bluuebunny/crossref_metadata_2025 huggingface dataset:
Treatment of Industrial Wastewater in a Floating Treatment Wetland: A Case Study of Sialkot Tannery
Authors: Younas Adeel , Kumar Love , Deitch Matthew J. , Qureshi Sundus Saeed , Shafiq Jawad , Ali Naqvi Sohail , Kumar Avinash , Amjad Arjmand Qayyum , Nizamuddin Sabzoi
Published: October 2022

The city of Sialkot in Pakistan is a hub of leather tanneries, with approximately 260 tanneries in operation and, while producing millions of leather products per day, the city discharges millions of gallons of untreated effluent into drains each day. In order to devise a cost-effective system for the treatment of tannery wastewater, a floating treatment wetland (FTW) was established to treat the effluent using local plant species through phytoremediation. The efficiency of the FTW was tested with three different plant species, each grown separately and operating for three months in the FTW tank. Two of the plant species introduced, water hyacinth and water lettuce, were floating and vascular; the third plant species Typha latifolia was vegetated on a floating mat of styrofoam while the roots extended down to the contaminated water. Wastewater from a tannery drain was pumped into the FTW tank with a flow of 0.5 L per minute and was given a retention time of six days. The influent and effluent from the FTW were periodically tested to determine the percentage removal of contaminants, primarily the total suspended solids, biochemical oxygen demand, chemical oxygen demand, and chromium. After two months with each species, a significant change in the quality of wastewater was measured: chromium was removed by up to 95 percent by the water hyacinth and water lettuce and 33 percent by the Typha latifolia. The pilot model indicates that FTWs are an effective system to treat effluent from tanneries in a cost-effective way as an alternative to establishing an expensive treatment system with high associated operational costs. It can help in achieving the circular economy concept of conventional wastewater schemes towards more sustainable ones. Moreover, to achieve the principles of circular economy and environmentally friendly development, it is crucial that the substances used for a wetland foundation have the capacity to be recycled, are available at a cheap price, and are locally available.
Upper-Basic Schoolteachers’ Beliefs about Their Students’ Awareness of Digital Citizenship
Authors: Daher Wajeeh , Omar Amal , Swaity Hadeel , Allan Bushra , Dar Issa Sarah , Amer Zahera , Halabi Aseel
Published: October 2022

Students’ awareness of digital citizenship (DC) is a growing topic in educational technology. Teachers’ beliefs regarding this awareness are a primary factor to influence this awareness. The current research aimed to verify the level of upper-basic schoolteachers’ beliefs about their students’ awareness of DC. It also intended to verify whether this level is significantly different due to teachers’ gender, discipline, academic qualification, and experience. The present research followed random sampling and the sample for the present research consisted of 153 teachers. The teachers were upper-basic schoolteachers that teach Arabic language, mathematics, and technology. The data were collected using a DC questionnaire, while the analysis was done using statistical exams, specifically one-sample t-test, independent-sample t-test, and ANOVA. The research results indicated that the mean score of schoolteachers’ beliefs about their students’ awareness of Cyberbullying, Digital Privacy, and Digital Netiquette was significantly higher than the good DC beliefs score, while the mean score of schoolteachers’ beliefs about their students’ awareness of Digital Identity and Digital Footprint was significantly higher than the normal DC beliefs score. In addition, the results indicated no significant differences in teachers’ beliefs about the awareness of DC’s components due to gender, academic qualification, or years of experience. Moreover, there are no significant differences in teachers’ beliefs about students’ DC’s awareness due to the discipline, except for Digital Privacy.
A Review of Sustainable Urban Regeneration Approaches Based on Augmented Reality Technology: A Case of the Bund in Shanghai
Authors: You Fang , He Hanfu , Cui Wei
Published: October 2022

Both physical and cultural aspects are important for urban areas. In the context of urban space involving cultural resources, the application of augmented reality (AR) could physically integrate cultural resources into the physical facilities of the city. In this paper, the narrative approach is introduced to the construction of an urban cultural scene based on AR technology. Following the collection of historical materials about the Bund in Shanghai in the 1920s and 1930s, this study creates the characters and events in a non-fictional way, organizing a series of narrative elements around themes based on real historical contexts. This is in line with AR, a technology that superimposes virtual information in the real world. As part of this non-fictional narrative design, the author has chosen suitable characters as ‘avatars’ to observe and experience the development of the narrative from a first-person perspective. A participatory viewing can be brought about by adopting a non-fictional approach, rather than a simple information transfer and passive reception. The result is that instead of the traditional guide centric model, a multi-path tour model is created. In conclusion, this paper believes that the use of AR technology can link the narrative to the region more directly and closely. Further, a new cultural scene is created that allows visitors to have an immersive experience. AR technology provides a narrative perspective based on regional knowledge that reinforces and represents the image of the region in a cohesive way.
Can Polylactic Acid (PLA) Act as an Important Vector for Triclosan?
Authors: Lang Zihan , Xue Lidong
Published: October 2022

