bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Multi-Cell Cooperative Control Algorithm Based on Fuzzy Brain Emotional Learning
Authors: Zhao Jing , Hou Hui , Zheng Peng-Sheng , Wang Da-Han , Yang Yong-Kuan
Published: January 2023

Multi-cell cooperative control can be competent for the current increasingly complex biomedical experiments, greatly improving the efficiency of cell manipulation experiments. At present, this kind of multi-cell cooperative control algorithm is becoming more and more important. In this study, holographic optical tweezers are used to capture multiple cells, and a cell manipulation controller is designed based on the Fuzzy Brain Emotional Learning (FBEL) neural network. Firstly, the dynamic model of trapping yeast cells by optical tweezers is analyzed. The distance between the trap position and the cell position is constrained to avoid cell detachment due to the trap moving too fast. Then, the design cell manipulation controller is relied upon to realize single transport trajectory tracking control. Finally, a multi-cell cooperative control algorithm is designed, and combined with the cell manipulation controller, a multi-cell cooperative controller based on the FBEL neural network is formed. The error between the cell position and the desired trajectory is the input of the multi-cell cooperative controller. The output of the multi-cell cooperative controller is the optical trap position, which is used to realize the cooperative control of multiple cells by holographic optical tweezers. The simulation results showed that the multi-cell cooperative controller based on the FBEL neural network can effectively control multiple yeast cells and quickly converge the cell formation, while ensuring a higher control accuracy than other traditional cell manipulation controllers. It provides a new solution for the efficient and precise automatic manipulation of multiple cells.
A Mobile Gait Training System Providing an Active Interaction
Authors: Lee Ro-Bin , Lee Young Seung , Kweon Hyosun , Kim Hyun Kyung , Kim Yoon Sang
Published: January 2023

In this paper, we propose an interactive mobile gait training system that allows trainees to interact actively with its content (the gait training content). The proposed system is a new type of gait training one combining a mobile robot with virtual reality (contents). It is a mobile system that projects virtual contents (for example, virtual footprints) for gait training on the actual ground (or floor). The performance and effectiveness of the proposed system were examined through a trainee’s foot recognition test and usability evaluation. The test results confirmed that the proposed system showed an average recognition ratio of more than 97%, meaning that the system could accurately recognize the trainee’s foot. In addition, as a result of usability evaluation, the overall satisfaction was 86%, confirming that the proposed system is effective.
Genetic Algorithms for Optimal Control of Lactic Fermentation: Modelling the Lactobacillus paracasei CBA L74 Growth on Rice Flour Substrate
Authors: Ponticelli Gennaro Salvatore , Gallo Marianna , Cacciotti Ilaria , Giannini Oliviero , Guarino Stefano , Budelli Andrea , Nigro Roberto
Published: January 2023

Modelling and predicting of the kinetics of microbial growth and metabolite production during the fermentation process for functional probiotics foods development play a key role in advancing and making such biotechnological processes suitable for large-scale production. Several mathematical models have been proposed to predict the bacterial growth rate, but they can replicate only the exponential phase and require an appropriate empirical data set to accurately estimate the kinetic parameters. On the other hand, computational methods as genetic algorithms can provide a valuable solution for modelling dynamic systems as the biological ones. In this context, the aim of this study is to propose a genetic algorithm able to model and predict the bacterial growth of the Lactobacillus paracasei CBA L74 strain fermented on rice flour substrate. The experimental results highlighted that the pH control does not influence the bacterial growth as much as it does with lactic acid, which is enhanced from 1987 ± 90 mg/L without pH control to 5400 ± 163 mg/L under pH control after 24 h fermentation. The Verhulst model was adopted to predict the biomass growth rate, confirming the ability of exclusively replicating the log phase. Finally, the genetic algorithm allowed the definition of an optimal empirical model able to extend the predictive capability also to the stationary and to the lag phases.
Application of the Impedance Measurement Method to Evaluate the Results of Winter Grafting of Pear Cuttings Using Cold Plasma
Authors: Filippov Rostislav A. , Solovchenko Alexei , Khort Dmitry , Smirnov Igor G. , Kutyrev Alexey I. , Pobedonostsev Roman V. , Yanykin Denis V.
Published: January 2023

Electroimpedance spectroscopy technology can be used to accelerate the healing of complete trees and estimate the plant condition after grafting. This approach will allow sorting out low-vigor plants at the early stages of their development to save time and resources. Still, in some cases, the use of electrical impedance spectroscopy can be difficult due to the complexity of the equipment and special measurement conditions. In this paper, we attempt to overcome this limitation by suggesting a compact device developed in-house that is usable even in the field. Pear (Pyrus communis L.) Otradnenskaya was used as the object of this study. We assessed the treatment effect of the scion–rootstock interface with cold atmospheric plasma (CAP) and plasma-treated solution (PTS) on the survival of the grafts. The dependence of the impedance of the complete grafted tree on the signal frequency and the length of the measuring section was analyzed. It is shown that the treatment of the scion and rootstock with CAP and PTS promotes the fusion of scion and rootstock. The impedance value in the control was on average 24–35% higher than in plants treated with CAP and PTS, which indicates a better healing process of the grafting site. This can be an indication of better quality of the planting material which can be obtained much earlier than with the conventional approach (monitoring the plants in a nursery).
Experiences of the Telemedicine and eHealth Conferences in Poland—A Cross-National Overview of Progress in Telemedicine
Authors: Doniec Rafał J. , Piaseczna Natalia J. , Szymczyk Karen A. , Jacennik Barbara , Sieciński Szymon , Mocny-Pachońska Katarzyna , Duraj Konrad , Cedro Tomasz , Tkacz Ewaryst J. , Glinkowski Wojciech M.
Published: January 2023

