bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards Building a Visual Behaviour Analysis Pipeline for Suicide Detection and Prevention
Authors: Li Xun , Onie Sandersan , Liang Morgan , Larsen Mark , Sowmya Arcot
Published: June 2022

Understanding human behaviours through video analysis has seen significant research progress in recent years with the advancement of deep learning. This topic is of great importance to the next generation of intelligent visual surveillance systems which are capable of real-time detection and analysis of human behaviours. One important application is to automatically monitor and detect individuals who are in crisis at suicide hotspots to facilitate early intervention and prevention. However, there is still a significant gap between research in human action recognition and visual video processing in general, and their application to monitor hotspots for suicide prevention. While complex backgrounds, non-rigid movements of pedestrians and limitations of surveillance cameras and multi-task requirements for a surveillance system all pose challenges to the development of such systems, a further challenge is the detection of crisis behaviours before a suicide attempt is made, and there is a paucity of datasets in this area due to privacy and confidentiality issues. Most relevant research only applies to detecting suicides such as hangings or jumps from bridges, providing no potential for early prevention. In this research, these problems are addressed by proposing a new modular design for an intelligent visual processing pipeline that is capable of pedestrian detection, tracking, pose estimation and recognition of both normal actions and high risk behavioural cues that are important indicators of a suicide attempt. Specifically, based on the key finding that human body gestures can be used for the detection of social signals that potentially precede a suicide attempt, a new 2D skeleton-based action recognition algorithm is proposed. By using a two-branch network that takes advantage of three types of skeleton-based features extracted from a sequence of frames and a stacked LSTM structure, the model predicts the action label at each time step. It achieved good performance on both the public dataset JHMDB and a smaller private CCTV footage collection on action recognition. Moreover, a logical layer, which uses knowledge from a human coding study to recognise pre-suicide behaviour indicators, has been built on top of the action recognition module to compensate for the small dataset size. It enables complex behaviour patterns to be recognised even from smaller datasets. The whole pipeline has been tested in a real-world application of suicide prevention using simulated footage from a surveillance system installed at a suicide hotspot, and preliminary results confirm its effectiveness at capturing crisis behaviour indicators for early detection and prevention of suicide.
Quad-Band Polarization-Insensitive Square Split-Ring Resonator (SSRR) with an Inner Jerusalem Cross Metamaterial Absorber for Ku- and K-Band Sensing Applications
Authors: Hakim Mohammad Lutful , Alam Touhidul , Islam Mohammad Tariqul , Baharuddin Mohd Hafiz , Alzamil Ahmed , Islam Md. Shabiul
Published: June 2022

The development of metamaterial absorbers has become attractive for various fields of application, such as sensing, detectors, wireless communication, antenna design, emitters, spatial light modulators, etc. Multiband absorbers with polarization insensitivity have drawn significant attention in microwave absorption and sensing research. In this paper, we propose a quad-band polarization-insensitive metamaterial absorber (MMA) for Ku- and K-band applications. The proposed patch comprises two square split-ring resonators (SSRR), four microstrip lines, and an inner Jerusalem cross to generate four corresponding resonances at 12.62 GHz,14.12 GHz, 17.53 GHz, and 19.91 GHz with 97%, 99.51%, 99%, and 99.5% absorption, respectively. The complex values of permittivity, permeability, refractive index, and impedance of MMA were extracted and discussed. The absorption mechanism of the designed MMA was explored by impedance matching, equivalent circuit model, as well as magnetic field and electric field analysis. The overall patch has a rotational-symmetrical structure, which plays a crucial role in acquiring the polarization-insensitive property. The design also shows stable absorption for both transverse electric (TE) and transverse magnetic (TM) modes. Its near-unity absorption and excellent sensing performance make it a potential candidate for sensing applications.
Urethane-Foam-Embedded Silicon Pressure Sensors including Stress-Concentration Packaging Structure for Driver Posture Monitoring
Authors: Takamatsu Seiichi , Sato Suguru , Itoh Toshihiro
Published: June 2022

We propose urethane-foam-embedded silicon pressure sensors, including a stress-concentration packaging structure, for integration into a car seat to monitor the driver’s cognitive state, posture, and driving behavior. The technical challenges of embedding silicon pressure sensors in urethane foam are low sensitivity due to stress dispersion of the urethane foam and non-linear sensor response caused by the non-uniform deformation of the foam. Thus, the proposed package structure includes a cover to concentrate the force applied over the urethane foam and frame to eliminate this non-linear stress because the outer edge of the cover receives large non-linear stress concentration caused by the geometric non-linearity of the uneven height of the sensor package and ground substrate. With this package structure, the pressure sensitivity of the sensors ranges from 0 to 10 kPa. The sensors also have high linearity with a root mean squared error of 0.049 N in the linear regression of the relationship between applied pressure and sensor output, and the optimal frame width is more than 2 mm. Finally, a prototype 3 × 3 sensor array included in the proposed package structure detects body movements, which will enable the development of sensor-integrated car seats.
Environmental Controls to Soil Heavy Metal Pollution Vary at Multiple Scales in a Highly Urbanizing Region in Southern China
Authors: Li Cheng , Jiang Xinyu , Jiang Heng , Sha Qinge , Li Xiangdong , Jia Guanglin , Cheng Jiong , Zheng Junyu
Published: June 2022

