2023

A long-term field experiment has been ongoing since 1999 at the Experimental Station of Vytautas Magnus University’s Agriculture Academy. According to the latest edition of the International Soil Classification System, the soil in the experimental field can be classified as Planosol, with a silty medium-loam texture at a depth of 0–20 cm and a silty light-loam texture at a depth of 20–40 cm. Studies were carried out on winter wheat crops in 2014, 2017, and 2023. This research aimed to assess how different long-term tillage systems impact soil shear strength and aggregate stability, their interconnection, and the effect of crop residues on soil stability. The treatments were arranged using a split-plot design. In a two-factor field experiment, straw was removed from one part of the experimental field, while the entire straw yield was chopped and spread at harvest in the other part (Factor A). The subplot factor (Factor B) included three different tillage systems: conventional deep ploughing, cover cropping for green manure with no tillage, and no tillage. The soil samples were analyzed at the Laboratory of Agrobiology at Vytautas Magnus University’s Agriculture Academy. The findings indicated that the long-term application of reduced tillage significantly increased the soil shear strength. Shallower tillage depths led to a higher soil shear strength, while the effect of spreading plant residues was relatively lower. The long-term tillage of different intensities, spreading plant residues, and catch crop cultivation for green manure did not significantly affect the soil structure. However, the soil structural stability was found to be highly dependent on soil tillage. Cover cropping for green manure with no tillage and no tillage alone positively affected the soil aggregate stability in the upper 0–10 cm and 10–25 cm layers. The correlation–regression analysis showed that, in the top 0–10 cm and 10–25 soil layers, there were moderate to strong correlations between the soil structural stability, soil shear strength, and the effect of crop residues on soil stability.
Genome-Wide Identification and Expression Analysis of the TCP Gene Family Related to Developmental and Abiotic Stress in Ginger
Authors: Jiang Yajun , Jiang Dongzhu , Xia Maoqin , Gong Min , Li Hui , Xing Haitao , Zhu Xuedong , Li Hong-Lei
Published: September 2023

Ginger (Zingiber officinale Roscoe), a widely consumed edible and medicinal plant, possesses significant nutritional and economic value. Abiotic stresses such as drought and low temperatures can impact the growth and development of ginger. The plant-specific transcription factor Teosinte branched1/cycloidea/proliferating cell factor (TCP) has progressively been identified in various plants for its role in regulating plant growth and development as well as conferring resistance to abiotic stresses. However, limited information on the TCP family is available in ginger. In this study, we identified 20 TCP members in the ginger genome, which were randomly distributed across 9 chromosomes. Based on phylogenetic analysis, these ginger TCP were classified into two subfamilies: Class I (PCF) and Class II (CIN, CYC/TB). The classification of the identified ginger TCPs was supported by a multi-species phylogenetic tree and motif structure analysis, suggesting that the amplification of the ginger TCP gene family occurred prior to the differentiation of angiosperms. The promoter region of ginger TCP genes was found to contain numerous cis-acting elements associated with plant growth, development, and abiotic stress response. Among these elements, the stress response element, anaerobic induction, and MYB binding site play a dominant role in drought responsiveness. Additionally, expression pattern analysis revealed variations in the expression of ginger TCP gene among different tissues and in response to diverse abiotic stresses (drought, low temperature, heat, and salt). Our research offers a thorough examination of TCP members within the ginger plant. This analysis greatly contributes to the understanding of how TCP genes regulate tissue development and response to stress, opening up new avenues for further exploration in this field.
Sustainable Process Study on Emergy and Carbon Emission Analysis of Building System Based on Neural Network Algorithm
Authors: Wang Ye , Wang Hairuo , Zhang Junxue , Jia Meng
Published: September 2023

Sustainable building systems can effectively reduce environmental pressures and mitigate the deterioration of the global climate. The sustainability of complex building systems is influenced by various factors. This article quantitatively analyzes building systems from an ecological emergy and carbon emissions perspective, and considers typical feedback structures’ impact. A neural network algorithm is employed for sustainability prediction analysis. The results demonstrate that both from an emergy and carbon emissions perspective, the operational phase of the building and the production phase of building materials are the main contributors (accounting for over 90%). Among the three types of feedback subsystems, the cross-feedback structure has a more significant impact and yields the best corrective effect. For example, the correction proportion of the building’s emergy sustainability parameter reaches 11.3%, while it is 15.8% for carbon emissions. The neural network model predicts a decreasing trend in the energy sustainability of buildings and increasing carbon emissions over time. To improve the sustainability of building systems, measures such as ecological landscape design and carbon sequestration in building materials are considered, which can enhance the sustainability of buildings to a certain extent.
Application and Comparison of a Modified Protection Scheme Utilizing a Proportional–Integral Controller with a Conventional Design to Enhance Doubly Fed Induction Generator Wind Farm Operations during a Balanced Voltage Dip
Authors: Loulijat Azeddine , Chojaa Hamid , El Marghichi Mouncef , Ettalabi Naoufl , Hilali Abdelilah , Barnawi Abdulwasa B. , Elbarbary Z. M. S. , Mossa Mahmoud A.
Published: September 2023