The progress in telemedicine can be observed globally and locally. Technological changes in telecommunications systems are intertwined with developments in telemedicine. The recent COVID-19 pandemic has expanded the potential of teleconsultations and telediagnosis solutions in all areas of medicine. This article presents: (1) an overview of milestones in the development of telecommunications systems that allow progress in telemedicine and (2) an analysis of the experiences of the last seven conferences of telemedicine and eHealth in Poland. The telemedicine and eHealth conferences have grown steadily in Poland since their inception in the late 1990s. An exemplary conference program content was used to assess the scientific maturity of the conference, measured by the indices of research dissemination and the impact of publications. The overview presents progress in selected areas of telemedicine, looking at local developments and broader changes. The growing interest in telemedicine in the world’s medical sciences is demonstrated by visibility metrics in Google Scholar, Pubmed, Scopus and Web of Science. National scientific events are assumed to raise interest in the population and influence the creation of general policies. As seen in the example of Poland, the activity of the scientific community gathered around the Polish Telemedicine Society led to novel legal acts that allowed the general practice of telemedicine during the SARS-CoV-2 pandemic. Local scientific conferences focusing on telemedicine research can be a catalyst for changes in attitudes and regulations and the preparation of recommendations for the practice of telemedicine and electronic health. On the basis of the results of this study, it can be concluded that the progress in telemedicine cannot be analyzed in isolation from the ubiquitous developments in technology and telecommunications. More research is needed to assess the cumulative impact of long-standing scientific conferences in telemedicine, as exemplified by the telemedicine and eHealth conferences in Poland.
Special Issue on Wireless and Passive Surface Acoustic Wave Sensor
Authors: Wang Wen
Published: January 2023

The surface acoustic wave (SAW) generated by the so-called piezoelectric effect was confined to the piezoelectric substrate surface at a depth of one or two wavelengths; hence, it was very sensitive towards the external perturbations [...]
Research on Human-Computer Interaction Technology of Large-Scale High-Resolution Display Wall System
Authors: Huang Chen , Chen Yimin , Tong Weiqin , Feng Tao , Deng Mingxing
Published: January 2023

As an effective solution for data visualization and analysis, the large-scale high-resolution display wall system has been widely used in various scientific research fields. On the basis of investigating existing system cases and research results, this paper introduces the SHU-VAS system (60 screens, 120 megapixels) for data visualization and analysis. In order to improve the efficiency of human-computer interaction in large-scale high-definition display wall systems, we propose an interaction framework based on gesture and double-precision pointing technology. During the interaction process, an adaptive mode switching method based on user action features is used to switch between rough and precise control modes. In the evaluation experiments, we analyzed the characteristics of different interaction methods in movement and navigation interaction tasks, and verified the effectiveness of the gesture-based interaction framework proposed in this paper.
Feature Drift in Fake News Detection: An Interpretable Analysis
Authors: Fu Chenbo , Pan Xingyu , Liang Xuejiao , Yu Shanqing , Xu Xiaoke , Min Yong
Published: January 2023

In recent years, fake news detection and its characteristics have attracted a number of researchers. However, most detection algorithms are driven by data rather than theories, which causes the existing approaches to only perform well on specific datasets. To the extreme, several features only perform well on specific datasets. In this study, we first define the feature drift in fake news detection methods, and then demonstrate the existence of feature drift and use interpretable models (i.e., Shapley Additive Explanations and Partial Dependency Plots) to verify the feature drift. Furthermore, by controlling the distribution of tweets’ creation times, a novel sampling method is proposed to explain the reason for feature drift. Finally, the Anchors method is used in this paper as a supplementary interpretation to exhibit the potential characteristics of feature drift further. Our work provides deep insights into the temporal patterns of fake news detection, proving that the model’s performance is also highly related to the distribution of datasets.
Countering the Novelty Effect: A Tutorial for Immersive Virtual Reality Learning Environments
Authors: Miguel-Alonso Ines , Rodriguez-Garcia Bruno , Checa David , Bustillo Andres
Published: January 2023

