bluuebunny/crossref_metadata_2025 huggingface dataset:
Vertical Structure of Dust Aerosols Observed by a Ground-Based Raman Lidar with Polarization Capabilities in the Center of the Taklimakan Desert
Authors: Zhang Shuang , Huang Zhongwei , Li Meishi , Shen Xingtai , Wang Yongkai , Dong Qingqing , Bi Jianrong , Zhang Jiantao , Li Wuren , Li Ze , Song Xiaodong
Published: May 2022

The vertical structure of dust properties in desert sources is crucial for evaluating their long-range transportation and radiative forcing. To investigate vertical profiles of dust optical properties in the Taklimakan Desert, we conducted ground-based polarization Raman lidar measurements in Tazhong (83.39°E, 38.58°N, 1103 m above sea level), located at the center of the Taklimakan Desert in the summer of 2019. The lidar system developed by Lanzhou University for continuous network observation is capable of measuring polarization at 532 and 355 nm and detecting Raman signals at 387, 407, and 607 nm. The results indicate that dust aerosols in the central Taklimakan Desert were regularly lifted over 6 km during the summer with a mass concentration of 400–1000 µg m−3, while the majority of the dust remained restricted within 2 km. Moreover, the height of the boundary layer can reach 5–6 km in the afternoon under the strong convention. Above 3 km, dust is composed of finer particles with an effective radius (Reff.) less than 3 μm and a Ångström exponent (AE) related to the extinction coefficient (AEE)532,355 greater than 4; below 3 km, however, dust is dominated by coarser particles. In addition, the particle depolarization ratios (PDR) of Taklimakan dust are 0.32 ± 0.06 at 532 nm and 0.27 ± 0.04 at 355 nm, while the lidar ratios (LRs) are 49 ± 19 sr at 532 nm and 43 ± 12 sr at 355 nm. This study firstly provides information on dust vertical structure and its optical properties in the center of the desert, which may aid in further evaluating their associated impacts on the climate and ecosystem.
Using UAV Survey, High-Density LiDAR Data and Automated Relief Analysis for Habitation Practices Characterization during the Late Bronze Age in NE Romania
Authors: Mihu-Pintilie Alin , Brașoveanu Casandra , Stoleriu Cristian Constantin
Published: May 2022

The characterization of prehistoric human behavior in terms of habitation practices using GIS cartography methods is an important aspect of any modern geoarchaeological approach. Furthermore, using unmanned aerial vehicle (UAV) surveys to identify archaeological sites with temporal resolution during the spring agro-technical works and automated mapping of the geomorphological features based on LiDAR-derived DEM can provide valuable information about the human–landscape relationships and lead to accurate archaeological and cartographic products. In this study, we applied a GIS-based landform classification method to relief characterization of 362 Late Bronze Age (LBA) settlements belonging to Noua Culture (NC) (cal. 1500/1450-1100 BCE) located in the Jijia catchment (NE Romania). For this purpose, we used an adapted version of Topographic Position Index (TPI) methodology, abbreviated DEV, which consists of: (1) application of standard deviation of TPI for the mean elevation (DEV) around each analyzed LBA site (1000 m buffer zone); (2) classification of the archaeological site’s location using six slope position classes (first method), or ten morphological classes by combining the parameters from two small-DEV and large-DEV neighborhood sizes (second method). The results indicate that the populations belonging to Noua Culture preferred to place their settlements on hilltops but close to the steep slope and on the small hills/local ridges in large valleys. From a geoarchaeological perspective, the outcomes indicate a close connection between occupied landform patterns and habitation practices during the Late Bronze Age and contribute to archaeological predictive modelling in the Jijia catchment (NE Romania).
Extraction of Broad-Leaved Tree Crown Based on UAV Visible Images and OBIA-RF Model: A Case Study for Chinese Olive Trees
Authors: Yang Kaile , Zhang Houxi , Wang Fan , Lai Riwen
Published: May 2022

Chinese olive trees (Canarium album L.) are broad-leaved species that are widely planted in China. Accurately obtaining tree crown information provides important data for evaluating Chinese olive tree growth status, water and fertilizer management, and yield estimation. To this end, this study first used unmanned aerial vehicle (UAV) images in the visible band as the source of remote sensing (RS) data. Second, based on spectral features of the image object, the vegetation index, shape, texture, and terrain features were introduced. Finally, the extraction effect of different feature dimensions was analyzed based on the random forest (RF) algorithm, and the performance of different classifiers was compared based on the features after dimensionality reduction. The results showed that the difference in feature dimensionality and importance was the main factor that led to a change in extraction accuracy. RF has the best extraction effect among the current mainstream machine learning (ML) algorithms. In comparison with the pixel-based (PB) classification method, the object-based image analysis (OBIA) method can extract features of each element of RS images, which has certain advantages. Therefore, the combination of OBIA and RF algorithms is a good solution for Chinese olive tree crown (COTC) extraction based on UAV visible band images.
Application of Geophysical Methods in Archaeological Survey of Early Medieval Fortifications
Authors: Milo Peter , Vágner Michal , Tencer Tomáš , Murín Igor
Published: May 2022

