bluuebunny/crossref_metadata_2025 huggingface dataset:
Arsenic(V) Removal from Water by Resin Impregnated with Cyclodextrin Ligand
Authors: Zawierucha Iwona , Nowik-Zajac Anna , Girek Tomasz , Lagiewka Jakub , Ciesielski Wojciech , Pawlowska Barbara , Biczak Robert
Published: January 2022

More rigorous environmental rules on hazardous metals release require the implementation of diverse methods to remove them from contaminated streams. The adsorption process is the most attractive method for removal of toxic metal ions from different aqueous solutions. In the present study, batch and fixed bed column experiments were carried out to investigate the performance of permethylated β-cyclodextrin impregnated resin for the removal of As(V) ions from aqueous solutions. Sorption of As(V) ions was performed in groups under a variety of pH and metal concentrations. It was noted that removal efficiency was the highest (98%) at pH 6.0, and at an initial As(V) concentration equal to 0.1 mg/L. Sorption model use for experimental data indicates that the removal mechanism of As(V) by the permethylated β-cyclodextrin impregnated resin was the physical sorption. The adsorption capacity of the cyclodextrin ligand immobilized onto Amberlite XAD-4 resin was 19 mg/g. In addition, the impregnated resin was regenerable, thus was able to be used over and over.
Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data
Authors: Cao Yunfeng , Li Manyao , Zhang Yuzhen
Published: January 2022

Surface longwave downward radiation (LWDR) plays a key role in determining the Arctic surface energy budget, especially in insolation-absent boreal winter. A reliable LWDR product is essential for understanding the intrinsic physical mechanisms of the rapid changes in the Arctic climate. The Medium-Resolution Spectral Imager (MERSI-2), a major payload of the Chinese second-generation polar-orbiting meteorological satellite, FengYun-3D (FY-3D), was designed similar to the NASA Moderate-Resolution Imaging Spectroradiometer (MODIS) in terms of the spectral bands. Although significant progress has been made in estimating clear-sky LWDR from MODIS observations using a variety of methods, few studies have focused on the retrieval of clear-sky LWDR from FY-3D MERSI-2 observations. In this study, we propose an advanced method to directly estimate the clear-sky LWDR in the Arctic from the FY-3D MERSI-2 thermal infrared (TIR) top-of-atmosphere (TOA) radiances and auxiliary information using the extremely randomized trees (ERT) machine learning algorithm. The retrieval accuracy of RMSE and bias, validated with the Baseline Surface Radiation Network (BSRN) in situ measurements, are 14.14 W/m2 and 4.36 W/m2, respectively, which is comparable and even better than previous studies. The scale effect in retrieval accuracy evaluation was further analyzed and showed that the validating window size could significantly influence the retrieval accuracy of the MERSI-2 clear-sky LWDR dataset. After aggregating to a spatial resolution of 9 km, the RMSE and bias of MERSI-2 retrievals can be reduced to 9.43 W/m2 and −0.14 W/m2, respectively. The retrieval accuracy of MERSI-2 clear-sky LWDR at the CERES SSF FOV spatial scale (approximately 20 km) can be further reduced to 8.64 W/m2, which is much higher than the reported accuracy of the CERES SSF products. This study demonstrates the feasibility of producing LWDR datasets from Chinese FY-3D MERSI-2 observations using machine learning methods.
Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images
Authors: Ghandorh Hamza , Boulila Wadii , Masood Sharjeel , Koubaa Anis , Ahmed Fawad , Ahmad Jawad
Published: January 2022

Road detection technology plays an essential role in a variety of applications, such as urban planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there has been much development in detecting roads in high-resolution (HR) satellite images based on semantic segmentation. However, the objects being segmented in such images are of small size, and not all the information in the images is equally important when making a decision. This paper proposes a novel approach to road detection based on semantic segmentation and edge detection. Our approach aims to combine these two techniques to improve road detection, and it produces sharp-pixel segmentation maps, using the segmented masks to generate road edges. In addition, some well-known architectures, such as SegNet, used multi-scale features without refinement; thus, using attention blocks in the encoder to predict fine segmentation masks resulted in finer edges. A combination of weighted cross-entropy loss and the focal Tversky loss as the loss function is also used to deal with the highly imbalanced dataset. We conducted various experiments on two datasets describing real-world datasets covering the three largest regions in Saudi Arabia and Massachusetts. The results demonstrated that the proposed method of encoding HR feature maps effectively predicts sharp segmentation masks to facilitate accurate edge detection, even against a harsh and complicated background.
Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques
Authors: Sipols Ana E. , Valcarce-Diñeiro Rubén , Santos-Martín Maria Teresa , Sánchez Nilda , de Blas Clara Simón
Published: January 2022