Immersive Virtual Reality (iVR) is a new technology, the novelty effect of which can reduce the enjoyment of iVR experiences and, especially, learning achievements when presented in the classroom; an effect that the interactive tutorial proposed in this research can help overcome. Its increasingly complex levels are designed on the basis of Mayer’s Cognitive Theory of Multimedia Learning, so that users can quickly gain familiarity with the iVR environment. The tutorial was included in an iVR learning experience for its validation with 65 users. It was a success, according to the user satisfaction and tutorial usability survey. First, it gained very high ratings for satisfaction, engagement, and immersion. Second, high skill rates suggested that it helped users to gain familiarity with controllers. Finally, a medium-high value for flow pointed to major concerns related to skill and challenges with this sort of iVR experience. A few cases of cybersickness also arose. The survey showed that only intense cybersickness levels significantly limited performance and enjoyment; low levels had no influence on flow and immersion and little influence on skill, presence, and engagement, greatly reducing the benefits of the tutorial, despite which it remained useful.
Protective Effect of Ethanolic Extract of Djulis Hull on Indomethacin-Induced Gastric Injury
Authors: Isnain Fuad Sauqi , Liao Nai-Chen , Tsai Hui-Yun , Hsu Jue-Liang , Tsai Pi-Jen , Wardani Agustin Krisna , Chen Yu-Kuo
Published: January 2023

Djulis (Chenopodium formosanum), a pseudocereal crop native to Taiwan, is often utilized as a source of grain in the diet because of its high nutritional value. The hull of djulis is discarded as waste during cooking or processing because of its bitter taste. However, recent studies have shown that djulis hull possesses certain benefits, such as antioxidant, blood sugar-lowering, and gut microbiota-regulating properties. Herein, the gastroprotective activity of ethanolic extract of djulis hull (EEDH) against stomach injury caused by indomethacin (IND) in C57BL/6J mice and its mechanism of action was assessed. Preadministration of EEDH significantly attenuated the gastric ulcer caused by IND in a dose-dependent manner (p < 0.05). Additionally, gastric mucosal injury and gastric wall edema within the submucosal layer observed in histopathological examination were improved by administration of EEDH. EEDH preadministration also reinstated the reduction of glutathione (GSH) content and catalase (CAT), and superoxide dismutase (SOD) activities induced by IND, indicating that EEDH can modulate the antioxidant status of gastric mucosa in mice. Moreover, IND-induced decline of gastric COX-1 expression was upregulated in mice of EEDH treatment groups. Administration of IND increased the expression of proinflammatory proteins in the gastric mucosa of mice, including tumor necrosis factor-α (TNF-α) and inducible nitric oxide synthase (iNOS), whereas EEDH treatment significantly decreased their expression (p < 0.05). Consequently, EEDH can improve gastric injury by regulating antioxidant status and inhibiting proinflammatory signaling pathways, and has the potential to be developed as a functional food for gastric protection.
A Shallow Seafloor Reverberation Simulation Method Based on Generative Adversarial Networks
Authors: Hu Ning , Rao Xin , Zhao Jiabao , Wu Shengjie , Wang Maofa , Wang Yangzhen , Qiu Baochun , Zhu Zhenjing , Chen Zitong , Liu Tong
Published: January 2023

Reverberation characteristics must be considered in the design of sonar. The research on reverberation characteristics is based on a large number of actual reverberation data. Due to the cost of trials, it is not easy to obtain actual lake and sea trial reverberation data, which leads to a lack of actual reverberation data. Traditionally, reverberation data are obtained by modeling the generation mechanism of seafloor reverberation. The usability of the models requires a large amount of actual seafloor reverberation data to verify. In terms of the reverberation modeling theory, scattering models are mostly empirical, computationally intensive and inefficient. In order to solve the above obstacles, we propose a shallow seafloor reverberation data simulation method based on the generative adversarial network (GAN), which uses a small amount of actual reverberation data as reference samples to train the GAN to generate more reverberation data. The reverberation data generated by the GAN are compared with that simulated by traditional methods, and it is found that the reverberation data generated by the GAN meet the reverberation characteristics. Once the network is trained, the reverberation data are generated with very little computation. In addition, the method is universal and can be applied to any sea area. Compared with the traditional method, this method has a simple modeling idea, less computation and strong universality. It can be used as an alternative method for sea trials to provide data support for the study of seafloor reverberation characteristics, and it has broad application prospects in antireverberation technology research and active sonar design.
Optimization of Effective Throughput in NOMA-Based Cognitive UAV Short-Packet Communication
Authors: Zhao Senhao , Hu Hang , Huang Yangchao , Cheng Guobing , Huang Tao , Han Huizhu , An Qi
Published: January 2023

Unmanned aerial vehicles (UAVs) are considered an important component of 6G wireless technology. However, there are many challenges to the employment of UAVs, one of which is spectrum scarcity. To address this challenge, non-orthogonal multiple access (NOMA) and cognitive radio (CR) techniques are employed in UAV short-packet communication systems. In this paper, we consider a NOMA-based cognitive UAV short-packet communication system. Firstly, a mathematical expression for the effective throughput of the secondary users is derived. Then, we aim to maximize the effective throughput of the far secondary user by optimizing the sensing time, power allocation, and information bits under the constraints of the transmission power and effective decoding error probability. A joint optimization algorithm is used to solve this problem, where the bisection method and the one-dimensional linear search algorithm are used to solve the subproblem. The simulation results show that the proposed algorithm has low complexity and similar performance compared to the exhaustive method. In addition, the necessity of joint optimization is shown in the simulation results.
Evaluation of Integrated CNN, Transfer Learning, and BN with Thermography for Breast Cancer Detection
Authors: Aidossov N. , Zarikas Vasilios , Mashekova Aigerim , Zhao Yong , Ng Eddie Yin Kwee , Midlenko Anna , Mukhmetov Olzhas
Published: January 2023

