bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Sensor Context-Aware Based Chatbot Model: An Application of Humanoid Companion Robot
Authors: Kuo Ping-Huan , Lin Ssu-Ting , Hu Jun , Huang Chiou-Jye
Published: July 2021

In aspect of the natural language processing field, previous studies have generally analyzed sound signals and provided related responses. However, in various conversation scenarios, image information is still vital. Without the image information, misunderstanding may occur, and lead to wrong responses. In order to address this problem, this study proposes a recurrent neural network (RNNs) based multi-sensor context-aware chatbot technology. The proposed chatbot model incorporates image information with sound signals and gives appropriate responses to the user. In order to improve the performance of the proposed model, the long short-term memory (LSTM) structure is replaced by gated recurrent unit (GRU). Moreover, a VGG16 model is also chosen for a feature extractor for the image information. The experimental results demonstrate that the integrative technology of sound and image information, which are obtained by the image sensor and sound sensor in a companion robot, is helpful for the chatbot model proposed in this study. The feasibility of the proposed technology was also confirmed in the experiment.
A Micron-Sized Laser Photothermal Effect Evaluation System and Method
Authors: Xu Jingjing , Zeng Ming , Xu Xin , Liu Junhui , Huo Xinyu , Han Danhong , Wang Zhenhai , Tian Lan
Published: July 2021

The photothermal effects of lasers have played an important role in both medical laser applications and the development of cochlear implants with optical stimulation. However, there are few methods to evaluate the thermal effect of micron-sized laser spots interacting with other tissues. Here, we present a multi-wavelength micro-scale laser thermal effect measuring system that has high temporal, spatial and temperature resolutions, and can quantitatively realize evaluations in real time. In this system, with accurate 3D positioning and flexible pulsed laser parameter adjustments, groups of temperature changes are systematically measured when the micron-sized laser spots from six kinds of wavelengths individually irradiate the Pd/Cr thermocouple junction area, and reference data of laser spot thermal effects are obtained. This work develops a stable, reliable and universal tool for quantitatively exploring the thermal effect of micron-sized lasers, and provides basic reference data for research on light-stimulated neuron excitement in the future.
Affective Computing on Machine Learning-Based Emotion Recognition Using a Self-Made EEG Device
Authors: Mai Ngoc-Dau , Lee Boon-Giin , Chung Wan-Young
Published: July 2021

In this research, we develop an affective computing method based on machine learning for emotion recognition using a wireless protocol and a wearable electroencephalography (EEG) custom-designed device. The system collects EEG signals using an eight-electrode placement on the scalp; two of these electrodes were placed in the frontal lobe, and the other six electrodes were placed in the temporal lobe. We performed experiments on eight subjects while they watched emotive videos. Six entropy measures were employed for extracting suitable features from the EEG signals. Next, we evaluated our proposed models using three popular classifiers: a support vector machine (SVM), multi-layer perceptron (MLP), and one-dimensional convolutional neural network (1D-CNN) for emotion classification; both subject-dependent and subject-independent strategies were used. Our experiment results showed that the highest average accuracies achieved in the subject-dependent and subject-independent cases were 85.81% and 78.52%, respectively; these accuracies were achieved using a combination of the sample entropy measure and 1D-CNN. Moreover, our study investigates the T8 position (above the right ear) in the temporal lobe as the most critical channel among the proposed measurement positions for emotion classification through electrode selection. Our results prove the feasibility and efficiency of our proposed EEG-based affective computing method for emotion recognition in real-world applications.
Forces: A Motion Capture-Based Ergonomic Method for the Today’s World
Authors: Marín Javier , Marín José J.
Published: July 2021

Approximately three of every five workers are affected by musculoskeletal disorders, especially in production environments. In this regard, workstation ergonomic evaluations are especially beneficial for conducting preventive actions. Nevertheless, today’s context demonstrates that traditional ergonomic methods should lead to smart ergonomic methods. This document introduces the Forces ergonomic method, designed considering the possibilities of inertial motion capture technology and its applicability to evaluating actual workstations. This method calculates the joint risks for each posture and provides the total risk for the assessed workstation. In this calculation, Forces uses postural measurement and a kinetic estimation of all forces and torques that the joints support during movement. This paper details the method’s fundamentals to achieve structural validity, demonstrating that all parts that compose it are logical and well-founded. This method aims to aid prevention technicians in focusing on what matters: making decisions to improve workers’ health. Likewise, it aims to answer the current industry needs and reduce musculoskeletal disorders caused by repetitive tasks and lower the social, economic, and productivity losses that such disorders entail.
Rapid Estimation of Crop Water Stress Index on Tomato Growth
Authors: Alordzinu Kelvin Edom , Li Jiuhao , Lan Yubin , Appiah Sadick Amoakohene , AL Aasmi Alaa , Wang Hao
Published: July 2021

