bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Ionizing Radiation Measurements for Trajectography Radars
Authors: Barbosa Filho J. Marcos Leal , Campos Millena M. de M. , Flor Daniel L. , Alves William S. , D’Assunção Adaildo G. , Rodrigues Marcio E. C. , de Sousa Vicente A.
Published: September 2022

This work presents a Non-Ionizing Radiation (NIR) measurement campaign and proposes a specific measurement method for trajectography radars. This kind of radar has a high gain narrow beam antenna and emits a high power signal. Power density measurements from a C-band trajectography radar are carried out using bench equipment and a directional receiving antenna, instead of the commonly used isotropic probe. The measured power density levels are assessed for compliance test via comparison with the occupational and general public exposure limit levels of both the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Brazilian National Telecommunication Agency (Anatel). The limit for the occupational public is respected everywhere, evidencing the safe operation of the studied radar. However, the limit for the general public is exceeded at a point next to the radar’s antenna, showing that preventive measures are needed.
Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array
Authors: Ou Fang , van Klinken Anne , Ševo Petar , Petruzzella Maurangelo , Li Chenhui , van Elst Don M. J. , Hakkel Kaylee D. , Pagliano Francesco , van Veldhoven Rene P. J. , Fiore Andrea
Published: September 2022

For decades, near-infrared (NIR) spectroscopy has been a valuable tool for material analysis in a variety of applications, ranging from industrial process monitoring to quality assessment. Traditional spectrometers are typically bulky, fragile and expensive, which makes them unsuitable for portable and in-field use. Thus, there is a growing interest for miniaturized, robust and low-cost NIR sensors. In this study, we demonstrate a handheld NIR spectral sensor module, based on a fully-integrated multipixel detector array, sensitive in the 850–1700 nm wavelength range. Differently from a spectrometer, the spectral sensor measures a limited number of NIR spectral bands. The capabilities of the spectral sensor module were evaluated alongside a commercially available portable spectrometer for two application cases: to quantify the moisture content in rice grains and to classify plastic types. Both devices achieved the two sensing tasks with comparable performance. Moisture quantification was achieved with a root mean square error (RMSE) prediction of 1.4% and 1.1% by the spectral sensor and spectrometer, respectively. Classification of the plastic type was achieved with a prediction accuracy on unknown samples of 100% and 96.4% by the spectral sensor and spectrometer, respectively. The results from this study are promising and demonstrate the potential for the compact NIR modules to be used in a variety of NIR sensing applications.
Machine Learning Methods in Predicting Patients with Suspected Myocardial Infarction Based on Short-Time HRV Data
Authors: Chumachenko Dmytro , Butkevych Mykola , Lode Daniel , Frohme Marcus , Schmailzl Kurt J. G. , Nechyporenko Alina
Published: September 2022

Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world’s population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and introduction of personalized medicine in healthcare institutions, including at the individual level when designing smart houses. Therefore, this study aims to analyze short 10-s electrocardiogram measurements taken from 12 leads. In addition, the task is to classify patients with suspected myocardial infarction using machine learning methods. We have developed four models based on the k-nearest neighbor classifier, radial basis function, decision tree, and random forest to do this. An analysis of time parameters showed that the most significant parameters for diagnosing myocardial infraction are SDNN, BPM, and IBI. An experimental investigation was conducted on the data of the open PTB-XL dataset for patients with suspected myocardial infarction. The results showed that, according to the parameters of the short ECG, it is possible to classify patients with a suspected myocardial infraction as sick and healthy with high accuracy. The optimized Random Forest model showed the best performance with an accuracy of 99.63%, and a root mean absolute error is less than 0.004. The proposed novel approach can be used for patients who do not have other indicators of heart attacks.
A Review of Exoskeletons Considering Nurses
Authors: Rayssiguie Esther , Erden Mustafa Suphi
Published: September 2022

Daily tasks of nurses include manual handling to assist patients. Repetitive manual handling leads to high risk of injuries due to the loads on nurses’ bodies. Nurses, in hospitals and care homes, can benefit from the advances in exoskeleton technology assisting their manual handling tasks. There are already exoskeletons both in the market and in the research area made to assist physical workers to handle heavy loads. However, those exoskeletons are mostly designed for men, as most physical workers are men, whereas most nurses are women. In the case of nurses, they handle patients, a more delicate task than handling objects, and any such device used by nurses should easily be disinfected. In this study, the needs of nurses are examined, and a review of the state-of-the-art exoskeletons is conducted from the perspective of to what extent the existing technologies address the needs of nurses. Possible solutions and technologies and particularly the needs that have not been addressed by the existing technologies are discussed.
Application of Adaptive Filtering Based on Variational Mode Decomposition for High-Temperature Electromagnetic Acoustic Transducer Denoising
Authors: Zhao Shuaijie , Zhou Jinjie , Liu Yao , Zhang Jitang , Cui Jie
Published: September 2022

