bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating Multi-Criteria Techniques in Life-Cycle Tools for the Circular Bioeconomy Transition of Agri-Food Waste Biomass: A Systematic Review
Authors: Romero-Perdomo Felipe , González-Curbelo Miguel Ángel
Published: March 2023

Agri-food waste biomass (AWB) is consolidating as a relevant bioresource for supplying material products and energy in a circular bioeconomy. However, its recovery and sustainable processing present trade-offs that must be understood. The integration of multi-criteria decision analysis (MCDA) into life-cycle assessment (LCA) tools has emerged as a novel way to address this challenge. This paper aims to conduct a systematic literature review to critically synthesize how MCDA has been integrated into LCA in an assessment framework and how helpful it is in AWB’s circular bioeconomy transition. The literature shows that the most studied AWBs are rice husk, sugarcane bagasse, and household food waste. These are processed through the technologies of composting, anaerobic digestion, and pyrolysis for applications such as biofuels, bioenergy, and soil amendment. Environmental LCA (E-LCA) is the most widely used LCA tool, while both the analytical hierarchy process (AHP) and the technique for ordering preference by similarity to the ideal solution (TOPSIS) are the most applied techniques for MCDA. The current trend of integrating MCDA into LCA does not fully cover the LCA phases, favoring solely the impact assessment phase and indicating that the other phases are overlooked. The potential and involvement of the stakeholders are partially explored. Although there are holistic sustainability assessments, the social implications are rarely considered. The number of MCDA/LCA studies is expected to increase, assessments at the micro-, meso-, and macro-scales to become more articulated, and the impact of the results to become more aligned with government and company goals.
Parameters Identification of Solar PV Using Hybrid Chaotic Northern Goshawk and Pattern Search
Authors: Satria Habib , Syah Rahmad B. Y. , Nehdi Moncef L. , Almustafa Monjee K. , Adam Abdelrahman Omer Idris
Published: March 2023

This article proposes an effective evolutionary hybrid optimization method for identifying unknown parameters in photovoltaic (PV) models based on the northern goshawk optimization algorithm (NGO) and pattern search (PS). The chaotic sequence is used to improve the exploration capability of the NGO algorithm technique while evading premature convergence. The suggested hybrid algorithm, chaotic northern goshawk, and pattern search (CNGPS), takes advantage of the chaotic NGO algorithm’s effective global search capability as well as the pattern search method’s powerful local search capability. The effectiveness of the recommended CNGPS algorithm is verified through the use of mathematical test functions, and its results are contrasted with those of a conventional NGO and other effective optimization methods. The CNGPS is then used to extract the PV parameters, and the parameter identification is defined as an objective function to be minimized based on the difference between the estimated and experimental data. The usefulness of the CNGPS for extraction parameters is evaluated using three distinct PV models: SDM, DDM, and TDM. The numerical investigates illustrate that the new algorithm may produce better optimum solutions and outperform previous approaches in the literature. The simulation results display that the novel optimization method achieves the lowest root mean square error and obtains better optima than existing methods in various solar cells.
Technological Innovations for Citizen Environmental Participation: Case of Poland
Authors: Roszczyńska-Kurasińska Magdalena , Wróblewska Nina
Published: March 2023

Citizen science is a social innovation that has recently been recognized by social initiatives as a possible tool to increase participation, build knowledge, and raise civic awareness. In order to work efficiently, citizen science requires the adoption of proper technological solutions by a critical mass of people. According to the Unified Theory of Acceptance and Use of Technology, people are more likely to adopt a technology that is compatible with their norms, values, and beliefs. In our research, we studied technological solutions that Polish environmental civic initiatives are using in order to diagnose their potential to implement citizen science projects and increase citizen participation. We interviewed 28 board representatives, managers, and initiators of social movements and conducted desk research of 65 social movements in Poland. Every technological solution was recorded and later categorized. The diagnostic analysis of the technological advancement of grassroots movements in Poland reveals that the full potential for launching citizen science projects has not yet been reached. First of all, the recognition of the citizen science approach is still low. Secondly, grassroots movements operate using standard and easily accessible technological solutions, rarely developing tailored and more advanced technologies that would enable people to be involved in citizen science projects.
Evaluation of the Mechanism and Effectiveness of Digital Inclusive Finance to Drive Rural Industry Prosperity
Authors: Zhang Lanhua , Ning Manxiu , Yang Chaoying
Published: March 2023

