bluuebunny/crossref_metadata_2025 huggingface dataset:
Progress in Hybrid Plasma Wakefield Acceleration
Authors: Hidding Bernhard , Assmann Ralph , Bussmann Michael , Campbell David , Chang Yen-Yu , Corde Sébastien , Cabadağ Jurjen Couperus , Debus Alexander , Döpp Andreas , Gilljohann Max , Götzfried J. , Foerster F. Moritz , Haberstroh Florian , Habib Fahim , Heinemann Thomas , Hollatz Dominik , Irman Arie , Kaluza Malte , Karsch Stefan , Kononenko Olena , Knetsch Alexander , Kurz Thomas , Kuschel Stephan , Köhler Alexander , Ossa Alberto Martinez de la , Nutter Alastair , Pausch Richard , Raj Gaurav , Schramm Ulrich , Schöbel Susanne , Seidel Andreas , Steiniger Klaus , Ufer Patrick , Yeung Mark , Zarini Omid , Zepf Matt
Published: January 2023

Plasma wakefield accelerators can be driven either by intense laser pulses (LWFA) or by intense particle beams (PWFA). A third approach that combines the complementary advantages of both types of plasma wakefield accelerator has been established with increasing success over the last decade and is called hybrid LWFA→PWFA. Essentially, a compact LWFA is exploited to produce an energetic, high-current electron beam as a driver for a subsequent PWFA stage, which, in turn, is exploited for phase-constant, inherently laser-synchronized, quasi-static acceleration over extended acceleration lengths. The sum is greater than its parts: the approach not only provides a compact, cost-effective alternative to linac-driven PWFA for exploitation of PWFA and its advantages for acceleration and high-brightness beam generation, but extends the parameter range accessible for PWFA and, through the added benefit of co-location of inherently synchronized laser pulses, enables high-precision pump/probing, injection, seeding and unique experimental constellations, e.g., for beam coordination and collision experiments. We report on the accelerating progress of the approach achieved in a series of collaborative experiments and discuss future prospects and potential impact.
Advances in the Implementation of the Exactly Energy Conserving Semi-Implicit (ECsim) Particle-in-Cell Method
Authors: Lapenta Giovanni
Published: January 2023

The energy-conserving semi-implicit (ECsim) method presented by the author in 2017, is a particle-in-cell (PIC) algorithm for the simulation of plasmas. Energy conservation is achieved within a semi-implicit formulation that does not require any non-linear solver. A mass matrix is introduced to linearly express the particle-field coupling. With the mass matrix, the algorithm preserves energy conservation to machine precision. The construction of the mass matrix is the central nature of the method and also the main cost of the computational cycle. Here, three methods that modify the construction of the mass matrix are analyzed. First, the paper considers how the sub-cycling of the particle motion modifies the mass matrix. Second, a form of smoothing that reduces the noise while retaining exact energy conservation is introduced. Finally, an approximation of the mass matrix is discussed that transforms the ECsim scheme to the implicit moment method.
Attributing Evapotranspiration Changes with an Extended Budyko Framework Considering Glacier Changes in a Cryospheric-Dominated Watershed
Authors: Chang Yaping , Ding Yongjian , Zhao Qiudong , Zhang Shiqiang
Published: January 2023

The retreat of glaciers has altered hydrological processes in cryospheric regions and affects water resources at the basin scale. It is necessary to elucidate the contributions of environmental changes to evapotranspiration (ET) variation in cryospheric-dominated regions. Considering the upper reach of the Shule River Basin as a typical cryospheric-dominated watershed, an extended Budyko framework addressing glacier change was constructed and applied to investigate the sensitivity and contribution of changes in environmental variables to ET variation. The annual ET showed a significant upward trend of 1.158 mm yr−1 during 1982–2015 in the study area. ET was found to be the most sensitive to precipitation (P), followed by the controlling parameter (w), which reflects the integrated effects of landscape alterations, potential evapotranspiration (ET0), and glacier change (∆W). The increase in P was the dominant factor influencing the increase in ET, with a contribution of 112.64%, while the decrease in w largely offset its effect. The contributions of P and ET0 to ET change decreased, whereas that of w increased when considering glaciers using the extended Budyko framework. The change in glaciers played a clear role in ET change and hydrological processes, which cannot be ignored in cryospheric watersheds. These findings are helpful for better understanding changes in water resources in cryospheric regions.
Feature Selection for Airbone LiDAR Point Cloud Classification
Authors: Kuprowski Mateusz , Drozda Pawel
Published: January 2023