Natural and anthropogenic activities affect soil heavy metal pollution at different spatial scales. Quantifying the spatial variability of soil pollution and its driving forces at different scales is essential for pollution mitigation opportunities. This study applied a multivariate factorial kriging technique to investigate the spatial variability of soil heavy metal pollution and its relationship with environmental factors at multiple scales in a highly urbanized area of Guangzhou, South China. We collected 318 topsoil samples and used five types of environmental factors for the attribution analysis. By factorial kriging, we decomposed the total variance of soil pollution into a nugget effect, a short-range (3 km) variance and a long-range (12 km) variance. The distribution of patches with a high soil pollution level was scattered in the eastern and northwestern parts of the study domain at a short-range scale, while they were more clustered at a long-range scale. The correlations between the soil pollution and environmental factors were either enhanced or counteracted across the three distinct scales. The predictors of soil heavy metal pollution changed from the soil physiochemical properties to anthropogenic dominated factors with the studied scale increase. Our study results suggest that the soil physiochemical properties were a good proxy to soil pollution across the scales. Improving the soil physiochemical properties such as increasing the soil organic matter is essentially effective across scales while restoring vegetation around pollutant sources as a nature-based solution at a large scale would be beneficial for alleviating local soil pollution.
Industrial Needs in the Fields of Artificial Intelligence, Internet of Things and Edge Computing
Authors: Stadnicka Dorota , Sęp Jarosław , Amadio Riccardo , Mazzei Daniele , Tyrovolas Marios , Stylios Chrysostomos , Carreras-Coch Anna , Merino Juan Alfonso , Żabiński Tomasz , Navarro Joan
Published: June 2022

Industry 4.0 corresponds to the Fourth Industrial Revolution, resulting from technological innovation and research multidisciplinary advances. Researchers aim to contribute to the digital transformation of the manufacturing ecosystem both in theory and mainly in practice by identifying the real problems that the industry faces. Researchers focus on providing practical solutions using technologies such as the Industrial Internet of Things (IoT), Artificial Intelligence (AI), and Edge Computing (EC). On the other hand, universities educate young engineers and researchers by formulating a curriculum that prepares graduates for the industrial market. This research aimed to investigate and identify the industry’s current problems and needs from an educational perspective. The research methodology is based on preparing a focused questionnaire resulting from an extensive recent literature review used to interview representatives from 70 enterprises operating in 25 countries. The produced empirical data revealed (1) the kind of data and business management systems that companies have implemented to advance the digitalization of their processes, (2) the industries’ main problems and what technologies (could be) implemented to address them, and (3) what are the primary industrial needs and how they can be met to facilitate their digitization. The main conclusion is that there is a need to develop a taxonomy that shall include industrial problems and their technological solutions. Moreover, the educational needs of engineers and researchers with current knowledge and advanced skills were underlined.
Understanding Factors Underlying Fatigue among Collegiate Aviation Pilots in the United States
Authors: Keller Julius , Mendonca Flavio Antonio Coimbra , Adjekum Daniel Kwasi
Published: June 2022

An increase in evidence-based studies into the deleterious effects of fatigue on flight operations has been reported by key aviation groups globally. The collegiate aviation flight training environment has not been researched at the same level when compared to military and airline operations. College aged students are unique in the sense that they are tasked with classwork, studying, participation in student organizations, social activities, and often have part time jobs within and outside of the academic environment. These conditions may cause errors, incidents, accidents, poor academic performance, and undesirable health metrics. The purpose of this study was to understand fatigue as a multi-factorial dimension and to assess potential relationships among these factors using hypothesized measurement models. The research team distributed the Collegiate Aviation Fatigue Inventory II (CAFI-II) to eight small, medium, and large collegiate aviation programs in the United States. The CAFI-II primarily focuses on fatigue awareness, causes and symptoms of fatigue, and lifestyle choices. Four hundred and twenty-two (n = 422) valid responses were obtained. Results suggested a direct predictive relationship between fatigue in collegiate flight training and the perceptions of respondents of conditions that are known to cause fatigue. Findings also suggested that respondents who had a favorable perception of fatigue risk and management programs had a better understanding of the causes of fatigue.
The Feasibility and Acceptability of an Experience-Based Co-Design Approach to Reducing Domestic Abuse
Authors: Gander-Zaucker Shoshana , Unwin Gemma L. , Larkin Michael
Published: June 2022