Digital inclusive finance is an important policy for promoting rural industrial development in China. Can digital inclusive finance effectively contribute to the development of rural industries? What is its driving mechanism? Clarifying these questions can: (1) Release the value of digital inclusive finance; (2) Strengthen its driving role in rural industrial development; and (3) Implement the concept of inclusive development to give rural industrial subjects a greater sense of access and well-being. Based on the interpretation of the connotation of rural industrial prosperity, this paper constructs a theoretical framework of “digital inclusive finance—alleviating financing constraints—rural industrial prosperity”. Using the panel data of 31 provinces in China from 2011 to 2020, the study adopts the entropy weight method to measure the rural industry prosperity index; at the same time, it constructs a panel regression model to conduct benchmark tests, mediating effect tests and heterogeneity tests on the mechanisms and effects of digital inclusive finance to promote rural industrial prosperity. The article finds that digital inclusive finance effectively drives rural industrial prosperity; the alleviation of financing constraints plays a fully mediating role; the effect is significant in less economically developed regions. Therefore, this article proposes policy recommendations to advance rural digital construction, promote the digital transformation of traditional financial institutions, strengthen the regulation of internet-inclusive finance, and enhance the financial literacy of inclusive groups.
Capturing Dynamic Interests of Similar Users for POI Recommendation Using Self-Attention Mechanism
Authors: Fan Xinhua , Hua Yixin , Cao Yibing , Zhao Xinke
Published: March 2023

The integration of location-based social networks and POI recommendation systems has the potential to enhance the urban experience by facilitating the exploration of new and relevant locales. The deployment of graph neural networks (GNNs) drives the development of POI recommendations, but this approach also brings with it the challenge of over-smoothing, where information propagation between nodes in the graph can lead to an excessive homogenization of the data. In prior works that utilized GNNs for POI recommendation, the bipartite graphs constructed from users and POIs as nodes failed to incorporate temporal dynamics, limiting the scope of the analysis to only spatial structure information. To circumvent this issue, the incorporation of a temporal component can be introduced during the aggregation process of graph convolution. In light of these considerations, the present study proposes a novel regionalized temporal GCN (RST-GCN) recommendation model that leverages self-attention mechanism to capture various levels of temporal information to better reflect the dynamic changes of time. By combining the graph’s spatial structure with geospatial features, similar users are distributed into distinct regional subgraphs, effectively avoiding the influence of non-similar users. The efficacy of the proposed model has been demonstrated through empirical evaluations conducted on two real-world datasets.
Constructed Technosols as a Soil Rebuilding Technique to Reclaim Abandoned Limestone Quarries in the Mediterranean Region: A Field Study
Authors: Grilli Eleonora , Vigliotti Renata Concetta , Fiorentino Antonio , Scognamiglio Monica , Rossetti Luigi , Nogueira Thiago Assis Rodrigues , Jani Arun Dilipkumar , Abreu-Junior Cassio Hamilton , Ribeiro Roder Ludmila , Ganga Antonio , Capra Gian Franco
Published: March 2023

Soil rebuilding represents a major challenge in the recovery of abandoned quarries. In this study, we explored the possibility of using reconstructed Technosols, to achieve soil rebuilding goals at an abandoned quarry site. We first investigated the use of a mixture containing commercial manure and limestone debris (LD) as pedotechnomaterials for an “ad hoc” (re)constructed Technosol (CT), for the recovery of an opencast limestone quarry in one of most concentrated quarry areas in the world. In a field experiment, we tested and monitored different pedotechnosystems (PTSs) made up of constructed Technosol + pasture species + different Mediterranean plant species. Specifically, a control (CT, without any additional treatments) was compared to treatments with organic amendment (CTOA) and conventional fertilizers (CTCF). Data were collected over a 12-month period and included crop performance, plant nutritional state, soil physical-chemical parameters, and metabolites. Analysis of variance compared differences among treatments, while factor analysis (FA) interpreted multiple relationships while explaining observed variability. Results showed that CTOA had better soil physical-chemical properties, greater plant growth, and overall superior agronomic performances compared to all other treatments due to the improved substrate conditions. According to FA, these results appear related to the creation of fertile soil conditions, with most of the investigated metabolites (i) playing a pivotal role in observed outcomes, together with (ii) a clear potential in being considered as a reliable fingerprint for investigating plant responses in constructed PTSs. The proposed pedotechniques in CTOA development show a great potential for the full recovery of abandoned limestone quarries in degraded Mediterranean areas by providing an excellent medium for plant growth, facilitating environmental reclamation.
Influence of Organic Amendments Based on Garden Waste for Microbial Community Growth in Coastal Saline Soil
Authors: Li Jingnan , Zhang Haiyang , Zheng Li
Published: March 2023

Garden waste compost (GWC) has been applied as an amendment to improve the desalination efficiency, nutrient availability and diversity of the microbial community in coastal saline soil. Understanding the response of the microbial community to garden waste compost application is of great significance in coastal ecological restoration. Four treatments were established: CK, nonamended control; T1, application of 68 kg·m−3 garden waste compost; T2, application of 15 kg·m−3 bentonite; and T3, a mixture of garden waste compost and bentonite. In addition, soil physicochemical properties, soil enzymes, microbial biomass carbon and the soil microbial community were measured. The results show that T3 had a more significant effect on increasing soil enzymes, as well as microbial biomass carbon and nitrogen, urease, sucrase and dehydrogenase activities. Based on the relative abundance, microbial diversity and linear discriminant effect size (LEfSe) analyses, the amendments can be seen to have increased the microbial abundance and alpha diversity of the bacterial structure and also altered the microbial community structure. RDA and Pearson correlation analysis at the phylum level indicated that available nitrogen, total porosity, hydraulic conductivity, bulk density and EC were the primary determinants of microbial communities associated with this amendment. In conclusion, the application of garden waste compost enables more microorganisms to participate in the soil material cycle, indicating that garden waste composting is beneficial to the restoration of coastal soils.
Rediscovering the Shift-Share EM2 Model: A Decomposition Framework of Unbalanced Employment Growth at the Industrial Level
Authors: Luo Jian , Yang Yongchun
Published: March 2023