The goal of this research is to use a WORKSWELL WIRIS AGRO R INFRARED CAMERA (WWARIC) to assess the crop water stress index (CWSIW) on tomato growth in two soil types. This normalized index (CWSI) can map water stress to prevent drought, mapping yield, and irrigation scheduling. The canopy temperature, air temperature, and vapor pressure deficit were measured and used to calculate the empirical value of the CWSI based on the Idso approach (CWSIIdso). The vegetation water content (VWC) was also measured at each growth stage of tomato growth. The research was conducted as a 2 × 4 factorial experiment arranged in a Completely Randomized Block Design. The treatments imposed were two soil types: sandy loam and silt loam, with four water stress treatment levels at 70–100% FC, 60–70% FC, 50–60% FC, and 40–50% FC on the growth of tomatoes to assess the water stress. The results revealed that CWSIIdso and CWSIW proved a strong correlation in estimating the crop water status at R2 above 0.60 at each growth stage in both soil types. The fruit expansion stage showed the highest correlation at R2 = 0.8363 in sandy loam and R2 = 0.7611 in silt loam. VWC and CWSIW showed a negative relationship with a strong correlation at all the growth stages with R2 values above 0.8 at p < 0.05 in both soil types. Similarly, the CWSIW and yield also showed a negative relationship and a strong correlation with R2 values above 0.95, which indicated that increasing the CWSIW had a negative effect on the yield. However, the total marketable yield ranged from 2.02 to 6.8 kg plant−1 in sandy loam soil and 1.75 to 5.4 kg plant−1 in silty loam soil from a low to high CWSIW. The highest mean marketable yield was obtained in sandy loam soil at 70–100% FC (0.0 < CWSIW ≤ 0.25), while the least-marketable yield was obtained in silty loam soil 40–50% FC (0.75 < CWSIW ≤ 1.0); hence, it is ideal for maintaining the crop water status between 0.0 < CWSIW ≤ 0.25 for the optimum yield. These experimental results proved that the WWARIC effectively assesses the crop water stress index (CWSIW) in tomatoes for mapping the yield and irrigation scheduling.
Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty
Authors: Bolam Scott M. , Batinica Bruno , Yeung Ted C. , Weaver Sebastian , Cantamessa Astrid , Vanderboor Teresa C. , Yeung Shasha , Munro Jacob T. , Fernandez Justin W. , Besier Thor F. , Monk Andrew Paul
Published: July 2021

(Background) Inertial Measurement Units (IMUs) provide a low-cost, portable solution to obtain functional measures similar to those captured with three-dimensional gait analysis, including spatiotemporal gait characteristics. The primary aim of this study was to determine the feasibility of a remote patient monitoring (RPM) workflow using ankle-worn IMUs measuring impact load, limb impact load asymmetry and knee range of motion in combination with patient-reported outcome measures. (Methods) A pilot cohort of 14 patients undergoing primary knee arthroplasty for osteoarthritis was prospectively enrolled. RPM in the community was performed weekly from 2 up to 6 weeks post-operatively using wearable IMUs. The following data were collected using IMUs: mobility (Bone Stimulus and cumulative impact load), impact load asymmetry and maximum knee flexion angle. In addition, scores from the Oxford Knee Score (OKS), EuroQol Five-dimension (EQ-5D) with EuroQol visual analogue scale (EQ-VAS) and 6 Minute Walk Test were collected. (Results) On average, the Bone Stimulus and cumulative impact load improved 52% (p = 0.002) and 371% (p = 0.035), compared to Post-Op Week 2. The impact load asymmetry value trended (p = 0.372) towards equal impact loading between the operative and non-operative limb. The mean maximum flexion angle achieved was 99.25° at Post-Operative Week 6, but this was not significantly different from pre-operative measurements (p = 0.1563). There were significant improvements in the mean EQ-5D (0.20; p = 0.047) and OKS (10.86; p < 0.001) scores both by 6 weeks after surgery, compared to pre-operative scores. (Conclusions) This pilot study demonstrates the feasibility of a reliable and low-maintenance workflow system to remotely monitor post-operative progress in knee arthroplasty patients. Preliminary data indicate IMU outputs relating to mobility, impact load asymmetry and range of motion can be obtained using commercially available IMU sensors. Further studies are required to directly correlate the IMU sensor outputs with patient outcomes to establish clinical significance.
A Study on Seizure Detection of EEG Signals Represented in 2D
Authors: Xiong Zhiwen , Wang Huibin , Zhang Lili , Fan Tanghuai , Shen Jie , Zhao Yue , Liu Yang , Wu Qi
Published: July 2021

A seizure is a neurological disorder caused by abnormal neuronal discharges in the brain, which severely reduces the quality of life of patients and often endangers their lives. Automatic seizure detection is an important research area in the treatment of seizure and is a prerequisite for seizure intervention. Deep learning has been widely used for automatic detection of seizures, and many related research works decomposed the electroencephalogram (EEG) raw signal with a time window to obtain EEG signal slices, then performed feature extraction on the slices, and represented the obtained features as input data for neural networks. There are various methods for EEG signal decomposition, feature extraction, and representation, and most of the studies have been based on fixed hardware resources for the design of the scheme, which reduces the adaptability of the scheme in different application scenarios and makes it difficult to optimize the algorithms in the scheme. To address the above issues, this paper proposes a deep learning-based model for seizure detection, mainly characterized by the two-dimensional representation of EEG features and the scalability of neural networks. The model modularizes the main steps of seizure detection and improves the adaptability of the model to different hardware resource constraints, in order to increase the convenience of the algorithm optimization or the replacement of each module. The proposed model consists of five parts, and the model was tested using two epilepsy datasets separately. The experimental results showed that the proposed model has strong generality and good classification accuracy for seizure detection.
A Blockchain-Based Spatial Crowdsourcing System for Spatial Information Collection Using a Reward Distribution
Authors: Kamali Masoud , Malek Mohammad Reza , Saeedi Sara , Liang Steve
Published: July 2021