Triclosan (TCS) has been widely employed as active ingredient in household products and has received attention for its hepatotoxicity, endocrine disruption and disturbance on immune function. Polylactic acid (PLA) has been highlighted as an alternative biodegradable microplastic, and the knowledge about the adsorption affinity towards TCS is limited. In this study, the ability to act as carrier of TCS by PLA and non-biodegradable microplastics, including polystyrene (PS), polyvinyl chloride (PVC) and polyethylene (PE) with different particle sizes were explored. The influence factors (e.g., dosage, pH and salinity), adsorption kinetics and isotherms were also investigated. Batch experiment results indicated that the TCS adsorption onto PLA and non-biodegradable microplastics exhibited a pronounced pH-dependent pattern (pH of 4, 7 and 10), and the adsorption capacity decreased gradually as pH increased. Furthermore, the adsorption capacity of TCS on PS, PVC and PE decreased as salinity increased from 0 to 3.5%, while no significant inhibition for the sorption capacity of PLA was observed. The adsorption kinetic data of TCS was best fitted with the pseudo-second order model. The Freundlich model with R2 (0.999) was suitable to describe the adsorption isotherms of TCS on PLA, while the isotherms data of TCS on PS, PVC and PE was fitted by linear and Freundlich model. The higher adsorption capacity of PLA (38.6 mg g−1) compares to those of PS, PVC and PE (31.3, 11.4 and 9.64 mg g−1, respectively), illustrated by the fact that the physicochemical properties of microplastics have a noticeable impact on adsorption process, and the biodegradable PLA is a stronger vector than the non-biodegradable microplastics.
Computing Models to Predict the Compressive Strength of Engineered Cementitious Composites (ECC) at Various Mix Proportions
Authors: Ghafor Kawan , Ahmed Hemn Unis , Faraj Rabar H. , Mohammed Ahmed Salih , Kurda Rawaz , Qadir Warzer Sarwar , Mahmood Wael , Abdalla Aso A.
Published: October 2022

Concrete has relatively high compressive strength (resists breaking when squeezed) but significantly lower tensile strength (vulnerable to breaking when pulled apart). The compressive strength is typically controlled by the ratio of water-to-cement when forming the concrete, and tensile strength is increased by additives, typically steel, to create reinforced concrete. In other words, we can say concrete is made up of sand (which is a fine aggregate), ballast (which is a coarse aggregate), cement (which can be referred to as a binder), and water (which is an additive). Highly ductile material engineered cementitious composites (ECC) were developed to address these issues by spreading short polymer fibers randomly throughout a cement-based matrix. It has a high tensile strain capacity of more than 3%, hundreds of times more than conventional concrete. On the other hand, among the other examined qualities, compressive strength (CS) is a critical property. Consequently, developing reliable models to predict an ECC’s compressive strength is crucial for cost, time, and energy savings. It also includes instructions for planning construction projects and calculating the optimal time to remove the formwork. The artificial neural network (ANN), nonlinear model (NLR), linear relationship model (LR), multi-logistic model (MLR), and M5P-tree model were all proposed as alternative models to estimate the CS of ECC mixtures created by fly ash in this research (M5P). To create the models, a large amount of data were gathered and evaluated, totaling roughly 205 mixes. Various mixture proportions, fiber length, diameter, and curing durations were explored as input variables. To test the effectiveness of the suggested models, several statistical evaluations, including determination coefficient (R2), Mean Absolute Error (MAE), Scatter Index (SI), Root Mean Squared Error (RMSE), and Objective (OBJ) value, were utilized. Based on the statistical evaluations, the ANN model performed better in forecasting the CS of ECC mixes incorporating fly ash than other models. This model’s RMSE, MAE, OBJ, and R2 values were 4.55 MPa, 3.46 MPa, 4.39 MPa, and 0.98, respectively. A large database presented in this investigation can be used as the bench mark for future mixture proportions of the ECC. Moreover, the sensitivity analysis showed the contribution of each mixture ingredient on the CS of ECC.
Constructing Factors Related to Sociotechnical Analysis in Elderly House
Authors: Chiu Jun-Zhi , Hsieh Chao-Chen
Published: October 2022

As the senior population is increasing, elderly housing is an essential activity in society, prompting the demand for an array of new and extended services. Hence, building information systems, communication, workflow processes, and the end-user are regarded as parts of the information system. The process adopted here combines the FAHP model and ETHICS approach (which we call FETHICS) to deal with the sociotechnical analysis in the elderly house while we are constructing work systems. The purpose of this study is to use the socio-technical analysis of mental and human implementation to capture information content and systems. The results show that environment monitoring, on the job training, providing increased effective care work, and being able to respond to changes in the general environment represent the most important critical information about housing the elderly. Based on the factors identified, a hierarchy model of critical information regarding elderly housing is proposed. The results suggest the content of the elderly house for collecting a weight to each member within this group experience, while also indicating the configuration of the information service framework.
Enhanced Treatment of Decentralized Domestic Sewage Using Gravity-Flow Multi-Soil-Layering Systems Coupled with Iron-Carbon Microelectrolysis
Authors: Ren Shan , Song Pei , Cheng Haichun , Liu Chao , Chen Rongsheng
Published: October 2022

