bluuebunny/crossref_metadata_2025 huggingface dataset:
A Transferable Learning Classification Model and Carbon Sequestration Estimation of Crops in Farmland Ecosystem
Authors: Wang Lijun , Bai Yang , Wang Jiayao , Qin Fen , Liu Chun , Zhou Zheng , Jiao Xiaohao
Published: October 2022

Frequent agricultural activities in farmland ecosystems bring challenges to crop information extraction from remote sensing (RS) imagery. The accurate spatiotemporal information of crops serves for regional decision support and ecological assessment, such as disaster monitoring and carbon sequestration. Most traditional machine learning algorithms are not appropriate for prediction classification due to the lack of historical ground samples and poor model transfer capabilities. Therefore, a transferable learning model including spatiotemporal capability was developed based on the UNet++ model by integrating feature fusion and upsampling of small samples for Sentinel-2A imagery. Classification experiments were conducted for 10 categories from 2019 to 2021 in Xinxiang City, Henan Province. The feature fusion and upsampling methods improved the performance of the UNet++ model, showing lower joint loss and higher mean intersection over union (mIoU) values. Compared with the UNet, DeepLab V3+, and the pyramid scene parsing network (PSPNet), the improved UNet++ model exhibits the best performance, with a joint loss of 0.432 and a mIoU of 0.871. Moreover, the overall accuracy and macro F1 values of prediction classification results based on the UNet++ model are higher than 83% and 58%, respectively. Based on the reclassification rules, about 3.48% of the farmland was damaged in 2021 due to continuous precipitation. The carbon sequestration of five crops (including corn, peanuts, soybean, rice, and other crops) is estimated, with a total carbon sequestration of 2460.56, 2549.16, and 1814.07 thousand tons in 2019, 2020, and 2021, respectively. The classification accuracy indicates that the improved model exhibits a better feature extraction and transferable learning capability in complex agricultural areas. This study provides a strategy for RS semantic segmentation and carbon sequestration estimation of crops based on a deep learning network.
An Efficient Method to Compensate Receiver Clock Jumps in Real-Time Precise Point Positioning
Authors: Xu Shaoguang , Long Jialu , Wang Jinling , Zhang Wenhao
Published: October 2022

In global navigation satellite systems (GNSSs)-based positioning, user receiver clock jump is a common phenomenon on the low-cost receiver clocks and can break the continuity of observation time tag, carrier phase and pseudo range. The discontinuity may affect precise point positioning-related parameter estimation, including receiver clock error, position, troposphere and ionosphere parameters. It is important to note that these parameters can be used for timing, positioning, atmospheric inversion and so on. In response to this problem, the receiver clock jumps are divided into two types. The first one can be expressed by the carrier phase and pseudo range having the same scale jump, and the second one is that they are having different scale jumps. For the first type, if a small priori variance of receiver clock error is provided, it can affect the accuracy of ionospheric delay estimation both in static and kinematic mode, while in the latter mode, it also affects position estimation. However, if large process noise is provided, numerical problems may arise since other parameters’ process noises are usually small, it is proposed to use the single point positioning with pseudo ranges to provide a priori value of receiver clock error, and an empiric value is assigned to its prior variance, this handle can avoid the above problems. For the second type, instead of compensating so many raw observations in the traditional methods, it is proposed to compensate the ambiguities at the clock jump epochs only in a new method. The new method corrects the Melbourne–Wubbena (MW) combination firstly in order to avoid the misjudging of cycle slips for current epoch, and the second step is to compensate the corresponding ambiguities, then, after Kalman filtering, the MW and its mean should be corrected back in order to avoid the misjudging of cycle slips at the next epoch. This approach has the advantage of handling the clock jump epoch-wise and can avoid correcting the rest of the observations as the traditional methods used to. With the numerical validation examples both in static and kinematic modes, it shows the new method is simple but efficient for real time precise point positioning (PPP).
The Use of Terrestrial and Maritime Autonomous Vehicles in Nonintrusive Object Inspection
Authors: Mamchur Dmytro , Peksa Janis , Kolodinskis Antons , Zigunovs Maksims
Published: October 2022

Traditional nonintrusive object inspection methods are complex or extremely expensive to apply in certain cases, such as inspection of enormous objects, underwater or maritime inspection, an unobtrusive inspection of a crowded place, etc. With the latest advances in robotics, autonomous self-driving vehicles could be applied for this task. The present study is devoted to a review of the existing and novel technologies and methods of using autonomous self-driving vehicles for nonintrusive object inspection. Both terrestrial and maritime self-driving vehicles, their typical construction, sets of sensors, and software algorithms used for implementing self-driving motion were analyzed. The standard types of sensors used for nonintrusive object inspection in security checks at the control points, which could be successfully implemented at self-driving vehicles, along with typical areas of implementation of such vehicles, were reviewed, analyzed, and classified.
Portuino—A Novel Portable Low-Cost Arduino-Based Photo- and Fluorimeter
Authors: Di Nonno Sarah , Ulber Roland
Published: October 2022

