bluuebunny/crossref_metadata_2025 huggingface dataset:
Determination of the Parameters of Ground Acoustic-Impedance in Wind Farms
Authors: Wu Jiaying , Wang Jing , Sun Zhenye , Zhu Wei Jun , Shen Wen Zhong
Published: November 2022

The ground surface near a wind turbine has a significant influence on the sound propagation from the turbine, and it is therefore important to determine the ground impedance, a quantity that characterizes the ground surface acoustically. Outdoor ground parameters required by a multi-parameter model used to calculate the ground acoustic-impedance are typically unknown, which brings inconvenience for the model use. This paper introduces a technique to determine the parameters of ground acoustic-impedance for use in a multi-parameter impedance model (for example, the Attenborough four-parameter model). The technique consists of three steps: first, the data for sound-pressure level measured at a distance from two different heights are collected, and the sound-pressure-level difference is calculated; second, in line with the experimental data and the sound-pressure-level calculation formula, the MATLAB optimization tool is used to find the optimal values of the parameters used in the impedance model; and finally, when the optimization is finished, the acoustic impedance of the ground is obtained by substituting the optimal values into the impedance model. To check the performance of the calculation, the calculated sound-pressure-level difference is compared to the experimental one. Compared with a traditional method, the technique can significantly reduce the calculation error.
Road Tunnels Operation: Effectiveness of Emergency Teams as a Risk Mitigation Measure
Authors: Borghetti Fabio , Frassoldati Alessio , Derudi Marco , Lai Igino , Trinchini Cristian
Published: November 2022

Managing a major event in a road tunnel requires more resources than an open-air event. In the case of fire, the confined environment of road tunnels can represent a critical situation for both users and rescuers. The safety level of a tunnel can be estimated by using dedicated risk models that consider, on the one hand, the traffic (type, quantity and distribution) of a tunnel and, on the other hand, the structural and plant safety measures. According to the European Directive, road tunnel managers can adopt additional safety measures aimed at increasing the level of safety for users exposed to the consequences of an accidental event. One of these measures is the rapid intervention of emergency teams located in the proximity of the tunnel. These teams use pick-up and scooter vehicles properly equipped to cope with a fire event and have detailed knowledge of the specific tunnel system. A further advantage of the emergency teams is the possibility of supporting the evacuation of tunnel users by providing indications on emergency exits, bypasses and safe places considering the evolution of the specific event. In this perspective, the present research contributes to the evaluation of the emergency teams’ effectiveness. Thus, the emergency team was included as a safety measure within a risk analysis model for road tunnels developed by the authors in previous works. After an analysis of the technical and scientific literature, we focused on 15 interventions carried out on some highway tunnels in Italy between the year 2019 and the year 2021. The intervention times of the teams were analyzed using data provided by Strada dei Parchi S.p.A., a company that manages 14 highway tunnels in Italy. These 14 tunnels range in length from 589 m to 10,121 m and are subject to the European Directive. The observed intervention times of the emergency teams range between 2 min and 10 min with an average value of 5.9 min. Such a short intervention time is possible because emergency teams are in the proximity of the different tunnels. Because of the short intervention time and the training of the personnel, all the fires were properly managed by the teams. Furthermore, considering the results of the scientific literature and the data presented in this work, it was possible to estimate and validate an effectiveness value (higher than 90%) of the emergency teams to be used within the risk analysis model developed by the authors and which can also be used in other risk analysis models.
Features of Sustainability-Oriented Innovations: A Content Analysis of Patent Abstracts
Authors: Celone Andrea , Cammarano Antonello , Caputo Mauro , Michelino Francesca
Published: November 2022

This article aims to identify the features of sustainability-oriented innovation starting from the content analysis of patent abstracts. An automatic tool was developed capable of finding the keywords, or groups of keywords, related to the 169 targets of sustainable development goals (SDGs). Once the patents deemed useful for pursuing SDGs were selected through the tool, they were analyzed to obtain information on their features in terms of breadth, scope, novelty, openness, prior art and scientific base. Among the most significant results, it is found that a larger number of applicants, suggesting the adoption of “open innovation” strategies, contributes to sustainability orientation. Moreover, patent originality contributes to the probability of pursuing sustainable objectives, especially related to environmental issues. On the contrary, claims are inversely correlated with the attitude to pursue SDGs, i.e., the larger number of areas in which a patent claims to intervene, the lower the probability that such innovation is sustainable. The results obtained by adopting a quantitative approach are in line with suggestions proposed by the literature and, so far, only supported by logical arguments or case studies. The potential of the tool developed, applied to the field of innovation and sustainability, is demonstrated as significant.
Unfolding the Impact of Quality 4.0 Practices on Industry 4.0 and Circular Economy Practices: A Hybrid SEM-ANN Approach
Authors: Huang Zengjian , Shahzadi Amna , Khan Yaser Daanial
Published: November 2022