The unbalanced growth of employment among regions is ultimately attributed to the difference in industrial structure and industrial competitiveness. At the regional level, both shift-share EM1 and EM2 models can realize the purpose of the shift-share model, that is, thoroughly separate the effects of the industrial structure and industrial competitiveness on employment growth deviation. While the expectation is to further achieve a complete separation on employment growth deviation at the industrial level, the EM1 model is not competent, and this is precisely the role of the EM2 model—to separate the employment growth deviation caused by the differences in industrial structure and industrial competitiveness at the industrial level. Therefore, the shift-share EM2 model can realize the separation of the structural component and competitive component at the industrial level. In the process of industrialization, the manufacturing industry presents a significant trend of unbalanced growth in both spatial and industrial dimensions. The setting of the share component in the EM2 model covers the balanced growth of employment in both spatial and industrial dimensions. The allocation component is reinterpreted as the magnification or inhibition effect of industrial competitiveness on the initial industrial structure. In order to exclude the influence of the regional employment scale difference, the concept and calculation method of the regional deviation degree is put forward. Finally, the spatial pattern of unbalanced employment growth in China’s manufacturing industry from 1999 to 2019 was analyzed using the shift-share EM2 model at the regional level. The results show that the spatial imbalance trend of employment growth in China’s manufacturing industry is significant, the regional deviation scale of employment growth forms a north–south difference pattern, and the regional deviation degree forms a southeast to northwest difference pattern. Taking Sichuan Province as an example, the application of the shift-share EM2 model at the industrial level is demonstrated.
Green HRM Practices and Knowledge Sharing Improve Environmental Performance by Raising Employee Commitment to the Environment
Authors: Ahmad Farooq , Hossain Md Billal , Mustafa Khurram , Ejaz Faisal , Khawaja Kausar Fiaz , Dunay Anna
Published: March 2023

In this research, the moderating effect of green knowledge sharing was used to investigate the association between green human resources management (green HRM) practices (competence, motivation, and involvement) and environmental performance via employee environmental commitment. Using previously validated metrics, an online survey of 155 academic staff members from 25 Pakistani universities ranked in the UI-Green Metric 2021 for having green campuses was carried out. The findings demonstrated a significant relationship between green HRM practices, employee environmental commitment, and the university’s environmental performance. The correlation between all three green HRM practices and environmental performance was mediated by the employee’s environmental commitment. The findings indicate that in order to improve environmental performance and reach environmental sustainability goals, it is essential to foster green knowledge sharing among employees and increase employee environmental commitment through green HRM practices.
Exploring Regenerative Tourism Using Media Richness Theory: Emerging Role of Immersive Journalism, Metaverse-Based Promotion, Eco-Literacy, and Pro-Environmental Behavior
Authors: Hui Xiaozhe , Raza Syed Hassan , Khan Sanan Waheed , Zaman Umer , Ogadimma Emenyeonu C.
Published: March 2023

The evolving tourism industry and increasing number of travelers are not only raising environmental concerns about tourism sites, but also posing challenges for local communities. In this scenario, the notion and agenda for sustainable tourism are widely criticized due to their limited scope and emphasis on creating a balance between economic and adverse environmental and communal benefits. In response, the call for a necessary paradigm transformation has become intense. Consequently, a new approach—regenerative tourism—has been developed to create awareness about pro-environmental behavior to satisfy the primary needs of the community. Regenerative tourism supports the quality of life of local people. Therefore, there is a great need to promote eco-literacy through innovative and better audience experience-laden communication strategies, such as immersive journalism and metaverse-based promotional content. However, little is known about how these future technologies interplay with psychological and social mechanisms to enhance regenerative tourism intention. Drawing an analogy from pro-environmental theory and media richness theory, this research intends to identify whether virtual, augmented reality merger (i.e., immersive journalism), and metaverse-based environmental delineations may contribute to educating tourists and lead to regenerative tourism intention. This research was carried out using a cross-sectional online survey that collected data from 776 digital media users from Pakistan who plan to visit a destination or have done so previously. The results from the data, based on structural equation modeling, suggested that immersive journalism and metaverse-based regenerative tourism promotion are communication strategies that effectively enhance eco-literacy and lead to pro-environmental behavior. However, dispositional empathy has critical moderating implications; the greater the extent of the empathy concerns that individuals uphold, the stronger the eco-literacy and pro-environmental behavior. Finally, regenerative tourism intention can be predicted by these antecedents effectively. Therefore, these pioneer results confirmed that innovative technology-driven media content can augment awareness of regenerative tourism activities and transform travelers’ intention to adopt regenerative practices during destination visits. This research suggests strategic guidelines for organizations and governments to implement practical, innovative, and communicative tools that support adopting regenerative practices among prospective travelers.
Experimental Investigation of the Parapet Effect on the Wind Load of Roof-Mounted Solar Arrays
Authors: Yao Jianfeng , Tu Zhibin , Wang Dong , Shen Guohui , Yu Shice , Lou Wenjuan
Published: March 2023