The doubly fed induction generator (DFIG) is vulnerable to grid faults due to its direct stator connection, causing issues like excess stator current during voltage dips. Consequently, sensitive inverters suffer from increased currents, and the DC-link capacitor undergoes overcharging. This document examines two protection strategies employing a proportional–integral (PI) controller to manage the transient rotor current and mitigate DC-link overcharging, thereby optimizing DFIG behavior during network faults. One option combines a classic crowbar circuit with a DC-chopper, while the other is a modified protection scheme (MPS) that includes an impedance with passive elements and a crowbar. The impedance forms a resistance Rp parallel with an inductance Lp. Both configurations, situated between the rotor coils and the rotor-side converter (RSC), augment the capacity for low-voltage ride-through (LVRT). MATLAB/SIMULINK simulations of the two schemes demonstrate successful rotor current reduction at 2.9 kA and 3.4 kA, and DC-link tension reduction below and at 1.4 KV. In addition, the conventional crowbar and MPS configurations efficiently restrict the RSC current to levels below 0.21 kA and 2.94 kA, while absorbing up to 2.52 kA and 1.52 kA, respectively. The key difference lies in the fact that fine-tuning the parameters in the MPS design prevents rotor disconnection when faced with a balanced fault. This enhancement enhances machine performance and enables full stator power control via the RSC.
Encountering the Divine, Resisting Patriarchy: Rosemary Radford Ruether’s Prophetic Catholicism
Authors: Robinson Jim
Published: September 2023

While Rosemary Radford Ruether is widely, and rightly, acknowledged as a prophetic Catholic scholar–activist, her interest in and experience of mysticism is rarely emphasized. However, Ruether had an impactful mystical experience as a young woman, and the themes of this experience echo throughout her body of work. This paper paints a portrait of Ruether as both a profoundly prophetic scholar–activist and a spiritually attuned seeker of the very divinity that she encountered in her twenties. In the process, this paper first offers a democratized and demystified vision of mysticism by drawing on the work of Bernard McGinn, Dorothee Söelle, and Jess Byron Hollenback. Next, it offers a biographical sketch of Ruether, contextualizing her early mystical experience within the broader pattern of her spiritual and intellectual path. It interprets Ruether’s mystical experience, through which she encountered the divine as a feminine presence suffusing creation, as a meaningful source of inspiration for her decades-long commitment to an anti-patriarchal, ecofeminist theology.
K.E. Løgstrup: Phenomenology of the Social World and Systematic Theology
Authors: Christoffersen Svein Aage
Published: September 2023

In K.E. Løgstrup’s (1905–1981) theology, the point of intersection between phenomenology and systematic theology is our life experiences. In this article, Løgstrup’s way of combining phenomenology and theology is explored from the 1930s to the 1970s. The idea that life is not an amorphous abyss, but God’s creation runs like a connecting thread throughout Løgstrup’s oeuvre. This idea negating a nihilistic understanding of life requires a phenomenology of the social world that explores both the ethical and the metaphysical implications of our life experiences. Human beings are interdependent animals, and in this interdependency, an anonymous and unavoidable ethical demand makes itself present, saying that you have to take care of the life you have in your hands. Sovereign expressions of life are phenomena that support the ethical demand and the idea of creation. In the 1970s, Løgstrup broadened the perspective and explored how the universe is present in our life experiences through our bodily existence and our senses. Even so, there is not an unbroken way from these metaphysical considerations to theology. Christian Faith is based on God’s revelation in Jesus Christ. Life experiences are just the horizon against which it is possible to understand what the Christian message is. Systematic theology connects phenomenology on the one hand and the proclamation of the Gospel on the other hand.
“The New Americans”, “the New Muslims”: African American Muslims and the Recreation of American Muslim Identities after 9/11, 2001
Authors: Ben Hadj Salem Hajer
Published: September 2023