In the era of Industry 4.0, Quality 4.0 (Q4.0) relates to quality management. To that end, it focuses on digital technologies that integrate social and technical resources and offer the best possible product and service to its customers. Few real-world studies have been done on the social and technical aspects of Q4.0. Thus, the purpose of this study is to investigate empirically the impact of social and technical Q4.0 on I4.0 technologies and circular economy practices (CEP) in small- and medium-sized (SME) manufacturing enterprises. A framework based on the resource-based view (RBV) theory is developed and empirically validated by an online questionnaire of 189 Malaysian SME manufacturing enterprises. In contrast to the other existent QM investigations, which made use of structural equation modelling (SEM), this study performed an analysis in two stages. First, the Q4.0 practices that significantly influence I4.0 technologies and CEP are identified using the SEM approach. Second, the significant predictors obtained from SEM are ranked according to their relative importance using the artificial neural network (ANN) technique. The findings indicate that social and technical Q4.0 practices have improved I4.0 technologies and CEP. The findings also highlight the role performed by technical Q4.0 practices as a mediator between social Q4.0 practices, I4.0 technologies, and CEP. The findings of ANN highlight that the role of social and technical Q4.0 are crucial to the successful deployment of I4.0 technologies and CEP in manufacturing companies. The purpose of the current research is to shed light on the importance of Q4.0 multidimensions, hence contributing to theory application, especially given the scarcity of multidimensional perspectives of Q4.0 literature. In essence, the SEM-ANN methodology adds something new to the bodies of literature on Q4.0, I4.0, and CEP. As an outcome of the research, organisations can develop innovative strategies to adopt Q4.0 by gaining a better understanding of the elements that contribute to effective Q4.0 implementation in the digital transformation era.
Analysis of Distribution and Structures of Heteroatom Compounds in Asphaltene of Medium/Low Temperature Coal Tar by Negative Anion Mode ESI FT-ICR MS
Authors: Fan Xiaoyong , Li Dong , Cui Louwei , Shao Ruitian , Chang Chunran , Yan Long , Yang Bo
Published: November 2022

The existence of heteroatomic compounds with complex structure and different polarity in the asphaltene of medium and low temperature coal tar (M/LTCT) limits its processing and utilization. Combined with negative ion electrospray ionization source (ESI), Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used to characterize the molecular composition of O, N, and S heteroatom compounds in M/LTCT asphaltenes. Acidic oxygen-containing compounds (OCCs) and non-basic nitrogen-containing compounds (NCCs) in asphaltenes were identified, except for sulfur-containing compounds (SCCs). The mass spectra showed that the heteroatom compounds in asphaltene mainly existed as NX, N1OX, N2OX, N3OX, N4OX, N5OX, N6OX, and OX class species (where x = 1–6). The M/LTCT asphaltenes were enriched with O4, N4, and N1O1 class species. The core structure of O4 class species were likely to be composed of 1–7 aromatic rings with 4 phenolic hydroxyl groups, the core structure of N4 class species were likely to be comprised of 4–7 aromatic rings with a piperazine ring and a pyrazole ring, and the core structure of N1O1 was mainly 3–6 aromatic rings with a phenolic hydroxyl group and a pyrrole ring. These results suggest that more condensed NCCs and OCCs with short, substituted alky side chains are presented, which are more easily to undergo condensation to generate fused molecules, making it too difficult to be removed by hydrogenation. Through the analysis of the molecular structures of OCCs and non-basic NCCs in M/LTCT asphaltenes, important information about the molecular composition can be obtained, which can provide basic data for the hydrogenation of deasphaltene.
Application of a Decision-Making Tool for Ranking Wellness Tourism Destinations
Authors: Lopes Ana Paula , Rodríguez-López Nuria
Published: November 2022

One of the tourism industry’s segments with the strongest growth rates today is health tourism. Health tourism includes two subgroups: medical tourism (traveling outside one’s country of residence for the purpose of receiving medical care, such as surgery and health services) and wellness tourism (travel to specific locations for health promotion in a preventive way). The economic strength and sustainable growth of nations can both benefit from health tourism. This study applies a methodology to quantify the potential of Portuguese wellness tourism (thermal spas in Northern Portugal) using a multi-criteria decision making (MCDM) tool, namely the preference ranking organization method for enrichment evaluations (PROMETHEE) and geometrical analysis for interactive aid (GAIA), to achieve a robust evaluation and ranking the alternatives. Therefore, in this study, the aim is to rank ten thermal spas in Northern Portugal in terms of fifteen indicators, mostly related to digital services, containing the tourism data obtained between 2020 and 2022. The suggested approach offers trustworthy and reliable outcomes for any qualitative or quantitative criteria to assess thermal spas, which is crucial for consumers, businesses, and even governments. The results showed that PROMETHEE and GAIA can be implemented as an effective method in wellness tourism destinations evaluation.
Identification of Key Areas for Ecosystem Restoration Based on Ecological Security Pattern
Authors: Duan Jiaquan , Fang Xuening , Long Cheng , Liang Yinyin , Cao Yue ‘e , Liu Yijing , Zhou Chentao
Published: November 2022