Breast cancer comprises a serious public health concern. The three primary techniques for detecting breast cancer are ultrasound, mammography, and magnetic resonance imaging (MRI). However, the existing methods of diagnosis are not practical for regular mass screening at short time intervals. Thermography could be a solution to this issue because it is a non-invasive and low-cost method that can be used routinely as a self-screening method. The research significance of this work lies in the implementation and integration of multiple different AI techniques for achieving diagnosis based on breast thermograms from several data sources. The data sources contain 306 images. The concept of transfer learning with several pre-trained models is implemented. Bayesian Networks (BNs) are also used to have interpretability of the diagnosis. A novel feature extraction from images (related to temperature) has been implemented and feeds the BNs. Finally, all methods and the classification results of pre-trained models are compared. It is found that the best result amongst the transfer learning concept is achieved with MobileNet, which delivered 93.8% accuracy. Furthermore, the BN achieves an accuracy of 90.20%, and finally, the expert model that combines CNNs and BNs gives an accuracy of 90.85%, even with a limited amount of data available. The integration of CNN and BN aims to overcome the hardship of interpretability. These approaches demonstrate high performance with added interpretability compared to previous works. In conclusion, the deep neural network provides promising results in breast cancer detection. It could be an ideal candidate for Breast Self-Exam (BSE), the goal recommended by WHO for mass screening.
Numerical Simulation of Forming MICP Horizontal Seepage Reducing Body in Confined Aquifer for Deep Excavation
Authors: Wang Jianxiu , Long Yanxia , Zhao Yu , Pan Weiqiang , Qu Jianxun , Yang Tianliang , Huang Xinlei , Liu Xiaotian , Xu Na
Published: January 2023

The drawdown outside of a deep foundation pit has to be controlled during excavation. However, the vertical curtain cannot cutoff a deep and thick confined aquifer during deep excavation. In this study, a microbial-induced carbonate precipitation (MICP) horizontal seepage reducing body (HSRB) was proposed to control drawdown combined with a partially penetrating curtain. MICP HSRB is formed by using the seepage field generated by the recharge wells to drive the migration of a Sporosarcina pasteurii solution, stationary solution, and cementation solution into the deep confined aquifer. The migration of each solution was numerically simulated to study the HSRB formation process. The influence of different factors on solute migration was studied. The results show that the solutes in the fixed fluid and cementation fluid can reach the area under the driving of the seepage field, which proves that MICP HSRB can be formed. The calcium ions and urea in the cementation solution are more likely to migrate to the designated area than the bacterial solution. Increasing the injection rate of bacterial solution and adding recharge wells both made the bacterial solution migrate more quickly to the designated area. In the case of multiple grouting, the solute migration in the later stage will be hindered by the plugging of pores caused by calcium carbonate generated in the earlier stage. Therefore, different grouting methods need to be designed to drive the seepage field so that the solute injected in the later stage can continue to migrate. The MICP HSRB grouting technology can be used in foundation pit dewatering, providing reference for similar engineering.
Adaptive Local Context and Syntactic Feature Modeling for Aspect-Based Sentiment Analysis
Authors: Huang Jie , Cui Yunpeng , Wang Shuo
Published: January 2023

Aspect-based sentiment analysis is a fine-grained sentiment analysis task that consists of two types of subtasks: aspect term extraction and aspect sentiment classification. In the aspect term extraction task, current methods suffer from the lack of fine-grained information in aspect term extraction and difficulty in identifying aspect term boundaries. In the aspect sentiment classification task, the current aspect sentiment classifier cannot adapt itself to the text and determine the local context. To address these two challenges, this work proposes an adaptive semantic relative distance approach based on dependent syntactic analysis, which uses adaptive semantic relative distance to determine the appropriate local context for each text and increase the accuracy of sentiment analysis. Meanwhile, the study also predicts the current word labels by combining local information features extracted by local convolutional neural networks and global information features to precisely locate the word labels. In two subtasks, our proposed model improves accuracy and F1 scores on the SemEval-2014 Task 4 Restaurant and Laptop datasets compared to the state-to-the-art approaches, especially in the aspect sentiment classification subtask.
Cleaning Schedule Optimization of Heat Exchanger Network Using Moving Window Decision-Making Algorithm
Authors: Dekebo Simegnsh Bekele , Oh Gi-Taek , Lee Min-Woo
Published: January 2023