The classification of airborne LiDAR data is a prerequisite for many spatial data elaborations and analysis. In the domain of power supply networks, it is of utmost importance to be able to discern at least five classes for further processing—ground, buildings, vegetation, poles, and catenaries. This process is mainly performed manually by domain experts with the use of advanced point cloud manipulation software. The goal of this paper is to find a set of features which would divide space well enough to achieve accurate automatic classification on all relevant classes within the domain, thus reducing manual labor. To tackle this problem, we propose a single multi-class approach to classify all four basic classes (excluding ground) in a power supply domain with single pass-through, using one network. The proposed solution implements random forests and gradient boosting to create a feature-based per-point classifier which achieved an accuracy and F1 score of over 99% on all tested cases, with the maximum of 99.7% for accuracy and 99.5% for F1 score. Moreover, we achieved a maximum of 81.7% F1 score for the most sparse class. The results show that the proposed set of features for the LiDAR data cloud is effective in power supply line classification.
Assessing the Use of Sentinel-2 Data for Spatio-Temporal Upscaling of Flux Tower Gross Primary Productivity Measurements
Authors: Spinosa Anna , Fuentes-Monjaraz Mario Alberto , El Serafy Ghada
Published: January 2023

The conservation, restoration and sustainable use of wetlands is the target of several international agreements, among which are the Sustainable Development Goals (SDGs). Earth Observation (EO) technologies can assist national authorities in monitoring activities and the environmental status of wetlands to achieve these targets. In this study, we assess the capabilities of the Sentinel-2 instrument to model Gross Primary Productivity (GPP) as a proxy for the monitoring of ecosystem health. To estimate the spatial and temporal variation of GPP, we develop an empirical model correlating in situ measurements of GPP, eight Sentinel-2 derived vegetation indexes (VIs), and different environmental drivers of GPP. The model automatically performs an interdependency analysis and selects the model with the highest accuracy and statistical significance. Additionally, the model is upscaled across larger areas and monthly maps of GPP are produced. The study methodology is applied in a marsh ecosystem located in Doñana National Park, Spain. In this application, a combination of the red-edge chlorophyll index (CLr) and rainfall data results in the highest correlation with in situ measurements of GPP and is used for the model formulation. This yields a coefficient of determination (R2) of 0.93, Mean Absolute Error (MAE) equal to 0.52 gC m−2 day−1, Root Mean Squared Error (RMSE) equal to 0.63 gC m−2 day−1, and significance level p < 0.05. The model outputs are compared with the MODIS GPP global product (MOD17) for reference; an enhancement of the estimation of GPP is found in the applied methodology.
Changes in Land Use and Ecosystem Service Values of Dunhuang Oasis from 1990 to 2030
Authors: Yi Fan , Yang Qiankun , Wang Zhongjing , Li Yonghua , Cheng Leilei , Yao Bin , Lu Qi
Published: January 2023

Maintaining the integrity and stability of oasis ecosystems is an important topic in the field of ecological research. Assessment of ecosystem services and their changes can provide important support for the sustainable development of oases. This study took the Dunhuang oasis in the hyper-arid area as the research object and used 1990, 2010, and 2020 Landsat series satellite images to complete the land use interpretation by random forest classification. Then we estimated the ecosystem services value (ESV) by using benefit transfer method, and predicted the trend of ecosystem service value changes under three scenarios using the Analytic Hierarchy Process method and the patch generation land use simulation model (AHP-PLUS model). The results showed that the vegetation areas of the Dunhuang Oasis first decreased and then increased during 1990–2020. The decrease was largely due to the expansion of built-up land and farmland, and the increase was mainly contributed by the implementation of ecological protection policies. The path of changes in the ESV of the Dunhuang Oasis during 1990–2020 was well consistent with that of vegetation areas, with a maximum of 9068.15×106 yuan (in 1990) and a minimum of 6271.46×106 yuan (in 2010). Spatial autocorrelation analysis showed that urbanization reduced ESV, and the implementation of ecological policies enhanced ESV. The ESV of the Dunhuang Oasis for the year 2030 under the ecological conservation scenario could reach 7631.07×106 yuan, which is 381.1×106 yuan higher that under the economic development scenario. The ecological conservation scenario is the optimal option to achieve sustainable development of the Dunhuang Oasis. We suggested that the government should continuously enhance the protection of forests and waterbodies, reasonably restrict production and domestic water consumption, and efficiently increase the proportion of ecological water consumption. In addition, this study improved the evaluation method of oasis ESV based on the proportion of Normalized Difference Vegetation Index (NDVI) of grasslands with different coverage, which is important for improving the environment in arid areas.
Unabated Global Ocean Warming Revealed by Ocean Heat Content from Remote Sensing Reconstruction
Authors: Su Hua , Wei Yanan , Lu Wenfang , Yan Xiao-Hai , Zhang Hongsheng
Published: January 2023