As powerful economic and cultural centers, fortified sites played an important role in early medieval society. In Central Europe, early medieval fortified site research has been an essential topic for several generations. However, gradual changes in the landscape are a threat to these cultural heritage monuments. The main task of this paper was to compare the previous results from archaeological excavations with new data acquired by geophysical methods. The presented study is based on the three methods widely used in archaeology: magnetometry, ground-penetrating radar, and electrical resistivity tomography. New surveys provide information about the internal structure and the state of preservation of the fortifications in a non-destructive way. Comparison of the results encourages the evaluation of archaeological excavation and helps determine the suitability and effectiveness of geophysical methods in specific natural conditions.
Hyperspectral Data Compression Using Fully Convolutional Autoencoder
Authors: La Grassa Riccardo , Re Cristina , Cremonese Gabriele , Gallo Ignazio
Published: May 2022

In space science and satellite imagery, better resolution of the data information obtained makes images clearer and interpretation more accurate. However, the huge data volume gained by the complex on-board satellite instruments becomes a problem that needs to be managed carefully. To reduce the data volume to be stored and transmitted on-ground, the signals received should be compressed, allowing a good original source representation in the reconstruction step. Image compression covers a key role in space science and satellite imagery and, recently, deep learning models have achieved remarkable results in computer vision. In this paper, we propose a spectral signals compressor network based on deep convolutional autoencoder (SSCNet) and we conduct experiments over multi/hyperspectral and RGB datasets reporting improvements over all baselines used as benchmarks and than the JPEG family algorithm. Experimental results demonstrate the effectiveness in the compression ratio and spectral signal reconstruction and the robustness with a data type greater than 8 bits, clearly exhibiting better results using the PSNR, SSIM, and MS-SSIM evaluation criteria.
Remote Sensing of Surface Water Dynamics in the Context of Global Change—A Review
Authors: Sogno Patrick , Klein Igor , Kuenzer Claudia
Published: May 2022

Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource—if not overexploited—sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution.
Compression Reconstruction and Fault Diagnosis of Diesel Engine Vibration Signal Based on Optimizing Block Sparse Bayesian Learning
Authors: Bai Huajun , Wen Liang , Ma Yunfei , Jia Xisheng
Published: May 2022

It is critical to deploy wireless data transmission technologies remotely, in real-time, to monitor the health state of diesel engines dynamically. The usual approach to data compression is to collect data first, then compress it; however, we cannot ensure the correctness and efficiency of the data. Based on sparse Bayesian optimization block learning, this research provides a method for compression reconstruction and fault diagnostics of diesel engine vibration data. This method’s essential contribution is combining compressive sensing technology with fault diagnosis. To achieve a better diagnosis effect, we can effectively improve the wireless transmission efficiency of the vibration signal. First, the dictionary is dynamically updated by learning the dictionary using singular value decomposition to produce the ideal sparse form. Second, a block sparse Bayesian learning boundary optimization approach is utilized to recover structured non-sparse signals rapidly. A detailed assessment index of the data compression effect is created. Finally, the experimental findings reveal that the approach provided in this study outperforms standard compression methods in terms of compression efficiency and accuracy and its ability to produce the desired fault diagnostic effect, proving the usefulness of the proposed method.
A Phase-Dependent Effect That Enables Multi-Scale Moisture Measurements in Heterogeneous Substrates Using Tubular RH Sensors
Authors: Lazik Detlef
Published: May 2022

A knowledge of the moisture in soils/soil litter allows for the estimation of irrigation needs or the risk of forest fire. A membrane-based humidity sensor (MHS) can measure the relative humidity (RH) as an average value in such heterogeneous substrates via its sensitive tubular silicone membrane. This RH corresponds to the moisture-dependent water potential of the substrate. For humid conditions in soil, however, the RH is already larger than 98% and hence is insensitively correlated with the water potential. For such conditions, a step-like response of the MHS was found, which occurs if the silicone membrane is wetted with water. This appears to correspond to oversaturated water vapor and must be attributed to a phase-dependent sorption mechanism of the membrane. This effect allows the expansion of the range of applications of the MHS in the detection of liquid water, such as in dew point detection. Based on this, the dependency of the measurement signal on the mean water saturation in a substrate along the tubular membrane is demonstrated. A comparison of the measurement signal with an internal reference signal according to the MHS measurement principle makes it possible to distinguish this new, saturation-dependent measurement scale from the one used for RH measurement.
Preliminary Evaluation of the Effect of Mechanotactile Feedback Location on Myoelectric Prosthesis Performance Using a Sensorized Prosthetic Hand
Authors: Wells Eric D. , Shehata Ahmed W. , Dawson Michael R. , Carey Jason P. , Hebert Jacqueline S.
Published: May 2022

