bluuebunny/crossref_metadata_2025 huggingface dataset:
Visual Perceptual Quality Assessment Based on Blind Machine Learning Techniques
Authors: Takam Tchendjou Ghislain , Simeu Emmanuel
Published: December 2021

This paper presents the construction of a new objective method for estimation of visual perceiving quality. The proposal provides an assessment of image quality without the need for a reference image or a specific distortion assumption. Two main processes have been used to build our models: The first one uses deep learning with a convolutional neural network process, without any preprocessing. The second objective visual quality is computed by pooling several image features extracted from different concepts: the natural scene statistic in the spatial domain, the gradient magnitude, the Laplacian of Gaussian, as well as the spectral and spatial entropies. The features extracted from the image file are used as the input of machine learning techniques to build the models that are used to estimate the visual quality level of any image. For the machine learning training phase, two main processes are proposed: The first proposed process consists of a direct learning using all the selected features in only one training phase, named direct learning blind visual quality assessment DLBQA. The second process is an indirect learning and consists of two training phases, named indirect learning blind visual quality assessment ILBQA. This second process includes an additional phase of construction of intermediary metrics used for the construction of the prediction model. The produced models are evaluated on many benchmarks image databases as TID2013, LIVE, and LIVE in the wild image quality challenge. The experimental results demonstrate that the proposed models produce the best visual perception quality prediction, compared to the state-of-the-art models. The proposed models have been implemented on an FPGA platform to demonstrate the feasibility of integrating the proposed solution on an image sensor.
Multi-Level Sensing Technologies in Landslide Research—Hrvatska Kostajnica Case Study, Croatia
Authors: Podolszki Laszlo , Kosović Ivan , Novosel Tomislav , Kurečić Tomislav
Published: December 2021

In March 2018, a landslide in Hrvatska Kostajnica completely destroyed multiple households. The damage was extensive, and lives were endangered. The question remains: Can it happen again? To enhance the knowledge and understanding of the soil and rock behaviour before, during, and after this geo-hazard event, multi-level sensing technologies in landslide research were applied. Day after the event field mapping and unmanned aerial vehicle (UAV) data were collected with the inspection of available orthophoto and “geo” data. For the landslide, a new geological column was developed with mineralogical and geochemical analyses. The application of differential interferometric synthetic aperture radar (DInSAR) for detecting ground surface displacement was undertaken in order to determine pre-failure behaviour and to give indications about post-failure deformations. In 2020, electrical resistivity tomography (ERT) in the landslide body was undertaken to determine the depth of the landslide surface, and in 2021 ERT measurements in the vicinity of the landslide area were performed to obtain undisturbed material properties. Moreover, in 2021, detailed light detection and ranging (LIDAR) data were acquired for the area. All these different level data sets are being analyzed in order to develop a reliable landslide model as a first step towards answering the aforementioned question. Based on applied multi-level sensing technologies and acquired data, the landslide model is taking shape. However, further detailed research is still recommended.
Drift-Free Integration in Inductive Magnetic Field Measurements Achieved by Kalman Filtering
Authors: Arpaia Pasquale , Buzio Marco , Di Capua Vincenzo , Grassini Sabrina , Parvis Marco , Pentella Mariano
Published: December 2021

Sensing coils are inductive sensors commonly used to measure magnetic fields, such as those generated by electromagnets used in many kinds of industrial and scientific applications. Inductive sensors rely on integrating the output voltage at the coil’s terminals in order to obtain flux linkage, which may suffer from the magnification of low-frequency noise resulting in a drifting integrated signal. This article presents a method for the cancellation of integrator drift. The method is based on a first-order linear Kalman filter combining the data from the coil and a second sensor. Two case studies are presented. In the first one, the second sensor is a Hall probe, which senses the magnetic field directly. In a second case study, the magnet’s excitation current was used instead to provide a first-order approximation of the field. Experimental tests show that both approaches can reduce the measured field drift by three orders of magnitude. The Hall probe option guarantees, in addition, one order of magnitude better absolute accuracy than by using the excitation current.
Study on the Optimization of Hyperspectral Characteristic Bands Combined with Monitoring and Visualization of Pepper Leaf SPAD Value
Authors: Yuan Ziran , Ye Yin , Wei Lifei , Yang Xin , Huang Can
Published: December 2021