Due to the increasing relevance of spatial information in different aspects of location-based services, various methods are used to collect this information. The use of crowdsourcing due to plurality and distribution is a remarkable strategy for collecting information, especially spatial information. Crowdsourcing can have a substantial effect on increasing the accuracy of data. However, many centralized crowdsourcing systems lack security and transparency due to a trusted party’s existence. With the emergence of blockchain technology, there has been an increase in security, transparency, and traceability in spatial crowdsourcing systems. In this paper, we propose a blockchain-based spatial crowdsourcing system in which workers confirm or reject the accuracy of tasks. Tasks are reports submitted by requesters to the system; a report comprises type and location. To our best knowledge, the proposed system is the first system that all participants receive rewards. This system considers spatial and non-spatial reward factors to encourage users’ participation in collecting accurate spatial information. Privacy preservation and security of spatial information are considered in the system. We also evaluated the system efficiency. According to the experiment results, using the proposed system, information accuracy increased by 40%, and the minimum time for reviewing reports by facilities reduced by 30%. Moreover, we compared the proposed system with the current centralized and distributed crowdsourcing systems. This comparison shows that, although our proposed system omits the user’s history to preserve privacy, it considers a consensus-based approach to guarantee submitted reports’ accuracy. The proposed system also has a reward mechanism to encourage more participation.
Experimental Validation of a Microwave Imaging Method for Shallow Buried Target Detection by Under-Sampled Data and a Non-Cooperative Source
Authors: Brancaccio Adriana , Leone Giovanni , Pierri Rocco , Solimene Raffaele
Published: July 2021

In microwave imaging, it is often of interest to inspect electrically large spatial regions. In these cases, data must be collected over a great deal of measurement points which entails long measurement time and/or costly, and often unfeasible, measurement configurations. In order to counteract such drawbacks, we have recently introduced a microwave imaging algorithm that looks for the scattering targets in terms of equivalent surface currents supported over a given reference plane. While this method is suited to detect shallowly buried targets, it allows one to independently process all frequency data, and hence the source and the receivers do not need to be synchronized. Moreover, spatial data can be reduced to a large extent, without any aliasing artifacts, by properly combining single-frequency reconstructions. In this paper, we validate such an approach by experimental measurements. In particular, the experimental test site consists of a sand box in open air where metallic plate targets are shallowly buried a (few cm) under the air/soil interface. The investigated region is illuminated by a fixed transmitting horn antenna, whereas the scattered field is collected over a planar measurement aperture at a fixed height from the air-sand interface. The transmitter and the receiver share only the working frequency information. Experimental results confirm the feasibility of the method.
Design and Experimental Characterization of L-CADEL v2, an Assistive Device for Elbow Motion
Authors: Ceccarelli Marco , Riabtsev Mykhailo , Fort Axel , Russo Matteo , Laribi Med Amine , Urizar Monica
Published: July 2021

An experimental characterization is presented for an improved version of a wearable assistive device for elbow motion. The design is revised with respect to requirements for elbow motion assistance, looking at applications both in rehabilitation therapies and exercising of elderly people. A laboratory prototype is built with lightweight, portable, easy-to-use features that are verified with test results, whose discussion is also provided as a characterization of operating performance.
A Model for the Magnetoimpedance Effect in Non-Symmetric Nanostructured Multilayered Films with Ferrogel Coverings
Authors: Buznikov Nikita A. , Kurlyandskaya Galina V.
Published: July 2021

Magnetoimpedance (MI) biosensors for the detection of in-tissue incorporated magnetic nanoparticles are a subject of special interest. The possibility of the detection of the ferrogel samples mimicking the natural tissues with nanoparticles was proven previously for symmetric MI thin-film multilayers. In this work, in order to describe the MI effect in non-symmetric multilayered elements covered by ferrogel layer we propose an electromagnetic model based on a solution of the 4Maxwell equations. The approach is based on the previous calculations of the distribution of electromagnetic fields in the non-symmetric multilayers further developed for the case of the ferrogel covering. The role of the asymmetry of the film on the MI response of the multilayer–ferrogel structure is analyzed in the details. The MI field and frequency dependences, the concentration dependences of the MI for fixed frequencies and the frequency dependence of the concentration sensitivities are obtained for the detection process by both symmetric and non-symmetric MI structures.
Analysis of Vehicle Collision on an Assembled Anti-Collision Guardrail
Authors: Yao Juncheng , Wang Bo , Hou Yujie , Huang Liang
Published: July 2021