Soil-based decentralized treatment technology has become increasingly popular as an ideal solution for water pollution control in rural areas. It is very necessary to optimize the removal mechanisms and performance of such technologies on rural domestic sewage treatment. This was the first study of a gravity-flow multi-soil-layering (MSL) system coupled with iron-carbon microelectrolysis (ICM). Influent COD/TN (C/N) ratio and bottommost soil mixture block (SMB) submersion were selected as the operating factors relevant to the ICM in MSL systems. Such two key factors were investigated in the factorial experiment. The removal efficiencies of COD, TP, NH3-N, NO3−-N, and TN could be reached up to 96.3, 100, 95.4, 93.8, and 79.6%, respectively. Different levels of factors could comprehensively drive the performance variation. The factorial analysis indicated that the bottommost SMB submersion had the most significant and dominant negative effects on aerobic processes. The ideal TP removal attributed to the presence of the bottommost SMB submersion. It played the dominant role for the bottommost SMB submersion in facilitating an electrochemical reaction through the ICM. Zero-valent iron or ferrous ions could be transformed to final ferric ions more efficiently during the period of the ICM reactions. The ICM could promote the capability of a SMB for removing nutrients in sewage, especially provide electron donors to denitrifying bacteria in MSL systems. However, there were non-significant effects of the influent C/N ratio on the removal performance of MSL systems. This study can help enrich the pollutant removal mechanisms in MSL systems.
Does Local Government’s Competitive Behavior to Attract Foreign Investment Affect Ecological Welfare Performance? Evidence from China
Authors: Wu Dandan , Dong Wei
Published: October 2022

Ecological welfare performance (EWP) is an essential indicator of sustainable socioeconomic development. In China, the government-led economic development paradigm mandates that the competitive behavior of local governments is a major influencing factor on EWP. This research explores how the government’s competitive behavior to attract foreign investment affects ecological welfare performance. Based on the super-efficiency slacks-based measure (SBM) model to assess the level of EWP in China, this paper utilizes a two-way fixed-effects model to determine the impact of local governments’ foreign investment competition on EWP. The results indicate the following. (1) Although introducing foreign investment may promote regional EWP, local governments’ vicious competition in introducing foreign investment is detrimental to its improvement. (2) The effect of local governments’ foreign investment competition on EWP exhibits various heterogeneous characteristics that depend on the differences in the regional distribution and intensity of competition for fiscal revenue and expenditures. (3) Resource factor mobility has a significant moderating effect on the impact of local governments’ competition for foreign investment on EWP. Capital mobility weakens the inhibitory effect of governments’ competition for foreign investment on the enhancement of EWP, while technological mobility and labor mobility have the opposite moderating effect. These findings may clarify the impact of governments’ competition for foreign investment on EWP and provide policy guidelines and implications for other countries pursuing the expansion of foreign direct investment (FDI).
Can Proximal Environments Prevent Social Inequalities Amongst People of All Ages and Abilities? An Integrative Literature Review Approach
Authors: Ramírez Saiz Alba , Alonso Andrea , Jiménez Martín Delfín , Lamíquiz Patxi
Published: October 2022

Although many studies are currently examining the city of proximity as a way to promote sustainable and environmentally friendly cities, few consider it meaningful to achieve an “inclusive” mobility model for people of all ages and abilities, including people with disabilities, children, or the elderly. This literature review paper focuses on the extent to which the city of proximity can provide inclusive mobility and reduce inequalities in the urban scene, thus achieving social sustainability. Out of the 256 references analysed under an integrative review methodology, only 10 delivered solid results. One of the main contributions of this paper is an indicator and sub-indicator system to improve the integrative methodology in urban studies, which led to the identification of several incoherencies in proximity models in terms of accessibility and design for all risking fostering urban with these policies. Although the mentioning of vulnerable collectives may mean a rise in inclusion awareness, one of the most relevant outputs of this paper is the lack of specific measures to revert the disadvantageous situations that conventional mobility planning delivers, as well as the neglection to use proximity actions to promote inclusive and socially resilient urban cities.
Embedded Piezo-Sensor-Based Automatic Performance Monitoring of Chloride-Induced Corrosion in Alkali-Activated Concrete
Authors: Bansal Tushar , Talakokula Visalakshi , Rama Jyosyula Sri Kalyana , Vicente Romeu , Ascensão Guilherme
Published: October 2022