As the most relevant indicator of global warming, the ocean heat content (OHC) change is tightly linked to the Earth’s energy imbalance. Therefore, it is vital to study the OHC and heat absorption and redistribution. Here we analyzed the characteristics of global OHC variations based on a previously reconstructed OHC dataset (named OPEN) with four other gridded OHC datasets from 1993 to 2021. Different from the other four datasets, the OPEN dataset directly obtains OHC through remote sensing, which is reliable and superior in OHC reconstruction, further verified by the Clouds and the Earth’s Radiant Energy System (CERES) radiation flux data. We quantitatively analyzed the changes in the upper 2000 m OHC of the oceans over the past three decades from a multisource and multilayer perspective. Meanwhile, we calculated the global ocean heat uptake to quantify and track the global ocean warming rate and combined it with the Oceanic Niño Index to analyze the global evolution of OHC associated with El Niño–Southern Oscillation variability. The results show that different datasets reveal a continuously increasing and non-decaying global ocean warming from multiple perspectives, with more heat being absorbed by the subsurface and deeper ocean over the past 29 years. The global OHC heating trend from 1993 to 2021 is 7.48 ± 0.17, 7.89 ± 0.1, 10.11 ± 0.16, 7.78 ± 0.17, and 12.8 ± 0.26 × 1022 J/decade according to OPEN, IAP, EN4, Ishii, and ORAS5, respectively, which shows that the trends of the OPEN, IAP, and Ishii datasets are generally consistent, while those of EN4 and ORAS5 datasets are much higher. In addition, the ocean warming characteristics revealed by different datasets are somewhat different. The OPEN OHC dataset from remote sensing reconstruction shows a unique remote sensing mapping advantage, presenting a distinctive warming pattern in the East Indian Ocean. Meanwhile, the OPEN dataset had the largest statistically significant area, with 85.6% of the ocean covered by significant positive trends. The significant and continuous increase in global ocean warming over the past three decades, revealed from remote sensing reconstruction, can provide an important reference for projecting ocean warming in the context of global climate change toward the United Nations Sustainable Development Goals.
Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy
Authors: Polo Jesús , García Redlich J.
Published: January 2023

Solar cadasters are excellent tools for determining the most suitable rooftops and areas for PV deployment in urban environments. There are several open models that are available to compute the solar potential in cities. The Solar Energy on Building Envelopes (SEBE) is a powerful model incorporated in a geographic information system (QGIS). The main input for these tools is the digital surface model (DSM). The accuracy of the DSM can contribute significantly to the uncertainty of the solar potential, since it is the basis of the shading and sky view factor computation. This work explores the impact of two different methodologies for creating a DSM to the solar potential. Solar potential is estimated for a small area in a university campus in Madrid using photogrammetry from google imagery and LiDAR data to compute different DSM. Large differences could be observed in the building edges and in the areas with a more complex and diverse topology that resulted in significant differences in the solar potential. The RSMD at a measuring point in the building rooftop can range from 10% to 50% in the evaluation of results. However, the flat and clear areas are much less affected by these differences. A combination of both techniques is suggested as future work to create an accurate DSM.
A Review of Gas Measurement Practices and Sensors for Tunnels
Authors: Cepa Jorge J. , Pavón Rubén M. , Caramés Paloma , Alberti Marcos G.
Published: January 2023

The concentration of pollutant gases emitted by traffic in a tunnel affects the indoor air quality and contributes to structural deterioration. Demand control ventilation systems incur high operating costs, so reliable measurement of the gas concentration is essential. Numerous commercial sensor types are available with proven experience, such as optical and first-generation electrochemical sensors, or novel materials in detection methods. However, all of them are subjected to measurement deviations due to environmental conditions. This paper presents the main types of sensors and their application in tunnels. Solutions will also be discussed in order to obtain reliable measurements and improve the efficiency of the extraction systems.
An Ultracompact Angular Displacement Sensor Based on the Talbot Effect of Optical Microgratings
Authors: Yang Zhiyong , Ma Xiaochen , Yu Daguo , Cao Bin , Niu Qianqi , Li Mengwei , Xin Chenguang
Published: January 2023