One means of reducing violence against people experiencing domestic abuse is to improve the pathway which they use to access help from the police and other services. In this paper we report and reflect on a project which contributes to violence reduction via a participatory approach to service improvement, focusing on this pathway. We describe the four phases of an innovative experience-based co-design (EBCD) project, which involved collaborating with domestic abuse survivors as well as members of the police and domestic abuse organizations. We report on indicators of the acceptability and feasibility of EBCD in this context. We also reflect upon the potential of the EBCD approach for involving communities in collaborating with services to reduce domestic abuse. We discuss the conceptual and methodological implications with regard to adopting participatory and inclusive approaches in contexts where power-sharing may be difficult. We argue that EBCD has considerable potential for use in this setting and we identify several areas where insights from this project could be used to improve the future viability of any such initiatives.
Urban Living Lab: An Experimental Co-Production Tool to Foster the Circular Economy
Authors: Cuomo Federico
Published: June 2022

In recent decades; the balance of power between institutional and economic actors has radically changed; with a significant impact on the modes and dynamics of governance. In the broad array of experimental practices of co-production; Living Labs (LLs) represent a promising mode of collaboration among public bodies; research centres; private companies and citizens. By means of LLs; public actors aim to co-produce experimental policies; breaking out of traditional policy schemes to find new solutions to collective problems. On an urban scale; such tools have come to be known as Urban Living Labs (ULLs), and they are increasingly used by local governments to tackle complex problems such us stimulating the circular economy to tackle climate change. This paper provides a systematic review of case studies to understand whether and how the ULLs can represent an effective policy tool to foster the circular economy on an urban scale.
Sustainable Livelihoods in Rural Areas under the Shock of Climate Change: Evidence from China Labor-Force Dynamic Survey
Authors: Peng Yating , Liu Bo , Zhou Mengliang
Published: June 2022

The threat of climate change to the sustainability of farmers’ livelihoods is becoming more significant. Research on the impact of climate change on the sustainability of farmers’ livelihoods could provide a scientific basis for enhancing farmers’ adaptability to climate change, reducing farmers’ livelihood vulnerability, and promoting the formulation of governmental adaptation strategies. Although studies have assessed the impact of climate change on the sustainability of farmers’ livelihoods, their analysis units have been aggregated. Therefore, this study was grouped based on geographical location (north and south regions), and then an additional grouping was conducted according to the internal economic factors of each region. Using data from China’s labor-force dynamic survey as our sample, this study measured the sustainable livelihood in agricultural households. This research provided a method to quantify the sustainability of farmers’ livelihoods based on measurements of poverty vulnerability. Additionally, using the annual average temperature as the core explanatory variable to describe climate change, this study evaluated the impact and heterogeneity of climate change on the sustainability of farmers’ livelihoods and replaced the annual average temperature with the normalized vegetation index to conduct a robustness test. The empirical study showed that the average annual temperature significantly decreased the sustainability of farmers’ livelihoods. The average annual temperature change had a greater impact on farmers in the southern provinces as compared to those in the north. Southern coastal regions, eastern coastal regions, the middle reaches of the Yangtze River, and the northeast regions were the key areas of concern. Finally, considering the current risk vulnerability of farmers, we concluded that crop breeding should be oriented to the trend of climate change, farmers’ risk prevention awareness should be increased, financial tools should be enhanced to mitigate the impact of meteorological disasters, an appropriate sustainability developmental evaluation index should be implemented, and the construction of agrometeorological disaster prevention and mitigation infrastructure should be advanced.
The Integration of Local Actors in Policy Implementation: The Case of Organic Farming in Costa Rica
Authors: Gruber Mirjam
Published: June 2022

Like other countries of the world, Costa Rica faced the challenge of dealing with a variety of trade-offs when implementing sustainability goals in agriculture. Very often, economic promotion is in conflict with goals regarding human and environmental health protection. Organic farming practices could provide strategies to overcome some of these trade-offs. However, in Costa Rica, the majority of farmers still relies on conventional farm practices. In this paper, I investigate the potential for a sustainable transformation in Costa Rica’s agriculture by focusing on organic farming policies. I shed light on the role local actors and organizations play in this process compared to other actor types. I argue that local actors are “the agents of change” in these processes, as these are the target groups of organic farming policies and are the ones who are asked to change their farm practices. Based on survey data and network analysis, I was able to illustrate how differently integrated local actors are compared to other actor types in Costa Rica’s implementation of organic farming policies. Local actors show interest and willingness to further participate in land-use implementation processes when institutional barriers are alleviated, and further promotion instruments are available.
Fire Risk Assessment of Subway Stations Based on Combination Weighting of Game Theory and TOPSIS Method
Authors: Ju Weiyi , Wu Jie , Kang Qingchun , Jiang Juncheng , Xing Zhixiang
Published: June 2022