The primary goal of the construction industries worldwide is to improve material durability and achieve sustainability. In recent years of sustainable cement industry innovation, alkali-activated cement has emerged as one of the most promising alternatives to ordinary Portland cement (OPC). In terms of durability, corrosion of steel is a significant problem and has become a major cause of deterioration of reinforced concrete structures worldwide. Thus, structural health monitoring techniques are essential to monitor the corrosion in real-time to avoid unexpected failure since civil engineering structures serve as a crucial pillar of the economy. This paper presents through an experimental campaign a novel method of automatically monitoring the performance of alkali-activated concrete (AAC) and ordinary Portland cement concrete (OPCC) under chloride-induced corrosion conditions using an embedded piezo sensor (EPS) based on the electro-mechanical impedance (EMI) technique. AAC was produced using alkali silicate-activated fly ash and ground granulated blast furnace slag. The accelerated corrosion tests were conducted on reinforced AAC and OPCC specimens in which the EPS was attached to reinforcing steel bars inside the specimens to monitor the changes in the EMI signature during the corrosion progression. To quantify the damage due to chloride-induced corrosion, statistical damage indices such as root mean square deviation were calculated. Further, the deterioration in structural parameters was identified by extracting the equivalent structural parameters (ESPs) such as stiffness, mass and damping from the raw EMI signatures. Based on qualitative and quantitative results, it can be seen that the changes in raw signature and damage in AAC were lower than OPCC. The deterioration in term of stiffness loss was found to be 39.35% in OPCC and 12.73% in AAC. Hence, it is demonstrated that the AAC exhibits a superior corrosion resistance to OPCC.
The Sustainable Development and Strategic Approaches for Contemporary Higher Education
Authors: Hsieh Ming-Yuan
Published: October 2022

Due to the increasing appearance of global contagious diseases such as COVID-19, the goal of this research is to directly and explicitly advance the learning motivation, interests, and performance of online course participants into developing sustainable development and strategic approaches to discover the effective solution of the research question: how to provide the most effective online courses of sustainable development strategy for contemporary higher education in order to advance the student’s learning motivation, confidence, and desires? This is accomplished by integrating the three briefest analytical aspects of the Social Learning Theory, the main theoretical philosophies of Learning Community, and 10 core technological features to determine the most critical core determinants. Beyond the complex measured results, the most valuable conclusions were: (1) the highest Standardized Comparative Weight Scales (SCWS) was located in the Publicity Philosophy for contemporary online higher education sustainable development strategy, which meant the first hypothesis was accepted and the second and third hypotheses were denied. Hence, the Publicity Philosophy (PP) of the learning community directly and effectively advanced the contemporary online higher education sustainable development strategy for educational institutions as the best solution to the research question in order to achieve the main research objective. (2) Continuously, in detail, the PP of the learning community was directly and effectively enforced by the Professionalization Technology Feature of Course Function. This directly indicated that most online course participants focus on the professionalized technological features in the system operation, such as friendly operational platforms for easy uploads, convenient downloads of online course information, and real-time news during online courses at higher education institutions. Significantly, the aggregated technology in group discussions or teamwork assignments and the complete and fair evaluation of online course technological system can facilitate collaborative lesson preparation and lesson observation of the PP of the learning community in order to advance online course interests and learning performance to be the sustainable development strategic approach in contemporary higher education era.
Satisfaction Measurement in the Blended Learning System of the University: The Literacy Mediated-Discourses (LM-D) Framework
Authors: Lubis Muharman , Hasibuan Muhammad Azani , Andreswari Rachmadita
Published: October 2022

Effective incorporation of new technologies into the education system has become a basic need in today’s globalized world, especially in adapting life to the new normal, which is seen by an increase in online learning. Thus, a blended learning system (BLS) becomes the alternative solution to enhance the effectiveness and efficiency of the online learning system by adding certain characteristics from the traditional approach to the online learning system. Therefore, the educational institution still has reluctance to adopt this kind of system as a means to deliver knowledge to the student due to several reasons, such as remote effects, learning progress assessment, alignment of the course roadmap to learning strategy, self-paced environment support, retaining lecturer authenticity, quantifying informal learning, and engagement of the student community. Thus, this study wants to investigate factors that influence the satisfaction of students in terms of using mediated communication consisting of the modules, the channels, and the lecturers as the component to evaluate the understanding of literacy within offline and online classes. In fact, satisfaction is a threshold target for the BLS contribution in bringing the discourses aligned with the demands as well as delivering necessary value for the related users. Interestingly, the results showed Computer Self-Efficacy and Expectation of Quality have valid and reliable value as well significancy within the proposed model.
The Outcomes of Entrepreneurship, Relational Capital and Innovativeness on Tourist Satisfaction
Authors: Lopes Susana , Dias Alvaro , Pereira Leandro , Santos Vasco
Published: October 2022