Chlorophyll content is an important indicator of plant photosynthesis, which directly affects the growth and yield of crops. Using hyperspectral imaging technology to quickly and non-destructively estimate the soil plant analysis development (SPAD) value of pepper leaf and its distribution inversion is of great significance for agricultural monitoring and precise fertilization during pepper growth. In this study, 150 samples of pepper leaves with different leaf positions were selected, and the hyperspectral image data and SPAD value were collected for the sampled leaves. The correlation coefficient, stability competitive adaptive reweighted sampling (sCARS), and iteratively retaining informative variables (IRIV) methods were used to screen characteristic bands. These were combined with partial least-squares regression (PLSR), extreme gradient boosting (XGBoost), random forest regression (RFR), and gradient boosting decision tree (GBDT) to build regression models. The developed model was then used to build the inversion map of pepper leaf chlorophyll distribution. The research results show that: (1) The IRIV-XGBoost model demonstrates the most comprehensive performance in the modeling and inversion stages, and its Rcv2, RMSEcv, and MAEcv are 0.81, 2.76, and 2.30, respectively; (2) The IRIV-XGBoost model was used to calculate the SPAD value of each pixel of pepper leaves, and to subsequently invert the chlorophyll distribution map of pepper leaves at different leaf positions, which can provide support for the intuitive monitoring of crop growth and lay the foundation for the development of hyperspectral field dynamic monitoring sensors.
An Aggregated Mutual Information Based Feature Selection with Machine Learning Methods for Enhancing IoT Botnet Attack Detection
Authors: Al-Sarem Mohammed , Saeed Faisal , Alkhammash Eman H. , Alghamdi Norah Saleh
Published: December 2021

Due to the wide availability and usage of connected devices in Internet of Things (IoT) networks, the number of attacks on these networks is continually increasing. A particularly serious and dangerous type of attack in the IoT environment is the botnet attack, where the attackers can control the IoT systems to generate enormous networks of “bot” devices for generating malicious activities. To detect this type of attack, several Intrusion Detection Systems (IDSs) have been proposed for IoT networks based on machine learning and deep learning methods. As the main characteristics of IoT systems include their limited battery power and processor capacity, maximizing the efficiency of intrusion detection systems for IoT networks is still a research challenge. It is important to provide efficient and effective methods that use lower computational time and have high detection rates. This paper proposes an aggregated mutual information-based feature selection approach with machine learning methods to enhance detection of IoT botnet attacks. In this study, the N-BaIoT benchmark dataset was used to detect botnet attack types using real traffic data gathered from nine commercial IoT devices. The dataset includes binary and multi-class classifications. The feature selection method incorporates Mutual Information (MI) technique, Principal Component Analysis (PCA) and ANOVA f-test at finely-granulated detection level to select the relevant features for improving the performance of IoT Botnet classifiers. In the classification step, several ensemble and individual classifiers were used, including Random Forest (RF), XGBoost (XGB), Gaussian Naïve Bayes (GNB), k-Nearest Neighbor (k-NN), Logistic Regression (LR) and Support Vector Machine (SVM). The experimental results showed the efficiency and effectiveness of the proposed approach, which outperformed other techniques using various evaluation metrics.
Advances in Thermal Image Analysis for the Detection of Pregnancy in Horses Using Infrared Thermography
Authors: Domino Małgorzata , Borowska Marta , Kozłowska Natalia , Zdrojkowski Łukasz , Jasiński Tomasz , Smyth Graham , Maśko Małgorzata
Published: December 2021

Infrared thermography (IRT) was applied as a potentially useful tool in the detection of pregnancy in equids, especially native or wildlife. IRT measures heat emission from the body surface, which increases with the progression of pregnancy as blood flow and metabolic activity in the uterine and fetal tissues increase. Conventional IRT imaging is promising; however, with specific limitations considered, this study aimed to develop novel digital processing methods for thermal images of pregnant mares to detect pregnancy earlier with higher accuracy. In the current study, 40 mares were divided into non-pregnant and pregnant groups and imaged using IRT. Thermal images were transformed into four color models (RGB, YUV, YIQ, HSB) and 10 color components were separated. From each color component, features of image texture were obtained using Histogram Statistics and Grey-Level Run-Length Matrix algorithms. The most informative color/feature combinations were selected for further investigation, and the accuracy of pregnancy detection was calculated. The image texture features in the RGB and YIQ color models reflecting increased heterogeneity of image texture seem to be applicable as potential indicators of pregnancy. Their application in IRT-based pregnancy detection in mares allows for earlier recognition of pregnant mares with higher accuracy than the conventional IRT imaging technique.
Functional Resonance Analysis in an Overtaking Situation in Road Traffic: Comparing the Performance Variability Mechanisms between Human and Automation
Authors: Grabbe Niklas , Gales Alain , Höcher Michael , Bengler Klaus
Published: December 2021