With the rapid development of urban modernization, traffic congestion, travel delays, and other related inconveniences have become central features in people’s daily lives. The development of subway transit systems has alleviated some of these problems. However, numerous underground subway stations lack adequate fire safety protections, and this can cause rescue difficulties in the event of fire. Once the fire occurs, there will be huge property losses and casualties. In addition, this can have a vicious impact on sustainable development. Therefore, in order to make prevention in advance and implement targeted measures, we should quantify the risk and calculate the fire risk value. In this study, through consulting experts and analysis of data obtained from Changzhou Railway Company and the Emergency Management Bureau, the fire risk index system of subway stations was determined. We calculated the index weight by selecting the combination weighting method of game theory to eliminate the limitations and dependence of subjective and objective evaluation methods. The idea of relative closeness degree in TOPSIS method iwas introduced to calculate the risk value of each subway station. Finally, the subway station risk value model was established, and the risk values for each subway station were calculated and sorted. According to expert advice and the literature review, we divided the risk level into five levels, very high; high; moderate; low and very low. The results shown that 2 subway stations on Line 1 have very high fire risk, 2 subway stations on Line 1 have high fire risk, 2 subway stations on Line 1 have moderate fire risk, 8 subway stations on Line 1 have low fire risk, and 13 subway stations on Line 1 have very low fire risk. We hope that through this evaluation model method and the results to bring some references for local rail companies. Meanwhile, this evaluation model method also promotes resilience and sustainability in social development.
Spatial–Temporal Evolution and Sustainable Type Division of Fishery Science and Technology Innovation Efficiency in China
Authors: Zhu Wendong , Li Dahai , Han Limin
Published: June 2022

Science and technology innovation is an important driving force to promote the development of fishery industry, and is very important to improve the quality of fishery development. In this study, the Super-SBM model was used to evaluate the fishery science and technology innovation efficiency of 30 provinces and cities in China (excluding Hong Kong, Macao, Taiwan and Tibet) from 2011 to 2020. Combined with the kernel density estimation, the spatial and temporal differentiation characteristics were analyzed. Then, from the two dimensions of investment scale and innovation efficiency, the sustainable development types of fishery science and technology innovation were classified. The results show the following: (1) From the perspective of efficiency change, the overall efficiency of fishery science and technology innovation in China increased first and then decreased during 2011–2020, but the overall efficiency level was low, and the efficiency difference between regions gradually widened, and the eastern coastal regions became the development core of fishery science and technology innovation. (2) From the perspective of spatial differentiation characteristics, there was a large gap between the coastal and inland areas in China. The high-efficiency areas were mainly concentrated in the coastal provinces and cities, such as Guangdong, Jiangsu, Shandong, Shanghai and Tianjin, showing a decreasing trend from east to west. (3) From the perspective of investment scale and innovation efficiency, the study regions can be divided into four types: leading area, breakthrough area, catch-up area and backward area. This paper mainly calculates the efficiency of fishery science and technology innovation in various regions, and divides the type areas of fishery science and technology innovation and development. According to the advantages and problems of different types of areas, different development strategies and correction measures are proposed, which can effectively improve the efficiency of resource utilization, avoid resource waste and realize the sustainable development of fishery.
Stadium Travel and Subjective Well-Being of Football Spectators
Authors: Thormann Tim F. , Wicker Pamela , Braksiek Michael
Published: June 2022

In the context of leisure travel in sport, the United Nations’ Sustainable Development Goals to promote public health and combat climate change may be addressed simultaneously. This study investigates football spectators’ carbon footprint that is generated from traveling to the stadium. It also examines the effects of stadium travel and everyday pro-environmental behavior on spectators’ subjective well-being. The study uses data that were gathered from an online survey in Germany in 2021 (n = 1605). For a detailed carbon footprint assessment, spectators were allowed to indicate multiple transportation means if they switched them during their stadium journey. Seemingly unrelated regression models were calculated to examine the effect of transportation behavior (i.e., stadium travel) and everyday recycling, consumption, and energy-saving behavior on life satisfaction and happiness. Traveling to a home game caused an average carbon footprint of 7.79 kg CO2-e per spectator, or 190.4 tons CO2-e for all home game spectators. Regression results showed that sustainable consumption increased both well-being measures while recycling behavior only positively contributed to happiness. Stadium travel and energy-saving behavior showed no significant effect. These findings implicate that achieving both sustainable development goals can go hand in hand in some contexts of pro-environmental behavior, but not in all dimensions.
Industrial-Innovative Paradigm of Social Sustainability: Modeling the Assessment of Demoethical, Demographic, Democratic, and Demoeconomic Factors
Authors: Zhanbayev Rinat , Irfan Muhammad
Published: June 2022

The article presents an analysis of tools for influencing the sustainable development of regions, considering their industry specifics, as well as ways to influence socioeconomic growth. The purpose of the article is to model the assessment of demoetic, demographic, democratic, and demoeconomical factors as the basis of the industrial and innovative paradigm of social sustainability. Achieving sustainability is possible only along the vector of harmony through the systemic combination 4D = “D + 3D”, namely, demoethics and demography, democracy, demoeconomy. Analysis of the existing processes of development and harmonization of society is implemented in the example of Kazakhstan. Research methods include integral analysis for ranking regions and correlation and regression modeling to assess the impact of factors on the process of sustainable development of society in a particular territory. The article hypothesizes that the creation of conditions for the development of the main regional industry will stimulate its sustainable and harmonious socioeconomic growth and provide the necessary level for the process of social harmonization. The findings show that the proposed approach made it possible to identify harmonious and disharmonious factors in the development of the region and to identify tools for influencing the process of sustainable development of society to increase the level of harmonious socioeconomic development of a particular region.
Stabilization Strategy of a Novel Car-Following Model with Time Delay and Memory Effect of the Driver
Authors: Pan Yifan , Wang Yongjiang , Miao Baobin , Cheng Rongjun
Published: June 2022