A novel portable low-cost Arduino-controlled photo- and fluorimeter for on-site measurements has been developed. The device uses LEDs as a light source and a phototransistor as a light sensor. The circuit is based on the discharge of a capacitor with the photocurrent from the phototransistor. Validation experiments for absorbance measurements were performed by measuring protein concentration using the Bradford method and measuring phosphate ions in water using a commercial test kit. The emission light of the excited fluorescent dyes rhodamine 6G and calcofluor white was measured to validate the usability of the device as a fluorescence photometer. In all validation experiments, similar correlation coefficients and limit of detection could be achieved with the portable photo- and fluorimeter and a laboratory spectrometer and fluorimeter. Real sample analysis was performed, measuring phosphate concentration in freshwater and concentration of green fluorescent protein, extracted from Escherichia coli.
Visual Relationship Detection with Multimodal Fusion and Reasoning
Authors: Xiao Shouguan , Fu Weiping
Published: October 2022

Visual relationship detection aims to completely understand visual scenes and has recently received increasing attention. However, current methods only use the visual features of images to train the semantic network, which does not match human habits in which we know obvious features of scenes and infer covert states using common sense. Therefore, these methods cannot predict some hidden relationships of object-pairs from complex scenes. To address this problem, we propose unifying vision–language fusion and knowledge graph reasoning to combine visual feature embedding with external common sense knowledge to determine the visual relationships of objects. In addition, before training the relationship detection network, we devise an object–pair proposal module to solve the combination explosion problem. Extensive experiments show that our proposed method outperforms the state-of-the-art methods on the Visual Genome and Visual Relationship Detection datasets.
Underlying Security Transmission Design for Orthogonal Time Frequency Space (OTFS) Modulation
Authors: Liang Wei , Liu Xuan , Shi Jia , Li Lixin , Hu Junfan
Published: October 2022

With the aim of ensuring secure transmission in high-mobility wireless scenarios, this paper proposes a 2D permutation-aided Orthogonal Time Frequency Space (OTFS) secure transmission scheme, which uses the Gosudarstvennyi Standard (GOST) algorithm to perform disturbance control on the OTFS modulation domain. Furthermore, we develop an improved SeLective Mapping (SLM) algorithm, which can significantly improve the Peak-to-Average Power Ratio (PAPR) problem with very low complexity. In addition, we carry out the security analysis, investigating the proposed scheme’s resistance performance to a range of effective attacks. Finally, our numerical results show that our proposed transmission scheme can guarantee the underlying security property of OTFS.
Towards Online Ageing Detection in Transformer Oil: A Review
Authors: Elele Ugochukwu , Nekahi Azam , Arshad Arshad , Fofana Issouf
Published: October 2022

Transformers play an essential role in power networks, ensuring that generated power gets to consumers at the safest voltage level. However, they are prone to insulation failure from ageing, which has fatal and economic consequences if left undetected or unattended. Traditional detection methods are based on scheduled maintenance practices that often involve taking samples from in situ transformers and analysing them in laboratories using several techniques. This conventional method exposes the engineer performing the test to hazards, requires specialised training, and does not guarantee reliable results because samples can be contaminated during collection and transportation. This paper reviews the transformer oil types and some traditional ageing detection methods, including breakdown voltage (BDV), spectroscopy, dissolved gas analysis, total acid number, interfacial tension, and corresponding regulating standards. In addition, a review of sensors, technologies to improve the reliability of online ageing detection, and related online transformer ageing systems is covered in this work. A non-destructive online ageing detection method for in situ transformer oil is a better alternative to the traditional offline detection method. Moreover, when combined with the Internet of Things (IoT) and artificial intelligence, a prescriptive maintenance solution emerges, offering more advantages and robustness than offline preventive maintenance approaches.
Global Navigation Satellite System Real-Time Kinematic Positioning Framework for Precise Operation of a Swarm of Moving Vehicles
Authors: Kim Euiho , Kim Sae-kyeol
Published: October 2022

The global navigation satellite system (GNSS) real-time kinematic (RTK) technique is used to achieve relative positioning centimeter levels among multiple agents on the move. A typical GNSS RTK estimates the relative positions of multiple rover receivers with respect to a single-base receiver. In a fleet of rover GNSS receivers, this approach is inefficient because each rover receiver only uses GNSS measurements of its own and those sent from a single-base receiver. In this study, we propose a novel GNSS RTK framework that facilitates the precise positioning of a swarm of moving vehicles through the GNSS measurements of multiple receivers and broadcasts fixed-integer ambiguities of GNSS carrier phases. The proposed framework not only provides efficient RTK positioning but also reliable performance with a limited number of GNSS satellites in view. Our experimental flight tests with six GNSS receivers showed that the systematic procedure of the proposed framework could maintain lower than 6 cm of 3D RMS positioning errors, whereas the conventional RTK failed to resolve the correct integer ambiguities of double difference carrier phase measurements more than 13% in five out of nine total baselines.
A Novel Scheme for Discrete and Secure LoRa Communications
Authors: Demeslay Clément , Gautier Roland , Rostaing Philippe , Burel Gilles , Fiche Anthony
Published: October 2022