A wind tunnel test was conducted to investigate the effects of parapets on the aerodynamic wind loads of roof-mounted solar arrays. The distribution of the mean wind pressure coefficient and the extreme wind pressure coefficient in the solar arrays were discussed in detail, and the results were compared with some national standards. Results show that the mean and extreme values of the wind pressure coefficient are larger at oblique wind angles. The presence of the parapet can reduce the mean and extreme area-averaged net pressure coefficients in some areas of the solar arrays, and both the most critical positive and negative shape factors reduce at the corner and outer rows while less change occurs at the inner zones. The experimental shape factors are much smaller compared to the values calculated by the standards. The guidelines for the design of wind pressure on roof-mounted solar arrays are very conservative, and more research is needed to make the standards applicable and complete.
Optimal Parameter Identification of Single-Sensor Fractional Maximum Power Point Tracker for Thermoelectric Generator
Authors: Olabi Abdul Ghani , Rezk Hegazy , Sayed Enas Taha , Awotwe Tabbi , Alshathri Samah Ibrahim , Abdelkareem Mohammad Ali
Published: March 2023

A thermoelectric generator (TEG) is used for converting temperature difference and into DC directly to electric energy based on the Seebeck effect. This new technology has attracted researchers of sustainable energy. The energy obtained from the TEG depends on the temperature difference between the two sides of the TEG. A reliable MPP “maximum power point” tracker (MPPT) is mandatory to guarantee that the TEG is working close to the MPP under different operational conditions. There are two common methods that have been widely used to track the MPP: hill climbing (HC) and incremental conductance (INR). The HC method is very fast in tracking the MPP; however, oscillation can occur under a high steady state. On the contrary, the INR method needs more time to track the MPP but does not oscillate around the MPP. To overcome these issues, fractional control is adopted. Furthermore, the proposed MPPT requires only a single current sensor, as opposed to conventional MPPTs, which require at least two sensors: current and voltage sensors. The cost of the control system is reduced when the number of sensors is reduced. Hunger games search optimization is used to estimate the parameters of a single sensor optimized fractional MPPT (OFMPPT). During the optimization process, three parameters were assigned as decision variables: proportional gain, integral gain, and order, with the objective function being the TEG’s energy. The results demonstrated the superiority of OFMPPT in both transient and steady state compared to HC and INR.
To Share or Not to Share—Expected Transportation Mode Changes Given Different Types of Fully Automated Vehicles
Authors: Heubeck Laura , Hartwich Franziska , Bocklisch Franziska
Published: March 2023

When it comes to climate change, automated vehicles (AV) are often presented as a key factor to reducing emissions related with the transport sector. While studies promise emissions savings of up to 80%, it is often overlooked how AVs will be introduced and which transportation mode changes will arise from their implementation. Therefore, this online survey examined usage intentions regarding private and shared AV types, and underlying attitudes and mobility needs of 136 current users of different main modes of transport. Two main results counteract the general assumption of ecological sustainability benefits of AVs: First, current car drivers prefer private over shared AV types, even though notable sustainability gains can only be expected from shared AVs. Second, current users of more sustainable modes of transport (walking, bike, public transport) would replace theses modes by AVs for substantial shares of their trips, which represents a behavioural rebound effect, since AVs cannot be more sustainable than walking or biking. Group-specific mobility needs and knowledge gaps regarding the sustainability of different AV types are identified as reasons for these results and as starting points for deriving necessary measures accompanying the introduction of AVs into society through motivating ecologically sustainable transportation mode changes.
Job Crafting, Job Boredom and Generational Diversity: Are Millennials Different from Gen Xs?
Authors: Sesen Harun , Donkor Ama Asantewaa
Published: March 2023

The current working environment requires employees to have some control over their jobs. Drawing on the job demands–resource (JD-R) theory, we investigated the relationship between job crafting and job boredom. Based on the generational cohort theory, we determined the strength of the relationship using generational diversity as a moderator. Data from 320 participants employed in white-collar jobs in the private sector were collected over two time periods. Structural equation modeling and hierarchical regression were used in the analysis. The results of this study show that job crafting has a significant negative impact on job boredom. This effect is further differentiated by generational differences, that is, belonging to Gen X or the Millennial cohorts. The use of self-administered questionnaires may result in the selection of ‘socially desired’ outcomes. This study has implications for today’s intergenerational environment, since different generational groups have different attributes, priorities, desires and motivations that impact their actions. This study adds to the limited research on the impact of job crafting on job boredom. However, this is the first study to examine the moderating effect of Gen X and Millennials on the relationship between job crafting and boredom. As a result, appropriate incentives can be implemented to encourage crafting among generational cohorts within organizations, especially with the entry of Generation Z into the workforce.
Identification and Spatial Correlation of Imported Timber Landing Processing Industrial Clusters in Heilongjiang Province of China
Authors: Zhou Baixu , Qi Xinyue , Hou Xinru , Chen Zhili , Wu Jinzhuo
Published: March 2023