This study sheds light on the identity negotiation processes inside the African American Muslim communities and the post-1960s immigrant Muslim communities both before and after 9/11, and the various hurdles that have impeded the development of a pluralistic American Muslim identity. It locates the American Muslim experience within the omnibus context of religious pluralism and draws on Barbara McGraw’s “the American Sacred Ground” theoretical framework (2003) to gauge advances and setbacks in such identity negotiation processes. While gleaning insights from the works of scholars of Islam and religious pluralism in America, this study is based on ethnographic fieldwork conducted in the USA between 2002 and 2006. After 9/11, both communities came to realize that it is vital to engage in a process of self-critique and confront the challenges of reinventing themselves on the American pluralistic tapestry. While the African American Sunni communities tried to reinvent themselves as ‘new Muslims’, the immigrant communities found themselves compelled to reinvent themselves as “new Americans”. In studying some facets of such an inter- and intracommunity identity (re)negotiation process, this article argues that perennial internal factionalism and the promotion of changing US foreign policy agendas in the Muslim world still represent a major stumbling block towards developing an American Muslim identity that draws on its many streams.
Reading the Locust Plague in the Prophecy of Joel in the Context of African Biblical Hermeneutics and the Decolonial Turn
Authors: Udoekpo Michael Ufok
Published: September 2023

Joel is one of the 12 minor prophets (dōdekaprophēton). His prophecy aims at calling the nation and people to repentance through emphasizing that the Day of the Lord (yōm ădȏnay) is at hand (3:1–5 [2:28–32]). The locust plague (ʾarbbeh) in Joel’s message—which recalls the insects that threaten to destroy crops and vegetation in Africa and beyond, but which can also be used as food and livestock feed and offer other benefits as well—could be interpreted as Joel’s prophetic sign that the great Day of the Lord is near (1:2–2:17). Throughout history, scholars, theologians, and exegetes of differing schools of thought and from numerous locations have offered various interpretations for Joel’s prophecy and subjected it to diverse Eurocentric and Americo-centric hermeneutical methods. This work, however, with its focus on Africa, takes a different approach. Drawing from the work of many African hermeneuticians, it reads Joel’s prophecy using the tools of African Biblical Hermeneutics (ABH), a post-colonial enterprise, in light of the decolonial turn. The article exegetes and theologically analyzes the narrative of the locust plague (ʾarbbeh) in Joel 1:2–7, within the context of Joel 1–3, with the hopes that it will be transformational and beneficial for African readers within their faith context.
Water Body Extraction of the Weihe River Basin Based on MF-SegFormer Applied to Landsat8 OLI Data
Authors: Zhang Tianyi , Qin Chenhao , Li Weibin , Mao Xin , Zhao Liyun , Hou Biao , Jiao Licheng
Published: September 2023

In the era of big data, making full use of remote sensing images to automatically extract surface water bodies (WBs) in complex environments is extremely challenging. Due to the weak capability of existing algorithms in extracting small WBs and WB edge information from remote sensing images, we proposed a new method—Multiscale Fusion SegFormer (MF-SegFormer)—for WB extraction in the Weihe River Basin of China using Landsat 8 OLI images. The MF-SegFormer method adopts a cascading approach to fuse features output by the SegFormer encoder at multiple scales. A feature fusion (FF) module is proposed to enhance the extraction of WB edge information, while an Atrous Spatial Pyramid Pooling (ASPP) module is employed to enhance the extraction of small WBs. Furthermore, we analyzed the impact of four kinds of band combinations on WB extraction by the MF-SegFormer model, including true color composite images, false color images, true color images, and false color images enhanced by Gaussian stretch. We also compared our proposed method with several different approaches. The results suggested that false color composite images enhanced by Gaussian stretching are beneficial for extracting WBs, and the MF-SegFormer model achieves the highest accuracy across the study area with a precision of 77.6%, recall of 84.4%, F1-score of 80.9%, and mean intersection over union (mIoU) of 83.9%. In addition, we used the determination coefficient (R2) and root-mean-square error (RMSE) to evaluate the performance of river width extraction. Our extraction results in an overall R2 of 0.946 and an RMSE of 28.21 m for the mainstream width in the “Xi’an-Xianyang” section of the Weihe River. The proposed MF-SegFormer method used in this study outperformed other methods and was found to be more robust for WB extraction.
Underwater Image Restoration via Adaptive Color Correction and Contrast Enhancement Fusion
Authors: Zhang Weihong , Li Xiaobo , Xu Shuping , Li Xujin , Yang Yiguang , Xu Degang , Liu Tiegen , Hu Haofeng
Published: September 2023

When light traverses through water, it undergoes influence from the absorption and scattering of particles, resulting in diminished contrast and color distortion within underwater imaging. These effects further constrain the observation of underwater environments and the extraction of features from submerged objects. To address these challenges, we introduce an underwater color image processing approach, which amalgamates the frequency and spatial domains, enhancing image contrast in the frequency domain, adaptively refining image color within the spatial domain, and ultimately merging the contrast-enhanced image with the color-corrected counterpart within the CIE L*a*b* color space. Experiments conducted on standard underwater image benchmark datasets highlight the significant improvements our proposed method achieves in terms of enhancing contrast and rendering more natural colors compared to several state-of-the-art methods. The results are further evaluated using four commonly used image metrics, consistently showing that our method yields the highest average value. The proposed method effectively addresses challenges related to low contrast, color distortion, and obscured details in underwater images, a fact especially evident in various scenarios involving color-affected underwater imagery.
Secure and Privacy-Preserving Intrusion Detection and Prevention in the Internet of Unmanned Aerial Vehicles
Authors: Ntizikira Ernest , Lei Wang , Alblehai Fahad , Saleem Kiran , Lodhi Muhammad Ali
Published: September 2023