Ecosystem degradation and conversion are leading to a widespread reduction in the provision of ecosystem services. It is crucial for the governance of regional land spaces to rapidly identify key areas for ecosystem restoration. Herein, we combined the InVEST Habitat Quality Model with the granularity inverse method to identify ecological sources in Jiashi county, China, based on the “source-corridor” ecological security pattern paradigm. The minimum cumulative resistance model and circuit theory were adopted to diagnose the ecological “pinch points”, barrier points, break points, and key restoration areas for land space. Our results show that: (1) the area of the ecological source and the total length of the ecological corridor were identified as 1331.13 km2 and 316.30 km, respectively; (2) there were 164 key ecological “pinch points” and 69 key ecological barrier points in Jiashi county, with areas of 15.13 km2 and 14.57 km2, respectively. Based on the above ecological security pattern, recovery strategies are put forward to improve regional ecosystem health. This study describes the best practices which can be used to guide the planning and implementation of ecosystem restoration at the local landscape scale.
Aquatic Weed for Concrete Sustainability
Authors: Yehualaw Mitiku Damtie , Alemu Mihiret , Hailemariam Behailu Zerihun , Vo Duy-Hai , Taffese Woubishet Zewdu
Published: November 2022

Ordinary Portland cement (OPC) is the primary binder of concrete, accounting for approximately 5% to 7% of greenhouse gas (GHG) and carbon dioxide (CO2) emissions with an annual production rate of more than 4 billion tons. It is critical to reduce the carbon footprint of concrete without sacrificing its performance. To this end, this study focuses on the use of water hyacinth ash (WHA) as a pozzolanic binder in the production of concrete as a partial replacement for cement. Four mixes are designed to achieve C-25-grade concrete with varying proportions of cement replacement with WHA of 0%, 5%, 10%, and 15% of the cement weight. Extensive experiments are performed to examine the workability, strength, durability, and microstructure of concrete specimens. The test results confirm that incorporating WHA in concrete improved its workability, strength, and durability. The optimal results are obtained at the maximum OPC replacement level, with 10% WHA. The use of WHA as a partial replacement for cement greatly reduces the energy required for cement production and preserves natural resources. More research is needed to use WHA on a large scale to achieve greater sustainability in the concrete industry.
A Case Study of Delayed Action PIR Urinal-Controls in a University Setting and Their Impact before, during and after COVID-19
Authors: Daly James E. M. , Saroj Devendra P. , Chenoweth Jonathan L. , Parrott Thomas
Published: November 2022

This study looks at the application of delayed action Passive Infrared (PIR) sensors in the control of water use for urinal flushing. In this we briefly review the literature on urinal controls before reviewing four different approaches to PIR urinal controls. Existing literature discusses some of the pros and cons of different types of urinal control. However, the literature does not consider the differences that occur within individual approaches, based on the way controls operate. This study was initiated at the University of Surrey during 2019 following a water saving audit, in an attempt to bring down one of their largest users of water. This paper therefore aims to identify the most effective way to reduce water consumption of urinal systems, through retro-fitting PIR control systems within the variety of settings across university campuses. This paper also reviews the different reductions achieved over periods of differing use, during term-time, holidays, COVID-19 lockdowns, and the ‘new normal’. It found that grouped delayed action flushing was the most effective form of urinal control for reducing water use. It, achieved a 59–64% adjusted reduction during non-COVID-19 periods, and a 35% reduction against the control group during lockdowns saving 98,000 L/day on average across the study.
Durability and Acoustic Performance of Rubberized Concrete Containing POFA as Cement Replacement
Authors: Mhaya Akram M. , Shahidan Shahiron , Zuki Sharifah Salwa Mohd , Huseien Ghasan Fahim , Azmi Mohamad Azim Mohammad , Ismail Mohammad , Mirza Jahangir
Published: November 2022

Given that rubber tires are almost immune to biological degradation, this vast amount of solid waste is a major environmental concern worldwide. Reuse of these waste tires in the construction industry is one of the strategies to minimize their environmental pollution and landfill problems, while contributing to more economical building design. Thus, we assessed the improved traits of rubberized concrete made by combining palm oil fuel ash (POFA) with tire rubber aggregates (TRAs). Studies on the effects of POFA inclusion on the durability properties of rubberized concrete with TRAs as the replacement agent for fine or coarse aggregates remain deficient. Herein, the rubberized concrete contained 20% POFA as ordinary Portland cement (OPC) substitute, and various amounts of TRAs (5, 10, 20 and 30%). The proposed mixes enclosing three types of TRAs (fiber, fine and coarse aggregates) were characterized to determine their durability and acoustic performance. The water absorption, fire endurance performance, chloride penetration, and acoustic properties of the proposed concrete were evaluated. The designed concrete showed a systematic increase in water absorption and chloride penetration with the increase in rubber amount and particle size. These POFA-modified rubberized concretes displayed a satisfactory performance up to 500 °C, and superior acoustic properties in terms of sound absorption. The presence of TRA as 30% coarse aggregate replacement was found to improve the sound absorption properties by as much as 42%.
A New Green Labeling Scheme for Agri-Food Supply Chains: Equilibrium and Information Sharing under Uncertainties
Authors: Philip Ajay , Marathe Rahul R.
Published: November 2022