In this paper, a novel car-following model is established integrating the drivers’ memory of previous information. The drivers’ memory of the vehicle ahead is introduced as an influencing factor on the drivers’ expected behavior. The time delay feedback control term is added to the model to increase the stability interval of the system. By comparing the stability intervals of the controlled and uncontrolled models, the necessity of adding a delay feedback control item is demonstrated. The validity and feasibility of the time delay feedback control strategy are proved by numerical simulations. In this paper, the stability interval of the system is determined by the definite integral stability method (DISM) and the Hopf bifurcation analysis method. According to the number of unstable eigenvalues derived from the system eigenvalue equation, the appropriate time delay feedback control parameters are set. By choosing the optimal parameters, the new model can optimize the traffic flow to the maximum extent, eliminate the stop-and-go of vehicles, and make the traffic stable. Numerical examples close to actual traffic conditions are given to verify the feasibility of the control strategy using the verified design steps. Next generation simulation (NGSIM) measurements are used to conduct parameter calibration of the new model.
Spatiotemporal Variations in Summertime Ground-Level Ozone around Gasoline Stations in Shenzhen between 2014 and 2020
Authors: Mei Yingying , Xiang Xueqi , Xiang Deping
Published: June 2022

Ground-level ozone has become the primary air pollutant in many urban areas of China. Oil vapor pollution from gasoline stations accelerates the generation of ground-level ozone, especially in densely populated urban areas with high demands for transportation. An accurate spatiotemporal distribution of ground-level ozone concentrations (GOCs) around gasoline stations is urgently needed. However, urban GOCs vary sharply over short distances, increasing the need for GOCs at a high-spatial resolution. Thus, a high-spatial resolution (i.e., 1 km) concentration retrieval model based on the GLM and BME method was developed to obtain the daily spatiotemporal characteristics of GOCs. The hourly ozone records provided by the national air quality monitoring stations and multiple geospatial datasets were used as input data. The model exhibited satisfactory performance (R2 = 0.75, RMSE = 10.86 µg/m3). The derived GOCs show that the ozone levels at gasoline stations and their adjacent areas (1~3 km away from the gasoline stations) were significantly higher than the citywide average level, and this phenomenon gradually eased with the increasing distance from the gasoline stations. The findings indicate that special attention should be given to the prevention and control of ground-level ozone exposure risks in human settlements and activity areas near gasoline stations.
Using Modified Harmonic Analysis to Estimate the Trend of Sea-Level Rise around Taiwan
Authors: Hsieh Chih-Min , Chou Dean , Hsu Tai-Wen
Published: June 2022

Sea-level rise (SLR) has become an essential global environmental problem and great importance is attached by all sectors of society. This study aims to estimate the trends of SLR from the tide-gauge measurements located in different sites of Taiwan. Different methods of analysis, such as the linear-regression method (LRM), Hilbert–Huang transform (HHT), and modified harmonic analysis (MHA) are used to estimate SLR and their applicability is discussed. Limitations of these methods are also compared and discussed via the analyzed results. MHA is the focus of the present paper. It has the advantage of representing tidal harmonic motion as well as the long-term trend of SLR more accurately, even in the condition of data loss caused by mechanical failures or anomaly. The analyzing results reveal that MHA is more applicable for estimating SLR than the above traditional methods. The most important analyzed results indicate that the recent 20-year SLR rate is within the range of −0.9 mm/yr and 18.1 mm/yr, using the tidal database observed at 17 stations along the Taiwanese coast. SLR is also compared with analyzed results from different databases or scenarios. The value of SLR is modified by adding the vertical-change rate of the benchmark. It is interesting to note that correction tends to reduce the bias of the variation trend of SLR.
Barriers for Homeowners in Decisions to Undertake Government-Led Energy Efficiency Renovation Projects in Northern China
Authors: Ma Jiefang , Qian Queena Kun , Visscher Henk , Song Kun
Published: June 2022