A moving window decision-making algorithm is proposed for the cleaning schedule optimization of heat exchanger network system subject to fouling in refinery crude preheat train. This algorithm is designed by incorporating the moving window scheme into a conventional multi-period optimal control problem (OCP) framework and has a distinct feature that it can efficiently handle a complex problem where a long-time horizon is considered. When compared with the conventional multi-period OCP method using fixed time horizon, our algorithm always shows an excellent performance regarding the computational time, still finding a compatible optimal solution. In our moving window decision-making algorithm, it is important to determine the optimal moving window size for the given time horizon as it significantly influences the optimization performance.
A Study of the Factors Influencing the Thermal Radiation Received by Pedestrians from the Electric Vehicle Fire in Roadside Parking Based on PHRR
Authors: Zhang Dingli , Huang Guozhong , Li Haoxuan , Deng Qing , Gao Xuehong
Published: January 2023

Electric vehicle (EV) fire accidents are caused by multiple factors, including the traffic conditions, parking environment and firefighting facilities, and are a typical public safety issue in cities. Owing to the lack of accurate and quick estimation methods for the EV fire analysis in roadside parking scenarios and their impacts, this study applied the solid flame model to simplify the determination of the dynamic turbulence characteristics of the EV fire flames and proposed a thermal radiation model of an EV thermal runaway combustion flame based on the peak heat release rate. Subsequently, the radiation accuracy of the model near the flame was verified by a simulation and a comparison with the point source flame model, where the safety threshold of the fire accident propagation was determined. Finally, the evacuation strategy for pedestrians in an EV fire was investigated based on the proposed model. From the results, the safe distance of adjacent vehicles and the cumulative value of the pedestrians affected by the thermal radiation of EV fires can be obtained under the influence of the environmental factors. The proposed model can be used to optimize the design of roadside parking lots and guide the formulation of pedestrian emergency plans during an EV fire.
A Review of the Relationship between Gut Microbiome and Obesity
Authors: Zsálig Dorottya , Berta Anikó , Tóth Vivien , Szabó Zoltán , Simon Klára , Figler Mária , Pusztafalvi Henriette , Polyák Éva
Published: January 2023

Obesity is a rapidly growing problem of public health on a worldwide scale, responsible for more than 60% of deaths associated with high body mass index. Recent studies underpinned the augmenting importance of the gut microbiota in obesity. Gut microbiota alterations affect the energy balance of the host organism; namely, as a factor affecting energy production from the diet and as a factor affecting host genes regulating energy expenditure and storage. Gut microbiota composition is characterised by constant variability, and is affected by several dietary factors, suggesting the probability that manipulation of the gut microbiota may promote leaning or prevent obesity. Our narrative review summarizes the results of recent years that stress the effect of gut microbiota in the development of obesity. It investigates the factors (diet, dietary components, lifestyle, and environment) that might affect the gut microbiota composition. Possible strategies for the prevention and/or treatment of obesity include restoring or modifying the composition of the microbiota by consuming prebiotics and probiotics, fermented foods, fruits, vegetables, and avoiding foods of animal origin high in saturated fat and sugar.
Prospective Scenarios for Addressing the Agricultural Plastic Waste Issue: Results of a Territorial Analysis
Authors: Hachem Ali , Vox Giuliano , Convertino Fabiana
Published: January 2023

Agricultural activities have been positively affected by the use of plastic products, but this has resulted in the production of plastic waste and led to an increase in environmental pollution. To continue benefiting from the use of plastics but addressing at the same time the environmental issue, two strategies seem viable: the development of technologies for extending plastics lifespan and the gradual replacement of traditional non-biodegradable materials by biodegradable ones, at least for some products. This study focuses on a territorial analysis, performed using a Geographic Information System (GIS) in an agricultural area of the Apulia region (southern Italy). Areas of agricultural plastic waste production were identified through land-use maps. The application of plastic waste indices to different crop types and plastic products allowed quantifying and georeferencing actual plastic waste production. From this actual visualization, the other strategies were obtained by properly managing the indices. Two improved scenarios were obtained, the first consisted of extending the lifespan of some plastics, and the second entailed the introduction of some biodegradable alternatives. About 11,103 tons of agricultural plastic waste are yearly produced in the area and 7450 tons come from covering films. Lifespan extension would reduce the annual waste amount by about 25%, while more alternative products are needed to achieve significant results in the second scenario.
Experimental Investigation of the Vibration Reduction of the Pipeline System with a Particle Impact Damper under Random Excitation
Authors: Wang Jiao , Juan Mingxin , Yang Shuguo , Zhang Decong , Zhang Zhongyi , Jin Jie , Yu Tao
Published: January 2023

In the engineering field, severe vibration of the pipeline system occurs under random excitation, which leads to vibration failure of the pipeline system due to overload. The traditional method is to increase the rigidity of the pipeline system, and to avoid low-frequency resonance by using clamps or damping materials. However, due to structural limitations, it is difficult to apply clamps and damping materials. Particle damping technology has been applied in many fields, and the vibrational energy in the broadband frequency domain could be dissipated based on nonlinear particle collision damping. In this paper, a particle impact damper is designed for vibration reduction of the pipeline system. The damping capability is identified to investigate the effects of particle material, filling rate, particle size, damper structure, and boundary conditions. The results indicate that the ideal damping performance can be obtained by properly selecting particle parameters. Based on applying particle damping on the pipeline system, the proposed particle impact damper showed excellent damping capability under random excitation.
Analyzing the Enablers of Customer Engagement in Healthcare Using TISM and Fuzzy MICMAC
Authors: Chauhan Trishala , Sindhu Shilpa , Mor Rahul S.
Published: January 2023