In high-temperature environments, the signal-to-noise ratio (SNR) of the signal measured by electromagnetic acoustic transducers (EMAT) is low, and the signal characteristics are difficult to extract, which greatly affects their application in practical industry. Aiming at this problem, this paper proposes the least mean square adaptive filtering interpolation denoising method based on variational modal decomposition (AFIV). Firstly, the high-temperature EMAT signal was decomposed by variational modal decomposition (VMD). Then the high-frequency and low-frequency noises in the signal were filtered according to the excitation center frequency. Following the wavelet threshold denoising (WTD) for the noise component after VMD decomposition was carried out. Afterward, the noise component and signal component were connected by an adaptive filtering process to achieve further noise reduction. Finally, cubic spline interpolation was used to smooth the noise reduction curve and obtain the time information. To verify the effectiveness of the proposed method, it was applied to two kinds of ultrasonic signals from 25 to 700 °C. Compared with VMD, WTD, and empirical mode decomposition denoising, the SNR was increased by 2 times. The results show that this method can better extract the effective information of echo signals and realize the online thickness measurement at high temperature.
Processing Photoplethysmograms Recorded by Smartwatches to Improve the Quality of Derived Pulse Rate Variability
Authors: Polak Adam G. , Klich Bartłomiej , Saganowski Stanisław , Prucnal Monika A. , Kazienko Przemysław
Published: September 2022

Cardiac monitoring based on wearable photoplethysmography (PPG) is widespread because of its usability and low cost. Unfortunately, PPG is negatively affected by various types of disruptions, which could introduce errors to the algorithm that extracts pulse rate variability (PRV). This study aims to identify the nature of such artifacts caused by various types of factors under the conditions of precisely planned experiments. We also propose methods for their reduction based solely on the PPG signal while preserving the frequency content of PRV. The accuracy of PRV derived from PPG was compared to heart rate variability (HRV) derived from the accompanying ECG. The results indicate that filtering PPG signals using the discrete wavelet transform and its inverse (DWT/IDWT) is suitable for removing slow components and high-frequency noise. Moreover, the main benefit of amplitude demodulation is better preparation of the PPG to determine the duration of pulse cycles and reduce the impact of some other artifacts. Post-processing applied to HRV and PRV indicates that the correction of outliers based on local statistical measures of signals and the autoregressive (AR) model is only important when the PPG is of low quality and has no effect under good signal quality. The main conclusion is that the DWT/IDWT, followed by amplitude demodulation, enables the proper preparation of the PPG signal for the subsequent use of PRV extraction algorithms, particularly at rest. However, post-processing in the proposed form should be applied more in the situations of observed strong artifacts than in motionless laboratory experiments.
Spectral-Free Double Light Detection of DNA Based on a Porous Silicon Bragg Mirror
Authors: Zhang Shuangshuang , Sun Miao , Wang Xinli , Wang Jiajia , Jia Zhenhong , Lv Xiaoyi , Huang Xiaohui
Published: September 2022

To improve the detection sensitivity of a porous silicon optical biosensor in the real-time detection of biomolecules, a non-spectral porous silicon optical biosensor technology, based on dual-signal light detection, is proposed. Double-light detection is a combination of refractive index change detection and fluorescence change detection. It uses quantum dots to label probe molecules to detect target molecules. In the double-signal-light detection method, the first detection-signal light is the detection light that is reflected from the surface of the porous silicon Bragg mirror. The wavelength of the detection light is the same as the wavelength of the photonic band gap edge of the porous silicon Bragg mirror. CdSe/ZnS quantum dots are used to label the probe DNA and hybridize it with the target DNA molecules in the pores of porous silicon to improve its effective refractive index and enhance the detection-reflection light. The second detection-signal light is fluorescence, which is generated by the quantum dots in the reactant that are excited by light of a certain wavelength. The Bragg mirror structure further enhances the fluorescence signal. A digital microscope is used to simultaneously receive the digital image of two kinds of signal light superimposed on the surface of porous silicon, and the corresponding algorithm is used to calculate the change in the average grey value before and after the hybridization reaction to calculate the concentration of the DNA molecules. The detection limit of the DNA molecules was 0.42 pM. This method can not only detect target DNA by hybridization, but also detect antigen by immune reaction or parallel biochip detection for a porous silicon biosensor.
An Image Fusion Method of SAR and Multispectral Images Based on Non-Subsampled Shearlet Transform and Activity Measure
Authors: Huang Dengshan , Tang Yulin , Wang Qisheng
Published: September 2022