In smart cities, unmanned aerial vehicles (UAVS) play a vital role in surveillance, monitoring, and data collection. However, the widespread integration of UAVs brings forth a pressing concern: security and privacy vulnerabilities. This study introduces the SP-IoUAV (Secure and Privacy Preserving Intrusion Detection and Prevention for UAVS) model, tailored specifically for the Internet of UAVs ecosystem. The challenge lies in safeguarding UAV operations and ensuring data confidentiality. Our model employs cutting-edge techniques, including federated learning, differential privacy, and secure multi-party computation. These fortify data confidentiality and enhance intrusion detection accuracy. Central to our approach is the integration of deep neural networks (DNNs) like the convolutional neural network-long short-term memory (CNN-LSTM) network, enabling real-time anomaly detection and precise threat identification. This empowers UAVs to make immediate decisions in dynamic environments. To proactively counteract security breaches, we have implemented a real-time decision mechanism triggering alerts and initiating automatic blacklisting. Furthermore, multi-factor authentication (MFA) strengthens access security for the intrusion detection system (IDS) database. The SP-IoUAV model not only establishes a comprehensive machine framework for safeguarding UAV operations but also advocates for secure and privacy-preserving machine learning in UAVS. Our model’s effectiveness is validated using the CIC-IDS2017 dataset, and the comparative analysis showcases its superiority over previous approaches like FCL-SBL, RF-RSCV, and RBFNNs, boasting exceptional levels of accuracy (99.98%), precision (99.93%), recall (99.92%), and F-Score (99.92%).
A Hybrid Deep Learning Approach: Integrating Short-Time Fourier Transform and Continuous Wavelet Transform for Improved Pipeline Leak Detection
Authors: Siddique Muhammad Farooq , Ahmad Zahoor , Ullah Niamat , Kim Jongmyon
Published: September 2023

A hybrid deep learning approach was designed that combines deep learning with enhanced short-time Fourier transform (STFT) spectrograms and continuous wavelet transform (CWT) scalograms for pipeline leak detection. Such detection plays a crucial role in ensuring the safety and integrity of fluid transportation systems. The proposed model leverages the power of STFT and CWT to enhance detection capabilities. The pipeline’s acoustic emission signals during normal and leak operating conditions undergo transformation using STFT and CWT, creating scalograms representing energy variations across time–frequency scales. To improve the signal quality and eliminate noise, Sobel and wavelet denoising filters are applied to the scalograms. These filtered scalograms are then fed into convolutional neural networks, extracting informative features that harness the distinct characteristics captured by both STFT and CWT. For enhanced computational efficiency and discriminatory power, principal component analysis is employed to reduce the feature space dimensionality. Subsequently, pipeline leaks are accurately detected and classified by categorizing the reduced dimensional features using t-distributed stochastic neighbor embedding and artificial neural networks. The hybrid approach achieves high accuracy and reliability in leak detection, demonstrating its effectiveness in capturing both spectral and temporal details. This research significantly contributes to pipeline monitoring and maintenance and offers a promising solution for real-time leak detection in diverse industrial applications.
Harnessing Wearable Devices for Emotional Intelligence: Therapeutic Applications in Digital Health
Authors: Arabian Herag , Abdulbaki Alshirbaji Tamer , Schmid Ramona , Wagner-Hartl Verena , Chase J. Geoffrey , Moeller Knut
Published: September 2023

Emotional intelligence strives to bridge the gap between human and machine interactions. The application of such systems varies and is becoming more prominent as healthcare services seek to provide more efficient care by utilizing smart digital health apps. One application in digital health is the incorporation of emotion recognition systems as a tool for therapeutic interventions. To this end, a system is designed to collect and analyze physiological signal data, such as electrodermal activity (EDA) and electrocardiogram (ECG), from smart wearable devices. The data are collected from different subjects of varying ages taking part in a study on emotion induction methods. The obtained signals are processed to identify stimulus trigger instances and classify the different reaction stages, as well as arousal strength, using signal processing and machine learning techniques. The reaction stages are identified using a support vector machine algorithm, while the arousal strength is classified using the ResNet50 network architecture. The findings indicate that the EDA signal effectively identifies the emotional trigger, registering a root mean squared error (RMSE) of 0.9871. The features collected from the ECG signal show efficient emotion detection with 94.19% accuracy. However, arousal strength classification is only able to reach 60.37% accuracy on the given dataset. The proposed system effectively detects emotional reactions and can categorize their arousal strength in response to specific stimuli. Such a system could be integrated into therapeutic settings to monitor patients’ emotional responses during therapy sessions. This real-time feedback can guide therapists in adjusting their strategies or interventions.
Biodegradation of Malathion in Amended Soil by Indigenous Novel Bacterial Consortia and Analysis of Degradation Pathway
Authors: Dar Mohd Ashraf , Kaushik Garima
Published: September 2023