In this paper, we present a new LoRa transceiver scheme to ensure discrete communications secure from potential eavesdroppers by leveraging a simple and elegant spread spectrum philosophy. The scheme modifies both preamble and payload waveforms by adapting a current state-of-the-art LoRa synchronization front-end. This scheme can also be seen as a self-jamming approach. Furthermore, we introduce a new payload demodulation method that avoids the adverse effects of the traditional cross-correlation solution that would otherwise be used. Our simulation results show that the self-jamming scheme exhibits very good symbol error rate (SER) performance with a loss of just 0.5 dB for a frequency spread factor of up to 10.
LBSS: A Lightweight Blockchain-Based Security Scheme for IoT-Enabled Healthcare Environment
Authors: Said Omar
Published: October 2022

Recently, global healthcare has made great progress with the use of Internet of Things technology. However, for there to be excellent patient care, there must be a high degree of safety for the IoT health system. There has been a massive increase in hacking systems and the theft of sensitive and highly confidential information from large health centers and hospitals. That is why establishing a highly secure and reliable healthcare system has become a top priority. In this paper, a security scheme for the IoT-enabled healthcare environment, LBSS, is proposed. This security scheme comprises three security mechanisms. The first mechanism is based on the blockchain technology and is used for transaction integrity. The second mechanism is used to store the healthcare system data in a secure manner through the distribution of its data records among multiple servers. The third mechanism is used to access the healthcare data after applying a proposed authorization test. To minimize the security overhead, the healthcare data is prioritized in regard to its importance. Therefore, each security mechanism has specific steps for each level of data importance. Finally, the NS3 package is used to construct a simulation environment for IoT-enabled healthcare systems to measure the proposed security scheme performance. The simulation results proved that the proposed healthcare security scheme outperformed the traditional models in regard to the performance metrics.
Calculation Method for Investigating the Behavior of Ground Surface Settlement of Underpass Buildings in TBM Double-Line Tunnels
Authors: Ren Ting , Zhang Hailong , Guo Yuancheng , Tang Yang , Li Qinglin , Okubo Seisuke
Published: October 2022

This study aims to investigate the behavior of ground surface settlement in TBM double-line tunnels constructed under existing buildings and to devise a calculative representation for that behavior. Numerical simulation and field monitoring methods were used to examine the Zhongcong Tunnel in Chongqing Metro Line 9. The ground surface settlement was analyzed using an orthogonal test of 3D numerical simulation methods. The results showed that ground surface settlement was influenced by TBM tunneling parameters and the location of the existing building in the following manner. The existing building reduced the settlement trough width. Surface settlement was increased by frictional and palm surface thrust forces but reduced by grouting pressure. The settlement trough width of the first excavation iz correlated with that of the last excavation iy. To accommodate the influence of existing buildings, the tilt factor of the settlement trough TR was introduced to improve the formula for calculating the ground surface settlement of TBM double-line tunnels. The improved formula was validated by comparing the calculated results with actual measurements.
Feasibility Analysis of Biogas Production by Using GIS and Multicriteria Decision Aid Methods in the Central African Republic
Authors: Dima Francis Auguste Fleury Junior , Li Zifu , Mang Heinz-Peter , Zhu Lixin
Published: October 2022

Organic waste-derived biogas production is an effective way to transform biowaste into renewable energy for the electricity supply in developed and developing countries. This study analyzes the feasibility of biogas production as a solution to waste management and electricity supply in Bangui, the capital city of the Central African Republic. The selection of the biogas plant site in an urban area is a complex process due to the area availability and different factors. The GIS, combined with the MCDA, could analyze the environmental, social, and economic factors and criteria such as slope, settlement, rivers, land, urban growth, and local and major roads. Applying the ELECTRE TRI as the MCDA method enhanced the techniques to determine the suitable biogas plant site. The biowaste amount and distance from the suitable site were determined using the ArcGIS distance toolset. The biogas plant’s economic and environmental benefits, such as the electricity production capacity and CO2 reduction, were analyzed based on the population growth and the biogas production per year. The analyzed results obtain an area of 3.5 km2 for a large-scale biogas plant construction, with a potential production of 2,126,799.68 kW per year using combined heat and power and 2,303,100.23 kW by converting the thermal energy to electricity. This large-scale biogas plant could treat 20% of the organic waste per year, cover 60% of the city’s electricity demand, and reduce 946,200 kg of CO2 equivalent per year.
Prediction of Tunnelling Parameters for Underwater Shield Tunnels, Based on the GA-BPNN Method
Authors: Liang Yu , Jiang Kai , Gao Shijun , Yin Yihao
Published: October 2022

Reasonable tunnelling parameters for underwater shield tunnels play an important role in maintaining driving efficiency and safety. In this paper, a neural network method was developed to predict tunnelling parameters. Soil properties and geometric parameters were taken as inputs for the neural network, which output the tunnelling parameters, such as advancing thrust, rotation, penetration, torque of the cutter head, and support pressure. In order to improve the stability of the neural network, a genetic algorithm (GA) with a global searching ability was used to optimize the initial weight of the neural network (GA-BPNN). The accuracy of the algorithm, based on GA-BPNN, was studied through an underwater shield tunnel project. The results showed that the integration of GA into the neural network significantly improves the prediction ability for shield tunnelling parameters, especially for adjustable parameters. Later, the developed GA-BPNN model was further utilized to predict and set the range of shield tunnelling parameters in fine sand stratum of high risk. Through a comparative analysis of tunnelling parameters, the reasons leading to ground instability have been found out, and the effectiveness of ground pre-reinforcement has been verified.
Spatiotemporal Change of Urban Ecologic Environment Quality Based on RSEI—Taking Meizhou City, China as an Example
Authors: Chen Zhiyun , Chen Renrong , Guo Quan , Hu Yinglong
Published: October 2022