Synthetic aperture radar (SAR) is an important remote sensing sensor whose application is becoming more and more extensive. Compared with traditional optical sensors, it is not easy to be disturbed by the external environment and has a strong penetration. Limited by its working principles, SAR images are not easily interpreted, and fusing SAR images with optical multispectral images is a good solution to improve the interpretability of SAR images. This paper presents a novel image fusion method based on non-subsampled shearlet transform and activity measure to fuse SAR images with multispectral images, whose aim is to improve the interpretation ability of SAR images easily obtained at any time, rather than producing a fused image containing more information, which is the pursuit of previous fusion methods. Three different sensors, together with different working frequencies, polarization modes and spatial resolution SAR datasets, are used to evaluate the proposed method. Both visual evaluation and statistical analysis are performed, the results show that satisfactory fusion results are achieved through the proposed method and the interpretation ability of SAR images is effectively improved compared with the previous methods.
Improvement of Baro Sensors Matrix for Altitude Estimation
Authors: Nagi Łukasz , Zygarlicki Jarosław , Hunek Wojciech P. , Majewski Paweł , Młotek Paweł , Warmuzek Piotr , Witkowski Piotr , Zmarzły Dariusz
Published: September 2022

The article presents the use of barometric sensors to precisely determine the altitude of a flying object. The sensors are arranged in a hexahedral spatial arrangement with appropriately spaced air inlets. Thanks to the solution used, the range of measurement uncertainty can be reduced, resulting in a lower probability of error during measurement by improving the accuracy of estimation. The paper also describes the use of pressure sensors in complex Tracking Vertical Velocity and Height systems, integrating different types of sensors to highlight the importance of this single parameter. The solution can find application in computational systems using different types of data in Kalman filters. The impact of pressure measurements in a geometric system with different spatial orientations of sensors is also presented. In order to compensate for local pressure differences, e.g., in the form of side wind gusts, an additional reference sensor was used, making the developed solution relevant for applications such as industrial ones.
Importance of Meteorological Parameters and Airborne Conidia to Predict Risk of Alternaria on a Potato Crop Ambient Using Machine Learning Algorithms
Authors: Meno Laura , Escuredo Olga , Abuley Isaac Kwesi , Seijo María Carmen
Published: September 2022

Secondary infections of early blight during potato crop season are conditioned by aerial inoculum. However, although aerobiological studies have focused on understanding the key factors that influence the spore concentration in the air, less work has been carried out to predict when critical concentrations of conidia occur. Therefore, the goals of this study were to understand the key weather variables that affect the hourly and daily conidia dispersal of Alternaria solani and A. alternata in a potato field, and to use these weather factors in different machine learning (ML) algorithms to predict the daily conidia levels. This study showed that conidia per hour in a day is influenced by the weather conditions that characterize the hour, but not the hour of the day. Specifically, the relative humidity and solar radiation were the most relevant weather parameters influencing the conidia concentration in the air and both in a linear model explained 98% of the variation of this concentration per hour. Moreover, the dew point temperature three days before was the weather variable with the strongest effect on conidia per day. An improved prediction of Alternaria conidia level was achieved via ML algorithms when the conidia of previous days is considered in the analysis. Among the ML algorithms applied, the CART model with an accuracy of 86% were the best to predict daily conidia level.
Parameter Sensitivity Analysis of Mounting Pedestals and Multi-Objective Optimization for a Multi-Support Rigid Body System
Authors: Zhu Qingyu , Han Qingkai , Yang Xiaodong , Lin Junzhe
Published: September 2022

In this paper, a parameter sensitivity analysis of mounting pedestals and a multi-objective optimization design for vibration reduction in a multi-support rigid body system, taking an aeroengine-lubricating oil tank supported by multiple mounting pedestals as an example, are conducted based on the third version of non-dominated sorting genetic algorithm (NSGA-Ⅲ) combined with Sobol’s sensitivity analysis method (SSAM). An aeroengine-lubricating oil tank with three mounting pedestals is simplified as a three-support dynamic system, and its dynamics model is established. Several structural parameters of mounting pedestals are taken as the design variables, and the system vibration response and the reaction force of the front and rear mounting pedestals are considered as the objective functions. The first-order results and total sensitivity index of different design parameters for each objective function are obtained via SSAM, and the five most sensitive parameters are selected. Based on the above five design parameters, multi-objective optimization designing for vibration reduction in a simplified lubricating oil tank system is conducted based on NSGA-Ⅲ, and the results of the above triple-objective optimization are obtained as a Pareto-front surface with an obvious frontier. It can be observed from the simulation results that the oil tank vibration of the optimized system is effectively suppressed under the unbalanced excitation of two typical engine speeds. The established method and the main results can provide guidance for designers of aeroengine external structural systems, which can help to achieve superior system dynamic performances in engineering applications.
Evaluation of 5-[(Z)-(4-nitrobenzylidene)]-2-(thiazol-2-ylimino)-4-thiazolidinone (Les-6222) as Potential Anticonvulsant Agent
Authors: Mishchenko Mariia , Shtrygol’ Sergiy , Lozynskyi Andrii , Hoidyk Mykhailo , Khyluk Dmytro , Gorbach Tatyana , Lesyk Roman
Published: September 2022