This paper aims to both fit and predict crop biophysical variables with a SAR image series by performing a factorial experiment and estimating time series models using a combination of forecasts. Two plots of barley grown under rainfed conditions in Spain were monitored during the growing cycle of 2015 (February to June). The dataset included nine field estimations of agronomic parameters, 20 RADARSAT-2 images, and daily weather records. Ten polarimetric observables were retrieved and integrated to derive the six agronomic and monitoring variables, including the height, biomass, fraction of vegetation cover, leaf area index, water content, and soil moisture. The statistical methods applied, namely double smoothing, ARIMAX, and robust regression, allowed the adjustment and modelling of these field variables. The model equations showed a positive contribution of meteorological variables and a strong temporal component in the crop’s development, as occurs in natural conditions. After combining different models, the results showed the best efficiency in terms of forecasting and the influence of several weather variables. The existence of a cointegration relationship between the data series of the same crop in different fields allows for adjusting and predicting the results in other fields with similar crops without re-modelling.
Hierarchical Transmission Tower Detection from High-Resolution SAR Image
Authors: Li Jianan , Li Yu , Jiang Haonan , Zhao Quanhua
Published: January 2022

The small scale of transmission towers and the environmental diversity around their situations make their detection in Synthetic Aperture Radar (SAR) images a challenging task. This paper presents a new hierarchical detection algorithm for transmission towers. First, Signal-to-Clutter Ratios (SCRs) of pixels are calculated. Afterwards, a SCR threshold is set. Since transmission towers possess strong scattering characteristics, pixels with SCRs above the threshold are considered as potential transmission tower pixels. Second, spatial densities of potential transmission tower pixels are calculated. According to the aggregation characteristics of transmission tower pixels, some potential transmission tower pixels with small spatial densities are removed. The remained potential transmission tower pixels are considered as candidate transmission tower pixels. The candidate transmission tower pixels are grouped by the nearest neighbour scheme such that in each group the distance between pixels is under a given threshold. Thus, each of the groups is viewed as a quasi-transmission tower. Convex-hulls of quasi-transmission towers are built, and then Minimum Bounding Rectangle (MBR) for each convex-hull is generated. According to the rectangle aspect ratios of MBRs, the real transmission towers are extracted. C-band HH-polarization GaoFen-3 (GF-3) amplitude images are used for experiments and four of the most popular transmission tower detection algorithms are selected as comparing algorithms to validate the proposed algorithms. The detection performance of transmission towers is evaluated with detection rate and quality factor. Experimental results verify that the proposed algorithm can efficiently and accurately detect transmission towers while maintaining the transmission tower geometry to a certain extent, which indicates that the proposed algorithm is efficient and promising.
Lidar Ratio Regional Transfer Method for Extinction Coefficient Accuracy Improvement in Lidar Networks
Authors: Tong Yicheng , Chen Sijie , Xiao Da , Zhang Kai , Fang Jing , Liu Chong , Shen Yibing , Liu Dong
Published: January 2022

Lidar networks are essential to study the three-dimensional distribution of aerosols on a regional scale. At present, both Mie-scattering lidar (ML) and advanced lidars are being used in lidar networks. The latter can retrieve extinction coefficients without strict assumptions of the lidar ratio, such as Raman lidar (RL) or high-spectral-resolution lidar (HSRL). In order to balance the data quality and instrument costs for the lidar network, the lidar ratio regional transfer method in a lidar network is proposed in this paper. We developed a Lidar Ratio and Aerosol Fraction Non-linear Regression (LR-AFNR) model between the lidar ratio and corresponding absorbing aerosol fraction (this paper studied two types of absorbing aerosols: dust and carbonaceous). The aerosol fraction of the sun photometer retrieval was used as a medium to transfer the lidar ratio of HSRL retrieval to a certain range of MLs. This lidar ratio can be the input parameter for ML retrieval and enables the improvement of the extinction coefficient accuracy. The results show that the LR-APNR model is applicable to atmospheric conditions with high mineral dust or carbonaceous aerosol loading, and the maximum relative error of the ML extinction coefficient can be reduced from 46% (dust) and 64% (carbonaceous aerosol) to 20%.
Triboelectric Nanogenerators as Active Tactile Stimulators for Multifunctional Sensing and Artificial Synapses
Authors: Zeng Jianhua , Zhao Junqing , Li Chengxi , Qi Youchao , Liu Guoxu , Fu Xianpeng , Zhou Han , Zhang Chi
Published: January 2022

The wearable tactile sensors have attracted great attention in the fields of intelligent robots, healthcare monitors and human-machine interactions. To create active tactile sensors that can directly generate electrical signals in response to stimuli from the surrounding environment is of great significance. Triboelectric nanogenerators (TENGs) have the advantages of high sensitivity, fast response speed and low cost that can convert any type of mechanical motion in the surrounding environment into electrical signals, which provides an effective strategy to design the self-powered active tactile sensors. Here, an overview of the development in TENGs as tactile stimulators for multifunctional sensing and artificial synapses is systematically introduced. Firstly, the applications of TENGs as tactile stimulators in pressure, temperature, proximity sensing, and object recognition are introduced in detail. Then, the research progress of TENGs as tactile stimulators for artificial synapses is emphatically introduced, which is mainly reflected in the electrolyte-gate synaptic transistors, optoelectronic synaptic transistors, floating-gate synaptic transistors, reduced graphene oxides-based artificial synapse, and integrated circuit-based artificial synapse and nervous systems. Finally, the challenges of TENGs as tactile stimulators for multifunctional sensing and artificial synapses in practical applications are summarized, and the future development prospects are expected.
A Preliminary Study on Realizing Human–Robot Mental Comforting Dialogue via Sharing Experience Emotionally
Authors: Fu Changzeng , Deng Qi , Shen Jingcheng , Mahzoon Hamed , Ishiguro Hiroshi
Published: January 2022