Automated driving promises great possibilities in traffic safety advancement, frequently assuming that human error is the main cause of accidents, and promising a significant decrease in road accidents through automation. However, this assumption is too simplistic and does not consider potential side effects and adaptations in the socio-technical system that traffic represents. Thus, a differentiated analysis, including the understanding of road system mechanisms regarding accident development and accident avoidance, is required to avoid adverse automation surprises, which is currently lacking. This paper, therefore, argues in favour of Resilience Engineering using the functional resonance analysis method (FRAM) to reveal these mechanisms in an overtaking scenario on a rural road to compare the contributions between the human driver and potential automation, in order to derive system design recommendations. Finally, this serves to demonstrate how FRAM can be used for a systemic function allocation for the driving task between humans and automation. Thus, an in-depth FRAM model was developed for both agents based on document knowledge elicitation and observations and interviews in a driving simulator, which was validated by a focus group with peers. Further, the performance variabilities were identified by structured interviews with human drivers as well as automation experts and observations in the driving simulator. Then, the aggregation and propagation of variability were analysed focusing on the interaction and complexity in the system by a semi-quantitative approach combined with a Space-Time/Agency framework. Finally, design recommendations for managing performance variability were proposed in order to enhance system safety. The outcomes show that the current automation strategy should focus on adaptive automation based on a human-automation collaboration, rather than full automation. In conclusion, the FRAM analysis supports decision-makers in enhancing safety enriched by the identification of non-linear and complex risks.
Identities and Precariousness in the Collaborative Economy, Neither Wage-Earner, nor Self-Employed: Emergence and Consolidation of the Homo Rider, a Case Study
Authors: López-Martínez Gabriel , Haz-Gómez Francisco Eduardo , Manzanera-Román Salvador
Published: December 2021

In recent years, courier and home delivery services have experienced extensive growth around the world. These platform companies, that operate through applications on smartphones, have experienced the benefits of the technological leap that has been produced by the conditions imposed by the COVID-19 pandemic and its restrictions on traditional commerce. This business model integrates novel elements that move away from a classic contractual relationship, employer-employee. They combine a strong cooperative culture, integrated by company values and principles that make the rider assume an identity that defines him/her as a worker and a member of a community. In addition, on the other hand, precarious working conditions, in which extreme competitiveness among colleagues and dependence on high standards of service compliance are encouraged. In Spain, there is a lack of research on the identity of workers in this type of platform. By means of in-depth interviews with drivers of two different companies in the Region of Murcia (Spain), the main objective of this article is to identify and describe the figure of what we define as homo rider, understood as a prototype individual in the context of contemporary labor relations, linked to the incorporation of new technologies for the intermediation and interconnection between people, goods and services. We approach to the socioeconomic spectrum and identity imaginary of the homo rider through two dimensions, material and ideological, to construct this broad, ambiguous figure between self-employment and wage-earner that would also represent a complex relation between precarious work and new technologies.
Numerical Simulation of Impact Rockburst of Elliptical Caverns with Different Axial Ratios
Authors: Wang Yang , Li Xue , Li Jiyu , Xu Jipeng
Published: December 2021

Herein, a finite discrete element method was used to simulate the rockburst phenomenon of elliptical caverns with different axis ratios. Two situations were employed, namely when the disturbance direction is perpendicular and parallel to the ellipse. Based on the peak stress, maximum velocity, stress nephogram, and image fractal characteristics, the influence of axis ratio and direction of the disturbance on rockburst were analyzed. The results show that the samples with different axis ratios experienced the same process of quiet period, slab cracking period, and rockburst. The rockburst pit had V shape, and the failure modes of rockburst primarily included shear cracks, horizontal tension cracks, and vertical tension cracks. With the rise in axis ratio, the peak stress and maximum speed increased. Furthermore, the pressure area on the left and right sides of the sample cavern decreased when the disturbance direction was parallel to the short axis of the ellipse, while it increased for the sample with a disturbance direction perpendicular to the short axis. The fractal dimension value of the crack was gradually amplified with disturbance. The fractal dimension value of the sample whose disturbance direction was perpendicular to the minor axis of the ellipse was lower, and it was more difficult to damage.
Determinants of Staff Localization in Headquarters-Subsidiary-Subsidiary Relationships
Authors: Kim Chan Bok , Choi Seong-Jin , Zhang Luyao
Published: December 2021

This paper investigates how cultural distance, the local experience of a foreign subsidiary, and the intensity of local competition jointly affect the staff localization of MNEs’ subsidiaries. While previous studies on the effects of cultural distance have mainly focused on the gap between home and host countries, we extend the existing “home-host” country perspective to the home-intermediary-host country relationship. This study regards Korea as an intermediary country and utilizes 520 observations from a unique survey conducted by the Export-Import Bank of Korea from 2006 to 2013. The results suggest that the impact of cultural distance on staff localization is a function of local experience and competitive environment in the home-intermediate-host relationship structure. This paper makes a theoretical contribution to our understanding of the behavior of multinational corporations by expanding the cultural distance perspective between the home and host countries explored in previous research to the home-subsidiary-subsidiary structure.
Physical Separation of Contaminated Soil Using a Washing Ejector Based on Hydrodynamic Cavitation
Authors: Cho Kanghee , Kim Hyunsoo , Purev Oyunbileg , Choi Nagchoul , Lee Jaewon
Published: December 2021