Traffic accidents such as vehicle collisions with bridge guardrails occur frequently. These accidents cause damage to the driver and the vehicle as well as the bridge. A new type of assembled anti-collision guardrail is proposed in this study. LS-DYNA is a nonlinear display dynamic analysis software used to evaluate the safety of a new type of assembled anti-collision guardrail. A specific, numerically analyzed model of vehicle–guardrail collision is established using LS-DYNA. The energy distribution–time curve of the vehicle collision process is obtained. After comparison with measured data from the vehicle collision test, the model of vehicle–guardrail collision is verified as being correct. Based on this, we analyze the process of a vehicle collision on the assembled anti-collision guardrail. The result shows that the assembled anti-collision guardrail proposed in this paper can better change the trajectory of a moving vehicle and can prevent the vehicle from falling off the bridge. From the car body collision results, the assembled anti-collision guardrail for bridges proposed in this paper can reduce vehicle damage and can protect the driver effectively. From the analysis of the main girder stress on the bridge, an anti-collision guardrail installed on an existing bridge will not cause damage to the main girder during a collision. In order to study the influence of the four parameters on the anti-collision effect, we carried out a comparative calculation of multiple working conditions. The results show that the new type of assembled anti-collision guardrail has good protective performance under different working conditions.
FlexiS—A Flexible Sensor Node Platform for the Internet of Things
Authors: Pham Duc Minh , Aziz Syed Mahfuzul
Published: July 2021

In recent years, significant research and development efforts have been made to transform the Internet of Things (IoT) from a futuristic vision to reality. The IoT is expected to deliver huge economic benefits through improved infrastructure and productivity in almost all sectors. At the core of the IoT are the distributed sensing devices or sensor nodes that collect and communicate information about physical entities in the environment. These sensing platforms have traditionally been developed around off-the-shelf microcontrollers. Field-Programmable Gate Arrays (FPGA) have been used in some of the recent sensor nodes due to their inherent flexibility and high processing capability. FPGAs can be exploited to huge advantage because the sensor nodes can be configured to adapt their functionality and performance to changing requirements. In this paper, FlexiS, a high performance and flexible sensor node platform based on FPGA, is presented. Test results show that FlexiS is suitable for data and computation intensive applications in wireless sensor networks because it offers high performance with low energy profile, easy integration of multiple types of sensors, and flexibility. This type of sensing platforms will therefore be suitable for the distributed data analysis and decision-making capabilities the emerging IoT applications require.
Stakeholder’s Perspective on Green Building Rating Systems in Saudi Arabia: The Case of LEED, Mostadam, and the SDGs
Authors: Al-Surf Mohammed , Balabel Ashraf , Alwetaishi Mamdooh , Abdelhafiz Ahmed , Issa Usama , Sharaky Ibrahim , Shamseldin Amal , Al-Harthi Mosleh
Published: July 2021

This paper discusses in detail the current level of awareness of the Saudi Arabia stakeholders regarding the use and application of green building rating systems. The paper used a mix of qualitative and quantitative research methods through an exploratory method that utilized an online survey targeting experts and construction stakeholders to fill the gap of previous research papers and support the argument of the increase in the level of the awareness of stakeholders in the use and application of green building rating systems in Saudi Arabia. This research aims to focus on the level of awareness of the Saudi construction market stakeholders on green building rating systems in Saudi Arabia with focus on the Leadership in Energy and Environmental Design system LEED and Mostadam. It also investigated which rating system responds to the need of the Saudi construction market with regard to energy conservation and water consumption more effectively. The methodology utilized in this research used a combination of primary and secondary data where the primary data were a survey sent to Saudi construction stakeholders where a total of 1320 respondents participated in the survey. Results from this research showed a promising number of agreements between the participating stakeholders to the level of awareness of green building rating systems in Saudi Arabia and to the willingness to use internationally recognized rating systems such as LEED and the use of locally recognized systems such as Mostadam. Furthermore, the research aims to link the results with the Sustainable Development Goals (SDGs) with a focus on SDGs 6 and 7. The results show a high level of appreciation and agreement to the importance of energy and water conservation in green buildings that will be using either LEED or Mostadam in Saudi Arabia and accomplish the targets outlined under the SDGs.
Corporate Social Responsibility Disclosure, Media Reports, and Enterprise Innovation: Evidence from Chinese Listed Companies
Authors: Wu Shilei , Zhang Hongjie , Wei Taoyuan
Published: July 2021

Given the limited response of enterprises to China’s national policy on the compulsory disclosure of corporate social responsibility (CSR), a deviation has occurred between policy orientation and reality. To explore the reasons behind this deviation, we investigated whether different types of media reports play an intermediary role in the process of CSR affecting corporate innovation based on the data of the companies listed on China’s Shenzhen Stock Exchange and Shanghai Stock Exchange from 2010 to 2019. The results show that the disclosure of CSR by the listed companies can significantly promote corporate innovation, which provides theoretical support for the national compulsory disclosure of CSR. Newspaper media reports and online media reports not only directly promote corporate innovation but also form a positive mediation path in the CSR disclosure and the promotion of corporate innovation. Further analysis shows that, among the five aspects of CSR, the disclosure of employee responsibility had the greatest effect on the corporate innovation, whereas the disclosure of social contribution responsibility only had a short-term inhibitory effect. Both newspaper media and online media reports on CSR disclosure were beneficial to corporate innovation. Positive and neutral reports may play the role of media governance to promote corporate innovation, whereas negative reports can restrain corporate innovation due to the market pressure effect produced by them, which also provides the basis for media supervision by the state.
The Effect of Abusive Supervision on Organizational Identification: A Moderated Mediation Analysis
Authors: Arasli Huseyin , Cengiz Mustafa , Arici Hasan Evrim , Arici Nagihan Cakmakoglu , Arasli Furkan
Published: July 2021