The Chinese government has taken actions to promote energy efficiency through the renovation of residential buildings in the Northern Heating Region. Homeowners have been encouraged to undertake government-led energy efficiency renovation; however, their decisions to undertake the renovation are affected by several barriers. The lack of participation from homeowners has brought difficulties in execution and financing. This study empirically investigated the barriers facing homeowners when undertaking the renovation, including barriers generated from the homeowner’s cognitive biases. The results show that barriers associated with capital cost, unbalanced financial plan, unclear process, comfort, and increased energy prices are the most widely considered when homeowners make decisions about undertaking renovation projects. An adverse decision is most likely to be generated when: (1) when homeowners perceive the financial plan as unfair, (2) when they have already done renovation at their own expense, or (3) when they have the feeling of losing initiative. Among all the individual factors, the homeowners’ gender, age, education level, and building type are significant in predicting their decisions. By drawing on insights from behavioral economics, we analyzed the mechanisms behind these barriers. The findings can help policymakers to design more cost-effective policy instruments to mitigate the barriers.
Short Time Series Forecasting: Recommended Methods and Techniques
Authors: Cruz-Nájera Mariel Abigail , Treviño-Berrones Mayra Guadalupe , Ponce-Flores Mirna Patricia , Terán-Villanueva Jesús David , Castán-Rocha José Antonio , Ibarra-Martínez Salvador , Santiago Alejandro , Laria-Menchaca Julio
Published: June 2022

This paper tackles the problem of forecasting real-life crime. However, the recollected data only produced thirty-five short-sized crime time series for three urban areas. We present a comparative analysis of four simple and four machine-learning-based ensemble forecasting methods. Additionally, we propose five forecasting techniques that manage the seasonal component of the time series. Furthermore, we used the symmetric mean average percentage error and a Friedman test to compare the performance of the forecasting methods and proposed techniques. The results showed that simple moving average with seasonal removal techniques produce the best performance for these series. It is important to highlight that a high percentage of the time series has no auto-correlation and a high level of symmetry, which is deemed as white noise and, therefore, difficult to forecast.
Conditioned Adaptive Control for an Uncertain Bioreactor with Input Saturation and Steep Settling Desired Output
Authors: Rincón Alejandro , Hoyos Fredy E. , Candelo-Becerra John E.
Published: June 2022

In this work, a controller is developed for a continuous bioreactor with an unknown reaction rate term, subject to input saturation. The substrate concentration and the dilution rate are chosen as output and input, respectively. The controller formulation and the stability analysis are performed by the theory of dead zone Lyapunov functions, Lyapunov stability, and model reference adaptive control. As the main results, the dynamics of the Lyapunov function is determined separately for saturation and non-saturation events, and then a unified expression is deduced. In addition, the asymptotic convergence of the tracking error and boundedness of updated parameters are determined for the whole closed loop regime encompassing saturation and non-saturation events, and also for input saturation events, as a function of the terms and parameters of the reference and system models. The main contributions over closely related control designs, are (i) the effect of input constraint limits and desired output on the convergence of the tracking error during input saturation events are determined, considering settling behavior of the desired output with a steep section; (ii) the upper limit of the input constraint that guarantees output convergence during input saturation events is determined as function of the model terms, but independently of the time derivative of the desired output and its limit; (iii) a new dead zone Lyapunov function is proposed which allows proving asymptotic convergence of the tracking error during input saturation events in the presence of a fast variation in the desired output. Finally, the effectiveness and advantages of the developed controller are illustrated by simulation.
Mesh Denoising Based on Recurrent Neural Networks
Authors: Xing Yan , Tan Jieqing , Hong Peilin , He Yeyuan , Hu Min
Published: June 2022

Mesh denoising is a classical task in mesh processing. Many state-of-the-art methods are still unable to quickly and robustly denoise multifarious noisy 3D meshes, especially in the case of high noise. Recently, neural network-based models have played a leading role in natural language, audio, image, video, and 3D model processing. Inspired by these works, we propose a data-driven mesh denoising method based on recurrent neural networks, which learns the relationship between the feature descriptors and the ground-truth normals. The recurrent neural network has a feedback loop before entering the output layer. By means of the self-feedback of neurons, the output of a recurrent neural network is related not only to the current input but also to the output of the previous moments. To deal with meshes with various geometric features, we use k-means to cluster the faces of the mesh according to geometric similarity and train neural networks for each category individually in the offline learning stage. Each network model, acting similar to a normal regression function, will map the geometric feature descriptor of each facet extracted from the mesh to the denoised facet normal. Then, the denoised normals are used to calculate the new feature descriptors, which become the input of the next similar regression model. In this system, three normal regression modules are cascaded to generate the last facet normals. Lastly, the model’s vertex positions are updated according to the denoised normals. A large number of visual and numerical results have demonstrated that the proposed model outperforms the state-of-the-art methods in most cases.
Antimagic Labeling for Product of Regular Graphs
Authors: Latchoumanane Vinothkumar , Varadhan Murugan
Published: June 2022