A washing ejector is a pre-treatment technology used to remediate contaminated soil by separating fine particles. The washing ejector developed in this study is a device that utilizes fast liquid jets to disperse soil aggregates by cavitation flow. The cavitation phenomenon is affected by the Bernoulli principle, and the liquid pressure decreases with the increase in kinetic energy. The cavitating flow of the fluid through the Ventrui nozzle can remove surface functional groups and discrete particles. The main methodology involves the removal of small particles bound to coarse particles and the dispersion of soil aggregates. Particle collisions occur on the surface soil, such as the metal phase that is weakly bound to silicate minerals. It was observed that the dispersed soil affected the binding of toxic heavy metals and the mineralogical characteristics of the soil. The quantity of oxides, organic matter, and clay minerals affected the properties of the soil. An almost 40–60% removal efficiency of total metals (As, Zn, and Pb) was obtained from the contaminated soils. After treatment by a washing ejector, the volume of fine particles was reduced by 28–47%. When the contaminants are associated with particulates, separation using a washing ejector can be more effective. Therefore, physical separation improves the removal efficiency of heavy metals from soil aggregates.
Multi-Depot Electric Bus Scheduling Considering Operational Constraint and Partial Charging: A Case Study in Shenzhen, China
Authors: Jiang Mengyan , Zhang Yi , Zhang Yi
Published: December 2021

Electric buses (e-buses) demonstrate great potential in improving urban air quality thanks to zero tailpipe emissions and thus being increasingly introduced to the public transportation systems. In the transit operation planning, a common requirement is that long-distance non-service travel of the buses among bus terminals should be avoided in the schedule as it is not cost-effective. In addition, e-buses should begin and end a day of operation at their base depots. Based on the unique route configurations in Shenzhen, the above two requirements add further constraint to the form of feasible schedules and make the e-bus scheduling problem more difficult. We call these two requirements the vehicle relocation constraint. This paper addresses a multi-depot e-bus scheduling problem considering the vehicle relocation constraint and partial charging. A mixed integer programming model is formulated with the aim to minimize the operational cost. A Large Neighborhood Search (LNS) heuristic is devised with novel destroy-and-repair operators to tackle the vehicle relocation constraint. Numerical experiments are conducted based on multi-route operation cases in Shenzhen to verify the model and effectiveness of the LNS heuristic. A few insights are derived on the decision of battery capacity, charging rate and deployment of the charging infrastructure.
Assessment of Non-Conventional Irrigation Water in Greenhouse Cucumber (Cucumis sativus) Production
Authors: Khan Muhammad Mumtaz , Al-Haddabi Mansour Hamed , Akram Muhammad Tahir , Khan Muhammad Azam , Farooque Aitazaz A. , Siddiqi Sajjad Ahmad
Published: December 2021

Climate change, urbanization and subsequent environmental changes are depleting freshwater resources around the globe. The reuse of domestic, industrial and agricultural wastewater is an alternative approach to freshwater that can be used for irrigation purposes. However, these wastewaters may contain hazardous and toxic elements, such as heavy metals that are hazardous for human health and the environment. Therefore, an experiment was conducted to evaluate the concentration of macro, micro and heavy metals in cucumber irrigated with different resources (tap water, greywater, dairy water and wastewater). The results showed that the use of different irrigation resources has increased the level of macro (sodium (Na), potassium (K), calcium (Ca), magnesium (Mg)), microelements (zinc (Zn), iron (Fe), manganese (Mn)), and heavy metals (copper (Cu), barium (Ba), lead (Pb) and cadmium (Cd)) in cucumber leaves and fruits. However, their levels were in the range that is safe for human health and the environment was as recommended by FAO maximum values of trace elements (Zn, 2.0; Fe 1.0; Mn, 0.2; Cu, 0.2; Pb, 5.0, and Cd, 0.01 mgL−1). Based on observations, it was also revealed that among different irrigation resources, the use of dairy water in cucumber improved its agronomic attributes and maximum plant yield (1191.02 g), while the different irrigation resources showed a non-significant impact on fruit diameter. However, total soluble solid contents (TSS) were more significant in cucumber fruits treated with wastewater (2.26 °brix) followed by dairy water (2.06 °brix), while the least TSS contents (1.57 °brix) were observed in cucumber plants treated with tap water. The significance of non-conventional irrigation water use in agriculture, particularly greenhouse cucumber (Cucumis sativus) production, is discussed.
Three Anchoring Managerial Mechanisms to Embed Sustainability in Service Organizations
Authors: Martin-Rios Carlos , Poretti Cédric , Derchi Giovanni Battista
Published: December 2021