Even though organic farming is perceived worldwide as the most eco-friendly agricultural method, its significantly lower yield compared to conventional farming poses a major challenge in ensuring food security for the ever-increasing world population. On the other hand, the adverse environmental impacts of conventional agriculture due to the uncontrolled use of key farm inputs like fertilizer and irrigation water cannot be overlooked. In this context, we develop a new eco-label to promote an efficient agricultural method that provides the right balance between yield and environmental impacts through the optimal use of these farm inputs. The proposed eco-label is applied to a game-theoretic model of a farmer-retailer supply chain under demand and yield uncertainties. We consider the demand as a function of the product’s retail price, greenness, and quality; and model yield using a crop-response function. The analytical results derived help optimize the farm inputs, retail prices, and order quantity so that the stakeholders’ profits are maximized. We also investigate the effects of yield information sharing in this supply chain and find that the stakeholders must share yield information when environmentally conscious consumers dominate the market.
Plant Growth-Promoting Rhizobacteria (PGPR): Approaches to Alleviate Abiotic Stresses for Enhancement of Growth and Development of Medicinal Plants
Authors: Kumar Rahul , Swapnil Prashant , Meena Mukesh , Selpair Shweta , Yadav Bal Govind
Published: November 2022

Plants are constantly exposed to both biotic and abiotic stresses which limit their growth and development and reduce productivity. In order to tolerate them, plants initiate a multitude of stress-specific responses which modulate different physiological, molecular and cellular mechanisms. However, many times the natural methods employed by plants for overcoming the stresses are not sufficient and require external assistance from the rhizosphere. The microbial community in the rhizosphere (known as the rhizomicrobiome) undergoes intraspecific as well as interspecific interaction and signaling. The rhizomicrobiome, as biostimulants, play a pivotal role in stimulating the growth of plants and providing resilience against abiotic stress. Such rhizobacteria which promote the development of plants and increase their yield and immunity are known as PGPR (plant growth promoting rhizobacteria). On the basis of contact, they are classified into two categories, extracellular (in soil around root, root surface and cellular space) and intracellular (nitrogen-fixing bacteria). They show their effects on plant growth directly (i.e., in absence of pathogens) or indirectly. Generally, they make their niche in concentrated form around roots, as the latter exude several nutrients, such as amino acids, lipids, proteins, etc. Rhizobacteria build a special symbiotic relationship with the plant or a section of the plant’s inner tissues. There are free-living PGPRs with the potential to work as biofertilizers. Additionally, studies show that PGPRs can ameliorate the effect of abiotic stresses and help in enhanced growth and development of plants producing therapeutically important compounds. This review focuses on the various mechanisms which are employed by PGPRs to mitigate the effect of different stresses in medicinal plants and enhance tolerance against these stress conditions.
Antecedents of Big Data Analytic Adoption and Impacts on Performance: Contingent Effect
Authors: Lutfi Abdalwali , Al-Khasawneh Akif Lutfi , Almaiah Mohammed Amin , Alshira’h Ahmad Farhan , Alshirah Malek Hamed , Alsyouf Adi , Alrawad Mahmaod , Al-Khasawneh Ahmad , Saad Mohamed , Ali Rommel Al
Published: November 2022

The adoption of big data analytics (BDA) is increasing pace both in practice and in theory, owing to the prospects and its potential advantages. Numerous researchers believe that BDA could provide significant advantages, despite constant battles with the constraints that limit its implementation. Here, we suggest an incorporated model to investigate the drivers and impacts of BDA adoption in the Jordanian hotel industry based on the technology–organisation–environment framework and the resource-based view theory. The suggested model incorporates both the adoption and performance components of BDA into a single model. For data collection, in this study, we used an online questionnaire survey. The research model was verified based on responses from 119 Jordanian hotels. This study yielded two significant findings. First, we discovered that relative advantage, organizational readiness, top management support, and government regulations have a major impact on BDA adoption. The study results also reveal a strong and favourable association between BDA adoption and firm performance. Finally, information sharing was found to have a moderating effect on the association between BDA adoption and firm performance. The data revealed how businesses might increase their BDA adoption for improved firm performance. The present study adds to the limited but growing body of literature investigating the drivers and consequences of technology acceptance. The findings of this study can serve as a resource for scholars and practitioners interested in big data adoption in emerging nations.
Impact Analysis of Population Aging on Public Education Financial Expenditure in China
Authors: Pan Feng , Zhu Keyi , Wang Lin
Published: November 2022