A commonly cited reason for the high abandonment rate of myoelectric prostheses is a lack of grip force sensory feedback. Researchers have attempted to restore grip force sensory feedback by stimulating the residual limb’s skin surface in response to the prosthetic hand’s measured grip force. Recent work has focused on restoring natural feedback to the missing digits directly through invasive surgical procedures. However, the functional benefit of utilizing somatotopically matching feedback has not been evaluated. In this paper, we propose an experimental protocol centered on a fragile object grasp and lift task using a sensorized myoelectric prosthesis to evaluate sensory feedback techniques. We formalized a suite of outcome measures related to task success, timing, and strategy. A pilot study (n = 3) evaluating the effect of utilizing a somatotopically accurate feedback stimulation location in able-bodied participants was conducted to evaluate the feasibility of the standardized platform, and to inform future studies on the role of feedback stimulation location in prosthesis use. Large between-participant effect sizes were observed in all outcome measures, indicating that the feedback location likely plays a role in myoelectric prosthesis performance. The success rate decreased, and task timing and task focus metrics increased, when using somatotopically-matched feedback compared to non-somatotopically-matched feedback. These results were used to conduct a power analysis, revealing that a sample size of n = 8 would be sufficient to achieve significance in all outcome measures.
Review of Thermal and Physiological Properties of Human Breast Tissue
Authors: Said Camilleri Jeantide , Farrugia Lourdes , Curto Sergio , Rodrigues Dario B. , Farina Laura , Caruana Dingli Gordon , Bonello Julian , Farhat Iman , Sammut Charles V.
Published: May 2022

Electromagnetic thermal therapies for cancer treatment, such as microwave hyperthermia, aim to heat up a targeted tumour site to temperatures within 40 and 44 °C. Computational simulations used to investigate such heating systems employ the Pennes’ bioheat equation to model the heat exchange within the tissue, which accounts for several tissue properties: density, specific heat capacity, thermal conductivity, metabolic heat generation rate, and blood perfusion rate. We present a review of these thermal and physiological properties relevant for hyperthermia treatments of breast including fibroglandular breast, fatty breast, and breast tumours. The data included in this review were obtained from both experimental measurement studies and estimated properties of human breast tissues. The latter were used in computational studies of breast thermal treatments. The measurement methods, where available, are discussed together with the estimations and approximations considered for values where measurements were unavailable. The review concludes that measurement data for the thermal and physiological properties of breast and tumour tissue are limited. Fibroglandular and fatty breast tissue properties are often approximated from those of generic muscle or fat tissue. Tumour tissue properties are mostly obtained from approximating equations or assumed to be the same as those of glandular tissue. We also present a set of reliable data, which can be used for more accurate modelling and simulation studies to better treat breast cancer using thermal therapies.
Threats from and Countermeasures for Unmanned Aerial and Underwater Vehicles
Authors: Khawaja Wahab , Semkin Vasilii , Ratyal Naeem Iqbal , Yaqoob Qasim , Gul Jibran , Guvenc Ismail
Published: May 2022

The use of unmanned aerial vehicles (UAVs) for different applications has increased tremendously during the past decade. The small size, high maneuverability, ability to fly at predetermined coordinates, simple construction, and affordable price have made UAVs a popular choice for diverse aerial applications. However, the small size and the ability to fly close to the terrain make the detection and tracking of UAVs challenging. Similarly, unmanned underwater vehicles (UUVs) have revolutionized underwater operations. UUVs can accomplish numerous tasks that were not possible with manned underwater vehicles. In this survey paper, we provide features and capabilities expected from current and future UAVs and UUVs, and review potential challenges and threats due to use of such UAVs/UUVs. We also overview the countermeasures against such threats, including approaches for the detection, tracking, and classification of UAVs and UUVs.
Investigation of Molecular Mean Free Path, Molecular Kinetic Energy, and Molecular Polarity Affecting Knudsen Diffusivity along Pore Channels
Authors: Xu Bin , Qin Haotian , Chen Lu
Published: May 2022