An ecological index that is constructed based on remote sensing images can enable a rapid evaluation of the quality of the urban ecological environment and can provide a scientific basis for the construction of urban ecological civilization. Taking Meizhou City, in Guangdong in China, as a study area, based on the Landsat TM/OLI and MODIS remote sensing data, this paper extracts the total primary productivity (GPP), land surface temperature (LST), humidity component (Wetness), and bare soil index (SI), which represent the remote sensing ecological index (RSEI) evaluation indicators. The greenness, heat, humidity, and dryness in the indicators are used to characterize the quality of the regional ecological environment and its change characteristics. The results show that: (1) the high-quality areas of ecological environment in the study area are increasing, and the proportion of high-grade RSEI areas has increased from 61.7% to 66.2%. (2) About 26.3% of the area in the study area has an optimized ecological environment quality. (3) The correlation between POI and each index is significant, among which GPP and LST have a high correlation with RSEI, while POI and RSEI have a moderately negative correlation. (4) MODIS data are suitable for regional ecological environmental quality assessments. In the future, research on RSEI data sources and processing efficiency and the spatiotemporal changes of ecological quality and environmental factors can be strengthened, and the sustainable development of ecological protection and urban construction planning can be explored.
Foldscope Embedded Pedagogy in Stem Education: A Case Study of SDG4 Promotion in India
Authors: Kulshreshtha Parul , Gupta Sunita , Shaikh Rafikh , Aggarwal Divya , Sharma Deuvshree , Rahi Praveen
Published: October 2022

Most government schools and colleges run on low budgets in India, yet they cater to a large population of students. In government settings, biology labs lack basic equipment such as simple microscopes or compound microscopes or sometimes possess just one instrument. In the absence of compound or simple microscopes, the students lose interest in science. To solve this issue, the Department of Biotechnology, Ministry of Science and Technology, Government of India, introduced the origami microscope, the foldscope, into the Indian educational system. In this article, we describe the design of a sustainable, inclusive, and equitable curricula for teaching biological concepts using the foldscope. We describe the implementation of foldscope-adapted curricula in post-secondary settings to teach natural selection, developmental biology, parasitology, and economic Zoology via individual, small-group, and large-group field trips, and project-based learning that involves experiential learning. We found that these culturally sensitive pedagogies involving translingual instructions had the potential to retain students and make science education accessible for the linguistically and culturally diverse population of India. We could successfully implement our project as per the five priority action areas outlined by UNESCO. Therefore, we propose the adoption of the foldscope-adapted curricula under SDG4 to make STEM education accessible in budget-frugal settings.
An Empirical Study of Factors Influencing the Perceived Usefulness and Effectiveness of Integrating E-Learning Systems during the COVID-19 Pandemic Using SEM and ML: A Case Study in Jordan
Authors: Abu-Taieh Evon M. , AlHadid Issam , Alkhawaldeh Rami S. , Khwaldeh Sufian , Masa’deh Ra’ed , Alrowwad Ala’Aldin , Al-Eidie Rabah
Published: October 2022

The purpose of this research paper is to identify and test the factors influencing the perceived usefulness and perceived effectiveness of adopting an e-learning system from the perspective of teachers in public and private schools as well as the United Nations Relief and Works Agency for Palestinian Refugees in the Near East (UNRWA) in Jordan during the first wave of the COVID-19 pandemic in the academic year 2019/2020. Based on the findings and best practices, the study intends to make appropriate recommendations to decision-makers. Its significance stems from the use of scientific tools of research and investigation, and it aims to ensure the quality and effectiveness of Jordanian schools’ e-learning systems. The study’s hypotheses were verified by electronically collecting 551 questionnaires from teachers in Jordan. To test the study hypotheses, the empirical validity of the research model was set up, and the data were analyzed with SPSS version 21.0. Structural equation modeling (SEM), confirmatory factor analysis (CFA), and machine learning (ML) methods were used to test the study hypotheses and validate the properties of the instrument items. Nineteen variables and one mediating variable were studied. The study found that independent variables pertaining to technology (relative advantage, compatibility, top management support, communication technologies, competitive pressure, technology competence, information intensity, and work flexibility) and moderating variables pertaining to the teacher’s personal income and those pertaining to school (school size, education program, and work sector) had a positive effect on teachers’ perceived usefulness of adopting e-learning systems during the COVID-19 pandemic. On the other hand, independent variables pertaining to technology (complexity and collaboration technology), moderating variables pertaining to the teacher (age, education level, and gender), and moderating variables pertaining to school (educational stage, number of students) were not supported.
Living on the Edge: Comparing the Quality of Life Transformation of Local Communities Induced by New Town Development in Different Peri-Urban Areas
Authors: Pratomo Rahmat Aris , Samsura D. Ary A. , van der Krabben Erwin
Published: October 2022