The problem of China’s aging population is becoming increasingly serious, which brings a variety of social and economic issues. This paper constructed the theoretical framework and analyzed the impact mechanism of the population aging on local public education financial expenditure, and selected provincial panel data from 2010 to 2020 for empirical testing. It is found that population aging has a significant negative impact on local public education financial expenditure, and that with every 1% increase in old-age dependency ratio, local public education financial expenditure will decrease by 0.304%. The increase of urbanization rate has a significant positive impact on local public education financial expenditure, and with every 1% increase in urbanization rate, the local public education financial expenditure will increase by 0.215%. The test of impact mechanism shows that local government fiscal revenue and public expenditure for the elderly has the mediating effect in the impact of population aging on local public education financial expenditure, and the mediating effect of public expenditure for the elderly is stronger. The conclusions of the research can help provide policy implications for solving the declining level of local government public education financial expenditure in the context of an ageing population, and provide theoretical support to improve the rational allocation of fiscal public expenditure.
Sustainable Agriculture: Relationship between Knowledge and Attitude among University Students
Authors: Durán Gabela Carlos , Trejos Bernardo , Lamiño Jaramillo Pablo , Boren-Alpízar Amy
Published: November 2022

Sustainable agriculture (SA) has emerged as an alternative to feeding an increasing global population. Several frameworks have been used in SA research. This study proposes understanding SA under five components: environment, economy, society, resilience, and persistence. The decision-making process for adopting SA is determined by several factors, such as knowledge and attitudes. Both constructs play a decisive role in SA’s development, a field where university students are called to be leaders and decision-makers. Despite the increase in the body of SA literature, little is known about SA in Latin America. This research aimed to analyze university students’ attitudes and knowledge of SA and the relationship between both constructs. A completely structured questionnaire was designed and distributed online. A Likert-type scale was used for attitude and multiple-choice questions for knowledge. It was found that, among participants (n = 374), the majority had a high level of attitude (71.9%) and a moderate level of knowledge (62.1%) of SA. Participants’ attitudes towards SA were positive, regardless of gender (p = 0.17) and perceived knowledge does not predict measured knowledge (R2 = 0.074; p < 0.001). Moreover, a low positive relationship was found between attitude and knowledge (rs = 0.252; p = 0.000). Further research should focus on analyzing other factors that could affect attitude and knowledge of SA.
Whose Sense of Place? Catering for Residents and Tourists from an Open-Access Protected Area in South Africa
Authors: Rouillard Tessa , Deponselle Keagan , Carlos Bezerra Joana
Published: November 2022

In addition to providing benefits to people, protected areas are valued in ways that go beyond the tangible. A sense of place, and the collection of values, feelings, and meanings associated with a place, can illuminate people-place relationships. Understanding how people relate to a place is essential in acquiring support for protected areas. This research investigates tourists’ and residents’ sense of place in Knysna, an open-access section of the Garden Route National Park, South Africa. Data was collected through questionnaires and semi-structured interviews. The sense of place was characterised using five variables: physical, cultural, social, dependent, and ideological. Although ‘physical’ was the dominant variable for both tourists and residents, the ‘ideological’ for residents and the ‘cultural’ for tourists came second, highlighting the importance of safe places and recreational activities, respectively. The physical environment influences sense of place, and the importance of protected areas to stakeholders offers an opportunity for management to engage with the public.
GIS Partial Discharge Pattern Recognition Based on Multi-Feature Information Fusion of PRPD Image
Authors: Yin Kaiyang , Wang Yanhui , Liu Shihai , Li Pengfei , Xue Yaxu , Li Baozeng , Dai Kejie
Published: November 2022

Partial discharge (PD) pattern recognition is a critical indicator for evaluating the insulation state of gas-insulated switchgear (GIS). Aiming at the disadvantage of traditional PD pattern recognition methods, such as single feature extraction and low recognition accuracy, a pattern recognition method of PD based on multi-feature information fusion is proposed in this paper. Firstly, a recognition model based on quasi-Hausdorff distance is established according to the statistical characteristics of the phase-resolved partial discharge (PRPD) image, and then a modified convolutional neural network recognition model is established according to the image features of the PRPD image. Finally, Dempster–Shafer (D–S) evidence theory is used to fuse the two pattern recognition results and complement the advantages of the two approaches to improve the accuracy of partial discharge pattern recognition. The experimental results show that the total recognition accuracy rate of this method for four typical PD is more than 94.00%, and the recognition rate is significantly improved compared to support vector machine and normal convolution neural network. Maintaining stability in typical bipedal robots is challenging due to two main reasons.
Ulam Stability of a General Linear Functional Equation in Modular Spaces
Authors: Aboutaib Issam , Benzarouala Chaimaa , Brzdęk Janusz , Leśniak Zbigniew , Oubbi Lahbib
Published: November 2022