The effective purification of corrosive gases at the cathode air stream side is essential for proton exchange membrane fuel cells’ performance in real-world applications. Gas molecular diffusion depth along the pore channel is a sufficient parameter that determines the effectiveness of the porous purification media. The collision between gas molecules and pore surfaces is the crucial determinant of the diffusion depth. An analytical model was developed to predict the gas molecular diffusion depth in the pore channels. Two different crystal sizes of UiO-66 were synthesized to validate against the model result and empirically determine the diffusion depths. The parametric effects of the mean free path, molecular kinetic energy, and molecular polarity on molecular diffusivity were assessed. A smaller molecular mean free path and greater molecular kinetic energy were favorable for larger diffusion depth, owing to the fewer collisions and enhanced bounces after collisions. Greater molecular polarity led to shorter diffusion depth due to the enhanced van der Waals force between molecules and pore surfaces.
Family Type Differences in Children’s Satisfaction with People They Live with and Perceptions about Their (Step)parents’ Parenting Practices
Authors: Nahkur Oliver , Kutsar Dagmar
Published: May 2022

Family complexity is increasing in Europe, experienced by a significant proportion of children. More evidence is needed in Europe how children’s family type influences their well-being, especially their family-related subjective well-being, and to what extent parenting practices are playing a role in these relationships. The aim of the paper is to study perceptions of children who live with two biological parents, with a biological and a stepparent, or with a single parent about the parenting practices of their (step)parents and their satisfaction with the people they live with. The analysis is based on the third wave of the “Children’s Worlds” harmonized dataset of 12-year-old children in Estonia, Finland, Hungary, Norway, Poland, and Romania. The findings reveal a ‘cascade of children’s appraisals’ by the family types—overall, living with two biological parents is the least and in a stepparent family the most complex family environment for children, reflected in their highest and lowest evaluations of parenting practices and family-related subjective well-being, respectively. The analyses showed that simple and complex family type differences in children’s family-related subjective well-being are entirely explained by parenting practices in Norway, Estonia, and Poland, but not or almost not at all in Finland, Hungary, and Romania. To conclude, in a caring, safe, and participation-enhancing family atmosphere, children can be inclusively flexible and adapt to new parent-figures.
Did Immigrants Perceive More Job Insecurity during the SARS-CoV-2 Pandemic? Evidence from German Panel Data
Authors: Bürmann Marvin , Jacobsen Jannes , Kristen Cornelia , Kühne Simon , Tsolak Dorian
Published: May 2022

Immigrants have been affected more than native-born ethnic majority populations by the negative economic consequences of the SARS-CoV-2 pandemic. This contribution examines whether they have also experienced higher levels of perceived job insecurity, reflected in a differential increase in financial concerns and the fear of job loss during the SARS-CoV-2 pandemic. This empirical study employs the SOEP-CoV survey, which assesses the socio-economic consequences of SARS-CoV-2. It is embedded in the ongoing German Socio-Economic Panel (SOEP). We present OLS models to compare perceptions of job insecurity across groups, capturing the situation before and during the pandemic. The analyses reveal that first-generation immigrants reported more financial worries, and they perceived a higher chance of job loss than second-generation immigrants and the native-born ethnic majority. This difference in economic concerns emerged only in the pandemic. Despite covering a wide range of conditions signaling objective risk of job loss, as well as individuals’ means and resources for dealing with looming job loss, these disparities persisted in the empirical study. Considering group-membership-related feelings of acceptance and inclusion could provide a promising route for future inquiry that may allow the remaining gap in subjective job insecurity to be accounted for.
Using Procurement Power to Accelerate Sustainable City Logistics: Lessons from Change Agents in The Netherlands
Authors: Balm Susanne
Published: May 2022

The role of large procurers (receivers) in improving city logistics is gaining increased attention among scientists and professionals. Knowledge, guidance, and agreements in this field have led to more willingness, ability, and opportunities among receivers to contribute to efficient and zero-emission city logistics when buying goods and services. Change agents play a vital role by initiating, managing, and implementing the change towards more sustainable processes within organisations. The experiences of change agents in The Netherlands show that the number of initiatives in which governments, universities, businesses, and health care institutions (jointly) use their procurement power to accelerate sustainable city logistics is growing. However, the development towards realisation and scaling in practice is going slowly. For this research, we asked change agents in The Netherlands to discuss together the circumstances and actions that support progress towards sustainable city logistics using the buying power of large (clusters of) organisations in cities. Qualitative data has been collected in three workshops, covering 10 initiatives in Amsterdam, Rotterdam, The Hague, Utrecht, and Nijmegen. A list of twelve lessons has been derived and compared with the existing literature. Their experiences confirmed that change is supported by knowledge networks, objectives that motivate stakeholders, a strategic vision, a baseline measurement, social pressure, monitoring and communicating progress, market dialogue, and a broad set of measures. The research also provides new recommendations for change agents. They are advised to form a ‘seed-group’, involve a high-ranking ambassador, and actively promote knowledge sharing among peers to increase involvement. Lastly, it has become clear that knowledge on financial feasibility is scarce. This is because every business case is made-to-measure and is barely quantified from the perspective of receivers.
A Study on Conformity Appeal Attributes and Social Contagion of Beauty-Focused One-Person Media in Sustainable E-Commerce
Authors: Kang Sungmin , Na Younkue
Published: May 2022