Addressing the needs of customers is fundamental to the success of companies, particularly in the long-term. In fact, most companies use customer satisfaction as a method to determine and evaluate their performance and outline their strategies for the future. Therefore, the main objective is to better understand entrepreneurship and new product development antecedents and implications on customer satisfaction, a key element for sustainable development. A model is proposed to assess the relationship between two antecedents of entrepreneurial orientation (EO) and new product development (NPD) and a measure of performance. Based on a survey sample of 137 tourism SMEs, the model was tested using Partial Least Squares (PLS). The results show that both the relational capital and innovativeness positively influence entrepreneurship and NPD. They also suggest a positive relationship between entrepreneurship and customer satisfaction. Although there is a positive impact of NPD on customer satisfaction, this relationship was not significant. In addition, the results indicate that relational capital and innovativeness positively influence customer satisfaction through entrepreneurship and NPD. Consequently, to improve the sustainable performance of tourism firms and to increase customer satisfaction, managers must invest in the development of entrepreneurship as well as in the development of new products and their antecedents.
Determining Factors Affecting Behavioral Intention to Organize an Online Event during the COVID-19 Pandemic
Authors: Kusonwattana Poonyawat , Prasetyo Yogi Tri , Vincent Stefanus , Christofelix Jefferson , Amudra Aryadaksa , Montgomery Hazel Juan , Young Michael Nayat , Nadlifatin Reny , Persada Satria Fadil
Published: October 2022

An online event, such as an online concert or online graduation, has been widely utilized as one of the solutions to connect people during the COVID-19 pandemic. The purpose of this study was to determine factors affecting behavioral intention to organize an online event during the COVID-19 pandemic by integrating Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Overall, 366 sets of data were collected from respondents through a convenience sampling approach from several social media platforms. They were asked to fill the online questionnaire which had 40 questions under 8 segments. Structural equation modeling (SEM) showed that hedonic motivation was found to have the strongest effect on attitude, which subsequently led to behavior intention. In addition, online event promotion and perceived usefulness were also found to have significant effects on attitude, which also subsequently led to behavior intention. This study is one of the first studies that explored the behavioral intention to utilize an online event during the COVID-19 pandemic. The findings would be beneficial mainly for online event organizers, particularly for enhancing the online event performance based on the contributing factors. Additionally, this study could act as a stepping stone to help future researchers understand online event better. Finally, the technology acceptance model and theory of planned behavior in this study can be extended for exploring the acceptance of an online event worldwide.
Some New Generalizations of Reverse Hilbert-Type Inequalities via Supermultiplicative Functions
Authors: Rezk Haytham M. , Saied Ahmed I. , AlNemer Ghada , Zakarya Mohammed
Published: October 2022

Our work in this paper is based on the reverse Hölder-type dynamic inequalities illustrated by El-Deeb in 2018 and the reverse Hilbert-type dynamic inequalities illustrated by Rezk in 2021 and 2022. With the help of Specht’s ratio, the concept of supermultiplicative functions, chain rule, and Jensen’s inequality on time scales, we can establish some comprehensive and generalize a number of classical reverse Hilbert-type inequalities to a general time scale space. In time scale calculus, results are unified and extended. At the same time, the theory of time scale calculus is applied to unify discrete and continuous analysis and to combine them in one comprehensive form. This hybrid theory is also widely applied on symmetrical properties which play an essential role in determining the correct methods to solve inequalities. As a special case of our results when the supermultiplicative function represents the identity map, we obtain some results that have been recently published.
OpenFOAMTM Simulation of the Shock Wave Reflection in Unsteady Flow
Authors: Monaldi Lucas , Marcantoni Luis Gutiérrez , Elaskar Sergio
Published: October 2022

This work studies the impact of a shock wave traveling with non-constant velocity over straight surfaces, generating an unsteady and complex reflection process. Two types of shock waves generated by sudden energy released are studied: cylindrical and spherical. Several numerical tests were developed considering different distances between the shock wave origin and the reflecting surface. The Kurganov, Noelle, and Petrova (KNP) scheme implemented in the rhoCentralFoam solver of the OpenFOAMTM software is used to reproduce the different shock wave reflections and their transitions. The numerical simulations of the reflected angle, Mach number of the shock wave, and position of the triple point are compared with pseudo-steady theory numerical and experimental studies. The numerical results show good accuracy for the reflected angle and minor differences for the Mach number. However, the triple point position is more difficult to predict. The KNP scheme in the form used in this work demonstrates the ability to capture the phenomena involved in the unsteady reflections.
NGD-Transformer: Navigation Geodesic Distance Positional Encoding with Self-Attention Pooling for Graph Transformer on 3D Triangle Mesh
Authors: Zhuang Jiafu , Liu Xiaofeng , Zhuang Wei
Published: October 2022