Mental health issues are receiving more and more attention in society. In this paper, we introduce a preliminary study on human–robot mental comforting conversation, to make an android robot (ERICA) present an understanding of the user’s situation by sharing similar emotional experiences to enhance the perception of empathy. Specifically, we create the emotional speech for ERICA by using CycleGAN-based emotional voice conversion model, in which the pitch and spectrogram of the speech are converted according to the user’s mental state. Then, we design dialogue scenarios for the user to talk about his/her predicament with ERICA. In the dialogue, ERICA shares other people’s similar predicaments and adopts a low-spirit voice to express empathy to the interlocutor’s situation. At the end of the dialogue, ERICA tries to encourage with a positive voice. Subsequently, questionnaire-based evaluation experiments were conducted with the recorded conversation. In the questionnaire, we use the Big Five scale to evaluate ERICA’s personality. In addition, the perception of emotion, empathy, and encouragement in the dialogue are evaluated. The results show that the proposed emotional expression strategy helps the android robot better present low-spirit emotion, empathy, the personality of extroversion, while making the user better feel the encouragement.
Wearable Sensing Systems for Monitoring Mental Health
Authors: Kang Mijeong , Chai Kyunghwan
Published: January 2022

Wearable systems for monitoring biological signals have opened the door to personalized healthcare and have advanced a great deal over the past decade with the development of flexible electronics, efficient energy storage, wireless data transmission, and information processing technologies. As there are cumulative understanding of mechanisms underlying the mental processes and increasing desire for lifetime mental wellbeing, various wearable sensors have been devised to monitor the mental status from physiological activities, physical movements, and biochemical profiles in body fluids. This review summarizes the recent progress in wearable healthcare monitoring systems that can be utilized in mental healthcare, especially focusing on the biochemical sensors (i.e., biomarkers associated with mental status, sensing modalities, and device materials) and discussing their promises and challenges.
Performance Evaluation of Information Gathering from Edge Devices in a Complex of Smart Buildings
Authors: Lăcătușu Florin , Ionita Anca Daniela , Lăcătușu Marian , Olteanu Adriana
Published: January 2022

The use of monitoring systems based on cloud computing has become common for smart buildings. However, the dilemma of centralization versus decentralization, in terms of gathering information and making the right decisions based on it, remains. Performance, dependent on the system design, does matter for emergency detection, where response time and loading behavior become very important. We studied several design options based on edge computing and containers for a smart building monitoring system that sends alerts to the responsible personnel when necessary. The study evaluated performance, including a qualitative analysis and load testing, for our experimental settings. From 700+ edge nodes, we obtained response times that were 30% lower for the public cloud versus the local solution. For up to 100 edge nodes, the values were better for the latter, and in between, they were rather similar. Based on an interpretation of the results, we developed recommendations for five real-world configurations, and we present the design choices adopted in our development for a complex of smart buildings.
Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor
Authors: Kim Won-Kyu , Kim Junkyeong , Park Jooyoung , Kim Ju-Won , Park Seunghee
Published: January 2022

The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel rods, upon which tensile force is applied that cannot be managed after construction, are embedded in the pier. If there is an excessive loss of tensile force applied to the steel rods, the segments can collapse owing to the unbalanced moment, which may cause personal and property damage. Therefore, it is essential to monitor the tensile force in the temporary steel rods to prevent such accidents. In this study, a tensile force estimation method for the temporary steel rods of an FCM bridge using embedded Elasto-Magnetic (EM) sensors was proposed. After the tensile force was applied to the steel rods, the change in tensile force was monitored according to the changing area of a magnetic hysteresis curve, as measured by the embedded EM sensors. To verify the field applicability of the proposed method, the EM sensors were installed in an FCM bridge pier under construction. The three sensors were installed in conjunction with a sheath tube, and the magnetic hysteresis curve was measured over nine months. Temperature data from the measurement period were used to compensate for the error due to daily temperature fluctuations. The estimated tensile force was consistent with an error range of ±4% when compared with the reference value measured by the load cell. Based on the results of this experiment, the applicability of the proposed method was demonstrated.
Stance Analysis of Distance Education in the Kingdom of Saudi Arabia during the COVID-19 Pandemic Using Arabic Twitter Data
Authors: Alqurashi Tahani
Published: January 2022