The capabilities of pure bacterial strains and their consortia isolated from agricultural soil were evaluated during a bioremediation process of the organophosphate pesticide malathion. The pure bacterial strains efficiently degraded 50.16–68.47% of the pesticide within 15 days of incubation, and metabolites were observed to accumulate in the soil. The consortia of three bacterial species [Micrococcus aloeverae (MAGK3) + Bacillus cereus (AGB3) + Bacillus paramycoides (AGM5)] degraded the malathion more effectively, and complete malathion removal was observed by the 15th day in soils inoculated with that consortium. In contrast, the combined activity of any two of these strains was lower than the mixed consortium of all of the strains. Individual mixed consortia of Micrococcus aloeverae (MAGK3) + Bacillus cereus (AGB3); Micrococcus aloeverae (MAGK3) + Bacillus paramycoides (AGM5); and Bacillus cereus (AGB3) + Bacillus paramycoides (AGM5) caused 76.58%, 70.95%, and 88.61% malathion degradation in soil, respectively. Several intermediate metabolites like malaoxon, malathion monocarboxylic acid, diethyl fumarate, and trimethyl thiophosphate were found to accumulate and be successively degraded during the bioremediation process via GC–MS detection. Thus, inoculating with a highly potent bacterial consortium isolated from in situ soil may result in the most effective pesticide degradation to significantly relieve soils from pesticide residues, and could be considered a prospective approach for the degradation and detoxification of environments contaminated with malathion and other organophosphate pesticides. This study reports the use of a mixed culture of Indigenous bacterial species for successful malathion degradation.
Factors Influencing Crowdworkers’ Continued Participation Behavior in Crowdsourcing Logistics: A Textual Analysis of Comments from Online Platforms
Authors: Xie Guojie , Lin Xuejun , Deng Baiding , Zhang Qianheng , Tian Yu
Published: September 2023

With the lazy economy’s rise in the digital era, the demand for crowdsourcing logistics delivery is increasing. In this process, the continued participation of crowdworkers has been a considerable challenge. In order to further clarify the influencing factors of crowdworkers’ continuous participation and better and targeted incentives for their participative behavior, we use ROST-CM 6.0 software to conduct textual analysis on 3000 comments from crowdworkers on China’s Meituan and Hummingbird crowdsourcing logistics platforms. The results show that the order dispatch system, reward and punishment system, and platforms’ service are the key factors concerned by crowdworkers. The total negative sentiment among crowdworkers regarding crowdsourcing logistics platforms is close to 20%. We also find that crowdsourcing logistics platforms still have room for improvement in the quantity and quality of orders dispatched, the evaluation factors and the appeal system for reward and punishment rules, and the freedom and flexibility of distribution work. Otherwise, this might lead to a trust issue between crowdworkers and the crowdsourcing logistics platform. Based on the research findings, we recommend that the crowdsourcing logistics platforms should enhance service awareness, provide a better work experience for crowdworkers, and optimize platform functions. The government should act as a regulator as well as a service provider. This paper’s innovations include methodologically, from the perspective of the crowdworkers, online comment texts are used to mine the behavioral factors that influence the crowdworker’s continued participation in crowdsourcing logistics; content-wise, it adds fresh insights to existing research on how the order allocation system and platform reward and punishment mechanisms affect the crowdworkers’ continuous participation behavior.
Riding the Waves of Artificial Intelligence in Advancing Accounting and Its Implications for Sustainable Development Goals
Authors: Peng Yixuan , Ahmad Sayed Fayaz , Ahmad Ahmad Y. A. Bani , Al Shaikh Mustafa S. , Daoud Mohammad Khalaf , Alhamdi Fuad Mohammed Hussein
Published: September 2023