Using the direct method, we prove the Ulam stability results for the general linear functional equation of the form ∑i=1mAi(fφi(x¯))=D(x¯) for all x¯∈Xn, where f is the unknown mapping from a linear space X over a field K∈{R,C} into a linear space Y over field K; n and m are positive integers; φ1,…,φm are linear mappings from Xn to X; A1,…,Am are continuous endomorphisms of Y; and D:Xn→Y is fixed. In this paper, the stability inequality is considered with regard to a convex modular on Y, which is lower semicontinuous and satisfies an additional condition (the Δ2-condition). Our main result generalizes many similar stability outcomes published so far for modular space. It also shows that there is some kind of symmetry between the stability results for equations in modular spaces and those in classical normed spaces.
Singularities for Focal Sets of Timelike Sabban Curves in de Sitter 3-Space
Authors: Wang Yongqiao , Yang Lin , Liu Yuxin , Chang Yuan
Published: November 2022

In the theory of cosmology, de Sitter space is the symmetrical model of accelerated expansions of the universe. It is derived from the solution of the Einstein field equation, which has a positive cosmological constant. In this paper, we define the evolutes and focal surfaces of timelike Sabban curves in de Sitter space. We find that de Sitter focal surfaces can be regarded as caustics and de Sitter evolutes corresponding to the locus of the polar vectors of osculating de Sitter subspaces. By using singularity theory, we classify the singularities of the de Sitter focal surfaces and de Sitter evolutes and show that there is a close relationship between a new geometric invariant and the types of singularities. Moreover, the Legendrian dual relationships between the hyperbolic tangent indicatrix of timelike Sabban curves and the focal surfaces are given. Finally, we provide an example to illustrate our main results.
Defense against SSDF Attack and PUE Attack in CR-Internet of Vehicles (IoVs) for Millimeter Wave Massive MIMO Beamforming Systems
Authors: Pari Deepanramkumar , Natarajan Jaisankar
Published: November 2022

The Internet of Vehicles (IoV) is witnessed to play the leading role in the future of Intelligent Transportation Systems (ITS). Though many works have focused on IoV improvement, there is still a lack of performance due to insufficient spectrum availability, lower data rates, and the involvement of attackers. This paper considers all three issues by developing a novel mmWave-assisted Cognitive Radio based IoV (CR-IoV) model. The integration of CR in IoV resolves the issue of spectrum management, while mmWave technology ensures symmetry in acquiring higher data rates for Secondary Users (SUs). With the proposed mmWave-assisted CR-IoV model, symmetric improvements in network performance were achieved in three main areas: security, beamforming, and routing. Optimum detection mechanisms isolate malicious Secondary Users (SUs) in the overall network. First, Spectrum Sensing Data Falsification (SSDF) attack is detected by a Hybrid Kernel-based Support Vector Machine (HK-SVM), which is the lightweight Machine Learning (ML) technique. Then, the Primary User Emulation (PUE) attack is detected by a hybrid approach, namely the Fang Algorithm-based Time Difference of Arrival (FA-TDoA) method. Further, security is assured by validating the legitimacy of each SU through a Lightweight ID-based Certificate Validation mechanism. To accomplish this, we employed the Four Q-curve asymmetric cryptographic algorithm. Overall, the proposed dual-step security provisioning approach assures that the network is free from attackers. Next, beamforming is performed for legitimate SUs by a 3D-Beamforming algorithm that relies on Array Factor (AF) and Beampattern Function. Finally, routing is enabled by formulating Forwarding Zone (FZ) based on the forwarding angle. In the forwarding zone, optimal forwarders are selected by the Multi-Objective Whale Optimization (MOWO) algorithm. Here, a new potential score is formulated for fitness evaluation. Finally, the proposed mmWave-assisted CR-IoV model is validated through extensive simulations in the ns-3.26 simulation tool. The evaluation shows better performance in terms of throughput, packet delivery ratio, delay, bit error rate, and detection accuracy.
Reversible Data Hiding Using an Improved Pixel Value Ordering and Complementary Strategy
Authors: Kumar Rajeev , Kumar Neeraj , Jung Ki-Hyun
Published: November 2022

Reversible data hiding (RDH) schemes based on pixel value ordering have gained significant popularity due to their unique capability of providing high-quality marked images with a decent embedding capacity, while also enabling secret information extraction and the lossless recovery of the original images at the receiving side. However, the marked image quality may be distorted severely when the pixel value ordering (PVO) method is employed in a layer-wise manner to increase the embedding capacity. In this paper, a new high-capacity RDH scheme using a complementary strategy is introduced to overcome the limitation of the image quality in the case of layer-wise embedding. The proposed RDH scheme first divides the cover image into non-overlapping blocks of 2 × 2 pixels uniformly and then sorts the pixels of each block according to their intensity values. The secret data are then embedded into two layers. In the first layer, the minimum value of the block is decreased and the maximum value is increased by either 1 or 2 to embed the secret data bits. The second layer is used as a complement to the first layer and is in symmetry with the first layer. In the second layer, the proposed RDH scheme increases the minimum valued pixel and decreases the maximum valued pixel in order to minimize the distortion resulting from the first layer embedding and to embed an additional amount of the secret data. As a result, the proposed RDH scheme significantly increases the embedding capacity, which is clearly evident from the conducted experimental results.
Impact of Reliability in Conceptual Design—An Illustrative Trade-Off Analysis
Authors: Barker Tevari , Parnell Gregory S. , Pohl Edward , Specking Eric , Goerger Simon R. , Buchanan Randy K.
Published: November 2022