Following the significant success of the transformer in NLP and computer vision, this paper attempts to extend it to 3D triangle mesh. The aim is to determine the shape’s global representation using the transformer and capture the inherent manifold information. To this end, this paper proposes a novel learning framework named Navigation Geodesic Distance Transformer (NGD-Transformer) for 3D mesh. Specifically, this approach combined farthest point sampling with the Voronoi segmentation algorithm to spawn uniform and non-overlapping manifold patches. However, the vertex number of these patches was inconsistent. Therefore, self-attention graph pooling is employed for sorting the vertices on each patch and screening out the most representative nodes, which were then reorganized according to their scores to generate tokens and their raw feature embeddings. To better exploit the manifold properties of the mesh, this paper further proposed a novel positional encoding called navigation geodesic distance positional encoding (NGD-PE), which encodes the geodesic distance between vertices relatively and spatial symmetrically. Subsequently, the raw feature embeddings and positional encodings were summed as input embeddings fed to the graph transformer encoder to determine the global representation of the shape. Experiments on several datasets were conducted, and the experimental results show the excellent performance of our proposed method.
A Triple-Structure Network Model Based upon MobileNet V1 and Multi-Loss Function for Facial Expression Recognition
Authors: Han Baojin , Hu Min , Wang Xiaohua , Ren Fuji
Published: October 2022

Existing facial expression recognition methods have some drawbacks. For example, it becomes difficult for network learning on cross-dataset facial expressions, multi-region learning on an image did not extract the overall image information, and a frequency multiplication network did not take into account the inter-class and intra-class features in image classification. In order to deal with the above problems, in our current research, we raise a symmetric mode to extract the inter-class features and intra-class diversity features, and then propose a triple-structure network model based upon MobileNet V1, which is trained via a new multi-branch loss function. Such a proposed network consists of triple structures, viz., a global branch network, an attention mechanism branch network, and a diversified feature learning branch network. To begin with, the global branch network is used to extract the global features of the facial expression images. Furthermore, an attention mechanism branch network concentrates to extract inter-class features. In addition, the diversified feature learning branch network is utilized to extract intra-class diverse features. The network training is performed by using multiple loss functions to decrease intra-class differences and inter-class similarities. Finally, through ablation experiments and visualization, the intrinsic mechanism of our triple-structure network model is proved to be very reasonable. Experiments on the KDEF, MMI, and CK+ datasets show that the accuracy of facial expression recognition using the proposed model is 1.224%, 13.051%, and 3.085% higher than that using MC-loss (VGG16), respectively. In addition, related comparison tests and analyses proved that our raised triple-structure network model reaches better performance than dozens of state-of-the-art methods.
Numerical Simulation of Entropy Optimization in Radiative Hybrid Nanofluid Flow in a Variable Features Darcy–Forchheimer Curved Surface
Authors: Hayat Asif , Ullah Ikram , Khan Hassan , Weera Wajaree , Galal Ahmed
Published: October 2022

Studies associated with ethylene glycol (EG) have great significance in various engineering sectors because EG is more useful as a cooling agent in various engines. Furthermore, fluid inspection using two distinct nanoparticles has applications in mechanical systems, electronic devices, medical apparatus, and the diagnosis and treatment of disease. Therefore, present comminution explored the entropy production in magnetized hybrid nanomaterials flowing via Darcy–Forchheimer space with varying permeability. Hybrid nano liquid is synthesized by adding cobalt ferrite and gold nanoparticles to ethylene glycol and water. Effects of thermal radiation, Joule heating, heat sources, and an exponential heat source are considered in the energy expression. The assumed problem is modeled in the form of nonlinear PDEs. Such types of problems have mostly occurred in symmetrical phenomena and are applicable in engineering, physics, and applied mathematics. The obtained system is converted to ODEs using suitable substitution transformations. Resultant ODEs are numerically computed with the help of the NDSolve technique using Mathematica software. Their outcomes are displayed through figures and tables. Obtained results reveal that variable permeability and curvature parameters improve the velocity profile, while an exponential heat source (EHS) enhances the thermal effect. It is also observed that entropy optimization improves with the increment in magnetic parameter.
The Golden Ratio in Nature: A Tour across Length Scales
Authors: Marples Callum Robert , Williams Philip Michael
Published: October 2022

The Golden ratio is an irrational number that has a tendency to appear in many different scientific and artistic fields. It may be found in natural phenomena across a vast range of length scales; from galactic to atomic. In this review, the mathematical properties of the Golden ratio are discussed before exploring where in nature it is claimed to appear; beginning at astronomical scales and progressing to smaller lengths, until reaching those of atomic and quantum physics. For each phenomenon discussed, the evidence for the presence of the Golden ratio is assessed. In making such a tour across length scales, it is illustrated just how prevalent this single number is within the natural universe.
Prospects for Heavy Neutral SUSY HIGGS Scalars in the hMSSM and Natural SUSY at LHC Upgrades
Authors: Baer Howard , Barger Vernon , Tata Xerxes , Zhang Kairui
Published: October 2022