Artificial intelligence (AI) is emerging as a disruptive force in many sectors, and using it in accounting isn’t an exception. This conceptual paper explores the role of AI in accounting, for financial reporting, auditing, and financial decision-making and provides accountants an opportunity to improve efficiency, accuracy, and decision support. AI, through data analytics, algorithms, automation, etc. has an important role in the field of accounting with some challenges also. The study also highlights the implications of AI in accounting for achieving several Sustainable Development Goals (SDGs). Firstly, AI-driven automation can restructure financial activities, reducing time and resource consumption, and contributing to SDG 8 (Decent Work and Economic Growth). In addition, by providing real-time data analysis, AI empowers businesses to make sustainable decisions based on real-time data, aligning with SDG 9 (Industry, Innovation, and Infrastructure) and SDG-16 (Peace, Justice, and Strong Institutions) and SDG 17 (Partnerships for the Goals). The paper has implications for policy makers, technology developers, financial institutions and business firms.
Study on the Correlation Characteristics between Scenic Byway Network Accessibility and Self-Driving Tourism Spatial Behavior in Western Sichuan
Authors: Zhang Bo , Zhou Liangyu , Yin Zhiwen , Zhou Ao , Li Jue
Published: September 2023

The scenic byways in Western Sichuan are some of the most popular self-driving tourism destinations in China. However, the current network of scenic byways in the region is not well-coordinated with the level of regional tourism development. This paper, based on travel digital footprints, uses methods such as spatial design network analysis, GIS spatial analysis, social network analysis models, and spatial econometric models to analyze the accessibility and self-driving tourism spatial behavior characteristics in Western Sichuan. The main research results are as follows: (1) the accessibility level of scenic byways in Western Sichuan exhibits significant spatial variation, with the majority of areas demonstrating moderate to poor accessibility; (2) the network structure of self-driving tourism spatial behavior displays characteristics of low overall network density, but with a high clustering coefficient and relatively short average path length, indicating a significant small-world phenomenon. All network node indicators exhibit significant heterogeneity, with the core nodes displaying clear clustering characteristics; (3) the accessibility of scenic byways and self-driving tourism spatial behavior exhibit significant spatial spillover effects. This study analyzes the relationship between the accessibility of scenic byways and self-driving tourism spatial behavior in Western Sichuan, providing valuable insights for the planning and construction of scenic byways and the development of self-driving tour routes.
Construction of Digital Transformation Capability of Manufacturing Enterprises: Qualitative Meta-Analysis Based on Current Research
Authors: Ren Xingmin , Jing Hao , Zhang Yaoyao
Published: September 2023

Competitive advantage in enterprises can be substantially enhanced by the strategic deployment of digital transformation capabilities, which can be considered as distinctive resources. Within the domain of manufacturing enterprises, the discernment and classification of the structural dimensions inherent in digital transformation capabilities can serve as a pivotal factor in facilitating a more adaptable and seamless progression through the digital transformation journey. In pursuit of this objective, 22 typical manufacturing enterprises are selected as data samples, and a four-dimensional digital transformation capability system is constructed through the processes of excerpt, coding, classification, reliability and validity, etc. Combined with the view of capability hierarchy, a three-level capability structure model of digital transformation capability is constructed. The results show that digital transformation capability includes digital technology capability, digital operation capability, digital organization capability and digital strategic capability, and it is found that there is a hierarchical relationship among the capabilities of each dimension. The research findings have extended the theoretical boundaries of digital transformation, augmented the applicability scenarios of dynamic capability theory, and established a foundational framework for future empirical investigations into the digital capabilities of manufacturing enterprises.
Feasibility Study of a Reverse Osmosis Desalination Unit Powered by Photovoltaic Panels for a Sustainable Water Supply in Algeria
Authors: Tigrine Zahia , Aburideh Hanene , Zioui Djamila , Hout Sarra , Sahraoui Naima , Benchoubane Yasmine , Izem Amina , Tassalit Djilali , Yahiaoui Fatma Zohra , Khateb Mohamed , Drouiche Nadjib , Lebouachera Seif El Islam
Published: September 2023

In recent years, reverse osmosis water desalination has developed rapidly and has become the most competitive and widely used technology in the world. The number of desalination plants is increasing rapidly as freshwater needs increase. Various membrane technologies have been developed and improved, including nanofiltration (NF) and reverse osmosis (RO), whose desalination costs have been relatively reduced. Therefore, this work proposes an experimental study for a small desalination unit based on RO generated by renewable energy, which is mainly suitable for arid regions or desert areas that do not have electricity and water and can be applied for emergency treatment to meet strong freshwater resource needs. In this study, to meet the drinking water demand, a reverse osmosis desalination system is designed and evaluated in order to improve and optimize its operation. This system has a daily capacity of 2 m3. We used brackish groundwater, which has been characterized as reference water, to produce synthetic water for different salinities until seawater. The analysis is based on data obtained from experiments carried out in the standalone RO pilot designed for the production of fresh water. For this purpose, we conducted relevant experiments to examine the influence of applied pressure, salt concentration and temperature on the RO membrane performance. The effects of different factors that affect the energy consumption in the RO desalination process were analyzed, and those with significant influence were explored. The effectiveness of RO desalination coupled with a photovoltaic (PV) energy system is shown. We found the recovery rate for system operation to be 32%. An optimization study is presented for the operation of an autonomous RO desalination system powered by photovoltaic panels. The energy produced by the PV system was used to feed two pumps forthe production of drinking waterwithanRO membrane, under the conditions of the town of Bou-Ismail. As results, a 3 kWp PV system was installed based on the energy demand. The design data have shown that a 3 kWp PV system can power a 1.8 W RO load given the Bou-Ismail climate. Energy consumption in the case study under Bou-Ismail weather conditions were analyzed. The desalination of brackish water at a TDS value of 5 g/L requires an energy of about 1.5 kWh/m3. Using seawater at a TDS value of 35 g/L, this value increases to 5.6 kWh/m3. The results showed that the optimal recovery rate for system operation was determined to be 32% for a feedwater salinity of 35 g/L, and 80% for a feedwater salinity of 1 g/L.
The Mechanism and Countermeasures of the Impact of State Subsidy Backslide on the Efficiency of Waste-to-Energy Enterprises—A Case Study in China
Authors: Wang Huo-Gen , Rao Han
Published: September 2023