The coronavirus has caused significant disruption to people’s everyday lives, altering how people live, work, and study. The Kingdom of Saudi Arabia (KSA) reacted very quickly to suppress the spread of the virus even before the first case of COVID-19 was confirmed in the country. In the education sector, all face-to-face activities at public and private schools and universities were suspended, as they switched from traditional to distance learning for the entire 2020 academic year. This study collected 1,846,285 tweets to analyze the public’s dynamic opinions towards distance education in the KSA during the 2020 academic year. Several classical machine-learning models and deep-learning models, including ensemble random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), multinomial naïve Bayes (MNB), convolutional neural network (CNN), and long short-term memory (LSTM), were tested on this data, and the best-performing models were selected to analyze the public stance towards distance education. Additionally, I correlated my analysis with the major events that were announced by the Ministry of Education (MOE). I observed that people in the KSA took some time to react and express their stances at the start of the academic year. Regarding the news, I observed that any exam-related topic attracted high engagement. In-favor stances increased when news headlines covered the topic of exams compared to other topics. The results show that the primary Saudi public stance favored distance education during the 2020 academic year.
A Novel Machine-Learning-Based Hybrid CNN Model for Tumor Identification in Medical Image Processing
Authors: Dhiman Gaurav , Juneja Sapna , Viriyasitavat Wattana , Mohafez Hamidreza , Hadizadeh Maryam , Islam Mohammad Aminul , El Bayoumy Ibrahim , Gulati Kamal
Published: January 2022

The popularization of electronic clinical medical records makes it possible to use automated methods to extract high-value information from medical records quickly. As essential medical information, oncology medical events are composed of attributes that describe malignant tumors. In recent years, oncology medicine event extraction has become a research hotspot in academia. Many academic conferences publish it as an evaluation task and provide a series of high-quality annotation data. This article aims at the characteristics of discrete attributes of tumor-related medical events and proposes a medical event. The standard extraction method realizes the combined extraction of the primary tumor site and primary tumor size characteristics, as well as the extraction of tumor metastasis sites. In addition, given the problems of the small number and types of annotation texts for tumor-related medical events, a key-based approach is proposed. A pseudo-data-generation algorithm that randomly replaces information in the whole domain improves the transfer learning ability of the standard extraction method for different types of tumor-related medical event extractions. The proposed method won third place in the clinical medical event extraction and evaluation task of the CCKS2020 electronic medical record. A large number of experiments on the CCKS2020 dataset verify the effectiveness of the proposed method.
Blockchain Adoption in Agricultural Supply Chain for Better Sustainability: A Game Theory Perspective
Authors: Song Luona , Luo Yiqing , Chang Zixi , Jin Chunhua , Nicolas Merveille
Published: January 2022

Within the context of the rise of the Internet of Things, blockchain, and other new technologies, telecommunications operators are committed to applying technologies to promote business transformation and upgrading. The government also actively applies technologies to traditional fields to promote social progress. In agriculture, the agricultural supply chain has a low information level and low degree of digitization. The application of blockchain technology in agriculture offers exceptional advantages because of its decentralization, openness, and transparency. Based on the application of blockchain in an agricultural scenario, an evolutionary game model made up of governments, telecom operators, and agricultural enterprises was established to analyze the model’s equilibrium stability and evolutionary stable strategy. Then, numerical simulation was carried out to study the influence of the initial green level, equipment deployment cost, technology operation cost, and other core factors on the tripartite evolution behaviour. The results show that each factor influences the behaviour of a third party in different ways. Finally, according to the simulation results, this paper puts forward practical suggestions, explores the long-term impact of the application cost and sustainable income of blockchain technology on cooperation, and provides new ideas for the governance of China’s traditional fields from the perspective of new technology application.
Flood Hazard and Risk Zonation in North Bihar Using Satellite-Derived Historical Flood Events and Socio-Economic Data
Authors: Tripathi Gaurav , Pandey Arvind Chandra , Parida Bikash Ranjan
Published: January 2022

North Bihar is one of the most flood-affected regions of India. Frequent flooding caused significant loss of life and severe economic damages. In this study, hydroclimatic conditions and historical flood events during the period of 2001 to 2020 were coupled over different basins in North Bihar. The main objective of this study is to assess the severity of floods by estimating flood hazards, vulnerability and risk in North Bihar. The uniqueness of this study is to assess flood risk at the village level as no such study was performed earlier. Other thematic data, namely, land-use and drainage networks, were also utilised with flood maps to validate the severity of the event. MOD09A1 satellite data (during 2001–2020) derived indices were used to derive inundation extents and flood frequency. Socio-economic vulnerability (SEV) was derived based on seven census parameters (i.e., population density, house-hold density, literacy rate, agricultural labour, and cultivator, total male, and female) and coupled with flood hazard to derive flood risk over the study region. The study exhibited that a total ~34% of the geographical area of North Bihar was inundated in the last 20 years and the maximum flood extent was seen in 2020. Flood risk map exhibited that ~7%, ~8%, ~13%, ~4%, and ~2% of the geographical area was mapped under Very High, High, Moderate, Low, and Very Low categories, respectively. The 2770 and 3535 number of villages was categorized under Very High and High flood risk zone which are located in north-central and central-western regions. These findings can be applied to distinguish and classify areas of various risk zones to assist in flood mitigation and management activities.
Performance of Socially Responsible Investment Funds in China: A Comparison with Traditional Funds
Authors: Saci Fateh , Jasimuddin Sajjad M. , Hasan Morshadul
Published: January 2022