Peri-urban development has both potential and consequences. It has consequences in terms of changes in the condition of livelihood assets and quality of life (QoL) of local communities, while it has benefits because it generates new urban activities. In theory, these impacts vary in significance for peri-urban with diverse characteristics. Therefore, this research aims to investigate and compare the impact of new town development on local communities in various peri-urban areas. Ample attention is given to two new town development projects: Metro Tanjung Bunga (MTB) in a coastal area and Kota Baru Parahyangan (KBP) in an inland area of Indonesia. There were 150 respondents involved from 13 kampungs (enclaves). The research begins with a qualitative descriptive analysis to determine the impact of development and continues with a t-test to validate and compare the magnitude of the impact in the two peri-urban areas. The findings show that the development of the new towns has resulted in a decrease in livelihood assets and community QoL levels. An intriguing finding also demonstrates that the two peri-urban areas have significantly different development impacts: coastal peri-urban communities experienced a more significant decrease in QoL than non-coastal peri-urban communities. This research would enrich the discussions about peri-urban transformation, effects of the process on local communities and sustainability of these effects in developing countries.
Robust Emission Reduction Strategies under Cap-and-Trade and Demand Uncertainty
Authors: Li Chaonan , Guo Tianyi , Chen Yan
Published: October 2022

In this study, we consider robust emission reduction strategies for a monopolistic manufacturer facing demand uncertainty under governments’ cap-and-trade regulations. We model the manufacturer’s decision making and associated profits under four different emission reduction strategies: no mitigation measure, undertaking remanufacturing, improving the greening level, and both remanufacturing and improving the greening level. We find that the cap-and-trade regulation enhances the manufacturer’s motivation to be engaged in reducing carbon emissions. Furthermore, the manufacturer’s optimal choice of emissions reduction strategy depends on the level of carbon trading price and the degree of demand uncertainty. Specifically, there exists a threshold of carbon trading price at which the manufacturer’s optimal emissions reduction strategy will change. When the carbon trading price is low (below the threshold), the best strategy for the manufacturer to reduce emissions is to improve the greening level of the products. When the carbon trading price is high (above the threshold), the manufacturer should consider both remanufacturing and improving the greening level. Moreover, the threshold of the carbon trading price is further impacted by the demand uncertainty. With market demand uncertainty rising, the threshold of carbon trading price increases as well. Finally, we find raising the carbon trading price may not necessarily benefit the environment. Overpriced carbon trading may hurt the manufacturer’s production instead of encouraging them to take emission reduction measures.
Board Diversity and ESG Performance: Evidence from the Italian Banking Sector
Authors: Menicucci Elisa , Paolucci Guido
Published: October 2022

This study examines the influence of the diversity of the board of directors (BoD) and the environmental, social and governance (ESG) performance of 105 Italian banks during the period 2017–2021. Our analysis investigates board diversity in terms of board attributes (board size, board age, board gender diversity, board independence and CSR (corporate social responsibility/sustainability committee) and measures ESG dimensions by using the ESG score provided by the Refinitiv database hosted by Thomson Reuters. The main empirical results reveal that the board size, board independence and the presence of a CSR/sustainability committee positively influence a bank’s ESG performance while no significant relationship between board average age and ESG performance is found. Additionally, the relationship between gender-balanced boards and ESG performance is positive but the impact of female directors on ESG performance is non-linear when a critical mass of women is reached. This paper comprises an in-depth inspection of the corporate governance (CG) in banks, since in Italy there is limited literature concerning diversity in BoDs despite the relevance of the topic. This study is the first that examines the impact of specific CG characteristics (board diversity) on ESG performance in the Italian banking sector, to date. The investigation is highly relevant to managers and investors considering ESG issues in their decision-making process. In addition, findings have implications for both regulators and practitioners, suggesting that policymakers and managers should pay more attention to corporate governance aspects to enhance ESG performance.
The Impact of Urban Warming on the Mortality of Vulnerable Populations in Seoul
Authors: Ngarambe Jack , Santamouris Mattheos , Yun Geun Young
Published: October 2022

Climate change influences urban mortality. The magnitude of such influences differs from locality to locality and is fundamentally driven by a facet of factors that include changes in local climatic conditions, demographics, and social-economic factors. Here, we employ regression and clustering methods to study linkages between mortality and local climatic changes in Seoul. Personal factors of the deceased (e.g., age and gender), social-economic factors (i.e., education level), and outdoor climatic factors, including heatwaves (HWs) and the urban heat island (UHI) phenomenon are considered in the analysis. We find that, among many elements of outdoor weather factors considered, the apparent temperature mostly correlated to daily mortalities; the mortality risk to apparent temperature exposure is more heightened for males (RR = 0.40, 95% CI; 0.23–0.54) than females (RR = 0.05, 95% CI; −0.10–0.20) at higher apparent temperatures (i.e., 60 °C). Furthermore, the influence of HWs on mortality is more apparent in the “Male” gender group and the “Above 65” age group. The results are useful in identifying vulnerable demographics amid the changing climate, especially in urban areas, and are fundamental in developing policies that promote climate resilience and adaptation.
The Impact of Fuel Cell Electric Freight Vehicles on Fuel Consumption and CO2 Emissions: The Case of Italy
Authors: Gallo Mariano , Marinelli Mario
Published: October 2022