The scientific investment decision model of waste incineration power generation is helpful in providing a scientific basis for the government and environmental protection enterprises to formulate reasonable waste prices. The waste incineration power generation project revenue and cost composition framework, based on the project net present value of factors affecting causality analysis, the construction of a waste incineration power generation PPP project net present value system dynamics model, and the use of Vensim PLE software, version 7.3.5, combined with the garbage power generation of listed companies, was built, and we put into use the enterprise’s financial data and the author’s research of the case of the BOT (Build–Operate–Transfer) project data to examine the validity of the model test, simulation, and sensitivity analysis. The results show that the regression of a national subsidy does not necessarily lead to a price adjustment of the waste disposal fee, and when a change in tariff subsidy occurs, the loss brought by the reduction in a feed-in tariff can be compensated by increasing the income from carbon sinks, decreasing the intensity of investment through technological advancement, improving the coefficient of waste power generation through garbage classification, and increasing the utilization of production capacity through the treatment of multiple wastes in a single or a combination of ways.
Innovation Ecosystems in Hydrocarbon-Based Economies: Opportunities and Challenges
Authors: Al-Sulaiti Ahmed , Madhoun Iman T. , Abdella Galal M. , Al-Yafei Hussein , Hamouda Abdel Magid
Published: September 2023

Innovation is rapidly growing and affecting various industries, including hydrocarbon processing. This study aims to conduct a comprehensive and organized review of the literature on innovation ecosystems and their performance within hydrocarbon-based economies. It will examine existing definitions of innovation ecosystems and related concepts and conduct an in-depth analysis of certain hydrocarbon-based economies and their Global Innovation Index (GII) development from 2011 to 2022. The term “innovation ecosystem” has gained considerable attention from scholars and practitioners over the past fifteen years. Despite the proliferation of research in this area, there are concerns about its fragmented knowledge base. While previous reviews have highlighted the theoretical connections between innovation ecosystems and related concepts, there is still a need for a more comprehensive understanding of the current state of innovation ecosystem research. This study used a systematic literature review approach that combines bibliographic coupling and content analysis methods, drawing on over 40 studies to identify five streams of current innovation ecosystem research: Technology innovation, platform innovation ecosystems, regional development, innovation ecosystem conceptualization and theorization, and entrepreneurship and innovation. This study’s contribution lies in highlighting the specific elements that contribute to the development of an innovative economy based on hydrocarbons.
Fire Accident Risk Analysis of Lithium Battery Energy Storage Systems during Maritime Transportation
Authors: Zhang Chunchang , Sun Hu , Zhang Yuanyuan , Li Gen , Li Shibo , Chang Junyu , Shi Gongqian
Published: September 2023

The lithium battery energy storage system (LBESS) has been rapidly developed and applied in engineering in recent years. Maritime transportation has the advantages of large volume, low cost, and less energy consumption, which is the main transportation mode for importing and exporting LBESS; nevertheless, a fire accident is the leading accident type in the transportation process of LBESS. This paper applied fault tree analysis and Bayesian network methods to evaluate the fire accident risk of LBESS in the process of maritime transportation. The Bayesian network was constructed via GeNIe 2.3 software, and the probability of LBESS fire accidents during maritime transportation was calculated based on the probability of basic events occurring. The results showed that an unsuitable firefighting system for putting out lithium battery fires, high humidity, and monitoring equipment without a real-time alarm function have the most significant influence on the occurrence of LBESS fire accidents during maritime transportation. The research work of this paper provides a theoretical basis for the risk assessment of LBESS during maritime transportation.
The Association between Corporate Social Responsibility, Employee Performance, and Turnover Intention Moderated by Organizational Identification and Commitment
Authors: Alnehabi Mohammad , Al-Mekhlafi Al-Baraa Abdulrahman
Published: September 2023