The spike in internet users led healthcare companies to confer their agile presence on various digital platforms and engage customers online to increase their viability amid the rising competition. Online customer engagement takes place through branded content, i.e., the content provided by the brand or the company. Healthcare companies can leverage customer engagement by focusing on various crucial enablers. Therefore, this study explores the enablers of customer engagement for branded content in healthcare and devises a model depicting interrelationships among them. The enablers were ascertained using the literature review and validated by experts. Further, the interrelationship among the enablers was analyzed using TISM (Total Interpretive Structural Modeling) approach, and Fuzzy MICMAC (Cross-impact matrix multiplication) classified the enablers into different clusters. Results exhibited that informativeness is the most significant enabler, deriving other enablers. In contrast, shareability and co-creation of content are the most dependent and strategic enablers in the model hierarchy. The outcomes of this research will aid healthcare companies in knowing and prioritizing the enabler’s contribution in engaging customers towards branded content.
Characteristics and Variations of Raindrop Size Distribution in Chengdu of the Western Sichuan Basin, China
Authors: Zhang Tao , Wei Wei , Zheng Liying , Chen Yangruixue
Published: January 2023

Knowledge of the microphysical characteristics of precipitation plays a significant role in meteorology, hydrology, and natural hazards management, especially in the western Sichuan Basin (WSB), which is located east of the Tibetan Plateau (TP) in southwestern China and thus has unique terrain conditions and weather systems. Nonetheless, the literature regarding raindrop size distribution (RSD) in the WSB is still very limited. This work investigates RSD characteristics and temporal variations in a site (Chengdu, CD) of the WSB by employing three years of quality-controlled RSD observation collected from a second-generation PARSIVEL disdrometer. The results show that RSD has noticeable seasonal and diurnal variations in CD. Specifically, the broadest mean raindrop spectra can be found in summer and the narrowest in winter, and the raindrop spectra of a day can be the narrowest during 1400–1500 BJT (Beijing Standard Time, UTC+8). In addition, the mass-weighted mean diameter (Dm) is lower in the daytime than in the nighttime, while the logarithm of the generalized intercept parameter (log10Nw, the unit of the Nw is m−3 mm−1) has a larger value in the daytime than in the nighttime. In addition, intercomparisons indicate that the mean Dm of convective rains in CD is smaller than in South China and it is higher than in the eastern slope of TP, East China, and North China; on the other hand, the corresponding mean log10Nw is close to the value at the middle TP. Local empirical relations of shape–slope parameters (μ–Λ) and reflectivity–rain rate (Z–R) are also presented to provide references for optimizing the RSD parameterization scheme and radar precipitation estimation in the local area.
April 2022 Floods over East Coast South Africa: Interactions between a Mesoscale Convective System and a Coastal Meso-Low
Authors: Thoithi Wanjiru , Blamey Ross C. , Reason Chris J. C.
Published: January 2023

Extreme rainfall occurred over the South African east coast during 10–12 April 2022, leading to over 500 deaths and massive damage. This study seeks to understand a key feature, namely the progression of the rainfall maxima from the northern KwaZulu-Natal (KZN) coast during the night of 10–11 April by ~550 km to the Eastern Cape coast about 48 h later. The large-scale circulation was dominated by a cut-off low over the South African interior with a strong ridging anticyclone southeast of the country in the South Indian Ocean. Satellite, rain gauge, and ERA5 reanalysis are used to show that the timing and location of the heaviest rainfall are closely tied to, firstly, the formation of a Mesoscale Convective System (MCS) at ~0300UTC April 11 on the northern KZN coast which tracked south and then offshore, and secondly, a meso-trough which formed a coastal meso-low by ~2100 UTC April 11. The meso-low tracked south over the warm waters of the Agulhas Current before strengthening into Subtropical Depression Issa. Mesoscale interaction between the MCS and coastal meso-low determined the positioning and timing of the strongest onshore low-level jet, moisture convergence and uplift, and hence the progression of the heavy rainfall down the coast. Such mesoscale interaction has not previously been documented in southern Africa or the Southern Hemisphere.
Assessing the Impact of Long-Term ENSO, SST, and IOD Dynamics on Extreme Hydrological Events (EHEs) in the Kelani River Basin (KRB), Sri Lanka
Authors: Wijeratne Vithana P. I. S. , Li Gang , Mehmood Muhammad Sajid , Abbas Adnan
Published: January 2023