The aim of this discussion paper is to address three major concerns in establishing sustainability in service organizations regarding the intersections among external reporting, internal governance, and business management and innovation. External reporting addresses issues related to sustainability information specificities and determinants, the pros and cons of mandating CSR disclosures, and the need for assurance. The internal management of sustainability refers to the opportunities and challenges for services to introduce sustainable business models and sustainability innovation. Finally, internal governance prioritizes the control process and systems employed by managers to make informed decisions and implement sustainability strategies. By means of an extensive and sophisticated literature review, the article contributes to untangling the opportunities and challenges that services face when adopting external and internal practices to commit to sustainability. Specifically, the paper addresses how company-level mechanisms of transparency, accountability, and innovation are linked to system-level mechanisms of implementation that lead to the adoption of sustainability in service organizations.
Assessment of Reactive Nitrogen Flows in Bangladesh’s Agriculture Sector
Authors: Rahman Md. Mizanur , Biswas Jatish Chandra , Sutton Mark A. , Drewer Julia , Adhya Tapan Kumar
Published: December 2021

To assess the status of and trends in agricultural nitrogen (N) flows and their wider consequences for Bangladesh, in this study, we analyzed data from national and international bodies. The increased rates of N fertilizer applied for increased food production leaves behind a huge amount of unutilized reactive N (Nr). N fertilizer use is the largest in the crop sector, an important sector, where current annual consumption is 1190 Gg. The present combined annual Nr production from crop, fishery, and livestock sectors is ~600 Gg, while emissions of nitrous oxide (N2O), a potent greenhouse gas, are ~200 Gg. Poor N management results in Nr leaking into the environment, which has increased approximately 16-fold since 1961. One potential consequence is the disruption of ecosystem functioning. The balanced tradeoff between food production and reducing Nr input needs to be achieved. One solution to reducing Nr may be a holistic approach that optimizes N application rates and incorporates waste of one subsector as an input to another applying the principle of the circular economy.
“Single System, Single-Standard” vs. “Single System, Multi-Standard”—The Impact of the Financing Method of Chinese Urban-Rural Integrated Medical Insurance System on the Rate of Joining Insurance for Middle-Aged and Elderly People
Authors: Zhong Hai , Wang Zhen
Published: December 2021

Basic Chinese medical insurance has achieved full coverage, but the inequality between urban and rural areas is still outstanding. Under this background, the government proposed the urban-rural Integrated Medical Insurance System which proposes two kinds of financing modes. Based on the decision-making theory of medical insurance and the logit regression model, this paper studies the influence of two kinds of financing modes on middle-aged and elderly people’s decisions to participate in integrated medical insurance in China. The two financing modes are “single-standard” and “multi-standard”. The results show that the two kinds of financing methods have positive and significant effects, and the incentive effect of “multi-standard” on the integrated medical insurance is greater than that of “single-standard”. Having an urban household registration promotes the development of the “multi-standard”. However, there are some central provinces are not eable to improve the integrated medical insurance participation rate through “multi-standard”. Improving the participation rate of integrated medical insurance can promote the balanced allocation of resources between urban and rural areas, as well as different income groups and regions. Moreover, it can ensure a smooth transition of medical insurance policies. We should hold and boost the financing method of “multi-standard” to guarantee medical insurance integration’s rapid and steady progress in China.
Does the Past Affect the Future? An Analysis of Consumers’ Dining Intentions towards Green Restaurants in the UK
Authors: Shishan Farah , Mahshi Ricardo , Al Kurdi Brween , Alotoum Firas , Alshurideh Muhammad
Published: December 2021

Due to the growing notion of environmental protection, many restaurants have started to apply operational practices to diminish their carbon footprint, leading to the emergence of “green” restaurants. Green restaurants are establishments committed to minimizing adverse environmental consequences throughout their operations. Nevertheless, further research is warranted to examine consumer behavior in this field. Taking the consumers’ perspective, this study uses an augmented theory of planned behavior (TPB) and a cross-section of 896 British diners to explain their dining intentions towards green restaurants. The extended model of the TPB was tested to justify the addition of past behavior and the impact of sociodemographic characteristics. Using structural equation analysis, the results identified past behavior, perceived behavioral control, subjective descriptive norms, and attitude as critical factors influencing behavioral intention. Furthermore, apart from gender, the relationships between sociodemographics and intentions to dine at green restaurants were insignificant. This research provides insightful implications in the green restaurant domain and suggestions for future research.
Heritage as Action Research
Authors: Reher Guillermo
Published: December 2021

This paper intends to weigh the importance of archaeology by how much impact it has, or could have, on society. Heritage values are precisely the language in which that impact translates to the general public. It is necessary, however, to balance the duty to protect heritage with the mutating and negotiated nature of these values. Archaeologists should not be seen as the wardens but rather as the enablers, the midwives, of local communities coming to terms with a deeper understanding of their past. The more effectively this heritage stimulates the relation of the community with these values, the greater the potential it will have to stimulate social innovation, which is the foundation for sustainable development or abandonment. For many the boon of cultural heritage is tourism, and this is true but to an insufficient extent. In order to be sustainable, tourism must be part of a broader social innovation strategy that foregoes easy pickings in favor of the creation of quality brands, employment, and the protection of traditional lifeways. Only in this way can heritage truly unlock a sustainable horizon.
Urban Rail Transit in Bangkok: Chronological Development Review and Impact on Residential Property Value
Authors: Vichiensan Varameth , Wasuntarasook Vasinee , Hayashi Yoshitsugu , Kii Masanobu , Prakayaphun Titipakorn
Published: December 2021