Corporate social responsibility (CSR) holds increasing significance within Saudi Arabia’s banking sector. By adopting responsible and sustainable practices, banks can not only enhance their financial performance but also bolster the trust and loyalty of their customers. The sector recognizes that high turnover rates and subpar performance can lead to elevated costs and reduced trust in the bank’s services. Consequently, this study aims to investigate how organizational identification and commitment mediate the relationship between CSR, employee performance (EP), and turnover intention (TI). Following a survey with 550 employees, the structural equation modelling technique was applied to test the study’s model and complex relationships. The study assessed 12 hypotheses, 8 of which represented direct relationships, while the remaining 4 explained the mechanisms of the mediating relationships. All of these hypotheses show significant relationships. All variables explained the variance of EP by 42% while explaining the variance of TI by 28%, which had a moderate effect on the dependent variables. The model indicates that values are well constructed and that the model has predictive relevance due to Q2 being above 0. The study’s findings demonstrate that organizational identification and commitment channel the link between corporate social responsibility and employee performance and turnover intention. The study underscores the significance of CSR, organizational identification, and commitment in the Saudi Arabian banking sector. It provides valuable insights for banks to enhance employee performance, reduce turnover intention, and strengthen corporate social responsibility initiatives.
Understanding Systemic Risk Dynamics and Economic Growth: Evidence from the Turkish Banking System
Authors: Derindere Köseoğlu Sinem
Published: September 2023

The banking crisis experienced at the beginning of 2023 in the aftermath of the global 2008 crisis served as a stark reminder of the importance of systemic risk once again across the world. This study examines the dynamics of systemic risk in the Turkish banking system and its impact on sustainable economic growth between the period of 2007 and 2022. Through the Component Expected Shortfall (CES) method and quantile spillover analysis, private banks, such as Garanti Bank (GARAN), Akbank (AKBNK), İş Bank (ISCTR), and Yapı ve Kredi Bank (YKBNK), are identified as major sources of systemic risk. The analysis reveals a high level of interconnectedness among the banks during market downturns, with TSKB, Vakıfbank (VAKBNK), İş Bank (ISCTR), Halk Bank (HALKB), Akbank (AKBNK), Yapı ve Kredi Bank (YKBNK), and Garanti Bank (GARAN) serving as net risk transmitters, while QNB Finansbank (QNBFB), ICBC Turkey Bank (ICBCT), Şekerbank (SKBNK), GSD Holding (GSD), and Albaraka Türk (ALBRK) act as net risk receivers. Employing the Markov switching VAR (MS-VAR) model, the study finds that increased systemic risk significantly reduces economic growth during heightened financial periods. These findings underscore the importance of monitoring systemic risks and implementing proactive measures in the banking sector. The policy implications highlight the requirement for regulators and policymakers to prioritize systemic risk management. Close monitoring helps detect weaknesses and imbalances that could put financial stability at risk. Timely implementation of policies and rules is crucial in the prevention of the accumulation of systemic risks and in dealing with the existing hazards. Such measures protect the stability of the banking sector and mitigate potential negative effects on the broader economy.
Arsenic Distribution and Pollution in Three Mountain Streams (Anzasca Valley, Italian Central Alps)
Authors: Guerrieri Nicoletta , Lami Andrea , Musazzi Simona , Austoni Martina , Marchetto Aldo , Orrù Arianna , Giacomotti Paola , Tartari Gabriele , Lucchini Giorgio , Scaglioni Leonardo , Borgonovo Gigliola
Published: September 2023

Anzasca Valley is part of the Monte Rosa gold district located in the Italian Central Alps. Since we do not know the effects of arsenic on the aquatic environment in Anzasca Valley, we investigated the biofilm of three streams. The three perennial streams studied are in the Anza catchment but with different lithology. Rio Rosso flows out of an ancient gold mine (Miniera dei Cani); its waters, acid mine drainages, are rich in iron and arsenic. Rio Gattera, a small stream adjacent to the Rio Rosso, flows through metamorphic rocks with mixed composition. Its waters are not acidic but contain a small amount of arsenic. Rio Roletto is upstream, with respect to the others, and drains different metamorphic rocks without arsenic. We analyzed the chemistry and the metals of the water, characterized by microscopic analysis and HPLC, the phytobenthic community living in the biofilm, and in the Rio Rosso, we measured the arsenic adsorbed in the biofilm. Sampling was performed between 2012 and 2014, and arsenic in the biofilm of Rio Rosso was measured in different seasons. In the three streams, the carotenoids of the biofilms showed the different stability of phytobenthic communities (Bacyllariophyceae vs. Cyanobacteria): in Rio Roletto and Rio Gattera, the ratio between the communities did not change; in Rio Rosso, the ratio between the communities changed completely, probably due to the peculiarity of water composition and presence of arsenic.