Hydrological extremes are common throughout the world and can be considered a globally significant phenomenon with severe environmental and social consequences. In recent decades, especially in the second half of the 20th century, Extreme Hydrological Events (EHEs) have attracted extensive attention. Physiological and anthropogenic factors have increased the frequency and severity of hydrological extremes worldwide in the last few decades. Recently, it has become a significant environmental issue in Sri Lanka. Both floods and droughts are widespread throughout the country, and the influence of floods is becoming more common every year. Currently, the frequency and severity of EHEs in the Kelani River Basin (KRB), Sri Lanka, are very common and have increased due to climate variations. Therefore, this study focused mainly on evaluating the EHEs and the impact of long-term El Niño Southern Oscillation (ENSO), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) dynamics on extreme events. Rainfall Anomaly Index (RAI) and Extreme Precipitation Indices (EPIs) were calculated to examine the EHEs and their spatial variability. In addition, the relationships between EHEs and ENSO were investigated using several climate indices based on SST anomalies. Both observed and satellite-derived daily precipitation from 1951 to 2019 were used to assess the EHEs in the KRB. The trend of EHEs and the change points were evaluated using the Pettitt test, and teleconnection with global indices was examined using the correlation coefficient in the R application. The result of the study revealed that the pattern of EHEs varied spatially from 1951 to 2019. The strong La Niña years showed a high degree of teleconnection with EHEs in April (r = 0.622 at 0.05 significance level) and August (r = −0.732 at 0.05 significance level). NINO3.4 and the Southern Oscillation Index (SOI) have shown a significant positive impact on EHEs in the Northeast Monsoon (NEM) period. This research on KRB will be a popular scientific measure that can provide scientific results and solutions for the comprehensive decision-making process in the future. Investigating the global physical changes that influence EHEs is critical to taking the necessary steps to reduce the severity of hydrological extremes in Sri Lanka.
Extreme Value Analysis and Modelling of Wet Snow Accretion on Overhead Lines in Hungary
Authors: Somfalvi-Tóth Katalin , Simon André
Published: January 2023

Wet snow events in Hungary can occasionally cause damage to overhead power lines and serious power supply failures. Return period calculation of such high snow mass events was determined upon a 50-year long data series available at 12 meteorological stations. Wet snow masses were estimated with a model of cylindrical accretion around wire of 3.1 cm diameter. Trends in the return periods and ice classes (according to the ISO 12494 standard) were assessed from division of the dataset into two periods (1965–1990 and 1991–2016). Ice classes in the range of R2 to R5 (mass of 0.7–6.1 kg m−1) were identified. The wet snow risk decreased in southern or central Hungary, while an increase was found in the western part of Hungary. Ice classes R6–R8 (up to 40 kg m−1) could occur in mountain areas of Hungary as indicated by numerical simulations in case studies. However, their return period is unknown due to the lack of long observation series.
Strategy for the Prediction of Typhoon Wind and Storm Surge Height Using the Parametric Typhoon Model: Case Study for Hinnamnor in 2022
Authors: Son Jun-Hyeok , Kim Hojin , Heo Ki-Young , Kwon Jae-Il , Jeong Sang-Hun , Choi Jin-Yong , Chun Je-Yun , Kwon Yeong-Yeon , Choi Jung-Woon
Published: January 2023

The parametric typhoon model is a powerful typhoon prediction and reproduction tool with advantages in accuracy, and computational speed. To simulate typhoons’ horizontal features, the longitude and latitude of the typhoon center, central pressure, radius of maximum wind speed (Rmax), and background states (such as surface air pressure and wind speed) are required. When a typhoon approaches or is predicted to affect Korea, the Korea Meteorological Agency (KMA) notifies the above-mentioned parameters, except for the Rmax and background state. The contribution of background wind and pressure is not very significant; however, Rmax is essential for calculating typhoon winds. Therefore, the optimized Rmax for the typhoons over the past five years was estimated at each time step compared with the in situ wind observation record. After that, a fifth-order polynomial fitting was performed between the estimated Rmax and the radius of strong wind (RSW; >15 m/s) provided by the KMA. Finally, the Rmax was calculated from the RSW via the empirical equation, and the horizontal fields of typhoon Hinnamnor (2211) were reproduced using a parametric model. Furthermore, the ocean storm surge height was adequately simulated in the surge model.
Study of the Possibility of Stimulating Cloud Convection by Solar Radiation Energy Absorbed in an Artificial Aerosol Layer
Authors: Abshaev Magomet T. , Abshaev Ali M. , Aksenov Andrey A. , Fisher Julia V. , Shchelyaev Alexander E. , Al Mandous Abdulla , Wehbe Youssef , El-Khazali Reyad
Published: January 2023