This study investigated the effect of abusive supervision on employee organizational identification by analyzing the mediating effect of psychological contract violation. In addition, it explored the moderating role of favoritism in the direct association of abusive supervision and organizational identification and the indirect effect through psychological contract violation. A total of 488 seasonal, immigrant, and part-time employees from family-run hotel organizations were surveyed during the data collection process. By utilizing Hayes’s macro, we found that abusive supervision and psychological contract violation had a significant negative effect on organizational identification. In addition, the results showed that psychological contract violation mediated the effect of abusive supervision on organizational identification and favoritism moderated the effect of abusive supervision on psychological contract violation. The findings highlight the detrimental effects of favoritism and abusive supervision on employee outcomes in the hospitality industry.
Technological Innovation and Circular Economy Practices: Business Strategies to Mitigate the Effects of COVID-19
Authors: Khan Syed Abdul Rehman , Ponce Pablo , Tanveer Muhammad , Aguirre-Padilla Nathalie , Mahmood Haider , Shah Syed Adeel Ali
Published: July 2021

The Corona Virus Disease 2019 (COVID-19) has been a tough test on companies in the global food sector supply chain, exacerbating the realities and deficiencies it presents in developing economies. This situation has been reflected in the firm’s performance (F.P.) due to the lack of business conditions to respond to the current pandemic. However, in some companies, the adverse effects of COVID-19 have been counteracted due to endowment and technological capabilities. Thus, this study examined the role of technological innovation (T.I.) and business data analytics (B.D.A.) in the F.P. of foods in Ecuador during COVID-19. A questionnaire collected the information from the food firms. Then, Covariance-Based Structural Equation Modeling processed the collected information. We found that (B.D.A.) mechanisms and different levels of T.I. within the developing market significantly shape the F.P. The results showed that the B.D.A. enables circular economy (C.E.) practices and the improvement of product delivery services, which constitutes an improvement of the F.P. The COVID-19 outbreak did not significantly affect T.I., unlike what happened with B.D.A. This study concluded that firms with the most extraordinary technological production processes have been the least affected during COVID-19. This study suggested that policy measures should boost food firms’ technological endowment to improve their resilience in uncertainty and risk scenarios.
Development of Teacher Digital Competence in the Area of E-Safety through Educational Video Games
Authors: Gordillo Aldo , Barra Enrique , López-Pernas Sonsoles , Quemada Juan
Published: July 2021

There is a clear need to promote motivating and effective training actions for the development of teachers’ digital competence, especially in the area of e-safety. Although educational video game-based learning has proven effective to improve motivation and learning outcomes, the existing evidence about its effectiveness for the development of teachers’ digital competence is very limited. This study examines the use of educational video games in an online course in MOOC format with the aim of developing teachers’ digital competence in the e-safety area. A total of 179 teachers from nonuniversity schools in the region of Castilla y León (Spain) participated in this study. A pre-test and a post-test were used to measure the knowledge acquired by the participants, and a questionnaire was used to measure their perceptions. The obtained results suggest that game-based learning using educational video games is an effective and viable approach to train teachers in the e-safety area of digital competence.
Spatiotemporal Analysis of the Frost Regime in the Iberian Peninsula in the Context of Climate Change (1975–2018)
Authors: García-Martín Abelardo , Paniagua Luis L. , Moral Francisco J. , Rebollo Francisco J. , Rozas María A.
Published: July 2021

Climate change is having many effects in the agricultural sector, which are being studied worldwide. Undoubtedly, warmer winters and earlier springs produce changes in frost regimes and severity that will affect the sustainability of agricultural production in the area. The Mediterranean region and the Iberian Peninsula (IP) are among the areas where the greatest impact of climate change is expected. Daily data from 68 weather stations of the IP belonging to the European Climate Assessment and Dataset (1975–2018) were used to conduct a spatiotemporal study of the frost regime. The variables calculated include the probability of three frost types according to their severity, frost day, mean absolute minimum yearly temperature, first frost day, last frost day, and frost-free period. These variables were integrated into a geographic information system, which allowed the graphical visualization of their patterns using of geostatistical interpolation techniques (kriging). Changes in frost variables were investigated using the Mann–Kendall test and Sen’s slope estimator. A general reduction in the number of frosts per year is observed (values between −0.04- and −0.8-day frosts per year), as well as an increase in the mean absolute minimum temperature (values between 0.04 and 0.10 °C per year), with very high significant trends throughout the territory. The reduction in the number of frosts is more pronounced at a higher elevation. Frost dates vary greatly due to the orographic characteristics of the IP. The generalized trend is of a significant delay of the autumn frosts (values between 0.4 and 1.06 days/year), as well as early spring frosts (between −0.429 and −1.29 days/year), and as a consequence a longer frost-free period, all changes were much stronger than those found in other regions of the world. These effects of climate change must be mitigated by modifying species, varieties, and cultivation techniques to guarantee sustainable agriculture.
Water Footprint Assessment of Carbon in Pulp Gold Processing in Turkey
Authors: Güney Emre , Demirel Nuray
Published: July 2021