System reliability is treated as a parameter and not modeled in the early concept design stages. We illustrate a reliability model for system reliability in early concept design using knowledge from similar systems, technology readiness levels (TRL), and functional analysis methods using an unmanned ground vehicle. We integrate the reliability model with performance and cost models to demonstrate the impact of reliability in early concept design. The resultant tradespace comparison with and without early reliability assessment illustrates that reliability modeling can identify infeasible solutions in early system design. This will allow system designers to focus development on the most promising concept designs.
The Capacity Decision-Making of Omnichannel Catering Firms Based on Queueing System Considering Customer Reference Behavior
Authors: Zhan Wen-Tao , Wang Xue-Ping , Jiang Ming-Hui , Jiang Han , Huo Da , Liu Yun-Tao
Published: November 2022

Omnichannel catering firms need to pay attention to the consumer behavior of customers in both online and offline channels to make the corresponding capacity decisions. However, customers’ consumption behavior is not only affected by base utility, but also by reference utility, which indicates that customers have reference dependence when making consumption decisions. In order to better help omnichannel catering firms to make capacity decisions more in line with customer consumption behavior in their actual operations, this paper adopts the queuing theory to construct an optimal capacity decision-making model for omnichannel catering firms. We also analyzed the impact of channel information availability on customer reference behavior and the subsequent impact on the firm’s optimal decision-making. The findings were as follows: when the channel information is unavailable, customers in each channel take their expectation of waiting time as the reference point. With the improvement of the sensitivity of customers in different channels to the reference point, firms should improve their safety capacity to meet customers’ needs. Moreover, at a higher reference point, the increase in customer sensitivity can make the firm obtain higher profits. When channel information is available, customers take the waiting time of customers in different channels as the reference point, and the increased sensitivity of online customers to the reference point will prompt firms to reduce safety capacity. Comparing the two scenarios, we also found that omnichannel catering firms could develop lower safety capacities and obtain higher profits more easily when channel information is available. This not only contributes to the development of omnichannel catering firms, but also expands the application scope of reference theory.
Deep Learning Prediction of Pathologic Complete Response in Breast Cancer Using MRI and Other Clinical Data: A Systematic Review
Authors: Khan Nabeeha , Adam Richard , Huang Pauline , Maldjian Takouhie , Duong Tim Q.
Published: November 2022

Breast cancer patients who have pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) are more likely to have better clinical outcomes. The ability to predict which patient will respond to NAC early in the treatment course is important because it could help to minimize unnecessary toxic NAC and to modify regimens mid-treatment to achieve better efficacy. Machine learning (ML) is increasingly being used in radiology and medicine because it can identify relationships amongst complex data elements to inform outcomes without the need to specify such relationships a priori. One of the most popular deep learning methods that applies to medical images is the Convolutional Neural Networks (CNN). In contrast to supervised ML, deep learning CNN can operate on the whole images without requiring radiologists to manually contour the tumor on images. Although there have been many review papers on supervised ML prediction of pCR, review papers on deep learning prediction of pCR are sparse. Deep learning CNN could also incorporate multiple image types, clinical data such as demographics and molecular subtypes, as well as data from multiple treatment time points to predict pCR. The goal of this study is to perform a systematic review of deep learning methods that use whole-breast MRI images without annotation or tumor segmentation to predict pCR in breast cancer.
Analysis on Spatio-Temporal Evolution and Influencing Factors of Air Quality Index (AQI) in China
Authors: Yang Renyi , Zhong Changbiao
Published: November 2022

After the reform and opening up, China’s economy has developed rapidly. However, environmental problems have gradually emerged, the top of which is air pollution. We have used the following methods: In view of the shortcomings of the current spatio-temporal evolution analysis of the Air Quality Index (AQI) that is not detailed to the county level and the lack of analysis of its underlying causes, this study collects the AQI of all counties in China from 2014 to 2021, and uses spatial autocorrelation and other analysis methods to deeply analyze the spatio-temporal evolution characteristic. Based on the provincial panel data, the spatial econometric model is used to explore its influencing factors and spillover effects. The research results show that: (1) From 2014 to 2021, the AQI of all counties in China showed obvious spatial agglomeration characteristics, and counties in central and western Xinjiang, as well as Beijing, Tianjin, and Hebei, were high-value agglomeration areas; (2) the change trend of the AQI value also has obvious spatial autocorrelation, and generally presents a downward trend. However, the AQI value in a small number of regions, such as Xinjiang, shows a slow decline or even a reverse rise; (3) there are some of the main factors affecting AQI, such as GDP per capita, percentage of forest cover, total emissions of SO2, and these factors have different impacts on different regions. In addition, the increase of GDP per capita, the reduction of industrialization level, and the increase of forest coverage will significantly improve the air quality of other surrounding provinces. An in-depth analysis of the spatio-temporal evolution, influencing factors, and spillover effects of AQI in China is conducive to formulating countermeasures to improve air quality according to local conditions and promoting regional sustainable development.
How Botulinum Neurotoxin Light Chain A1 Maintains Stable Association with the Intracellular Neuronal Plasma Membrane
Authors: Gardner Alexander P. , Barbieri Joseph T. , Pellett Sabine
Published: November 2022