An antimagic labeling of a graph G=(V,E) is a bijection from the set of edges of G to 1,2,⋯,E(G) and such that any two vertices of G have distinct vertex sums where the vertex sum of a vertex v in V(G) is nothing but the sum of all the incident edge labeling of G. In this paper, we discussed the antimagicness of rooted product and corona product of graphs. We proved that if we let G be a connected t-regular graph and H be a connected k-regular graph, then the rooted product of graph G and H admits antimagic labeling if t≥k. Moreover, we proved that if we let G be a connected t-regular graph and H be a connected k-regular graph, then the corona product of graph G and H admits antimagic labeling for all t,k≥2.
Uniqueness Criteria for Solving a Time Nonlocal Problem for a High-Order Differential Operator Equation l(·)—A with a Wave Operator with Displacement
Authors: Kanguzhin Baltabek , Koshanov Bakytbek
Published: June 2022

This article presents a criterion for the uniqueness of the solution of a problem nonlocal in time for a differential-operator equation with a symmetric operator part on space variables. The symmetry of the operator part of the operator-differential equation guarantees the existence of good basic properties of its system of root elements. The spectral properties of the symmetric operator part make it possible not only to prove the necessity of the criterion formulated by us, but also to substantiate their sufficiency. In contrast to previously known works, in this work the semiboundedness of the symmetric part of the differential-operator equation can be violated. In this article, the differential-operator equation is represented as the difference of two commuting operators. The uniqueness of the solution is guaranteed when the spectra of the commuting operators do not intersect. It is important that only one of the operators should be symmetrical.
Impact of Molecular Symmetry/Asymmetry on Insulin-Sensitizing Treatments for Type 2 Diabetes
Authors: Filisola-Villaseñor Jessica Georgina , Aranda-Barradas María E. , Miranda-Castro Susana Patricia , Mendieta-Wejebe Jessica Elena , Valdez Guerrero Amaranta Sarai , Guillen Castro Selene Amasis , Martínez Castillo Macario , Tamay-Cach Feliciano , Álvarez-Almazán Samuel
Published: June 2022

Although the advantages and disadvantages of asymmetrical thiazolidinediones as insulin-sensitizers have been well-studied, the relevance of symmetry and asymmetry for thiazolidinediones and biguanides has scarcely been explored. Regarding symmetrical molecules, only one thiazolidinedione and no biguanides have been evaluated and proposed as an antihyperglycemic agent for treating type 2 diabetes. Since molecular structure defines physicochemical, pharmacological, and toxicological properties, it is important to gain greater insights into poorly investigated patterns. For example, compounds with intrinsic antioxidant properties commonly have low toxicity. Additionally, the molecular symmetry and asymmetry of ligands are each associated with affinity for certain types of receptors. An advantageous response obtained in one therapeutic application may imply a poor or even adverse effect in another. Within the context of general patterns, each compound must be assessed individually. The current review aimed to summarize the available evidence for the advantages and disadvantages of utilizing symmetrical and asymmetrical thiazolidinediones and biguanides as insulin sensitizers in patients with type 2 diabetes. Other applications of these same compounds are also examined as well as the various uses of additional symmetrical molecules. More research is needed to exploit the potential of symmetrical molecules as insulin sensitizers.
Knowledge Management as a Domain, System Dynamics as a Methodology
Authors: Zanker Marek , Bureš Vladimír
Published: June 2022

For decades, system dynamics has been utilised as a framework for evaluating and interpreting various types of systems with varying degrees of complexity and knowledge demands. Knowledge management is strongly related to system dynamics on a thematic level. We did a thorough review to identify potential applications and analysed system dynamics and knowledge management domains. The systematic review followed the PRISMA method. We identified two major groups and one subgroup of the combination of system dynamics and knowledge management after examining and categorising 45 papers. Articles were searched for on Web of Science, Scopus, and LENS. We then concentrated on the categorisation of articles by theme. We discovered that system dynamics models were used as a component of a decision support tool or a knowledge management system in some instances, or the integration of knowledge management processes into specific systems. This study contributes to the growth of system dynamics as a methodology capable of generating novel ideas, highlighting limitations, and providing analogies for future research in a variety of academic areas.
Borneol Ester Derivatives as Entry Inhibitors of a Wide Spectrum of SARS-CoV-2 Viruses
Authors: Yarovaya Olga I. , Shcherbakov Dmitriy N. , Borisevich Sophia S. , Sokolova Anastasiya S. , Gureev Maxim A. , Khamitov Edward M. , Rudometova Nadezda B. , Zybkina Anastasiya V. , Mordvinova Ekaterina D. , Zaykovskaya Anna V. , Rogachev Artem D. , Pyankov Oleg V. , Maksyutov Rinat A. , Salakhutdinov Nariman F.
Published: June 2022

In the present work we studied the antiviral activity of the home library of monoterpenoid derivatives using the pseudoviral systems of our development, which have glycoproteins of the SARS-CoV-2 virus strains Wuhan and Delta on their surface. We found that borneol derivatives with a tertiary nitrogen atom can exhibit activity at the early stages of viral replication. In order to search for potential binding sites of ligands with glycoprotein, we carried out additional biological tests to study the inhibition of the re-receptor-binding domain of protein S. For the compounds that showed activity on the pseudoviral system, a study using three strains of the infectious SARS-CoV-2 virus was carried out. As a result, two leader compounds were found that showed activity on the Wuhan, Delta, and Omicron strains. Based on the biological results, we searched for the potential binding site of the leader compounds using molecular dynamics and molecular docking methods. We suggested that the compounds can bind in conserved regions of the central helices and/or heptad repeats of glycoprotein S of SARS-CoV-2 viruses.
From Open Access to Circular Health: Ilaria Capua’s Journey through Science and Politics
Authors: Crisci Elisa
Published: June 2022