This paper empirically examines and compares social responsibility investment funds to traditional funds, and explores the performance of the existing social responsibility investment funds in China. Based on 64 social responsibility investment funds (SRI Funds) and 64 traditional funds, this paper extracts the data of the sample fund from the fourth quarter of 2016 to the fourth quarter of 2019 as sample data to conduct a comparative analysis of the difference between the SRI fund and the traditional fund in terms of return and risk, and to then empirically study the performance of the funds. The results show that the difference between the return of China’s socially responsible investment funds and the traditional funds is insignificant, and the risk of socially responsible investment funds is significantly lower than that of traditional funds. The regression analysis is also carried out on a model of social responsibility as a factor affecting the performance of the funds. Subsequently, the results show that social responsibility has a significant positive impact on the fund’s return in the Chinese market.
A Study on Temporal Effects of Different Types of Mobile Application Updates
Authors: Lin Feiyan , Zhao Jing , Chi Maomao
Published: January 2022

The sustainability of market performance of mobile applications (apps) updates is a vital goal for e-commerce firms to continuously innovate for products and functions. E-commerce firms must formulate effective app update strategies and tackle the temporal uncertainties associated with different types of app updates. However, the existing literature on app updates mainly focuses on the effects of update frequency. At the same time, scant attention has been paid to clarifying the temporal effects of different types of app updates. Accordingly, based on the framework of exploration vs. exploitation, we investigate the temporal effects of different kinds of app updates on market performance in the hypercompetitive context of online travel mobile applications. We collected data on release notes and downloads of seven Chinese online travel apps available from the Android Market from April 2013 to January 2015; conducted structured content analysis to identify different types of app updates; and adopted the feasible generalized least-squares (FGLS) estimation to test our model. We found that exploitative app updates have an instant and continuous positive impact on market performance, while explorative app updates have no significant effect in the short term but will have a positive effect on market performance in the long term. Moreover, competition intensity shortens the duration of the positive effect of exploitative app updates and delays the time that explorative app updates have to take effect. By studying the different impacts that two types of app updates have on market performance from a time dimension, this study helps resolve the mixed findings on the effects of app updates and guides e-commerce firms on how to effectively formulate app update strategies in a hypercompetitive context.
History of Grape in Anatolia and Historical Sustainable Grape Production in Erzincan Agroecological Conditions in Turkey
Authors: Taskesenlioglu Muhammed Yasin , Ercisli Sezai , Kupe Muhammed , Ercisli Nazan
Published: January 2022

The Anatolian peninsula has long been linked with the origins of viticulture and winemaking. Erzincan province in Anatolia hosted many civilizations in the past, and each civilization used grapes for different purposes. From past to present, viticulture carried out with the famous ‘Karaerik’ grape (Vitis vinifera L.) on old traditional Baran training system to avoid cold damage occurred in winter months. During the old civilizations, the cultivar was used only for wine production, but after the first period of the 1900s, this situation changed, and the cultivar was used for table consumption because wine is banned by Islam. The archaeological findings in Erzincan province revealed the cultivar has existed in the province for centuries, and in each historical period, the cultivar was used sustainably, added value to the region, and brought cultural heritage from generation to generation. Grape production in Erzincan province has been a symbol of abundance, fertility and productivity since mythological times. The historical facts indicated that viticulture and winemaking had been a dispensable part of the Erzincan economy and rural development. The vineyards apply the same sustainable management practices from which they receive their grapes. The traditional Baran training system is used for all vineyards. The viticulture in the province has been strongly committed to improving environmental and social sustainability throughout history.
The Volumetric Method Describing the Life Cycle of Power Tools during Their Production with Different Ends of Life
Authors: Sovják Richard , Tichá Marie , Fridrichová Eva
Published: January 2022

The amount of power consumption of the product life cycle has a significant impact on global warming. To determine these negative impacts, life cycle assessment (LCA) is used. These methods are time-consuming and expensive training costs that require the characteristics of the mass and material characteristics of the products. The aim of the present study was to develop a method that uses only product typology and volumetric product properties without knowing the structural and material composition. To achieve the objective, 134 pieces of power tools were used, divided into 10 groups according to their type. The volume of the product was determined by 3D scanning with subsequent material and the LCA method based on the Oil Point Method (OPM). The end of life (EoL) of the product was evaluated in landfilling, combustion, and 90% recycling variants. Equations were obtained from Monte Carlo Simulation with 95% reliability and allowed the determination of the energy requirements for the production of power tools and CO2 emissions, including data for packaging and transport of goods. The Volumetric Evaluating Method of Ecodesign (VEME) can quickly evaluate impact in three EoL procedures and optimise the volume of power tools and the location of production of products without LCA knowledge.
Graviton Mass in the Era of Multi-Messenger Astronomy
Authors: Piórkowska-Kurpas Aleksandra
Published: January 2022