Botulinum neurotoxin serotype A (BoNT/A) is the most potent protein toxin for humans and is utilized as a therapy for numerous neurologic diseases. BoNT/A comprises a catalytic Light Chain (LC/A) and a Heavy Chain (HC/A) and includes eight subtypes (BoNT/A1-/A8). Previously we showed BoNT/A potency positively correlated with stable localization on the intracellular plasma membrane and identified a low homology domain (amino acids 268–357) responsible for LC/A1 stable co-localization with SNAP-25 on the plasma membrane, while LC/A3 was present in the cytosol of Neuro2A cells. In the present study, steady-state- and live-imaging of a cytosolic LC/A3 derivative (LC/A3V) engineered to contain individual structural elements of the A1 LDH showed that a 59 amino acid region (275–334) termed the MLD was sufficient to direct LC/A3V from the cytosol to the plasma membrane co-localized with SNAP-25. Informatics and experimental validation of the MLD-predicted R1 region (an α-helix, residues 275–300) and R2 region (a loop, α-helix, loop, residues 302–334) both contribute independent steps to the stable co-localization of LC/A1 with SNAP-25 on the plasma membrane of Neuro-2A cells. Understanding how these structural elements contribute to the overall association of LC/A1 on the plasma membrane may identify the molecular basis for the LC contribution of BoNT/A1 to high potency.
Pattern of Aedes aegypti and Aedes albopictus Associated with Human Exposure to Dengue Virus in Kinshasa, the Democratic Republic of the Congo
Authors: Mbanzulu Kennedy Makola , Wumba Roger , Mboera Leonard E. G. , Kayembe Jean-Marie Ntumba , Engbu Danoff , Bojabwa Michael Mondjo , Zanga Josué Kikana , Misinzo Gerald , Kimera Sharadhuli Iddi
Published: November 2022

Dengue is a worldwide public health concern. The current study assessed the extent of human exposure to the dengue virus in relation to the distribution pattern of Aedes aegypti and Ae. albopictus in Kinshasa. Cross-sectional surveys were carried out in 2021 and 2022. The baseline entomological survey involved 19 municipalities using a grid cell sampling approach. All containers holding water were inspected for the presence of larvae in each grid. The collected larvae were kept in an insectary until the adult emergence for morphological identification. Four hundred febrile patients attending the hospital were screened for the presence of dengue antibodies (IgG, IgM) and NS1 antigen using a rapid diagnostic test (RDT) Biosynex®. Residences of positive cases were geo-referenced. We evaluated 1850 grid cells, of which 19.5% were positive for Aedes larvae. The positive grid cells were identified in the Ndjili (44.0%), Mont Ngafula (32.0%) and Ngaliema (26.0%), and Limete (32.0%) municipalities. The Ae. aegypti (11.2%) predominated in the northwestern, and Ae. albopictus (9.1%) appeared in the high vegetation coverage areas. Of 61 (15.3%) participants exposed to dengue, 8.3% presented acute dengue. Young, (6–17 years), male, and Mont Amba district participants were most exposed to dengue. In conclusion, dengue occurrence in Kinshasa overlaps somewhat the geographical and ecological distributions of Ae. aegypti and Ae. albopictus. Both species are not homogenously distributed, likely due to environmental factors. These findings can assist the targeted control activities.
Understanding the Role of HLA Class I Molecules in the Immune Response to Influenza Infection and Rational Design of a Peptide-Based Vaccine
Authors: Muraduzzaman A. K. M. , Illing Patricia T. , Mifsud Nicole A. , Purcell Anthony W.
Published: November 2022

Influenza A virus is a respiratory pathogen that is responsible for regular epidemics and occasional pandemics that result in substantial damage to life and the economy. The yearly reformulation of trivalent or quadrivalent flu vaccines encompassing surface glycoproteins derived from the current circulating strains of the virus does not provide sufficient cross-protection against mismatched strains. Unlike the current vaccines that elicit a predominant humoral response, vaccines that induce CD8+ T cells have demonstrated a capacity to provide cross-protection against different influenza strains, including novel influenza viruses. Immunopeptidomics, the mass spectrometric identification of human-leukocyte-antigen (HLA)-bound peptides isolated from infected cells, has recently provided key insights into viral peptides that can serve as potential T cell epitopes. The critical elements required for a strong and long-living CD8+ T cell response are related to both HLA restriction and the immunogenicity of the viral peptide. This review examines the importance of HLA and the viral immunopeptidome for the design of a universal influenza T-cell-based vaccine.