We examine production and decay of heavy neutral SUSY Higgs bosons pp→H,A→ττ¯ within the hMSSM and compare against a perhaps more plausible natural supersymmetry scenario dubbed mh125(nat) which allows for a natural explanation for mweak≃mW,Z,h∼100 GeV while maintaining mh≃125 GeV. We evaluate signal against various Standard Model backgrounds from γ,Z→ττ¯, tt¯ and vector boson pair production VV. We combine the transverse mass method for back-to-back (BtB) taus along with the ditau mass peak mττ method for acollinear taus as our signal channels. This technique ultimately gives a boost to the signal significance over the standard technique of using just the BtB signal channel. We evaluate both the 95% CL exclusion and 5σ discovery reach in the mA vs. tanβ plane for present LHC with 139 fb−1, Run 3 with 300 fb−1 and high luminosity LHC (HL-LHC) with 3000 fb−1 of integrated luminosity. For tanβ=10, the exclusion limits range up to mA∼1, 1.1 and 1.4 TeV, respectively. These may be compared to the range of mA values gleaned from a statistical analysis of the string landscape wherein mA can range up to ∼8 TeV.
Controlling Achiral and Chiral Properties with an Electric Field: A Next-Generation QTAIM Interpretation
Authors: Yu Wenjing , Li Zi , Peng Yuting , Feng Xinxin , Xu Tianlv , Früchtl Herbert , van Mourik Tanja , Kirk Steven R. , Jenkins Samantha
Published: October 2022

We used the recently introduced stress tensor trajectory Uσ space construction within the framework of next-generation quantum theory of atoms in molecules (NG-QTAIM) for a chirality investigation of alanine when subjected to a non-structurally distorting electric field. The resultant sliding of the axial-bond critical point (BCP) responded significantly, up to twice as much, in the presence of the applied electric field in comparison to its absence. The bond flexing, a measure of bond strain, was always lower by up to a factor of four in the presence of the electric field, depending on its direction and magnitude. An achiral character of up to 7% was found for alanine in the presence of the applied electric field. The achiral character was entirely absent in the presence of the lowest value of the applied electric field. Future applications, including molecular devices using left and right circularly polarized laser pulses, are briefly discussed.
Duality on q-Starlike Functions Associated with Fractional q-Integral Operators and Applications
Authors: Amini Ebrahim , Al-Omari Shrideh , Fardi Mojtaba , Nonlaopon Kamsing
Published: October 2022

In this paper, we make use of the Riemann–Liouville fractional q-integral operator to discuss the class Sq,δ*(α) of univalent functions for δ>0,α∈C−{0}, and 0<|q|<1. Then, we develop convolution results for the given class of univalent functions by utilizing a concept of the fractional q-difference operator. Moreover, we derive the normalized classes Pδ,qζ(β,γ) and Pδ,q(β) (0<|q|<1, δ≥0,0≤β≤1,ζ>0) of analytic functions on a unit disc and provide conditions for the parameters q,δ,ζ,β, and γ so that Pδ,qζ(β,γ)⊂Sq,δ*(α) and Pδ,q(β)⊂Sq,δ*(α) for α∈C−{0}. Finally, we also propose an application to symmetric q-analogues and Ruscheweh’s duality theory.
Mean Value of r-gcd-sum and r-lcm-Sum Functions
Authors: Bu Zhengjin , Xu Zhefeng
Published: October 2022

In this paper we perform a further investigation for r-gcd-sum and r-lcm-sum functions. By making use of the properties of generalization of Euler’s φ-function, Abel’s identity and elementary arguments, we derive asymptotic formulas for the average of the r-gcd-sum function, r-lcm-sum function and their generalizations. Moreover, we also study the sums of reciprocals of r-gcd and r-lcm.
A New Approach to Approximate Solutions of Single Time-Delayed Stochastic Integral Equations via Orthogonal Functions
Authors: Kiaee Seyyedeh N. , Khodabin Morteza , Ezzati Reza , Lopes António M.
Published: October 2022

This paper proposes a new numerical method for solving single time-delayed stochastic differential equations via orthogonal functions. The basic principles of the technique are presented. The new method is applied to approximate two kinds of stochastic differential equations with additive and multiplicative noise. Excellence computational burden is achieved along with a O(h2) convergence rate, which is better than former methods. Two examples are examined to illustrate the validity and efficiency of the new technique.
On Three-Rainbow Dominationof Generalized Petersen Graphs P(ck,k)
Authors: Rupnik Poklukar Darja , Žerovnik Janez
Published: October 2022

New results on singleton rainbow domination numbers of generalized Petersen graphs P(ck,k) are given. Exact values are established for some infinite families, and lower and upper bounds with small gaps are given in all other cases.
A Class-Incremental Detection Method of Remote Sensing Images Based on Selective Distillation
Authors: Ruan Hang , Peng Jian , Chen Ye , He Silu , Zhang Zhenshi , Li Haifeng
Published: October 2022