The idea of massive graviton plays a fundamental role in modern physics as a landmark of most scenarios related to modified gravity theories. Limits on graviton mass can be obtained through different methods, using all the capabilities of multi-messenger astronomy available today. In this paper, we consider some emerging opportunities. In particular, modified relativistic dispersion relations of massive gravitons may lead to changes in the travel time of gravitational waves (GWs) emitted from distant astrophysical objects. Strong gravitational lensing of signals from a carefully selected class of extra-galactic sources such as compact object binaries (actually, binary neutron stars) is predicted to play an important role in this context. Comparing time delays between images of the lensed GW signal and its electromagnetic (EM) counterpart may be a new model-independent strategy (proposed by us in X.-L. Fan et al., 2017), which is especially promising in light of the fruitful observing runs of interferometric GW detectors, resulting in numerous GW signals. In addition to this direct, kinematic method, one can use an indirect, static method. In this approach, the non-zero graviton mass would modify estimates of the total cluster mass via a Yukawa term, influencing the Newtonian potential. In A. Piórkowska-Kurpas et al., 2022, using the X-COP galaxy cluster sample, we obtained mg<(4.99−6.79)×10−29 eV (at 95% C.L.), which is one of the best available constraints.
Levistolide A Inhibits PEDV Replication via Inducing ROS Generation
Authors: Zeng Wei , Ren Jingping , Li Zhonghua , Jiang Changsheng , Sun Qi , Li Chang , Li Wan , Li Wentao , He Qigai
Published: January 2022

Porcine epidemic diarrhea virus (PEDV) variant strains adversely affect the production of pigs globally. Vaccines derived from PEDV traditional strains impart less protection against the variant strains. Moreover, sequence diversity among different PEDV variant strains is also complicated. This necessitates developing alternative antiviral strategies for defending against PEDV. This study explored a natural product, Levistolide A (LA), to possess antiviral activity against PEDV. LA was found to suppress PEDV replication in a dose-dependent manner. And the inhibitory effect of LA against PEDV was maintained in the course of time. In terms of viral RNA and protein production, LA also showed a strong inhibitory effect. In addition, LA was indicated to inhibit PEDV from attaching to the cellular membrane or penetrating the cells. Further study revealed that LA can induce the generation of reactive oxygen species (ROS), and the corresponding inhibitor, NAC, was found to antagonize the effect of LA on inhibiting PEDV replication. This illustrated that the LA-induced ROS generation played an important role in its anti-PEDV activity. LA was also identified to stimulate ER stress, which is an important consequence of ROS production and was proven to be able to inhibit PEDV replication. To conclude, this study revealed that LA can inhibit PEDV replication via inducing ROS generation.
Characterization of the Novel Phage vB_VpaP_FE11 and Its Potential Role in Controlling Vibrio parahaemolyticus Biofilms
Authors: Yang Meiyan , Chen Hanfang , Huang Qiaolan , Xie Zhuanbei , Liu Zekun , Zhang Jumei , Ding Yu , Chen Moutong , Xue Liang , Wu Qingping , Wang Juan
Published: January 2022

Vibrio parahaemolyticus causes aquatic vibriosis. Its biofilm protects it from antibiotics; therefore, a new different method is needed to control V. parahaemolyticus for food safety. Phage therapy represents an alternative strategy to control biofilms. In this study, the lytic Vibrio phage vB_VpaP_FE11 (FE11) was isolated from the sewers of Guangzhou Huangsha Aquatic Market. Electron microscopy analysis revealed that FE11 has a typical podovirus morphology. Its optimal stability temperature and pH range were found to be 20–50 °C and 5–10 °C, respectively. It was completely inactivated following ultraviolet irradiation for 20 min. Its latent period is 10 min and burst size is 37 plaque forming units/cell. Its double-stranded DNA genome is 43,397 bp long, with a G + C content of 49.24% and 50 predicted protein-coding genes. As a lytic phage, FE11 not only prevented the formation of biofilms but also could destroy the formed biofilms effectively. Overall, phage vB_VpaP_FE11 is a potential biological control agent against V. parahaemolyticus and the biofilm it produces.
The Candidate Antigens to Achieving an Effective Vaccine against Staphylococcus aureus
Authors: Jahantigh Hamid Reza , Faezi Sobhan , Habibi Mehri , Mahdavi Mehdi , Stufano Angela , Lovreglio Piero , Ahmadi Khadijeh
Published: January 2022