We consider the possibility of creating artificial clouds similar to Pyro clouds formed in nature over large forest and other fires. It is assumed that the creation of an artificial surface aerosol layer that absorbs solar radiation can lead to the heating of local air volumes and initiate thermal convection. The possibility of such convection was examined theoretically using the computational fluid dynamics software package suite FlowVision, in which the equations of motion, energy and mass transfer are solved in relative variables. Numerical experiments showed the principal possibility of initiating cloud convection only under some favorable atmospheric conditions (low wind speeds, temperature lapse rate greater than 8–9 °C/km), with an aerosol layer area of at least 5–10 km2 and a duration of its existence (heating) of at least 30 min. To assess the possibility of the practical implementation of this method, eight variants of highly efficient smoke compositions were developed and tested, and two batches of aerosol checkers weighing 25 kg, creating an aerosol of optimal size to absorb solar radiation, were produced. Calculations of the required dose based on the results of laboratory and field tests of the checkers showed that for one experiment to initiate cloud convection several thousand checkers need to be burned. The consumption of pyrotechnic aerosol composition (tens of tons) is about 1.5 times less than the burning of petroleum products in previously tested meteotrons. However, for environmental safety purposes, full-scale tests and the application of the aerosol layer method is advisable to conduct away from populated areas.
Gaseous and Particulate Pollution in the Wu-Chang-Shi Urban Agglomeration on the Northern Slope of Tianshan Mountains from 2017 to 2021
Authors: Chen Zhi , Li Zhongqin , Xu Liping , Zhou Xi , Zhang Xin , Wang Fanglong , Luo Yutian
Published: January 2023

Rapid social development has led to serious air pollution problems in cities, and air pollutants, including gaseous pollutants and particulate matter, have an important impact on climate, the environment, and human health. This study analyzed the characteristics, potential sources, and causes of air pollution in the Wu-Chang-Shi urban cluster. The results showed that NO2, CO, SO2, PM10, and PM2.5 had a tendency to decrease, while O3 showed an increasing trend. The concentrations of SO2, NO2, CO, PM2.5, and PM10 showed the highest values in winter and the lowest values in summer, with similar seasonal variations. However, the concentration of O3 was highest in the summer and lowest in the winter. Compared with the pollutant concentrations in other Chinese cities, PM2.5, PM10, and NO2 are more polluted in the Wu-Chang-Shi urban. Meteorological factors have a greater impact on pollutant concentrations, with higher concentrations of major pollutants observed when wind speeds are low and specific wind directions are observed, and higher secondary pollutant O3 concentrations observed when wind speeds are low and specific wind directions are observed. The backward trajectory and concentration weighting analysis show that the particulate pollutants in the Wu-Chang-Shi urban in winter mainly come from Central Asia and surrounding cities. O3 showed an increasing trend before and after the novel coronavirus outbreak, which may be related to changes in NOX, volatile organic compounds, and solar radiation intensity, and the concentrations of SO2, NO2, CO, PM10, and PM2.5 showed an overall decreasing trend after the outbreak and was smaller than before the outbreak, which is related to the reduction of industrial and anthropogenic source emissions during the outbreak.
Analysis of the PM2.5–O3 Pollution Characteristics and Its Potential Sources in Major Cities in the Central Plains Urban Agglomeration from 2014 to 2020
Authors: Quan Shu , Liu Miaohan , Chen Boxuan , Huang Yuehua , Wang Meijuan , Ma Qingxia , Han Yan
Published: January 2023

To highlight the characteristics of PM2.5–O3 pollution in the Central Plains Urban Agglomeration, spatial and temporal characteristics, key meteorological factors, and source pollution data for the area were analyzed. These data from the period 2014–2020 were obtained from state-controlled environmental monitoring stations in seven major cities of the agglomeration. The results revealed the following: (1) Spatially, the PM2.5–O3 pollution days were aggregated in the central area of Xinxiang and decreased toward the north and south. Temporally, during the 2014–2020 period, 50 days of PM2.5–O3 pollution were observed in the major cities of the Central Plains Urban Agglomeration, with an overall decreasing trend. (2) A low-temperature, high-pressure environment appeared unfavorable for the occurrence of PM2.5–O3 pollution days. Wind speeds of 2.14–2.19 m/s and a southerly direction increased the incidence of PM2.5–O3 pollution days. (3) The external transport range in summer was smaller and mainly originated from within Henan Province. These results can provide important reference information for achieving a synergistic control of PM2.5–O3 pollution, determining the meteorological causes, as well as the potential sources, of PM2.5–O3 pollution in polluted areas and promoting air pollution control.
Evaporation Affects the In Vitro Deposition of Nebulized Droplet in an Idealized Mouth-Throat Model
Authors: Xia Xueying , Ding Ting , Chen Xiaole , Tao Feng , Sun Baobin , Lu Tong , Wang Jianwei , Huang Yu , Xu Yin
Published: January 2023

Nebulizer is one of inhalation therapy’s most widely used aerosol generation devices. Nowadays, the vibrating mesh nebulizer has become popular owing to its compactness and noiselessness. In this study, an experimental system is proposed to measure the deposition fraction (DF) of nebulized sodium chloride (NaCl) droplets in an idealized mouth-throat airway model. The results show that before the DF increases to 58.6% with an increasing flow rate to 60 L/min, there is a decrease in DF from 42.4% to 15.5% when the inhalation flow rate increases from 15 to 22.5 L/min for a normal saline solution. These results substantially differ from the conclusions of dry powder or particle experiments and simulations, which monotonously increases with increasing inhalation flow rate. This suggests that droplet evaporation during aerosol generation and transport in the airway plays an important role. The experiment also showed that droplets generated from solutions with a higher NaCl concentration have higher DFs.