This paper highlights the career of an exceptional woman virologist, Dr. Ilaria Capua. It recollects her major achievements, awards and noteworthy events that have shaped her scientific and political career. It retraces Dr. Capua’s major contributions to the study of viral zoonoses, in particular influenza virus, and her strong commitment to an open, more ethical science at the service of society in its broadest sense. It describes how she became the long-term champion of “Open Access” and “Data Sharing” for virus genetic sequences and introduces her new concept of “Circular Health”, where health becomes a circular system that represents a central and vital connection hub between humans and nature. This paper features Dr. Capua’s value as a role model for young women scientists and their empowerment.
The Present and Future of Virology in the Czech Republic—A New Phoenix Made of Ashes?
Authors: Ruml Tomas
Published: June 2022

The Czech Republic, a part of the former Czechoslovakia, has been at the forefront of several research directions in virology, genetics and physiology [...]
Neuraminidase (NA) 370-Loop Mutations of the 2009 Pandemic H1N1 Viruses Affect NA Enzyme Activity, Hemagglutination Titer, Mouse Virulence, and Inactivated-Virus Immunogenicity
Authors: Chen Ting-Hsuan , Chen Chung-Chu , Wu Suh-Chin
Published: June 2022

Hemagglutinin (HA) and neuraminidase (NA) are the two major envelope proteins of influenza viruses. The spatial organization of HA and NA on the virus surface needs to be optimized to promote viral fitness, host specificity, transmissibility, infectivity, and virulence. We previously demonstrated that the recombinant NA protein of the 2009 pandemic H1N1 (pH1N1) with the I365T/S366N mutation in the NA 370-loop elicited higher NA-inhibition antibody titers against the homologous pH1N1 virus and three heterologous H5N1, H3N2, and H7N9 viruses in mice. In this study, we used PR8-based reverse genetics (RG) by replacing the HA and NA genes of A/Texas/05/2009 pH1N1 virus to obtain the wild-type pH1N1 and three NA 370-loop mutant viruses of pH1N1 (I365T/S366N), RG pH1N1 (I365E/S366D), and RG pH1N1 (I365T/S366A). Our results revealed that the viral NA enzyme activity increased for the RG pH1N1(I365T/S366N) and RG pH1N1 (I365E/S366D) viruses but reduced for the RG pH1N1 (I365T/S366A) virus. The increased or decreased NA enzyme activity was found to correlate with the increase or decrease in HA titers of these NA 370-loop mutant viruses. All of these three NA 370-loop mutant RG pH1N1 viruses were less virulent than the wild-type RG pH1N1 virus in mice. Immunizations with the inactivated viruses carrying the three NA 370-loop mutations and the wild-type RG pH1N1 virus were found to elicit approximately the same titers of NA-inhibition antibodies against H1N1 and H5N1 viruses. These results may provide information for developing NA-based influenza virus vaccines.
A Hemagglutinin Stem Vaccine Designed Rationally by AlphaFold2 Confers Broad Protection against Influenza B Infection
Authors: Zeng Dian , Xin Jiabao , Yang Kunyu , Guo Shuxin , Wang Qian , Gao Ying , Chen Huiqing , Ge Jiaqi , Lu Zhen , Zhang Limin , Chen Junyu , Chen Yixin , Xia Ningshao
Published: June 2022

Two lineages of influenza B viruses (IBV) co-circulating in human beings have been posing a significant public health burden worldwide. A substantial number of broadly neutralizing antibodies (bnAbs) have been identified targeting conserved epitopes on hemagglutinin (HA) stem domain, posing great interest for universal influenza vaccine development. Various strategies to design immunogens that selectively present these conserved epitopes are being explored. However, it has been a challenge to retain native conformation of the HA stem region, especially for soluble expression in prokaryotic systems. Here, using a structure prediction tool AlphaFold2, we rationally designed a stable stem antigen “B60-Stem-8071”, an HA stem vaccine derived from B/Brisbane/60/2006 grafted with a CR8071 epitope as a linker. The B60-Stem-8071 exhibited better solubility and more stable expression in the E. coli system compared to the naïve HA stem antigen. Immunization with B60-Stem-8071 in mice generated cross-reactive antibodies and protected mice broadly against lethal challenge with Yamagata and Victoria lineages of influenza B virus. Notably, soluble expression of B60-stem-8071 in the E. coli system showed the potential to produce the influenza B vaccine in a low-cost way. This study represents a proof of concept for the rational design of HA stem antigen based on structure prediction and analysis.