Staphylococcus aureus (S. aureus) is an opportunistic pathogen that causes various inflammatory local infections, from those of the skin to postinfectious glomerulonephritis. These infections could result in serious threats, putting the life of the patient in danger. Antibiotic-resistant S. aureus could lead to dramatic increases in human mortality. Antibiotic resistance would explicate the failure of current antibiotic therapies. So, it is obvious that an effective vaccine against S. aureus infections would significantly reduce costs related to care in hospitals. Bacterial vaccines have important impacts on morbidity and mortality caused by several common pathogens, however, a prophylactic vaccine against staphylococci has not yet been produced. During the last decades, the efforts to develop an S. aureus vaccine have faced two major failures in clinical trials. New strategies for vaccine development against S. aureus has supported the use of multiple antigens, the inclusion of adjuvants, and the focus on various virulence mechanisms. We aimed to present a compressive review of different antigens of S. aureus and also to introduce vaccine candidates undergoing clinical trials, from which can help us to choose a suitable and effective candidate for vaccine development against S. aureus.
Evaluation of the COVID-19 Lockdown-Adapted Online Methodology for the Cytology and Histology Course as Part of the Degree in Veterinary Medicine
Authors: Balseiro Ana , Pérez-Martínez Claudia , de Paz Paulino , García Iglesias María José
Published: January 2022

The COVID-19 pandemic and lockdown brought numerous teaching challenges requiring innovative approaches to teaching and learning, including novel modes of content delivery, virtual classrooms, and online assessment schemes. The aim of this study is to describe and assess the efficacy of the methods implemented at the University of León (Spain) to adapt to lockdowns in the context of the Cytology and Histology (CH) course for veterinary medicine undergraduate students. To evaluate the success of lockdown-adapted methodologies, we used inferential statistical analysis to compare the academic outcomes of two cohorts: 2018–2019 (traditional face-to-face—presential—learning and evaluation) and 2019–2020 (some face-to-face and some online lockdown-adapted learning and online lockdown-adapted evaluation). This analysis considered scores in both theoretical and practical exams and students’ final subject score. We also evaluated the number of logs onto the Moodle platform throughout the 2019–2020 period, as well as performing a student satisfaction survey in both courses. The use of explanatory pre-recorded lectures, continuous online self-assessment tests, and virtual microscopy (VM) may have produced significant improvements in the acquisition of histology competencies among students in the lockdown cohort. However, we need to implement further strategies to improve the assessment of students’ true level of knowledge acquisition. According to the student feedback, VM is a well-accepted resource that is perceived as a flexible and enjoyable tool to use. However, while students found that the resource enhances their ability to learn about microscopic structures, they felt that it should not completely replace optical microscopy.
Characteristics of Ions Composition and Chemical Weathering of Tributary in the Three Gorges Reservoir Region: The Perspective of Stratified Water Sample from Xiaojiang River
Authors: Wang Di , Han Guilin , Li Bogen , Hu Mingming , Wang Yuchun , Liu Jinke , Zeng Jie , Li Xiaoqiang
Published: January 2022

River water chemistry offers information on watershed weathering and responds to the global carbon cycle. Watershed weathering processes and water chemistry in stratified water are still unclear in Xiaojiang River, as a major tributary of the Three Gorges Reservoir (TGR) which is the largest reservoir in the world. Major ions of river water at different depths were measured to reveal the ionic composition and chemical weathering properties by principal component analysis and stoichiometry in Xiaojiang River. Ca2+−HCO3− dominated the hydrochemical facies of river. Surface river water had the lowest total dissolved solid (146 mg/L) compared to other layers of water. According to principal component analysis, the major ions were divided into two principal components. PC1 was the weathering end-member of rocks, including the main ions except K+ and NO3–N, and PC2 may be the mixed end-member of atmospheric input and anthropogenic input. From stoichiometry, carbonate weathering dominated the cationic composition, with a contribution ratio of 56.7%, whereas atmospheric input (15.2%) and silicates weathering (13.9%) had similar extent of contribution. Compared with other major tributaries of TGR, Xiaojiang had more intense chemical weathering processes. The weathering rates of carbonates and silicates were 19.33 ± 0.68 ton/km2/year and 3.56 ± 0.58 ton/km2/year, respectively. Sulfuric acid as a proton may have participated less in the weathering processes of Xiaojiang River. The CO2 consumption budgets for silicates and carbonates weathering were 0.8 ± 0.2 × 109 mol/year and 2.8 ± 0.2 × 109 mol/year, respectively. These results enrich the watershed weathering information of TGR tributaries and provide data support for understanding the global carbon cycle.
Forest Fires, Land Use Changes and Their Impact on Hydrological Balance in Temperate Forests of Central Mexico
Authors: Ruíz-García Víctor H. , Borja de la Rosa Ma. Amparo , Gómez-Díaz Jesús D. , Asensio-Grima Carlos , Matías-Ramos Moisés , Monterroso-Rivas Alejandro I.
Published: January 2022