Bangkok suffered from the world’s worst traffic congestion in the 1990s due to rapidly increasing car ownership, reflecting the economic growth and road-dependent transport policy beginning in the 1960s. Due to its monocentric but scattered urban structure, traffic congestion is severe, causing tremendous economic loss, deteriorating air quality, and badly affecting the quality of life. A historical review reveals that the urban and transport plan and development were not efficiently coordinated, resulting in unorganized suburbanization and progressively more severe traffic congestion. It is important to reveal the impact of the transportation project on the housing market in order to incorporate the policies for transportation and urban development. To define the impact, the OLS hedonic price model and the local multiscale geographically weighted regression (MGWR) model were estimated, along with the condominium sales data. The results revealed that the impact of rail transit on a rise in property value significantly varied across the study area. It was estimated that, for the area along the major rail transit corridor in the city center, a premium of a location 100-m closer to the station would be more than 200 USD per square meter. At the same time, the value would be less than 80 USD for the area along the rail corridor in the suburb. These findings provide policy insights for future urban and railway development, including the proper coordination of rail transit development and urban development with subcenters, transit-oriented development, and improved pedestrian flow around transit stations.
Bim Machine Learning and Design Rules to Improve the Assembly Time in Steel Construction Projects
Authors: Soh Mathieu Fokwa , Bigras David , Barbeau Daniel , Doré Sylvie , Forgues Daniel
Published: December 2021

Integrating the knowledge and experience of fabrication during the design phase can help reduce the cost and duration of steel construction projects. Building Information Modeling (BIM) are technologies and processes that reduce the cost and duration of construction projects by integrating parametric digital models as support of information. These models can contain information about the performance of previous projects and allow a classification by linear regression of design criteria with a high impact on the duration of the fabrication. This paper proposes a quantitative approach that applies linear regressions on previous projects’ BIM models to identify some design rules and production improvement points. A case study applied on 55,444 BIM models of steel joists validates this approach. This case study shows that the camber, the weight of the structure, and its reinforced elements greatly influence the fabrication time of the joists. The approach developed in this article is a practical case where machine learning and BIM models are used rather than interviews with professionals to identify knowledge related to a given steel structure fabrication system.
The Sustainability of Graphene Research: A Novel Approach in Assessing the Role of Higher Education Policies in Developing Countries—The Case of Indonesia
Authors: Madsuha Alfian Ferdiansyah , Kurniawan Yandry , Permana Panji Anugrah , Sumaedi Sik
Published: December 2021

The development of so-called advanced materials is mainly driven by research devoted to supporting industry and now expands to many issues such as energy demand, climate change, healthy awareness, and many others. However, the process of this material evolution is arguably slow in many developing countries, putting them far behind developed counterparts in terms of technological advancement. One of the advanced materials that absorbed global attention and can be adopted to assess research development is graphene. In this work, graphene-related publications of universities and research institutes were utilized to assess how effective the higher education policies of Indonesia, as a developing country, encourage graphene research development. For this purpose, a multidisciplinary perspective was used to comprehensively analyze the findings, highlighting the emerging gaps, orientation, and promising future research that will benefit many researchers, governments, and industries. A total of 667 filtered publications were investigated. In addition, VOSviewer was utilized as a proper complement to visualize and analyze the publication trend based on keywords and authorship. Many aspects were explored, including publication, distribution, collaboration, and policies. The investigation revealed that supportive governmental policies, especially Law No. 12 of 2012, in classifying the entity of universities, had a remarkable impact on the productivity and geographical distribution of graphene research publications. The most important finding, after analyzing 535 publications, showed that publications of graphene research increased dramatically and is centralized on Java Island. Moreover, it strongly indicates that most universities with the authority to self-budget can contribute significantly to advanced materials research. International collaboration with many countries was also strongly formed. By contributing 114 co-authorships, Malaysia was shown to be a favorite counterpart. Therefore, this study confirms that research activity can be utilized to assess the effectiveness of higher education policies. In a broader context, the advanced materials research publication is emerging as an indicator in revealing Indonesia’s socio-economic development. The trend of graphene research itself demonstrates the raising of developing countries’ awareness of global issues.
A Framework for Crowd Management during COVID-19 with Artificial Intelligence
Authors: Almutairi Mishaal M. , Yamin Mohammad , Halikias George , Abi Sen Adnan Ahmed
Published: December 2021