The Italian Recovery and Resilience Plan promotes, among its many actions, the use of hydrogen by the deployment of refuelling stations for heavy-duty vehicles, predicting a 5–7% penetration rate of fuel cell electric vehicles (FCEVs) for long-distance freight transport. In this work, the impact of this action on the reduction of greenhouse gas emissions and consumption was estimated, assuming the plan’s objectives are met. To achieve this aim, a national simulation model of the road freight transport system was implemented, consisting of a graph of the national road network and an inter-provincial origin-destination matrix; the graph was based on data available from OpenStreetMap, while the interprovincial matrix was estimated from the interregional matrix with the use of two linear regression models, one for emitted goods and one for attracted goods. The simulation of the system made it possible to estimate the impact of this action on CO2 emissions and fuel consumption under three different scenarios. From 2025 to 2040, a reduction in CO2 emissions ranging from around 9 to around 16.5 million tonnes was estimated, and a reduction in consumption ranging from around 3 billion to around 5.6 billion litres of diesel. These results show how this action can be seen as one of the bricks contributing to the fight against global warming.
Some New Bennett–Leindler Type Inequalities via Conformable Fractional Nabla Calculus
Authors: AlNemer Ghada , Zakarya Mohammed , Butush Roqia , Rezk Haytham M.
Published: October 2022

In this article, we prove several new fractional nabla Bennett–Leindler dynamic inequalities with the help of a simple consequence of Keller’s chain rule, integration by parts, mean inequalities and Hölder’s inequality for the nabla fractional derivative on time scales. As a result of this, some new classical inequalities are obtained as special cases, and we extended our inequalities to discrete and continuous calculus. In addition, when α=1, we shall obtain some well-known dynamic inequalities as special instances from our results. Symmetrical properties are critical in determining the best ways to solve inequalities.
Fuzzy Reasoning for Mixture of Fuzzy/Intuitionistic Fuzzy Information Based on Triple I Method
Authors: Zheng Mucong , Liu Yan
Published: October 2022

Generalized modus ponens (GMP) is a basic model of approximate reasoning. GMP in fuzzy propositions is called fuzzy modus ponen (FMP) and it is called intuitionistic fuzzy modus ponens (IFMP) when fuzzy propositions are generalized to intuitionistic fuzzy propositions. In this paper, we aim to investigate fuzzy reasoning methods for GMP with mixture of fuzzy/intuitionistic fuzzy information. For mixed types of GMP, we present two basic methods to solve GMP problems based on the triple I method (TIM). One is to transform the GMP problem into two FMP problems by decomposition and aggregate the solutions of TIM for FMP problems to obtain the solution for GMP problem. The other is to transform the GMP problem into the IFMP problem by expansion and aggregate the solutions of TIM for the IFMP problem to obtain the solution for the GMP problem. These two methods are called the decomposition triple I method (DTIM) and expansion triple I method (ETIM), respectively. We analyze the relationship between DTIM and ETIM. Furthermore, we discuss the reversibility of DTIM and ETIM.
Quality of Service Based Radio Resources Scheduling for 5G eMBB Use Case
Authors: Nor Ahmed M. , Fratu Octavian , Halunga Simona
Published: October 2022

Several use cases appear with 5G and beyond networks such as enhanced mobile broadband (eMBB), where ultra-high data rates and low-latency connections become essential demands for asymmetric services, e.g., 8K video streaming and virtual reality (VR). The millimeter-wave (mmWave) band can be a promising player to handle these applications under the condition of efficient implementation of radio resource management (RRM) schemes, which distribute resources among user equipment (UEs) in the network. Firstly, mmWave UE channels are highly affected by the distance between the access point (AP) and UEs. Secondly, static and dynamic obstacles can easily block the AP-UE line-of-sight (LOS) link; hence, it highly attenuates mmWave signals. Moreover, eMBB applications lack symmetry in their data rate requirements, from 75 Mbps up to 300 Mbps; consequently, UE quality of service (QoS) should be considered in designing RRM schemes. In this paper, we study possible scheduling schemes that can be implemented for the 5G eMBB use case. Moreover, we propose a new demand-based proportional fairness (DPF) scheduling algorithm that first depends on both UE channel conditions and quality-of-service demands, then, if certain UEs reach the requirement, the algorithm prioritizes it only based on their channel quality. Furthermore, in this work, we consider a real model to simulate the effect of blockage occurrence on the performance of scheduling schemes. Results prove that the proposed DPF scheduling scheme outperforms conventional algorithms in terms of UE satisfaction while maintaining high total system throughput and fairness among UEs. For example, assuming blockage occurrence with 16 and 32 UEs, it guarantees satisfaction for more than 99% and 60% of UEs and, at the same time, obtains 3.29 and 4.24 Gbps system throughput and maintains fairness between UEs at 0.99 and 0.82, respectively. In contrast, conventional proportional fairness highly degrades satisfaction to only 74% and 30% to achieve total throughput equal to 3.1 and 4.3 Gbps, respectively.
Is Asymmetry Different Depending on How It Is Calculated?
Authors: Iglesias-Caamaño Mario , Álvarez-Yates Tania , Carballo-López Javier , Cuba-Dorado Alba , García-García Óscar
Published: October 2022