Temperate forests play a fundamental role in the provision, regulation, and support of hydrological environmental services, but they are subject to constant changes in land use (clearing, overgrazing, deforestation, and forest fires) that upset the hydrological balance. Through scenarios simulated with the Water Evaluation and Planning (WEAP) hydrological model, the present study analyzes the effects of forest fires and land use changes on the hydrological balance in the microwatersheds of central Mexico. The land use changes that took place between 1995 and 2021 were estimated, and projections based on the current scenario were made. Two trend scenarios were proposed for 2047: one with a positive trend (forest permanence) and the other with a negative trend (loss of cover from forest fires). The results show that with permanence or an increase in forest area, the surface runoff would decrease by 48.2%, increasing the base flow by 37% and the soil moisture by 2.3%. If forest is lost, surface runoff would increase up to 454%, and soil moisture would decrease by 27%. If the current forest decline trends continue, then there will be negative alterations in hydrological processes: a reduction in the interception of precipitation by the canopy and an increase in the velocity and flow of surface runoff, among others. The final result will be a lower amount of water being infiltrated into the soil and stored in the subsoil. The provision of hydrological environmental services depends on the maintenance of forest cover.
Impact of Historical Agrarian Landforms on Soil Water Content Variability at Local Scale in West Carpathian Region, Slovakia
Authors: Kenderessy Pavol , Dobrovodská Marta , Šatalová Barbora , Vlachovičová Miriam , Palaj Andrej
Published: January 2022

The historical agrarian landforms (AL) represent man-made features that alter the hydrological process on cultivated hillslopes. Soil water content (SWC) and its spatial and temporal variability represent an important state indicator for understanding of these processes. In order to assess the differences between individual AL in terms of SWC stability, continuous soil moisture measurements at five different monitoring localities characterized by a specific combination of AL and environmental factors were performed. Temporal SWC stability was evaluated using mean relative difference (MRD) and its standard deviation (SDRD). Differences in mean SWC and MRD values demonstrated the difference between saturated inner part of the AL and external parts such as terraced slopes and mounds, soil depths, and slope positions. In order to analyze the relationship between SWC and environmental variables, the methods of constrained ordination were applied. The most influential factors that regulate SWC variability during the periods of rain were identified as: stone content, sand fraction content, slope orientation, type of agrarian landform, and its orientation against the contour lines. Results also pointed to the fact that different factors predominate among individual localities and, therefore, SWC variability reflects the effect of combination of various environmental factors rather than effect of single parameter. Besides the improved understanding of SWC variability, our results also highlight the importance of AL in regulating the hydrological processes at historical agricultural landscape of the West Carpathian region.
Spatio-Temporal Dynamics in Physico-Chemical Properties, Phytoplankton and Bacterial Diversity as an Indication of the Bovan Reservoir Water Quality
Authors: Zlatković Slobodan , Medić Olja , Predojević Dragana , Nikolić Ivan , Subakov-Simić Gordana , Onjia Antonije , Berić Tanja , Stanković Slaviša
Published: January 2022

The study aimed to investigate the physico-chemical properties as well as phytoplankton and bacterial community diversity of Bovan Lake reservoir in Serbia to gain insight into the seasonal dynamic of water quality. All analyses were performed at three localities and water depths in spring, summer, autumn, and winter 2019. Seven phytoplankton phyla comprising 139 taxa were detected at all three localities (Chlorophyta 58%, Bacillariophyta 14%, Cyanobacteria 9%, Chrysophyta 5%, Dinophyta 5%, Euglenophyta 5%, and Cryptophyta 4%). Winter 2019 was characterized by the presence of 36 unique species in all phyla except Euglenophyta. Bacterial diversity analyses showed that Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, and Verrucomicrobia dominated the water intake locality at all three water depths (0.5, 10, and 20 m below the surface). In general, the physico-chemical parameters, phytoplankton, and bacterial community composition depended on the season and the water depth and showed that Bovan Lake was of satisfactory ecological status and water quality at all localities, and meets the needs for all intended purposes.
Development of the tourism and hospitality industry based on the cluster approach
Authors: Kochkurova E. A. , Zykova T. V. , Shimin N. A.
Published: January 2022

The article discusses the issues of increasing the competitiveness of the tourism and hospitality industry based on innovative approaches to the formation of a cluster structure. The essence of cluster formations in the tourism and hospitality industry of the Nizhny Novgorod region is analyzed — their goals, objectives and components; the system of relations within clusters, industry, organizational and functional structure, the advantages and disadvantages of the cluster approach to the development of the tourism industry in the studied area are listed.
Sistemas de control y seguridad alimentaria en los restaurantes del Parque del Marisco de la ciudad de Manta
Authors: Viera Emil
Published: January 2022

Los sistemas y controles de seguridad alimentaria en restaurantes garantizan la calidad, asegurando el éxito del negocio. El objetivo del trabajo es diagnosticar la aplicación de los sistemas de control y seguridad alimentaria en los restaurantes del Parque del Marisco de la ciudad de Manta, Ecuador. Se empleó el método descriptivo-cuali-cuantitativo y técnicas partiendo de la observación no estructurada, aplicando encuesta y entrevista a trabajadores, administradores y propietarios de los restaurantes. Los resultados reflejaron un nivel medio-bajo en conocimientos sobre sistemas de control y seguridad alimentaria; se manifiestan además coincidencias en las respuestas sobre la necesidad de fortalecer el nivel de competencias en sistemas y controles de seguridad alimentaria y falencias en la aplicación de normativas referidas a la seguridad alimentaria que garantizan el mejoramiento en la calidad de los servicios gastronómico