In the beauty industry, the use of one-person media is making new, more active relationships that differ from those of past online services and information sharing. Therefore, in this study, we developed conformity appeal attributes in one-person media, identifying their effects on information diffusion behavior through social conformity and collaborative innovation networks, to investigate the social contagion effect of information in beauty-focused one-person media and develop a model by connecting them to the conformity threshold of individuals influenced by others. In this study, a total of 694 complete samples of experienced consumers in the beauty-focused one-person media category were selected, and research questions were verified through reliability and validity tests, path analysis, and measurement model analysis. The research results are as follows. First, conformity appeal attributes of beauty-focused one-person media in terms of information cascade, utility value efficiency, reference group influence, and subnetwork structure significantly affected social imitation conformity. However, only subnetwork structure significantly affected social connection conformity. Similarly, only reference group influence and subnetwork structure significantly affected social comparative conformity. Second, social imitation conformity, social connection conformity, and social comparative conformity in beauty-focused one-person media significantly affected cocreation. Third, cocreation in beauty-focused one-person media significantly affected information diffusion behavior. The detailed use of the conformity appeal attribute factors shown in the above results will be combined with functional changes for online and mobile services of beauty companies, and it will be a driving force to create new value for the network. Moreover, the results of this study not only enable social connection among members within the reference group of beauty-focused one-person media but are also applied as an effective phenomenon to explain the continuous maintenance, reinforcement, and expansion of these relationships, thereby enabling researchers to achieve theoretical expansion and evaluation of relevant variables.
Profit Allocation Strategy of Virtual Power Plant Based on Multi-Objective Optimization in Electricity Market
Authors: Wang Yuqing , Zhang Min , Ao Jindi , Wang Zhaozhen , Dong Houqi , Zeng Ming
Published: May 2022

A virtual power plant (VPP) can aggregate distributed renewable energy and flexible load to participate in the electricity market as a virtual controllable assembly. This pattern can effectively avoid the bidding risk of users, and produce cooperation benefits such as reducing transaction costs. Reasonable profit allocation is the key factor to determine the formation and survival of a VPP, which means a reasonable allocation for the VPP’s market income among participating members. In view of that, this paper proposes a framework of profit allocation in VPPs based on cooperative game theory. Aiming at the competitive environment with multiple VPPs in the electricity market, a VPP’s profit allocation model based on bidding optimization is built, which considers multiple objectives such as fairness of profit allocation, stability of cooperation alliance, and attraction of participating members. Furthermore, a multi-objective evolutionary optimization algorithm based on reference points is introduced to solve the model. Then, a VPP composed of prosumers is taken as an example to carry out the emulation. The results show that all participating members can get satisfactory profit allocation. Its cost-saving ratio ranges from 7.82% to 18.66%, and it confirms that the proposed profit allocation method can encourage prosumers of small size to participate in the VPP cooperation effectively.
Implementation of Integrative Projects as a Contribution to the Major Design Experience in Chemical Engineering
Authors: Ocampo-López Carlos , Castrillón-Hernández Fabio , Alzate-Gil Hader
Published: May 2022

The training of chemical engineers requires creating dynamics that bring them closer to the reality of professional practice and providing active learning experiences to develop skills that strengthen critical thinking, autonomy, teamwork, and communication, as a contribution to sustainable engineering education. However, these experiences are isolated, and sometimes do not show an integrated vision between different areas of knowledge. This work aims to introduce the lessons learned by creating capstone integrative projects as tools for the design and control of processes in the Faculty of Chemical Engineering of the Universidad Pontificia Bolivariana. The capstone project was developed in randomly selected groups to develop a basic engineering proposal for an industrial process of local or national interest. Validation was carried out, consisting of surveys of 54 students in the last year of the program, an opinion query of 60 recent graduates, and a focus group of five graduates, with a profile of employers, management of innovation, development, and design of chemical processes. Between 2016 and 2020, more than 43 processes were evaluated with students, evidencing a significant improvement in the skills defined by the faculty in the graduation profile. A total of 94% of the graduates in that period recognize the capstone project as an integrator of design and process control, and it is concluded that this contributes positively to the professional development of the chemical engineer.
Corporate Social Responsibility Disclosure and Firm’s Productivity: Evidence from the Banking Industry in Bangladesh
Authors: Zheng Yubin , Rashid Md. Harun Ur , Siddik Abu Bakkar , Wei Wei , Hossain Syed Zabid
Published: May 2022