It was determined that the studied 5-[(Z)-(4-nitrobenzylidene)]-2-(thiazol-2-ylimino)-4-thiazolidinone (Les-6222) affects the cyclooxygenase pathway of the arachidonic acid cascade, the markers of damage to neurons on models of PTZ kindling. In the model of chronic epileptogenesis in mice (pentylenetetrazole kindling), a 4-thiazolidinone derivative showed high anticonvulsant activity, which is weaker than the effect of sodium valproate and higher than Celecoxib. The mentioned compound has a pronounced anti-inflammatory effect in the brain on the background of the PTZ kindling, reliably inhibiting COX-1 and COX-2. The predominant inhibition of COX-2 by 44.5% indicates this enzyme’s high selectivity of Les-6222. According to the molecular docking study results, the studied compound revealed the properties of COX-1/COX-2 inhibitor and especially 5-LOX/FLAP. The decreasing content of 8-isoprostane in the brain of mice of the Les-6222 group indicates a beneficial effect on cell membranes in the background of oxidative stress during the long-term administration of PTZ. In addition, Les-6222 significantly decreased the content of neuron-specific enolase, indicating neuroprotective properties in the background of chronic epileptogenesis. The obtained results experimentally substantiate the feasibility of further developing Les-6222 as a promising anticonvulsant agent.
Rail Sample Laboratory Evaluation of Eddy Current Rail Inspection Sustainable System
Authors: Wang Jiaqing , Dai Qingli , Lautala Pasi , Yao Hui , Si Ruizhe
Published: September 2022

Increasing the efficiency, frequency, and speed of rail defect detection can reduce maintenance costs and improve the sustainability of railways. The non-contact eddy current (EC) system can be operated along with a railcar for detecting rail flaws. Even if the EC can be utilized for rail defect identification and characterization, current commercial devices are not sufficient for defect classification on rails by providing highly sensitive signals for post-processing. In this study, we established an efficient and expandable eddy current rail inspection system and verified its capability for classification of different defect signals. The integrated hardware and software EC measurement system was firstly applied to detect notched cracks in steel samples with different crack depths and angles. The measured voltage and current analog inputs from the eddy current sensor were acquired and processed with a fast Fourier transformation (FFT) algorithm in the LabVIEW platform. The real-time impedance was then obtained by transferring signals to a normalized impedance plane plot. The processed EC signals showed adequate sensitivity and efficiency with changes of notched crack depths and angles during the sensor movement. A comparative case study on field rail samples was then conducted to examine the feasibility and capability of the established system on different types of actual rail defects. The experimental analysis and case study results demonstrate that the integrated eddy current system could possibly be used for non-destructive rail crack inspection and classification. The enhanced detection capability (especially on subsurface cracks) and real-time post-processing technique could further contribute to improving rail-life sustainability.
So Close, Yet So Far Away: Exploring the Role of Psychological Distance from Climate Change on Corporate Sustainability
Authors: V. Boivin David , Boiral Olivier
Published: September 2022

Despite some improvements and increasing social pressures, most organizations seem to be stagnating in a superficial implementation of sustainability practices despite the accumulation of climate change consequences. Research on corporate sustainability has shown that external pressures and psychological factors influence managers’ environmental decisions. However, these psychological factors have been undertheorized in the management research field. The concept of psychological distance has shown promising results in studying environmental behaviors. This concept is rooted in the construal level theory and is defined as the subjective experience of feeling that something is close or far away from the self, the here and the now. Therefore, it represents a relevant path for exploration in research on corporate sustainability. The main goals of this integrative review are to explore how the concept of psychological distance has been employed in research on corporate sustainability and to explore related concepts from this research field. Additionally, concepts that are related to the four dimensions of psychological distance (i.e., temporal, spatial, social, and hypothetical) are critically discussed. The links between these concepts and their impacts on sustainability endeavors within organizations are then visually presented through a conceptual map, which forms the main contribution of this review. Further theoretical contributions are presented, the implications for managers are discussed, and future research avenues are proposed.
Effect of Bentonite as Partial Replacement of Cement on Residual Properties of Concrete Exposed to Elevated Temperatures
Authors: Farhan Mushtaq Sardar , Ali Ather , Khushnood Rao Arsalan , Tufail Rana Faisal , Majdi Ali , Nawaz Adnan , Durdyev Serdar , Burduhos Nergis Dumitru Doru , Ahmad Jawad
Published: September 2022

This study investigated the effect of elevated temperature on the mechanical, physical and durability properties of normal strength concrete, modified with bentonite. The bentonite concrete was cast by substituting cement with bentonite content in proportions of 5, 10 and 15% by weight. Mechanical tests were conducted (compressive and splitting tensile strength). Furthermore, durability performance (mass loss and sorptivity) and specimen properties (elastic modulus, stress–strain behaviour, ductility and energy absorption) were evaluated and discussed. The results demonstrated that samples incorporating bentonite showed better fire endurance than the control mix. The inclusion of bentonite in concrete decreased the mass loss of the specimens exposed to high temperatures. The performance of bentonite concrete was better in terms of mechanical behaviour (compressive and tensile strength) than that of conventional concrete, and it had high resistance to water absorption. Higher ductility and energy absorption capacity were observed for the concrete specimen containing bentonite than its counterpart control specimens.
The Tripartite Evolutionary Game of Green Agro-Product Supply in an Agricultural Industrialization Consortium
Authors: Liu Haolong
Published: September 2022