This study aimed to (1) determine the magnitude and direction of asymmetry in volleyball players, (2) establish asymmetry thresholds, and (3) explore differences depending on the test used and the players’ category. Twenty-nine junior and senior male volleyball players were assessed through a muscle asymmetry battery test: active knee extension test (AKE), single-leg countermovement jump (SL-CMJ), single-leg squat jump (SL-SJ), triple hop test for distance (THTD), modified 20-yard shuttle run, Y-balance test, single-leg one-repetition maximum in leg press test (1RM-SL), and lateral symmetry in radial muscle belly displacement through Tensiomyography in the biceps femoris and rectus femoris. A two-way ANOVA alongside an individual analysis of asymmetry thresholds was used to analyze the test and categorize the influence on the magnitude and the direction of asymmetry. The 1RM-SL, SL-SJ, and the lateral symmetry in radial muscle belly displacement showed a clear asymmetry towards the non-dominant side, while the AKE, SL-CMJ, and THTD showed an asymmetry towards the dominant side. The magnitude of the asymmetry was highly variable between tests (1.46–30.26%). The individualized asymmetry thresholds revealed that the percentage of asymmetrical players varied depending on the type of test used. In conclusion, the type of test used determines the magnitude and direction of asymmetry in well-trained volleyball players.
Clostridium botulinum C3 Toxin for Selective Delivery of Cargo into Dendritic Cells and Macrophages
Authors: Fellermann Maximilian , Stemmer Mia , Noschka Reiner , Wondany Fanny , Fischer Stephan , Michaelis Jens , Stenger Steffen , Barth Holger
Published: October 2022

The protein toxin C3bot from Clostridium botulinum is a mono-ADP-ribosyltransferase that selectively intoxicates monocyte-derived cells such as macrophages, osteoclasts, and dendritic cells (DCs) by cytosolic modification of Rho-A, -B, and -C. Here, we investigated the application of C3bot as well as its non-toxic variant C3botE174Q as transporters for selective delivery of cargo molecules into macrophages and DCs. C3bot and C3botE174Q facilitated the uptake of eGFP into early endosomes of human-monocyte-derived macrophages, as revealed by stimulated emission depletion (STED) super-resolution microscopy. The fusion of the cargo model peptide eGFP neither affected the cell-type selectivity (enhanced uptake into human macrophages ex vivo compared to lymphocytes) nor the cytosolic release of C3bot. Moreover, by cell fractionation, we demonstrated that C3bot and C3botE174Q strongly enhanced the cytosolic release of functional eGFP. Subsequently, a modular system was created on the basis of C3botE174Q for covalent linkage of cargos via thiol–maleimide click chemistry. The functionality of this system was proven by loading small molecule fluorophores or an established reporter enzyme and investigating the cellular uptake and cytosolic release of cargo. Taken together, non-toxic C3botE174Q is a promising candidate for the cell-type-selective delivery of small molecules, peptides, and proteins into the cytosol of macrophages and DCs.
Host Cell Redox Alterations Promote Latent HIV-1 Reactivation through Atypical Transcription Factor Cooperativity
Authors: Cruz-Lorenzo Emily , Ramirez Nora-Guadalupe P. , Lee Jeon , Pandhe Sonali , Wang Lei , Hernandez-Doria Juan , Spivak Adam M. , Planelles Vicente , Petersen Tianna , Jain Mamta K. , Martinez Elisabeth D. , D’Orso Iván
Published: October 2022

Immune cell state alterations rewire HIV-1 gene expression, thereby influencing viral latency and reactivation, but the mechanisms are still unfolding. Here, using a screen approach on CD4+ T cell models of HIV-1 latency, we revealed Small Molecule Reactivators (SMOREs) with unique chemistries altering the CD4+ T cell state and consequently promoting latent HIV-1 transcription and reactivation through an unprecedented mechanism of action. SMOREs triggered rapid oxidative stress and activated a redox-responsive program composed of cell-signaling kinases (MEK-ERK axis) and atypical transcription factor (AP-1 and HIF-1α) cooperativity. SMOREs induced an unusual AP-1 phosphorylation signature to promote AP-1/HIF-1α binding to the latent HIV-1 proviral genome for its activation. Consistently, latent HIV-1 reactivation was compromised with pharmacologic inhibition of oxidative stress sensing or of cell-signaling kinases, and transcription factor’s loss of expression, thus functionally linking the host redox-responsive program to viral transcriptional rewiring. Notably, SMOREs induced the redox program in primary CD4+ T cells and reactivated latent HIV-1 in aviremic patient samples alone and in combination with known latency-reversing agents, thus providing physiological relevance. Our findings suggest that manipulation of redox-sensitive pathways could be exploited to alter the course of HIV-1 latency, thus rendering host cells responsive to help achieve a sterilizing cure.
Development of a Runoff Pollution Empirical Model and Pollution Machine Learning Models of the Paddy Field in the Taihu Lake Basin Based on the Paddy In Situ Observation Method
Authors: Xu Yunqiang , Su Baolin , Wang Hongqi
Published: October 2022