With the rapid development of remote sensing technology and the growing demand for applications, the classical deep learning-based object detection model is bottlenecked in processing incremental data, especially in the increasing classes of detected objects. It requires models to sequentially learn new classes of objects based on the current model, while preserving old categories-related knowledge. Existing class-incremental detection methods achieve this goal mainly by constraining the optimization trajectory in the feature of output space. However, these works neglect the case where the previously learned background is a new category to learn, resulting in performance degradation in the new category because of the conflict between remaining the background-related knowledge or updating the background-related knowledge. This paper proposes a novel class-incremental detection method incorporated with the teacher-student architecture and the selective distillation (SDCID) strategy. Specifically, it is the asymmetry architecture, i.e., the teacher network temporarily stores historical knowledge of previously learned objects, and the student network integrates historical knowledge from the teacher network with the newly learned object-related knowledge, respectively. This asymmetry architecture reveals the significance of the distinct representation of history knowledge and new knowledge in incremental detection. Furthermore, SDCID selectively masks the shared subobject of new images to learn and previously learned background, while learning new categories of images and then transfers the classification results of the student model to the background class following the judgment model of the teacher model. This manner avoids interferences between the background category-related knowledge from a teacher model and the learning of other new classes of objects. In addition, we proposed a new incremental learning evaluation metric, C-SP, to comprehensively evaluate the incremental learning stability and plasticity performance. We verified the proposed method on two object detection datasets of remote sensing images, i.e., DIOR and DOTA. The experience results in accuracy and C-SP suggest that the proposed method surpasses existing class-incremental detection methods. We further analyzed the influence of the mask component in our method and the hyper-parameters sensitive to our method.
Time-Lagged Correlation Analysis of Shellfish Toxicity Reveals Predictive Links to Adjacent Areas, Species, and Environmental Conditions
Authors: Patrício André , Lopes Marta B. , Costa Pedro Reis , Costa Rafael S. , Henriques Rui , Vinga Susana
Published: October 2022

Diarrhetic Shellfish Poisoning (DSP) is an acute intoxication caused by the consumption of contaminated shellfish, which is common in many regions of the world. To safeguard human health, most countries implement programs focused on the surveillance of toxic phytoplankton abundance and shellfish toxicity levels, an effort that can be complemented by a deeper understanding of the underlying phenomena. In this work, we identify patterns of seasonality in shellfish toxicity across the Portuguese coast and analyse time-lagged correlations between this toxicity and various potential risk factors. We extend the understanding of these relations through the introduction of temporal lags, allowing the analysis of time series at different points in time and the study of the predictive power of the tested variables. This study confirms previous findings about toxicity seasonality patterns on the Portuguese coast and provides further quantitative data about the relations between shellfish toxicity and geographical location, shellfish species, toxic phytoplankton abundances, and environmental conditions. Furthermore, multiple pairs of areas and shellfish species are identified as having correlations high enough to allow for a predictive analysis. These results represent the first step towards understanding the dynamics of DSP toxicity in Portuguese shellfish producing areas, such as temporal and spatial variability, and towards the development of a shellfish safety forecasting system.
Possible Reaction Mechanisms Involved in Degradation of Patulin by Heat-Assisted Cysteine under Highly Acidic Conditions
Authors: Diao Enjie , Ma Kun , Li Minghua , Zhang Hui , Xie Peng , Qian Shiquan , Song Huwei , Mao Ruifeng , Zhang Liming
Published: October 2022

Patulin (PAT) is one of mycotoxins that usually contaminates apple juice, and it is not easily detoxified by cysteine (CYS) at room temperature due to the highly acidic conditions based on the Michael addition reaction. However, it could be effectively degraded by a heating treatment at 120 °C for 30 min in the presence of cysteine. In our study, a total of eight degradation products (DP A–H) were characterized and identified via liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) in a negative ion mode, and their structures and formulas were proposed based on their accurate mass data. The fragmentation patterns of PAT and its degradation products were obtained from the MS/MS analysis. Meanwhile, the possible reaction mechanisms involved in the degradation of PAT were established and explained for the first time. According to the relation between the structure and toxicity of PAT, it could be deduced that the toxic effects of PAT degradation products were potentially much less than those of PAT-self.
Development of Therapeutic Vaccine for Chronic Hepatitis B: Concept, Cellular and Molecular Events, Design, Limitation, and Future Projection
Authors: Akbar Sheikh , Mahtab Mamun , Khan Sakirul , Yoshida Osamu , Hiasa Yoichi
Published: October 2022

Four decades have passed since the first usage of the therapeutic vaccine in patients with chronic hepatitis B (CHB). However, there is no approved regimen of vaccine therapy for the treatment of CHB. This is mainly attributable to faulty conception, an improper understanding of the cellular and molecular mechanisms of CHB, and the impaired design of vaccine therapy for CHB. With the advent of new techniques and a better understanding of cellular and molecular mechanisms underlying the genesis of CHB, the limitations and failures of previous regimens of therapeutic vaccines have been primarily understood. Additionally, the importance of immune therapy for treating millions of CHB patients and achieving the target of “Elimination of Hepatitis by 2030” has been focused on in the international arena. This has been amplified by the apparent limitation of commercially available antiviral drugs that are infinite in duration, endowed with safety concerns, and unable to cure liver damage due to their minimal immune modulation capacities. The proposed review article comprehensively discusses each of these points and proposes evidence-based approaches for viable types of vaccine therapy for the treatment of CHB.