In recent years, China has actively promoted the green transformation and low-carbon development of agriculture. New-type agricultural business entities such as family farms, specialized cooperatives and agro-processing enterprises have become important vehicles of agricultural green transformation due to their comparative advantages in multiple aspects. Within the agricultural industrialization consortium, the motivation of new-type agricultural business entities to synergistically implement the agricultural green transformation strategy is affected by bounded rationality as well as multiple economic and social factors. Clarifying the mechanism of the above factors would be of benefit to promoting agricultural green transformation in developing countries. In this article, a tripartite evolutionary game model about the production and sale of green agro-products is constructed, and the influences of various factors on the evolutionary game process are analyzed, based on new institutional economics and new economic sociology. According to the simulation results, it is found that the proportional quality contributions of the agents, the intensification of consumers’ preference for green agro-products and the increase of social embedding cost are conducive to the system converging to the favorable evolutionary equilibrium at a faster rate. However, the increases of marginal costs, market risks and spillover effects would prevent the system from converging to the favorable evolutionary equilibrium. Accordingly, corresponding suggestions are put forward to support the effective supply of green agricultural products in the agricultural industrialization consortium.
Indigenous Nutrient Supplying Capacity of Young Alluvial Calcareous Soils Favours the Sustainable Productivity of Hybrid Rice and Maize Crops
Authors: Singh Shiveshwar Pratap , Dutta Sudarshan , Jha Shankar , Prasad Shiv Shankar , Chaudhary Sanjay Kumar , Manna Madhab Chandra , Majumdar Kaushik , Srivastava Prashant , Brahmanand Pothula Srinivasa , Singh Krishna Murari , Kumar Krishna
Published: September 2022

The crop productivity in calcareous soils is low due to their low organic matter content, high pH levels and improper nutrient management without considering the indigenous nutrient supplying capacity and crop yield potential; therefore, this study was conducted for a quantitative assessment of the nutrient supplying capacity of a calcareous soil on the productivity of hybrid and conventional rice and maize crops using an omission plot technique. The treatments included the ample application of Nitrogen (N), Phosphorus (P), Potassium (K), Sulphur (S) and Zinc (Zn), and an unfertilized check and omissions of N, P, K, S and Zn in rice and maize for six cropping seasons. The impact of the nutrient omission towards crop productivity was highest for nitrogen followed by phosphorous, potassium, zinc and sulphur. The total grain yield (3 yr average) in the hybrid rice–maize system was highest (16.32 t ha−1) for the optimum fertilized plot and lowest (6.34 t ha−1) for the unfertilized check. The sustainable yield index indicated that hybrid and conventional rice-maize cropping systems were more sustainable in the amply fertilized plot than in the nutrient-limited and unfertilized treatment plots. The average percent contributions of nitrogen, phosphorous, and potassium from the soil towards total nutrient removal were 36, 80 and 137 kg ha−1, in the hybrid system and 24, 54 and 104 kg ha−1 in the conventional system, respectively. The return on investment (ROI) of the N, P, K, S and Zn for the hybrid rice was 21.2, 7.1, 6.7, 4.1, and 0.3 USD, respectively, while for the maize it was 28.8, 7.6, 4.9, 6.5, and 0.7 USD, respectively. The results suggest that there is a direct link between the soil nutrient supplying capacity and the nutrient requirements by different types of crops in calcareous soil; therefore, the omission plot technique used for the assessment of the indigenous nutrient supplying capacity could be used in the larger domain for improved nutrient management, through synchronization with a targeted crop yield for improved productivity, soil fertility, nutrient use efficiency and farm income.
An Integrated Automatic Writing Evaluation and SVVR Approach to Improve Students’ EFL Writing Performance
Authors: Wang Youmei , Luo Xia , Liu Chen-Chen , Tu Yun-Fang , Wang Naini
Published: September 2022

Writing is a challenging task for English Foreign Language (EFL) instruction. Based on artificial intelligence technology, Automatic Writing Evaluation (AWE) has received considerable attention from the EFL research community in recent years, since it can provide timely and personalized feedback to EFL writing learners. However, researchers have pointed out that while AWE can provide satisfactory feedback on vocabulary use and grammar, it is relatively inadequate at providing efficient feedback on organization, coherence, and content. Spherical Video-based Virtual Reality (SVVR) can provide a highly immersive and in-depth interaction learning environment that makes up for this shortcoming. Authentic experiences help enhance EFL writing learners’ perceptions and understanding of context, and assist students in creating constructive internal connections between their personal experiences and the topic of their writing, thus improving their writing quality. Therefore, the current study proposed an approach which integrated SVVR and AWE to investigate its effects on EFL writing. To investigate the effectiveness of the proposed approach, a quasi-experiment was carried out in a university’s EFL writing course. The experimental group (37 students) used the SVVR–AWE approach, while the control group (39 students) used the conventional approach with AWE. The results showed that the learning method not only considerably enhanced the students’ EFL writing performance, but also raised their motivation, self-efficacy, and sense of presence, as well as reduced their EFL writing anxiety. Furthermore, interviews were performed and a thematic inductive qualitative analysis of the interview data was conducted to investigate the impact of this learning method on students’ learning behaviors and perceptions.
Impact of COVID-19 Risk Perception on Residents’ Behavioural Intention towards Forest Therapy Tourism
Authors: Gao Yanjing , Chen Lijun
Published: September 2022