Since the empirical evidence on the relationship between corporate social responsibility disclosure (CSRD) and firm productivity is scarce in the context of the banking industry, the study examines whether CSRD leads banks in Bangladesh to higher productivity. Using annual report data of all 30 banks listed on the Dhaka Stock Exchange in Bangladesh from 2011 to 2018, the study applied a data envelopment analysis (DEA) to determine the productivity of the sample banks, and then ordinary least squares (OLS) analysis to examine the impact of CSR on the banks’ productivity. Furthermore, the study utilized two-stage least squares (2SLS) and a generalized method of moments (GMM) to check the robustness of the findings amid the detection of endogeneity issues. The study also used several alternative variables to check and verify the reliability of the study. The findings indicate that the greater a bank’s contribution to CSR, the higher its productivity. However, banks with more debt to assets are less productive. Additionally, the study observed that the impact of CSRD on bank productivity is higher in GRI banks compared to non-GRI banks, non-politically connected banks as opposed to politically connected banks, and conventional banks compared to Islamic banks. The study provides valuable insight into how CSR activities can promote bank productivity, thus motivating the banks to execute a well-thought-out action plan to ensure more CSR contribution. This study is the first ever bank-level evidence that provides insight into how the patterns of CSR activity of publicly traded banks impact their productivity.
Review on the Test Methods and Devices for Mechanical Properties of Hydrate-Bearing Sediments
Authors: Chen Mingtao , Li Yanlong , Merey Şükrü , Wu Nengyou , Hu Qiaobo , Zhang Yajuan , Dong Lin , Yu Guigang , Jiang Haiyang
Published: May 2022

Commercial exploitation of marine natural gas hydrate (NGH) is crucial for energy decarbonization. However, hydrate production would weaken reservoir mechanical properties and trigger geohazards. Experimental instruments are the basis to obtain the mechanical responses of hydrate-bearing sediments (HBS). Considering the reservoir deformation processes from elastic deformation to residual deformation during hydrate exploitation, this study comprehensively reviewed the feasibility and mechanical research progress of the bender element, resonance column, atomic force microscope, triaxial shear, direct shear, ring shear, and static penetration in mechanical testing. Each test method’s precision and sample size were comprehensively compared and analyzed. Finally, the limitations and challenges of the current mechanical testing methods for HBS were discussed, and their future development directions were proposed. The proposed development direction in mechanical testing methods is expected to provide insightful guidance for the development of instruments and improve the understanding of the mechanical behavior of HBS.
A Quality Decision Model Considering the Delay Effects in a Dual-Channel Supply Chain
Authors: Zhan Lizhen , Shu Hui , Zhou Xideng , Lin Xiaowei
Published: May 2022

Quality is not only the basis for business survival and development but also a key issue that cannot be ignored in supply chain management decisions. In practice, the impact of quality on goodwill does not show an immediate effect, and there is a dynamic delayed effect. Therefore, we developed a dynamic model that considers the delayed effect of quality on goodwill. Firstly, we constructed a delayed differential equation for the effect of quality on goodwill based on the Nerlove–Arrow model for a two-channel supply chain in a competitive environment and studied the dynamic quality decision problem of manufacturers and retailers under the delay effect. Secondly, we constructed the manufacturer and retailer Hamilton functions based on the principles of being of great value, solving and comparing the optimal product quality level, having an optimal service quality level, product goodwill, and overall profit of the supply chain under both decentralized and centralized decision modes, and investigated the effect of delay time on the profit and quality decisions of supply chain members. The conclusions show that: (i) delay time is an important reference for supply chain members when choosing the decision mode, and the overall profit size of the supply chain has different relationships with the different values of delay time taken into account with the two decision scenarios. (ii) Adopting a centralized decision mode can motivate manufacturers and retailers to improve the quality level, which in turn promotes the sales of products and the accumulation of brand goodwill.
Identification and Evaluation of Water Pollution Risk in the Chongqing Section of the Three Gorges Reservoir Area in China
Authors: Yao Zhihong , Liu Zhuangzhuang , Lei Junshan , Zhu Dun , Jia Haiyan , Jiang Muchen , Li Chunming , Xie Zhilong , Peng Chongchong , Zhang Yiwen
Published: May 2022