This paper analyzed the clustering degree and spatial distribution characteristics of the imported timber landing processing industry in China’s Heilongjiang province based on the survey and statistical data during 2019–2021. The location entropy method was used to quantify the clustering degree of timber landing processing. Multi-distance spatial clustering analysis, hotspot analysis, and spatial autocorrection analysis were conducted to identify the spatial pattern of enterprises and analyze the hotspots and spatial correlation among the prefecture-level cities in the region. Results showed that there was obvious industrial agglomeration in imported timber landing processing in Heilongjiang Province, and the overall spatial pattern of the industry showed significant spatial aggregation at different spatial scales. The hotspots were primarily concentrated in the southeast of the province with a high level of industrial development, while the cold spots were primarily in the western and northern parts with a low level of industrial development. The distribution of the imported timber landing processing industry at the provincial level was positively correlated, but not very significantly. There was large spatial heterogeneity for the imported timber landing processing industry. Some suggestions were put forward in order to accelerate the construction of imported timber landing processing industrial clusters in the region.
Tcs and Tcs¯ Family Production in Multi-Production Processes
Authors: Jiang Chuanhui , Jin Yi , Li Shi-Yuan , Liu Yan-Rui , Si Zong-Guo
Published: March 2023

The production mechanism of multiquark exotic hadrons in high energy multiproduction processes lies in the structure of the relevant exotic hadrons as well as in some important aspects of high energy scattering, such as multi-parton interactions, underlying events, etc. At mass pole around 2900 MeV, a family of open charm tetraquarks, Tcss and Tcs¯s, are observed in B decay. They are also suitable for study in multiproduction processes to obtain more information on their structure. If these resonances are produced as compact four-quark states, one can predict the production properties based on the similarities in their production mechanism to those of Ξc, Σc, and Λc. Physics implies that the colour and baryon number fluctuations of the preconfinement system in high energy scattering can enhance both the baryon and four-quark state production rates via ‘diquark fragmentation’. We calculate the production properties of the tetraquark family Tcss and Tcs¯s at LHC energy for the forthcoming LHC measurements.
A Detailed Study of Mathematical Rings in q-Rung Orthopair Fuzzy Framework
Authors: Razzaque Asima , Razaq Abdul , Alhamzi Ghaliah , Garg Harish , Faraz Muhammad Iftikhar
Published: March 2023

Symmetry-related problems can be addressed by means of group theory, and ring theory can be seen as an extension of additive group theory. Ring theory, a significant topic in abstract algebra, is currently active in a diverse range of study domains across the disciplines of mathematics, theoretical physics and coding theory. The study of ideals is vital to the theory of rings in a wide range of ways. The uncertainties present in the information are addressed well by the q-rung orthopair fuzzy set (q-ROFS). Considering the significance of ring theory and the q-ROFS, this article defines q-rung orthopair fuzzy ideals (q-ROFIs) in conventional rings and investigates its various algebraic features. We introduce the notion of q-rung orthopair fuzzy cosets (q-ROFCs) of a q-ROFI and demonstrate that, under certain binary operations, the collection of all q-ROFCs of a q-ROFI forms a ring. In addition, we provide a q-rung orthopair analog of the fundamental theorem of ring homomorphism. Furthermore, we present the notion of q-rung orthopair fuzzy semi-prime ideals (q-ROFSPIs) and provide a comprehensive explanation of their many algebraic properties. Finally, regular rings were characterized using q-ROFIs.
Fathoming the Mandela Effect: Deploying Reinforcement Learning to Untangle the Multiverse
Authors: Alhakamy A’aeshah
Published: March 2023