Risk perception has an important influence on tourism decision-making behaviour. Based on the extended Theory of Planned Behaviour, we examine the effect of COVID-19 risk perception on tourists’ behavioural intentions towards forest therapy tourism. A questionnaire survey was conducted during the pandemic. Based on structural equation modelling (SEM), our evidence shows that cognitive risk perception positively and significantly influenced subjective norms, while affective risk perception positively and significantly influenced attitudes. Subjective norms mediated perceived risk perception and behavioural intentions, while attitudes mediated emotional risk perception and behavioural intentions. Gender partially moderated perceived behavioural control and behavioural intentions. Finally, this study proposes corresponding management countermeasures of great practical importance in promoting the development of forest recreation tourism.
Daily Groundwater Level Prediction and Uncertainty Using LSTM Coupled with PMI and Bootstrap Incorporating Teleconnection Patterns Information
Authors: Chu Haibo , Bian Jianmin , Lang Qi , Sun Xiaoqing , Wang Zhuoqi
Published: September 2022

Daily groundwater level is an indicator of groundwater resources. Accurate and reliable groundwater level (GWL) prediction is crucial for groundwater resources management and land subsidence risk assessment. In this study, a representative deep learning model, long short-term memory (LSTM), is adopted to predict groundwater level with the selected predictors by partial mutual information (PMI), and bootstrap is employed to generate different samples combination for training many LSTM models, and the predicted values by many LSTM models are used for the uncertainty assessment of groundwater level prediction. Two wells of different climate zones in the USA were used as a case study. Different significant predictors of GWL for two wells were identified by PMI from candidate predictors incorporating teleconnection patterns information. The results show that GWL is significantly affected by antecedent GWL, AO, Niño 3.4, Niño 1 + 2, and precipitation in humid areas, and by antecedent GWL, AO, Niño 3.4, Niño 3, Niño 1 + 2, and PNA in arid areas. Predictor selection can assist in improving the prediction performance of the LSTM model. The relationship between GWL and significant predictors were modeled by the LSTM model, and it achieved higher accuracy in humid areas, while the performance in arid areas was poorer due to limited precipitation information. The performance of LSTM was improved by increasing correlation coefficient (R2) values by 10% and 25% for 2 wells compared to generalized regression neural network (GRNN). Three uncertainty evaluation metrics indicate that LSTM reduced the uncertainty compared to GRNN model. LSTM coupling with PMI and bootstrap can be a promising approach for accurate and reliable groundwater level prediction for different climate zones.
Nexus of Transformational Leadership, Employee Adaptiveness, Knowledge Sharing, and Employee Creativity
Authors: Żywiołek Justyna , Tucmeanu Elena Roxana , Tucmeanu Alin Iulian , Isac Nicoleta , Yousaf Zahid
Published: September 2022

The survival of an organization in the contemporary competitive and dynamic global business environment is associated with its creative workforce. This study explores the impact of transformational leadership (TL) and employee adaptiveness on workforce creativity. The mediating role of employee adaptiveness and the moderating role of knowledge sharing has also been tested. A simple random sampling technique was used to collect data from the 561 employees working in three star and five star hotels. Statistical techniques such as correlation and hierarchical regressions were used for testing hypotheses. To test the mediation effect, we used the statistical procedure suggested by Preacher and Hayes. The results revealed that employee creativity is initiated through TL in hotels and TL positively affects employee adaptiveness. The results of the mediating analysis confirmed the mediating role of employee adaptiveness between TL and creativity link in the context of hotel industry operating in developing nations. Moreover, the findings also revealed that knowledge sharing plays key role for TL and employee adaptiveness links. In this study, quantitative research design was utilized, and the cross-sectional method was used for data collection. Future research designs can be based on both quantitative and current qualitative analyses. The current model can be enriched using factors such as knowledge management systems, organizational structures, and digital platforms in the future.
Kinetic Analysis of Thermal Decomposition Process of Emulsion Explosive Matrix in the Presence of Sulfide Ores
Authors: Yang Fuqiang , Guo Yong , Lai Yong , Hong Yidu , Yuan Shuaiqi
Published: September 2022