The Three Gorges Reservoir is the largest freshwater resource reservoir in China. The water environment security in the Three Gorges Reservoir area has a prominent position in the major national strategy for the protection of the Yangtze River. Based on the pressure–state–response (PSR) model, this study comprehensively considers the dangerousness of risk source, the sensitivity of risk receptors, and the acceptable level of regional environmental risk to construct the grading evaluation index system of water environment pollution risk. By using spatial statistical methods, including the variation coefficient method and cold–hot spot pattern analysis, the risk distribution of water environment pollution in the Chongqing section of the Three Gorges Reservoir area was comprehensively identified and evaluated by administrative units. The results showed that: (1) the number of risk sources was largest in Yunyang County and the number of risk receptors was largest in Wanzhou District. However, the distribution of high-risk pollution sources and high-sensitivity receptors was most intensive in the main urban area and surrounding areas of Chongqing, and the regional environmental risk acceptance level was the lowest. (2) The statistical results of risk source dangerousness and the risk receptor sensitivity index at the county level in the study area showed an aggregated distribution pattern, with hotspot areas concentrated in the main urban area of Chongqing and the surrounding area in the upper reaches of the reservoir area. Moreover, the acceptable level of risk in this area showed a cold spot area, while other regions basically showed a balanced distribution pattern without forming significant hot spot or cold spot areas. (3) The high-risk river section of water pollution in the reservoir area comprised five counties, including Jiulongpo District, Yubei District, Shapingba District, Yuzhong District and Nanan District; the middle-risk river section comprised six counties, including Changshou District, Beipei District, Jiangbei District, Dadukou District, Fuling District and Shizhu County; and the low-risk river sections were mainly distributed in the Jiangjin District in the upper reaches of the reservoir area and the middle and lower reaches of the northeast ecological area of Chongqing. Therefore, the acceptable levels of water pollution risk sources, receptors and regional environmental risks in the Chongqing section of the Three Gorges Reservoir area are unevenly distributed, showing an aggregated distribution pattern. The spatial distribution of water environment pollution risk is uneven, and the significant potential risk area is the functional core area of Chongqing, which is the critical area of water environment risk management in the future.
Railway Signaling Safety Factors Quantitative Analysis Using an Improved 5M Model
Authors: Lin Haixiang , Yuan Tengfei , Bai Wansheng , Zhao Zhengxiang , Lu Ran , Li Xinqin , Lin Qi
Published: May 2022

In order to improve the sustainability of modern cities, the safe operation of rail transportation is critical. Meanwhile, rail signaling safety is also fundamental for rail transportation, and quantitative analysis of railway signaling safety factors can guarantee this basis. To achieve this, this research proposes an improved rail signaling 5M (Management-Machine-Man-Media-Mission) accident cause hierarchical model, which can make up for the previous lack of objectivity and statistics. According to the demands of rail signaling accident analysis, this research collects and classifies the rail signaling accident data from 2000 to 2017. Then, the hierarchical association rule method is used to calculate the relationships between the 5M factors, and the factor analysis method is applied to measure the weights of the 5M subfactors. Therefore, the safety evaluation index system for railway signaling system is established. The results show that the Management element is the most important factor in rail signaling accidents, while the Mission element is dispensable. Moreover, the subfactors, such as the equipment material, safety management, external humans affected, and hidden danger should also not be ignored. Eventually, the rail signaling accidents analysis is conducted between the 5M model and the improved 5M model; the comparison shows that the improved 5M can not only improve the safety factors influence rate by more than 84.64%, but it can also improve the railway signaling safety, which can provide strong support for the safe operation of rail transportation and sustainable development of a modern city.
The Impact of Public Transportation on Carbon Emissions—From the Perspective of Energy Consumption
Authors: Jing Qin-Lei , Liu Han-Zhen , Yu Wei-Qing , He Xu
Published: May 2022

Background: Transportation has become the second-largest source of global carbon emissions. Promoting low-carbon development by means of public transport and green travel and analyzing the mechanism and path of the carbon emissions reduction effect of public transport have become key to reducing carbon emissions in the transportation field and achieving “carbon peak and carbon neutrality”. Methods: The data from 30 provinces (2010–2019) were extracted from China Emission Accounts and Datasets (CEADs), China Energy Statistical Yearbook, China Statistical Yearbook, and China Automobile Statistical Yearbook. The two-way fixed-effect model was used to explore the carbon emissions reduction effect of public transport development level. The mediating-effect model was used to verify the transmission role of energy consumption in the carbon emissions reduction effect of public transport development level. Results: The study suggests that the public transport development level and CO2 emissions are negatively correlated, showing an “Inverted U-shaped” curve relationship. Energy consumption is the transmission path of the carbon emissions reduction effect of public transport development level. The public transport development level adjusts the energy consumption structure through the traffic substitution effect, energy input optimization effect, and industrial structure optimization effect and then acts on carbon emissions. Moreover, the contribution rate of energy consumption is about 4.22%. In addition, regional heterogeneity is present in the transmission path of the carbon emissions reduction effect of public transport development level based on energy consumption. The carbon emissions reduction effect of public transport development level is more significant in the central and western regions than the eastern and northeast regions of China. Conclusion: The transmission mechanism of energy consumption in the carbon emissions reduction effect of public transport is worthy of attention. To promote low-carbon and circular development in the transportation sector, it is urgent to accelerate the green upgrading of transportation infrastructure, promote the low-carbon transformation of energy production and consumption, promote carbon emissions reduction in public transport, and strengthen the linkage regulation between effective government and an effective market.
Quantitative Study on Road Traffic Environment Complexity under Car-Following Condition
Authors: Liu Wenlong , Chen Yixin , Li Hongtao , Zhang Hui
Published: May 2022