Multiverse is a hypothetical idea that other universes can exist beyond our own. Various scientific theories have suggested scenarios such as the existence of bubble universes that constantly expand or string theory that attempts to merge gravity with other forces. Thus, a multiverse is a complex theoretical phenomenon that can best be conceived through computer simulation. Albeit within the multiverse, the causality of the Mandela effect is entirely possible. To examine the behavior of the multiverse as a representative ensemble, each universe as a specific ensemble element needs to be generated. Our universe generation is based on unique universes for two binary attributes of a population of n=303. The maximum possible universes this could produce within the multiverse is in the exponent of 182. To computationally confine the simulation to the scope of this study, the sample count of the multiverse is nmultiverse=606. Parameters representing the existence of each multiverse are implemented through the μ and σ values of each universe’s attributes. By using a developed reinforcement learning algorithm, we generate a multiverse yielding various universes. The computer gains consciousness of the parameters that can represent the expanse of possibility to exist for multiple universes. Furthermore, for each universe, a heart attack prediction model is performed to understand the universe’s environment and behavior. We test the Mandela effect or déjà vu of each universe by comparing error test losses with the training size of order M. Our model can measure the behavior of environments in different regions referred to as specific ensemble elements. By explicitly exploiting the attributes of each universe, we can get a better idea of the possible outcomes for the creation of other specific ensemble elements, as seen in the multiverse space planes.
Investigating the Dynamics of Time-Fractional Drinfeld–Sokolov–Wilson System through Analytical Solutions
Authors: Noor Saima , Alshehry Azzh Saad , Dutt Hina M. , Nazir Robina , Khan Asfandyar , Shah Rasool
Published: March 2023

This study addresses a nonlinear fractional Drinfeld–Sokolov–Wilson problem in dispersive water waves, which requires appropriate numerical techniques to obtain an approximative solution. The Adomian decomposition approach, the homotopy perturbation method, and Sumudu transform are combined to tackle the problem. The Caputo manner is used to describe fractional derivative, and He’s polynomials and Adomian polynomials are employed to address nonlinearity. By following these approaches, we obtain solutions in the form of convergent series. We verify and demonstrate the effectiveness of our suggested strategies by examining the assumed model in terms of fractional order. We use plots for various fractional orders to represent the physical behavior of the suggested technique solutions, and show a numerical simulation. The results demonstrate that the suggested algorithms are systematic, simple to use, effective, and accurate in analyzing the behavior of coupled nonlinear differential equations of fractional order in related scientific and engineering fields.
PREIUD: An Industrial Control Protocols Reverse Engineering Tool Based on Unsupervised Learning and Deep Neural Network Methods
Authors: Ning Bowei , Zong Xuejun , He Kan , Lian Lian
Published: March 2023

The security of industrial control systems relies on the communication and data exchange capabilities provided by industrial control protocols, which can be complex, and may even use encryption. Reverse engineering these protocols has become an important topic in industrial security research. In this paper, we present PREIUD, a reverse engineering tool for industrial control protocols, based on unsupervised learning and deep neural network methods. The reverse process is divided into stages. First, we use the bootstrap voting expert algorithm to infer the keyword segment boundaries of the protocols, considering the symmetry properties. Then, we employ a bidirectional long short-term memory conditional random field with an attention mechanism to classify the protocols and extract their format and semantic features. We manually constructed data sample sets for six commonly used industrial protocols, and used them to train and test our model, comparing its performance to two advanced protocol reverse tools, MSERA and Discoverer. Our results showed that PREIUD achieved an average accuracy improvement of 7.4% compared to MSERA, and 15.4% compared to Discoverer, while also maintaining a balance between computational conciseness and efficiency. Our approach represents a significant advancement in the field of industrial control protocol reverse engineering, and we believe it has practical implications for securing industrial control systems.
Reverse Reconciliation for Optimal Error Correction in Quantum Key Distribution
Authors: Lizama-Perez Luis Adrián
Published: March 2023

In this work, we introduce a new method for the establishment of a symmetric secret key through the reconciliation process in QKD systems that, we claim, is immune to the error rate of the quantum channel and, therefore, has an efficiency of 100% since it does not present losses during the distillation of secret keys. Furthermore, the secret rate is scaled to the square of the number of pulses on the destination side. The method only requires a single data exchange from Bob over the classic channel. We affirmed that our results constitute a milestone in the field of QKD and error correction methods at a crucial moment in the development of classical and quantum cryptanalytic algorithms. We believe that the properties of our method can be evaluated directly since it does not require the use of complex formal-theoretical techniques. For this purpose, we provide a detailed description of the reconciliation algorithm. The strength of the method against PNS and IR attacks is discussed. Furthermore, we define a method to analyze the security of the reconciliation approach based on frames that are binary arrays of 2×2. As a result, we came to the conclusion that the conjugate approach can no longer be considered secure, while we came up with a way to increase the secret gain of the method with measured bits.
Cancellation of the Sigma Mode in the Thermal Pion Gas by Quark Pauli Blocking
Authors: Blaschke David , Friesen Alexandra , Kalinovsky Yuri
Published: March 2023