This study aims to characterize the whole reaction process of (i) emulsion explosive matrix and sulfide ores, and (ii) ammonium nitrate and pyrite by the thermodynamics analysis method. A series of experiments were carried out at atmospheric pressure from 25 °C to 350 °C at four heating rates (3, 5, 10, and 15 K/min) and the Coats–Redfern method was applied to calculate the apparent activation energy of samples at different heating rates. The results show that the thermogravimetric (TG) curve of sulfide ores and emulsion explosive matrix can be divided into four stages: the water evaporation stage, the dynamic balance stage, the thermal decomposition stage, and the extinguishment stage. However, the thermal decomposition process of ammonium nitrate and pyrite can be divided into the dynamic balance stage, the thermal decomposition stage, and the burnout stage. The ignition temperature (T0) and maximum peak temperature (Tm) of the samples increased with the heating rate, but the shape of the TG/DTG (Derivative Thermogravimetric) curve was not affected. The results show that the reaction process of sulfide ores and emulsion explosive matrix is similar to the reaction process of pyrite and ammonium nitrate. The thermal stability of emulsion explosive matrix decreases when sulfide ores are added. By contrast, when pyrite is added, the thermal stability of the ammonium nitrate decreases more significantly.
Capital or Technology? Which Is Better at Promoting the Value of AI Companies—Theoretical Analysis and Empirical Test
Authors: Luo Yuxi , Yu Liying
Published: September 2022

Capital and technology gradually replace land and labor factors to become the important production factors of enterprises, especially for artificial intelligence enterprises. How to use capital and technology factors to enhance enterprise value becomes an important topic when artificial intelligence enterprises are affected by internal and external factors. Using data from 55 AI concept companies, a multiple regression model was constructed to verify the mediating role of capital and technology, judge the dynamics of the two elements dialectically, and explore the paths that shape the value enhancement of AI companies. The study found that both degree of enterprise attention and government support positively affect firm value, and that the mediating role of both capital and technology is more pronounced. However, compared to the technology element, the capital element plays a leading role in the value enhancement mechanism of AI companies, with physical capital being the most effective, and strengthening the capital element is a more sensible path choice to increase the value of companies in the short term. However, in the long term, as the business cycle and the external environment change, the technology element is a driving force that cannot be underestimated.
Methodological System to Determine the Development Potential of Rural Tourism in Extremadura, Spain
Authors: Sánchez-Martín José-Manuel , Rengifo-Gallego Juan-Ignacio , Martín-Delgado Luz-María , Hernández Carretero Ana-María
Published: September 2022

There are methodologies that seek to know the tourism potential of the territory. However, their use has been very scarce and consequently, tourism plans lack a real vision of the possibility of developing tourism. In the case of Extremadura, Spain, a specific methodology has been proposed that considers types and subtypes of variables, both in terms of heritage and tourism facilities. In addition, these variables are ranked in five classes, and their importance is weighted according to the opinion of the demand. The results offer a global vision of the potential, coinciding with the area determined by official organizations in the country, but also facilitate the specific study of specific tourism sub-types. They also show that there is not always a clear relationship between the attractiveness of the environment and tourist facilities. It is concluded that it is important to bet on these evaluation methodologies to enhance the knowledge of any territory to determine its capacity to develop tourism. On the other hand, it helps tourism plans to be applied in the territory to consider the potential of each municipality to promote tourism.
Network Formation and Financial Inclusion in P2P Lending: A Computational Model
Authors: Katsamakas Evangelos , Sánchez-Cartas J. Manuel
Published: September 2022

What characteristics of fintech lending platforms improve access to funding and increase financial inclusion? We build a computational model of platform lending that is used to study the endogenous loan network formation process on the platform. Given the multidimensional nature of financial inclusion, we address what factors influence the number of loans, the level of investment/debt, and how those relate to the distribution of investment/debt across agents. We find that platform scale and SME reach are essential in determining the number of loans on the platform. However, the willingness to accept risks is the main driver behind the value of those loans. We also find that increased platform scale, high-risk thresholds, and low-interest rates lead to more evenly distributed investments. Moreover, we find that large platforms help increase diversity and lead to a more evenly distributed power among peers. We conclude that digital platforms increase financial inclusion, helping to foster investment and achieve a more egalitarian allocation of resources. These results can guide new theory development about the impact of P2P lending on inequality as well as help platforms to promote financial inclusion.
Effectiveness of Urban Climate Change Governance in Addis Ababa City, Ethiopia
Authors: Addis Tigezaw Lamesgin , Birhanu Belay Simane , Italemahu Tesfaye Zeleke
Published: September 2022