This paper presents water the footprint assessment (WFA) of carbon in pulp (CIP) gold processing. The main objectives of the study are determining grey and blue water footprints and identifying the hotspots of the process. Results revealed that the total blue water footprint, including the extraction and processing of the gold, was found to be 452.40 m3/kg Au, and the grey WF to be 2300.69 m3/kg Au. According to the results, the lost return flow on the direct blue WF side has the largest contribution, with a value of 260.61 m3/kg Au, and the only source of the lost return flow is the tailing pond. On the indirect side, it is seen that the oxygen consumption used for the leaching process has the highest value, with 37.38 m3/kg. Among the nine contaminants in the mine tailings, the critical component responsible for the grey water footprint is by far arsenic, with a value of 1777 m3/kg Au. The results will be used to make recommendations for reducing water consumption in mining operations, for a better design for the environment. The study is a pioneering study, being the first implementation of water footprint assessment in a gold mine in Turkey.
Field and Numerical Study on Deformation and Failure Characteristics of Deep High-Stress Main Roadway in Dongpang Coal Mine
Authors: Liu Shuaigang , Bai Jianbiao , Wang Xiangyu , Yan Shuai , Zhao Jiaxin
Published: July 2021

Deep horizontal high stress and high permeability geological factors appear when coal mines are converted to deep horizontal mining. When the roadway is damaged by the mining face, and the supporting components are mismatched, the deep roadways necessitate extensive repair work, which has a negative impact on the coal mining economy and sustainability. This paper carried out a series of field tests on the roadways deformation, crack distribution, and loose rock zone of the deep roadways. Furthermore, a numerical calculation model was established using the discrete element method (DEM) and calibrated with laboratory tests and RQD methods. Both the stress and crack distribution in the surrounding rock of the deep roadway were simulated. The field test and the corrected numerical model showed consistency. A FISH function was used to document the propagation of shear and tensile cracks around the roadway in three periods, and a damage parameter was adopted to evaluate the failure mechanism of the deep roadways under the dynamic stress disturbance. The matching of specifications of anchor cables, rock bolts, and anchoring agent is the primary point in the control of deep roadways, and revealing the stress evolution, crack propagation, and damage distribution caused by mining effects is another key point in deep roadway controlling. The field test and DEM in this paper provide a reference for the design of surrounding rock control of deep roadways and the sustainable development of coal mines.
Influence of Different Arm Positions in the Localizer Radiograph(s) on Patient Dose during Exposure-Controlled CT Examinations of the Neck to Pelvis
Authors: Svahn Tony M. , Peric Lovre , Ast Jennifer C.
Published: July 2021

Our aim was to examine the impact of different arm positions during imaging of the localizer radiograph(s) on effective dose for exposure-controlled computed tomography (CT) (Siemens/Canon) scans of the neck to pelvis. An anthropomorphic whole-body phantom was scanned from the neck to pelvis with the arms positioned in three different ways during the acquisition of the localizer radiograph: (i) above the head, (ii) alongside the trunk, and (iii) along the trunk with the hands placed on the abdomen. In accordance with clinical routines, the arms were not included in the subsequent helical scans. Effective doses were computed to a standard-sized patient (male/female) using a dedicated system-specific Monte Carlo-based software. Effective doses for the Canon CT scanner for the different alternatives (male/female) were (a) 5.3/6.62 mSv, (b) 5.62/7.15 mSv and (c) 5.92/7.44 mSv. For the Siemens CT scanner, effective doses were (a) 4.47/5.59 mSv, (b) 5.4/6.69 mSv and (c) 5.7/6.99 mSv. Arms placed above the head during localizer radiograph imaging in the current CT procedures substantially reduced the total effective dose to the patient.
Identification of Novel HBV/HDV Entry Inhibitors by Pharmacophore- and QSAR-Guided Virtual Screening
Authors: Kirstgen Michael , Müller Simon Franz , Lowjaga Kira Alessandra Alicia Theresa , Goldmann Nora , Lehmann Felix , Alakurtti Sami , Yli-Kauhaluoma Jari , Baringhaus Karl-Heinz , Krieg Reimar , Glebe Dieter , Geyer Joachim
Published: July 2021