COVID-19 requires crowded events to enforce restrictions, aimed to contain the spread of the virus. However, we have seen numerous events not observing these restrictions, thus becoming super spreader events. In order to contain the spread of a human to human communicable disease, a number of restrictions, including wearing face masks, maintaining social distancing, and adhering to regular cleaning and sanitization, are critical. These restrictions are absolutely essential for crowded events. Some crowded events can take place spontaneously, such as a political rally or a protest march or a funeral procession. Controlling spontaneous crowded events, like a protest march, political rally, celebration after a sporting event, or concert, can be quite difficult, especially during a crisis like the COVID-19 pandemic. In this article, we review some well-known crowded events that have taken place during the ongoing pandemic. Guided by our review, we provide a framework using machine learning to effectively organize crowded events during the ongoing and for future crises. We also provide details of metrics for the validation of some components in the proposed framework, and an extensive algorithm. Finally, we offer explanations of its various functions of the algorithm. The proposed framework can also be adapted in other crises.
Integral Representation and Explicit Formula at Rational Arguments for Apostol–Tangent Polynomials
Authors: Corcino Cristina B. , Corcino Roberto B. , Damgo Baby Ann A. , Cañete Joy Ann A.
Published: December 2021

The Fourier series expansion of Apostol–tangent polynomials is derived using the Cauchy residue theorem and a complex integral over a contour. This Fourier series and the Hurwitz–Lerch zeta function are utilized to obtain the explicit formula at rational arguments of these polynomials. Using the Lipschitz summation formula, an integral representation of Apostol–tangent polynomials is also obtained.
A Preconception Paternal Fish Oil Diet Prevents Toxicant-Driven New Bronchopulmonary Dysplasia in Neonatal Mice
Authors: Rumph Jelonia T. , Rayford Kayla J. , Stephens Victoria R. , Ameli Sharareh , Nde Pius N. , Osteen Kevin G. , Bruner-Tran Kaylon L.
Published: December 2021

New bronchopulmonary dysplasia is a developmental lung disease associated with placental dysfunction and impaired alveolarization. Risk factors for new BPD include prematurity, delayed postnatal growth, the dysregulation of epithelial-to-mesenchymal transition (EMT), and parental exposure to toxicants. Our group previously reported that a history of paternal toxicant exposure increased the risk of prematurity and low birth weight in offspring. A history of paternal toxicant exposure also increased the offspring’s risk of new BPD and disease severity was increased in offspring who additionally received a supplemental formula diet, which has also been linked to poor lung development. Risk factors associated with new BPD are well-defined, but it is unclear whether the disease can be prevented. Herein, we assessed whether a paternal fish oil diet could attenuate the development of new BPD in the offspring of toxicant exposed mice, with and without neonatal formula feeding. We investigated the impact of a paternal fish oil diet preconception because we previously reported that this intervention reduces the risk of TCDD associated placental dysfunction, prematurity, and low birth weight. We found that a paternal fish oil diet significantly reduced the risk of new BPD in neonatal mice with a history of paternal toxicant exposure regardless of neonatal diet. Furthermore, our evidence suggests that the protective effects of a paternal fish oil diet are mediated in part by the modulation of small molecules involved in EMT.
Characteristics of Adverse Events in Bee Venom Therapy Reported in South Korea: A Survey Study
Authors: Kim Kyeonghan , Jeong Hyein , Lee Gihyun , Jang Soobin , Yook Taehan
Published: December 2021

This study was aimed at investigating Korean patients’ experience with bee venom therapy (BVT) and providing evidence to enhance BVT safety. Thus, an anonymous online survey was conducted between August 22 and 28, 2018. Five hundred respondents who underwent pharmacopuncture (PA) within one year were surveyed (sample error: 95 ± 4.38%). Of these, 32 respondents were excluded and 468 were evaluated. Of the 468, 61 reported experiencing adverse events after PA. The adverse event rate was higher in the BV-PA(Bee venom-Pharmacopuncture) group than in the non-A group; however, intergroup differences were insignificant. There were no significant differences in mild symptom intensity between the BV-PA and non-BV-PA groups (p = 0.572). However, there was a significant intergroup difference in severe symptom intensity (p < 0.001). Additionally, the BV-PA and non-BV-PA groups did not significantly differ in their level of satisfaction either overall or in terms of effectiveness and safety (p = 0.414, p = 0.339, and p = 0.675, respectively). Furthermore, the BV-PA and non-BV-PA groups did not differ regarding intent to re-treat (p = 0.722). Severe adverse events such as anaphylactic shock were not reported; however, BVT practitioners should be cautious when applying it.
Pain in Patients with Post Paralytic Hemifacial Spasm: Before, during and after Botulinum Toxin Injections
Authors: Wehrlin Chloé , Picard Diane , Tankéré Frederic , Hervochon Rémi , Foirest Claire
Published: December 2021