With the development of the drive of electronic communication technology, the driving assistance system that perceives the external traffic environment has developed rapidly. However, when quantifying the complexity of the road traffic environment without fully considering the driving characteristics and subjective feelings, the false alarm rate of the driving warning system increases and affects the early warning effect. In order to more accurately quantify the complexity of the road traffic environment, we analyzed the impact of road traffic environment changes on drivers under the condition of car-following. Firstly, we selected the influencing factors of the traffic environment complexity, such as the driving operation indicators, the vehicle driving status indicators and the road environmental indicators. The weight calculation model of each influence factor is established based on the principal component analysis method. Secondly, the driver’s reaction time during car-following is used as the quantitative index of road traffic environment complexity. The quantitative model of road traffic environment complexity is constructed combined with the weight of road traffic environment complexity. Finally, the driving simulation experiment is designed to verify the complexity quantification model of the road traffic environment. The road traffic environment complexity value calculated in our study is better than the TTC, and the early-warning threshold is raised by 2–5%. The research conclusion can provide a basis for the design of the car alarm system.
The Impact of Improving the Quality of the Port’s Infrastructure on the Shippers’ Decisions
Authors: Wagner Natalia , Kotowska Izabela , Pluciński Michał
Published: May 2022

Important attributes of a transportation chain are the costs of their operation, the security of supply they provide, and reducing carbon emissions throughout the chain. When making managerial decisions about the chain configuration, shippers consider the optimal choice of means of transport, carriers, or ports. Seaports, as transport nodes, determine the functioning of supply chains they serve. A constant process observed in the world shipping is the consistent increase in the average size of ships. Adapting the port and port access infrastructure to the changes observed in the world shipping is a prerequisite for maintaining the competitive position of the port, and consequently of the entire transport chain. Adequate hydrological conditions ensuring safe access to ports for increasingly larger ships are necessary for the stable functioning and development of a port and the entire region. For shippers, the certainty that the handling of larger vessels is assured regardless of any fluctuating hydro-meteorological conditions and temporary vessel entry permits is a guarantee of security of supply. This study aims to demonstrate the impact of fairway deepening on port-oriented supply chain costs and security of supply, as well as verification of the importance of these factors for cargo shippers’ decision-making. The article used the case study method based on the port of Szczecin, for which the investment of deepening the fairway to 12.5 m is being implemented. The article estimates the transport costs of five transport chains served by the port of Szczecin. Our research showed that a 2.5 m increase in the permissible draught of ships results in a decrease of up to 25% in transport costs resulting mainly from the reduction in specific fuel consumption throughout the chain. The analysis of the results showed that a secondary benefit of deepening the fairway can change the structure of the port’s foreland. This conclusion was validated by means of in-depth interviews held with selected shippers cooperating with the port of Szczecin. An additional outcome of the interviews was identification of the remaining conditions that should be met to take full advantage of improved port accessibility. The research is the first step to broader studies assessing whether improving quality of port infrastructure can contribute to a reduction in emissions from ships in a port and thus facilitate the transition to zero-emission ports.
A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing
Authors: Bharany Salil , Sharma Sandeep , Khalaf Osamah Ibrahim , Abdulsahib Ghaida Muttashar , Al Humaimeedy Abeer S. , Aldhyani Theyazn H. H. , Maashi Mashael , Alkahtani Hasan
Published: May 2022

Global warming is one of the most compelling environmental threats today, as the rise in energy consumption and CO2 emission caused a dreadful impact on our environment. The data centers, computing devices, network equipment, etc., consume vast amounts of energy that the thermal power plants mainly generate. Primarily fossil fuels like coal and oils are used for energy generation in these power plants that induce various environmental problems such as global warming ozone layer depletion, which can even become the cause of premature deaths of living beings. The recent research trend has shifted towards optimizing energy consumption and green fields since the world recognized the importance of these concepts. This paper aims to conduct a complete systematic mapping analysis on the impact of high energy consumption in cloud data centers and its effect on the environment. To answer the research questions identified in this paper, one hundred nineteen primary studies published until February 2022 were considered and further categorized. Some new developments in green cloud computing and the taxonomy of various energy efficiency techniques used in data centers have also been discussed. It includes techniques like VM Virtualization and Consolidation, Power-aware, Bio-inspired methods, Thermal-management techniques, and an effort to evaluate the cloud data center’s role in reducing energy consumption and CO2 footprints. Most of the researchers proposed software level techniques as with these techniques, massive infrastructures are not required as compared with hardware techniques, and it is less prone to failure and faults. Also, we disclose some dominant problems and provide suggestions for future enhancements in green computing.