The hepatic bile acid transporter Na+/taurocholate co-transporting polypeptide (NTCP) was identified in 2012 as the high-affinity hepatic receptor for the hepatitis B and D viruses (HBV/HDV). Since then, this carrier has emerged as promising drug target for HBV/HDV virus entry inhibitors, but the synthetic peptide Hepcludex® of high molecular weight is the only approved HDV entry inhibitor so far. The present study aimed to identify small molecules as novel NTCP inhibitors with anti-viral activity. A ligand-based bioinformatic approach was used to generate and validate appropriate pharmacophore and QSAR (quantitative structure–activity relationship) models. Half-maximal inhibitory concentrations (IC50) for binding inhibition of the HBV/HDV-derived preS1 peptide (as surrogate parameter for virus binding to NTCP) were determined in NTCP-expressing HEK293 cells for 150 compounds of different chemical classes. IC50 values ranged from 2 µM up to >1000 µM. The generated pharmacophore and QSAR models were used for virtual screening of drug-like chemicals from the ZINC15 database (~11 million compounds). The 20 best-performing compounds were then experimentally tested for preS1-peptide binding inhibition in NTCP-HEK293 cells. Among them, four compounds were active and revealed experimental IC50 values for preS1-peptide binding inhibition of 9, 19, 20, and 35 µM, which were comparable to the QSAR-based predictions. All these compounds also significantly inhibited in vitro HDV infection of NTCP-HepG2 cells, without showing any cytotoxicity. The best-performing compound in all assays was ZINC000253533654. In conclusion, the present study demonstrates that virtual compound screening based on NTCP-specific pharmacophore and QSAR models can predict novel active hit compounds for the development of HBV/HDV entry inhibitors.
Diversity of Coronaviruses in Wild Representatives of the Aves Class in Poland
Authors: Domańska-Blicharz Katarzyna , Miłek-Krupa Justyna , Pikuła Anna
Published: July 2021

The revealed prevalence of coronaviruses in wild bird populations in Poland was 4.15% and the main reservoirs were birds from orders Anseriformes and Charadriiformes, with a prevalence of 3.51% and 5.59%, respectively. Gammacoronaviruses were detected more often than deltacoronaviruses, with detection rates of 3.5% and 0.7%, respectively. Gammacoronaviruses were detected in birds belonging to six orders, including Anseriformes, Charadriiformes, Columbiformes, Galliformes, Gruiformes, and Passeriformes, indicating a relatively wide host range. Interestingly, this was the only coronavirus detected in Anseriformes (3.51%), while in Charadriiformes, the prevalence was 3.1%. The identified gammacoronaviruses belonged to the Igacovirus and Brangacovirus subgeneras. Most of these were igacoviruses and formed a common phylogenetic group with a Duck Coronavirus 2714 and two with an Avian Coronavirus/Avian Coronavirus9203, while the viruses from the pigeons formed a distinct “pigeon-like” group, not yet officially represented. The presence of deltacoronaviruses was detected in birds belonging to three orders, Charadriiformes, Galliformes, and Suliformes indicating a narrower host range. Most identified deltacoronaviruses belonged to the Buldecovirus subgenus, while only one belonged to Herdecovirus. Interestingly, the majority of buldecoviruses were identified in gulls, and they formed a distinct phylogenetic lineage not represented by any officially ratified virus species. Another separate group of buldecoviruses, also not represented by the official species, was formed by a virus identified in a common snipe. Only one identified buldecovirus (from common pheasant) formed a group with the ratified species Coronavirus HKU15. The results obtained indicate the high diversity of detected coronaviruses, and thus also the need to update their taxonomy (establishing new representative virus species). The serological studies performed revealed antibodies against an infectious bronchitis virus in the sera of white storks and mallards.
Exosome-Based Vaccines: Pros and Cons in the World of Animal Health
Authors: Montaner-Tarbes Sergio , Fraile Lorenzo , Montoya María , Del Portillo Hernando
Published: July 2021

Due to the emergence of antibiotic resistance and new and more complex diseases that affect livestock animal health and food security, the control of epidemics has become a top priority worldwide. Vaccination represents the most important and cost-effective measure to control infectious diseases in animal health, but it represents only 23% of the total global animal health market, highlighting the need to develop new vaccines. A recent strategy in animal health vaccination is the use of extracellular vesicles (EVs), lipid bilayer nanovesicles produced by almost all living cells, including both prokaryotes and eukaryotes. EVs have been evaluated as a prominent source of viral antigens to elicit specific immune responses and to develop new vaccination platforms as viruses and EVs share biogenesis pathways. Preliminary trials with lymphocytic choriomeningitis virus infection (LCMV), porcine reproductive and respiratory syndrome virus (PRRSV), and Marek’s disease virus (MDV) have demonstrated that EVs have a role in the activation of cellular and antibody immune responses. Moreover, in parasitic diseases such as Eimeria (chickens) and Plasmodium yoelii (mice) protection has been achieved. Research into EVs is therefore opening an opportunity for new strategies to overcome old problems affecting food security, animal health, and emerging diseases. Here, we review different conventional approaches for vaccine design and compare them with examples of EV-based vaccines that have already been tested in relation to animal health.
Spatial and Long-Term Temporal Changes in Water Quality Dynamics of the Tonle Sap Ecosystem
Authors: Soum Savoeurn , Ngor Peng Bun , Dilts Thomas E. , Lohani Sapana , Kelson Suzanne , Null Sarah E. , Tromboni Flavia , Hogan Zeb S. , Chan Bunyeth , Chandra Sudeep
Published: July 2021