In this study, we calculate the pressure of the interacting pion gas using the Beth–Uhlenbeck approach to the relativistic virial expansion with Breit–Wigner phase shifts for the σ- and ϱ-meson resonances. The repulsive phase shift δ02 is taken from the quark interchange model of Barnes and Swanson, which is in very good agreement with the experimental data. In this work we show that the cancellation of the attractive (I = 0) and repulsive (I = 2) isospin channel contributions to the scalar ππ interaction in the low-energy region that is known for the vacuum phase shifts also takes place at a finite temperature. This happens despite the strong medium dependence of these phase shifts that enters our model by the temperature dependence of the σ-meson and constituent quark masses, because for these masses the relation Mσ(T)≈2mq(T) holds and the scattering length approximation is valid as long as the strong decay channel σ→ππ is open. Exploiting the Nambu–Jona-Lasinio model for describing the dynamical breaking of chiral symmetry in the vacuum and its restoration at a finite temperature, we justify with our approach that the σ-meson should be absent from the hadron resonance gas description at low temperatures because the above cancellation holds. However, since this cancellation breaks down in the vicinity of the hadronization transition, where due to chiral symmetry restoration the decay channel σ→ππ closes and the σ-meson becomes a good resonance, the latter should be included into the statistical model description of chemical freeze-out in heavy-ion collisions.
Strong Differential Subordination and Superordination Results for Extended q-Analogue of Multiplier Transformation
Authors: Lupaş Alina Alb , Ghanim Firas
Published: March 2023

The results obtained by the authors in the present article refer to quantum calculus applications regarding the theories of strong differential subordination and superordination. The q-analogue of the multiplier transformation is extended, in order to be applied on the specific classes of functions involved in strong differential subordination and superordination theories. Using this extended q-analogue of the multiplier transformation, a new class of analytic normalized functions is introduced and investigated. The convexity of the set of functions belonging to this class is proven and the symmetry properties derive from this characteristic of the class. Additionally, due to the convexity of the functions contained in this class, interesting strong differential subordination results are proven using the extended q-analogue of the multiplier transformation. Furthermore, strong differential superordination theory is applied to the extended q-analogue of the multiplier transformation for obtaining strong differential superordinations for which the best subordinants are provided.
Analysis of Milk Production and Failure Data: Using Unit Exponentiated Half Logistic Power Series Class of Distributions
Authors: Alghamdi Safar M. , Shrahili Mansour , Hassan Amal S. , Mohamed Rokaya Elmorsy , Elbatal Ibrahim , Elgarhy Mohammed
Published: March 2023

The unit exponentiated half logistic power series (UEHLPS), a family of compound distributions with bounded support, is introduced in this study. This family is produced by compounding the unit exponentiated half logistic and power series distributions. In the UEHLPS class, some interesting compound distributions can be found. We find formulas for the moments, density and distribution functions, limiting behavior, and other UEHLPS properties. Five well-known estimating approaches are used to estimate the parameters of one sub-model, and a simulation study is created. The simulated results show that the maximum product of spacing estimates had lower accuracy measure values than the other estimates. Ultimately, three real data sets from various scientific areas are used to analyze the performance of the new class.
Factors Influencing Investment Decisions in Financial Investment Companies
Authors: Abdul kareem Ahmed Amer , Fayed Zaki T. , Rady Sherine , Amin El-Regaily Salsabil , Nema Bashar M.
Published: March 2023

For making the most favorable financial decisions possible, it is essential to have an understanding of aspects and the factors which can play a role in the decision-making. In contrast to previous research on the subject, which has only examined a single factor in making investment decisions, our study takes a more holistic approach by looking at several factors. The purpose of this study was to discover the elements that influence investment decisions made by financial organizations that are listed on Iraqi stock exchanges (ISX). The research was carried out on the six companies that made up the study’s sample size. For the purpose of data collection, the researcher utilized a structured questionnaire that was delivered to the respondents in an individual capacity. The questionnaire contained eight items. The factors of the questionnaire were analyzed with respect to normal distribution, the problem of linear multiplicity, the validity of the questionnaire in terms of content and appearance, the stability of the questionnaire by the split-half method, and the test and re-test method. In addition, the research hypotheses were tested on both the independent variables and the dependent variables. We calculated the mean, standard deviation, weight percentile, and coefficient of variance from the collected data. The significance of the connection between the dimensions of the decision-making factors was clarified through the use of Spearman’s correlation coefficient and the t test. We concluded that in the last step of the proposed model there is an increase in coefficients of determination and it reaches a value of (0.98), which is a very excellent and almost complete interpretation of the impact of dimensions extracted in the model and their impact on investment decision. As is noted, a slight decline in the value of the regression coefficient for all variables occurred, and also we noticed that the signs for the coefficients for the five variables are positive, meaning that they reflect the extent of the direct effect of those variables in making the investment decision. The response rate for the questionnaire was 97.7%.
Bacillus thuringiensis Cyt Proteins as Enablers of Activity of Cry and Tpp Toxins against Aedes albopictus
Authors: Lai Liliana , Villanueva Maite , Muruzabal-Galarza Ane , Fernández Ana Beatriz , Unzue Argine , Toledo-Arana Alejandro , Caballero Primitivo , Caballero Carlos J.
Published: March 2023