Addis Ababa is one of the eleven cities in Africa that have been taking bold action in meeting the objectives of the Paris Agreement. At the present time, the city is working toward reducing greenhouse gas emissions and enabling the city to be resilient to the impacts of climate change. To make the city carbon neutral and resilient to climate change, the coordination of different sectors and actors is crucial. To this end, the planning and implementation of mitigation and adaptation measures needs effective climate change governance. Thus, this study was intended to explore the effectiveness of climate change governance in Addis Ababa City, Ethiopia. The study followed both quantitative and qualitative research approaches and relied on both primary and secondary data sources. A survey of 232 respondents, who were environment experts at different levels, was conducted using questionnaires. In addition, interviews and observations were conducted to gather relevant data. Secondary data were collected from different sources. The quantitative data were analysed using relative importance index (RII) analysis. The study found that existing environmental policies, strategies, regulations, proclamations, laws, and implementations in the city were facing major challenges in terms of weak accountability, the poor enforcement of regulation, and the failure to involve key actors, especially NGOs, communities, and private sectors; these failures were characterized by weak institutional setup and a lack of formal systems allowing actors (private sectors, communities, and NGOs) to interact to respond to climate change. Hence, climate change governance was ineffective in terms of accountability, participation, law enforcement, equity, institutions, the role of actors, and partnership. Thus, the Addis Ababa City Environmental Protection and Green Development Commission should give more emphasis to the coordination of other actors (NGOs, communities, private sectors, and research institutions) to respond to climate change in the city. In addition, the commission should provide training to the lower layers of experts and mobilise the community for climate change response, particularly in the undertaking of adaptation measures. Furthermore, Addis Ababa City administrators should give due attention to climate change response through an established strong accountability system to enforce regulation, rules, proclamations, laws, policies, and strategies in different sectors.
Equus caballus Papillomavirus Type-9 (EcPV9): First Detection in Asymptomatic Italian Horses
Authors: De Paolis Livia , De Ciucis Chiara Grazia , Peletto Simone , Cappelli Katia , Mecocci Samanta , Nervo Tiziana , Guardone Lisa , Crescio Maria Ines , Pietrucci Daniele , Fruscione Floriana , Gabbianelli Federica , Turco Silvia , Varello Katia , Donato Gian Guido , Maurella Cristiana , Modesto Paola , Maniaci Maria Grazia , Chillemi Giovanni , Ghelardi Alessandro , Razzuoli Elisabetta
Published: September 2022

Papillomavirus (PV) infections may be related to anogenital lesions and cancer development in humans and several other animal species. To date, 11 different PVs have been reported in horses. Among them, a newly described PV named Equus caballus Papillomavirus Type9 (EcPV9) was thus far only reported in the semen of a stallion with penile lesions in Australia. This study reports for the first time the presence of EcPV9 in asymptomatic Italian horses. From July 2020 to January 2022, genital brush samples were collected from 209 horses with no apparent signs of neoplastic disease and no PV-associated lesions, clinically examined at the Didactic Veterinary University Hospital (OVUD) of Perugia and at the Veterinary University Hospital (OVU) of Turin. Brushes were submitted to real-time PCR targeting the EcPV9-L1 region. The first amplification targeted a region of ~116 bp, followed by the amplification and sequencing of ~533 bp of the positive samples. EcPV9-L1 DNA was found in eleven horses (5.3%), all female and mainly English Thoroughbred. Co-infection with EcPV2-L1 was found in 7 out of the 11 EcPV9-L1 positive horses (63.6%). This study contributes to the description of the prevalence of exposure or infection of EcPVs in the horse population in Italy, for which data are still limited. In this regard, here we provide a phylogenetic analysis and the completely reconstructed viral genomes of two Italian EcPV type 9 isolates, as well as four EcPV type 2 obtained from co-infected animals.
Frontiers in Shigella Vaccine Development
Authors: MacLennan Calman Alexander , Steele Andrew Duncan
Published: September 2022

In recent years, there has been a resurgence of interest in the development of vaccines against Shigella driven by the growing awareness of the impact of this pathogen on global health [...]
The Waxing, Waning, and Predictors of Humoral Responses to Vector-Based SARS-CoV-2 Vaccine in Hemodialysis Patients
Authors: Fu Chung-Ming , Tsai Kai-Fan , Kuo Wei-Hung , Wu Chien-Hsing , Yu Ching-I , You Huey-Ling , Lee Chien-Te
Published: September 2022

Hemodialysis (HD) patients are vulnerable to coronavirus disease 2019 (COVID-19) and have a high mortality rate. We evaluated the anti-SARS-CoV-2 spike protein antibody (ACOV2S) levels in 385 HD patients before and 4 and 8 weeks after the second dose of vector-based ChAdOx1 nCoV-19 vaccine. For study control, week 4 ACOV2S levels after the second vaccination dose were measured in 66 healthcare workers (HCWs). The seroconversion rate of HD patients was 98.96% 4 weeks after the second vaccination. Despite low antibody levels before the second dose (week 0), week 4 ACOV2S levels after the second vaccine dose in HD patients increased prominently and were compatible with those in HCWs (p = 0.814 for HCWs vs. HD patients). The ACOV2S levels in HD patients waned significantly 8 weeks after the second vaccination dose (p < 0.001 at week 8 vs. 4). Older age and immunosuppressant use were negative predictors, while higher C-reactive protein (CRP) levels were positive predictors of ACOV2S waxing after the second vaccine dose in HD patients. Higher CRP levels and platelet counts were independently associated with decreased ACOV2S waning. The ChAdOx1 nCoV-19 vaccine is effective and safe for primary vaccination in HD patients and a booster dose is necessary.