Tonle Sap lake-river floodplain ecosystem (TSE) is one of the world’s most productive freshwater systems. Changes in hydrology, climate, population density, and land use influence water quality in this system. We investigated long term water quality dynamics (22 years) in space and time and identified potential changes in nutrient limitation based on nutrient ratios of inorganic nitrogen and phosphorus. Water quality was assessed at five sites highlighting the dynamics in wet and dry seasons. Predictors of water quality included watershed land use, climate, population, and water level. Most water quality parameters varied across TSE, except pH and nitrate that remained constant at all sites. In the last decade, there is a change in the chemical nutrient ratio suggesting that nitrogen may be the primary limiting nutrient across the system. Water quality was strongly affected by development in the watershed i.e., flooded forest loss, climatic variation, population growth, and change in water level. Seasonal variations of water quality constituents were driven by precipitation and hydrology, notably the Mekong’s distinct seasonal flood pulse.
Trends and Evolution in the Concept of Marine Ecosystem Services: An Overview
Authors: Buonocore Elvira , Grande Umberto , Franzese Pier Paolo , Russo Giovanni F.
Published: July 2021

The biotic and abiotic assets of the marine environment form the “marine natural capital” embedded in the global ocean. Marine natural capital provides the flow of “marine ecosystem services” that are directly used or enjoyed by people providing benefits to human well-being. They include provisioning services (e.g., food), regulation and maintenance services (e.g., carbon sequestration and storage, and coastal protection), and cultural services (e.g., tourism and recreational benefits). In recent decades, human activities have increased the pressures on marine ecosystems, often leading to ecosystem degradation and biodiversity loss and, in turn, affecting their ability to provide benefits to humans. Therefore, effective management strategies are crucial to the conservation of healthy and diverse marine ecosystems and to ensuring their long-term generation of goods and services. Biophysical, economic, and sociocultural assessments of marine ecosystem services are much needed to convey the importance of natural resources to managers and policy makers supporting the development and implementation of policies oriented for the sustainable management of marine resources. In addition, the accounting of marine ecosystem service values can be usefully complemented by their mapping to enable the identification of priority areas and management strategies and to facilitate science–policy dialogue. Given this premise, this study aims to review trends and evolution in the concept of marine ecosystem services. In particular, the global scientific literature on marine ecosystem services is explored by focusing on the following main aspects: the definition and classification of marine ecosystem services; their loss due to anthropogenic pressures, alternative assessment, and mapping approaches; and the inclusion of marine ecosystem services into policy and decision-making processes.
Water Distribution in a Socio-Technical System: Resilience Assessment for Critical Events Causing Demand Relocation
Authors: Logan Kevin T. , Leštáková Michaela , Thiessen Nadja , Engels Jens Ivo , Pelz Peter F.
Published: July 2021

This study presents an exploratory, historically-informed approach to assessing resilience for critical events that cause demand relocation within a water distribution system (WDS). Considering WDS as an interdependent socio-technical system, demand relocation is regarded as a critical factor that can affect resilience similarly to the more commonly analyzed component failures such as pipe leaks and pump failures. Critical events are modeled as events during which consumer nodes are evacuated within a perimeter varying in size according to a typical length scale in the studied network. The required demand drops to zero in the evacuated area, and the equivalent demand is relocated according to three sheltering schemes. Results are presented for analyzing the effect of the size of the evacuated area, the feasibility of sheltering schemes, vulnerability of particular parts of the city as well as the suitability of network nodes to accommodate relocated demand using a suitable resilience metric. The results provided by this metric are compared with those drawn from common graph-based metrics. The conclusions are critically discussed under the consideration of historical knowledge to serve as a basis for future research to refine resilience assessment of socio-technical systems.
Effect of Salinity on Evaporation from Water Surface in Bench-Scale Testing
Authors: Suchan Jared , Azam Shahid
Published: July 2021

Freshwater and hypersaline lakes in arid and semi-arid environments are crucial from agricultural, industrial, and ecological perspectives. The purpose of this paper was to investigate the effect of salinity on evaporation from water surfaces. The main achievement of this research is the successful capture of simulated climate–surface interactions prevalent in the Canadian Prairies using a custom-built bench-scale atmospheric simulator. Test results indicated that the evaporative flux has a large variation during spring (water/brine: 1452/764 10−4 g·s−1·m−2 and 613/230 × 10−4 g·s−1·m−2 night) and summer (1856/1187 × 10−4 g·s−1·m−2 day and 1059/394 × 10−4g·s−1·m−2 night), and small variation in the fall (1591/915 × 10−4 g·s−1·m−2 and 1790/1048 × 10−4 g·s−1·m−2 night). The primary theoretical contribution of this research is that the evaporation rate from distilled water is twice that of saturated brine. The measured data for water correlated well with mathematical estimates; data scatter was evenly distributed and within one standard deviation of the equality line, whereas the brine data mostly plotted above the equality line. The newly developed 2:1 water–brine correlation for evaporation was found to follow the combination equations with the Monteith model best matching the measurements.