It is well-established that botulinum toxin (BT) injections improve quality of life in patients with postparalytic hemifacial spasm. Nevertheless, injection-related pain and contracture-related pain have not yet been studied. The primary objective of our study was to evaluate injection-related pain in patients with facial palsy sequelae, and to compare the standard technique (syringe) with the Juvapen device. The secondary objective was to evaluate the improvement of contracture-related pain one month after BT injection. Methods: We conducted an observational, prospective, monocentric study based on 60 patients with facial palsy sequelae who received BT injections in our university ENT (ear, nose throat) department. There were 30 patients in the Juvapen group (J) and 30 in the standard technique group (ST). All patients completed Numerical Rating Scale (NRS) questionnaires immediately after the injections and one month later. Results: The average NRS score was 1.33/10 with Juvapen and 2.24/10 with the standard technique (p = 0.0058; Z = 2.75). In patients with contracture-related pain, the average NRS score was 3.53 before BT injection, and 0.41 one month after BT injection (p = 0.0001). Conclusions: Juvapen is a less-painful injection technique than the standard one. BT reduces contracture-related pain one month after injection.
Living Donor Kidney Transplantation for a Recipient after 41 Years of Hemodialysis
Authors: Tanaka Kosuke , Hidaka Yuji , Yamanaga Shigeyoshi , Kinoshita Kohei , Kaba Akari , Toyoda Mariko , Yokomizo Hiroshi
Published: December 2021

Due to atrophic bladder, patients undergoing long-term dialysis experience vesicoureteral reflux and complicated urinary tract infections after kidney transplantation. A 58-year-old woman underwent living donor kidney transplantation after 41 years of dialysis. She had no contraindications, with good cardiac function and minimal artery calcification despite the long history of hemodialysis. Immunosuppression was initiated with tacrolimus, mycophenolate mofetil, prednisolone, and basiliximab. Ureteroneocystostomy with an antireflux technique was carefully conducted as her bladder volume was 15 mL. The postoperative clinical course was uneventful with immediate graft function. The bladder volume gradually increased to 81 mL at discharge, 3 weeks postoperatively. The patient was initially depressed due to frequent urination early post-transplant but recovered soon after as the bladder volume gradually increased to 400 mL. The patient has not yet reported a urinary tract infection episode. This case highlights living donor kidney transplantation-induced recovery of bladder function with careful ureteroneocystostomy, despite the long dialysis history.
Progress in Understanding the Nature of SS433
Authors: Cherepashchuk Anatol
Published: December 2021

SS433 is the first example of a microquasar discovered in the Galaxy. It is a natural laboratory for studies of extraordinarily interesting physical processes that are very important for the relativistic astrophysics, cosmic gas dynamics and theory of evolution of stars. The object has been studied for over 40 years in the optical, X-ray and radio bands. By now, it is generally accepted that SS433 is a massive eclipsing X-ray binary in an advanced stage of evolution in the supercritical regime of accretion on the relativistic object. Intensive spectral and photometric observations of SS433 at the Caucasian Mountain Observatory of the P. K. Sternberg Astronomical Institute of M. V. Lomonosov Moscow State University made it possible to find the ellipticity of the SS433 orbit and to discover an increase in the system’s orbital period. These results shed light on a number of unresolved issues related to SS433. In particular, a refined estimate of the mass ratio MxMv>0.8 was obtained (Mx and Mv are the masses of the relativistic object and optical star). Based on these estimates, the relativistic object in the SS433 system is the black hole; its mass is >8M⊙. The ellipticity of the orbit is consistent with the “slaved” accretion disc model. The results obtained made it possible to understand why SS433 evolves as the semi-detached binary instead of the common envelope system.
miRNAs, from Evolutionary Junk to Possible Prognostic Markers and Therapeutic Targets in COVID-19
Authors: Bautista-Becerril Brandon , Pérez-Dimas Guillermo , Sommerhalder-Nava Paola C. , Hanono Alejandro , Martínez-Cisneros Julio A. , Zarate-Maldonado Bárbara , Muñoz-Soria Evangelina , Aquino-Gálvez Arnoldo , Castillejos-López Manuel , Juárez-Cisneros Armida , Lopez-Gonzalez Jose S. , Camarena Angel
Published: December 2021

The COVID-19 pandemic has been a public health issue around the world in the last few years. Currently, there is no specific antiviral treatment to fight the disease. Thus, it is essential to highlight possible prognostic predictors that could identify patients with a high risk of developing complications. Within this framework, miRNA biomolecules play a vital role in the genetic regulation of various genes, principally, those related to the pathophysiology of the disease. Here, we review the interaction of host and viral microRNAs with molecular and cellular elements that could potentiate the main pulmonary, cardiac, renal, circulatory, and neuronal complications in COVID-19 patients. miR-26a, miR-29b, miR-21, miR-372, and miR-2392, among others, have been associated with exacerbation of the inflammatory process, increasing the risk of a cytokine storm. In addition, increased expression of miR-15b, -199a, and -491 are related to the prognosis of the disease, and miR-192 and miR-323a were identified as clinical predictors of mortality in patients admitted to the intensive care unit. Finally, we address miR-29, miR-122, miR-155, and miR-200, among others, as possible therapeutic targets. However, more studies are required to confirm these findings.