Aedes albopictus is a species of mosquito, originally from Southeast Asia, that belongs to the Culicidae family and the Dipteran insect order. The distribution of this vector has rapidly changed over the past decade, making most of the temperate territories in the world vulnerable to important human vector-borne diseases such as dengue, yellow fever, zika or chikungunya. Bacillus thuringiensis var. israeliensis (Bti)-based insecticides represent a realistic alternative to the most common synthetic insecticides for the control of mosquito larvae. However, several studies have revealed emerging resistances to the major Bti Crystal proteins such as Cry4Aa, Cry4Ba and Cry11Aa, making the finding of new toxins necessary to diminish the exposure to the same toxicity factors overtime. Here, we characterized the individual activity of Cyt1Aa, Cry4Aa, Cry4Ba and Cry11Aa against A. albopictus and found a new protein, Cyt1A-like, that increases the activity of Cry11Aa more than 20-fold. Additionally, we demonstrated that Cyt1A-like facilitates the activity three new Bti toxins: Cry53-like, Cry56A-like and Tpp36-like. All in all, these results provide alternatives to the currently available Bti products for the control of mosquito populations and position Cyt proteins as enablers of activity for otherwise non-active crystal proteins.
Prevalence and Concentration of Mycotoxins in Animal Feed in the Middle East and North Africa (MENA): A Systematic Review and Meta-Analysis
Authors: Jalilzadeh-Amin Ghader , Dalir-Naghadeh Bahram , Ahmadnejad-Asl-Gavgani Masoud , Fallah Aziz A. , Mousavi Khaneghah Amin
Published: March 2023

This study seeks a comprehensive meta-analysis of mycotoxin contaminants in animal feed consumed in the Middle East and North Africa (MENA) region. The obtained articles were reviewed, and 49 articles that investigated the contamination of mycotoxins including aflatoxins (AFs), deoxynivalenol (DON), zearalenone (ZEA), T-2 toxin, fumonisins (FUM), and ochratoxin A (OTA), in feed samples or components of animal feed in the MENA region were selected. The titles of the final articles included in the study were meta-analyzed. Necessary information was extracted and categorized from the articles, and a meta-analysis was performed using Stata software. The highest contamination was in dry bread (80%), and Algeria was the most contaminated country (87% of animal feed), with the most mycotoxins contaminating AFs (47%) and FUM (47%). The highest concentration of mycotoxins in animal feed is related to FUM (1240.01 μg/kg). Climate change, economic situation, agricultural and processing methods, the nature of the animal feed, and improper use of food waste in animal feed are among the most critical factors that are effective in the occurrence of mycotoxin contamination in animal feed in MENA. Control of influential factors in the occurrence of contaminations and rapid screening with accurate identification methods to prevent the occurrence and spread of mycotoxin contamination of animal feed seem important.
Stability Analysis of the Inhomogeneous Perturbed Einstein Universe in Energy–Momentum Squared Gravity
Authors: Sharif Muhammad , Gul Muhammad Zeeshan
Published: March 2023

The main objective of this article is to examine the stability of Einstein static universe using inhomogeneous perturbations in the context of energy–momentum squared gravity. For this purpose, we used FRW spacetime with perfect matter distribution and formulated static as well as perturbed field equations. We took a minimal model of this theory to investigate the stable regions of the Einstein universe for conserved and non-conserved energy–momentum tensors. We found that stable modes of the Einstein universe appeared in both conserved and non-conserved cases for all values of the equation of state and model parameters corresponding to both open and closed cosmic models. We found that stable solutions in this modified theory were obtained for a broader ω-region compared to other modified theories.
The General Property of Tracking and Thawing Models and Their Observational Constraints
Authors: You Yujie , Qiang Qichao , Gao Qing
Published: March 2023

We study the general property of the evolution of a class of scalar fields with tracking and thawing behaviors. For the tracking solutions, we show explicitly with three different potentials that, independent of initial conditions, there exists a general relation between the equation of state wϕ and the fractional energy density Ωϕ, so that the scalar field follows the same wϕ−Ωϕ trajectory during the evolution. The analytical approximations of the wϕ−Ωϕ trajectories are derived even though the analytical expression depends upon the particular form of the potential. For thawing solutions, a universal wϕ−Ωϕ relation exists and the relation is independent of both the particular form of the potential and the initial condition of the scalar field. Based on the derived wϕ−Ωϕ relation for the thawing models, we derive a tighter upper limit on wϕ′=dwϕ/dlna. The observational data is also used to constrain the thawing potential with the help of the universal wϕ−Ωϕ relation.
Dual-Driven Solver for Reconstructing the Point Sources of Elastic Wave Based on Far-Field Data
Authors: Meng Pinchao , Chai Yuanyuan , Yin Weishi
Published: March 2023

Aiming at the inverse source problem of an elastic wave, a dual-driver solver is considered to reconstruct the point sources. In this way, the number, location, and magnitude of the point sources can be reconstructed from far-field measurement data. The solver is composed of a data-driven module and a physical-driven module, which is coupled by a loss. The loss of the data-driven module and the physical-driven module are both the driving force of the solver evolution. The solver takes the far-field data as the input, and the number, location, and magnitude of the point sources as the output. It is trained by the Adam algorithm. Numerical experiments show that this method is effective for reconstructing the multi-sources.