Agricultural non-point source (NPS) pollution has become a prominent problem for China’s water quality. Paddy fields pose a high risk of pollution to surrounding water bodies. The paddy in situ observation method (PIOM) can calculate the runoff pollution load of paddy fields in situ without changing the original runoff characteristics and agricultural water management measures. In this study, we carried out multisite field experiments during the rice growing period in the Taihu Lake basin and calculated the runoff pollution loads. Then, we developed a runoff pollution empirical model (RPEM) and runoff pollution machine learning models of paddy fields. Based on the PIOM, the average runoff volume was 342.1 mm, and the runoff pollution loads mainly occurred in the early-stage seedling and tillering stages. The mean TN, NH4+-N, TP and CODMn loads of paddy fields were 10.28, 3.35, 1.17 and 23.49 kg·ha−1, respectively. The mean N and P fertilizer loss rates were 4.09 and 1.95%, respectively. The RPEM mainly included the runoff model and surface water concentration model of paddy fields, the performance of which was validated based on the PIOM. The irrigation and runoff volumes of Zhoutie paddy (ZT) and Heqiao paddy (HQ) analyzed by RPEM and PIOM had an absolute difference of 1.2~3.1%. With the exception of the difference in CODMn loads of ZT, the absolute differences in TN, NH4+-N, TP and CODMn loads of ZT and HQ measured by two methods were less than 20%. This result illustrates the accuracy and feasibility of the RPEM for analysis of the water balance and runoff pollution loads of paddy fields. Based on 114 field runoff pollution datasets, RF provided the best machine learning model for TN, NH4+-N and TP, and SVM was the best model for CODMn. The training set R2 values of the best models for TN, NH4+-N and CODMn were above 0.8, and the testing set R2 values of the best models were above 0.7. The runoff pollution RF and SVM models can support the calculation and quantitative management of paddy field pollution load. This study provides a theoretical basis and technical support for the quantification of runoff pollution load and the formulation of pollution control measures in the Taihu Lake basin.
Performance of Micropollutant Removal during Wet-Weather Conditions in Advanced Treatment Stages on a Full-Scale WWTP
Authors: Neef Johanna , Leverenz Dominik , Launay Marie Alexandra
Published: October 2022

The reduction of organic micropollutants (OMP) in rivers, lakes and groundwater is an essential legal obligation of the European Water Framework Directive. Since OMP treatment in full-scale wastewater treatment plants (WWTPs) is not state of the art yet, there is little knowledge regarding removal performances, in particular during wet weather. We aimed to contribute to filling this knowledge gap by providing insights from a German case study. On-site measurements were conducted to investigate the impact of rain events on OMP removal with activated carbon processes using powdered activated carbon (PAC) and granular activated carbon (GAC). The study focused on 26 OMPs with different entry paths in the combined sewer system (CSS) and various physico-chemical properties. The monitored OMPs showed higher mass loads during wet weather at all sampling points: effluent of the secondary clarifier, effluent of the PAC treatment stage, and effluent of the GAC filter. As a result of shortened hydraulic retention time (HRT) due to rain events, the overall OMP removal was significantly lower (42% PAC and 46% GAC) than during dry weather (68% PAC and 62% GAC). In order to achieve constant removal rates during all weather conditions, the critical process control parameters are currently being investigated in ongoing studies.
Internal Erosion Experiments on Sandy Gravel Alluvium in an Embankment Dam Foundation Emphasizing Horizontal Seepage and High Surcharge Pressure
Authors: Jin Wei , Deng Zezhi , Wang Gang , Zhang Dan , Wei Linyi
Published: October 2022

For an internally unstable soil, fine particles can move in the pore channels between coarse particles along with seepage flow; this process is termed internal erosion. To evaluate the internal stability and internal erosion behavior of sandy gravel alluvium beneath the suspended cutoff wall in an embankment dam foundation, a series of horizontal seepage tests were carried out on the four representative gradations of the alluvium layer using a large-scale high-pressure erosion apparatus. The evolutionary trends of hydraulic conductivity, the erosion ratio of fine particles, and volumetric strain under stepwise increasing hydraulic loading were obtained. The results showed that the specimens of different gradations exhibited distinct properties in permeability, particle loss, and deformation, depending on the gradation continuity and fine particle content, which can be attributed to the difference in the composition of the soil skeleton and the arrangement of coarse and fine particles. For the specimens with continuous gradations or relatively high fine particle content, the surcharge pressure can significantly improve their internal stability. By contrast, in the situations of gap-graded gradations or low fine particle content, no considerable improvement was found because the stress was mainly borne by the coarse skeleton. The practical implications of the experimental results were demonstrated by evaluating the seepage safety of the zone beneath the suspended wall in the dam foundation.