Here, we report an ultracompact angular displacement sensor based on the Talbot effect of optical microgratings. Periodic Talbot interference patterns were obtained behind an upper optical grating. By putting another grating within the Talbot region, the total transmission of the two-grating structure was found to be approximatively in a linear relationship with the relative pitch angle between the two gratings, which was explained by a transversal shift of the Talbot interference patterns. The influence of the grating parameters (e.g., the grating period, the number of grating lines and the gap between the two gratings) was also studied in both a simulation and an experiment, showing a tunable sensitivity and range by simply changing the grating parameters. A sensitivity of 0.19 mV/arcsec was experimentally obtained, leading to a relative sensitivity of 0.27%/arcsec within a linear range of ±396 arcsec with the 2 μm-period optical gratings. Benefitting from tunable properties and an ultracompact structure, we believe that the proposed sensor shows great potential in applications such as aviation, navigation, robotics and manufacturing engineering.
Atomic Magnetometer Achieves Visual Salience Analysis in Drosophila
Authors: Liu Fan , Li Dongmei , Li Yixiao , Xiang Zhao , Chen Yuhai , Xu Zhenyuan , Lin Qiang , Ruan Yi
Published: January 2023

An atomic magnetometer (AM) was used to non-invasively detect the tiny magnetic field generated by the brain of a single Drosophila. Combined with a visual stimulus system, the AM was used to study the relationship between visual salience and oscillatory activity of the Drosophila brain by analyzing changes in the magnetic field. Oscillatory activity of Drosophila in the 1–20 Hz frequency band was measured with a sensitivity of 20 fT/Hz. The field in the 20–30 Hz band under periodic light stimulation was used to explore the correlation between short-term memory and visual salience. Our method opens a new path to a more flexible method for the investigation of brain activity in Drosophila and other small insects.
Multi-Class Classification and Multi-Output Regression of Three-Dimensional Objects Using Artificial Intelligence Applied to Digital Holographic Information
Authors: Mahesh R N Uma , Nelleri Anith
Published: January 2023

Digital holographically sensed 3D data processing, which is useful for AI-based vision, is demonstrated. Three prominent methods of learning from datasets such as sensed holograms, computationally retrieved intensity and phase from holograms forming concatenated intensity–phase (whole information) images, and phase-only images (depth information) were utilized for the proposed multi-class classification and multi-output regression tasks of the chosen 3D objects in supervised learning. Each dataset comprised 2268 images obtained from the chosen eighteen 3D objects. The efficacy of our approaches was validated on experimentally generated digital holographic data then further quantified and compared using specific evaluation matrices. The machine learning classifiers had better AUC values for different classes on the holograms and whole information datasets compared to the CNN, whereas the CNN had a better performance on the phase-only image dataset compared to these classifiers. The MLP regressor was found to have a stable prediction in the test and validation sets with a fixed EV regression score of 0.00 compared to the CNN, the other regressors for holograms, and the phase-only image datasets, whereas the RF regressor showed a better performance in the validation set for the whole information dataset with a fixed EV regression score of 0.01 compared to the CNN and other regressors.
Special Issue “Emotion Intelligence Based on Smart Sensing”
Authors: Park Sung , Whang Mincheol
Published: January 2023

Emotional intelligence is essential to maintaining human relationships in communities, organizations, and societies [...]
A Roadmap for Gigabit to Terabit Optical Wireless Communications Receivers
Authors: Matthews William , Collins Steve
Published: January 2023

Silicon photomultipliers’ relatively large areas and ability to detect single photons make them attractive as receivers for optical wireless communications. In this paper, the relative importance of the non-linearity and width of SiPMs’ fast output in their performance in receivers is investigated using Monte Carlo simulations. Using these results, the performances of receivers containing different SiPMs are estimated. This is followed by a discussion of the potential performances of arrays of existing SiPMs. Finally, the possible dramatic improvements in performance that could be achieved by using two stacked integrated circuits are highlighted.
Acute Intoxication by Bisoprolol and Drowning: Toxicological Analysis in Complex Suicides
Authors: Carfora Anna , Petrella Raffaella , Ambrosio Giusy , Fracassi Ilaria , Festinese Stefano , Liguori Bruno , Campobasso Carlo Pietro
Published: January 2023

In complex suicides, more than one suicide method is applied at the same time or one after the other. The most common complex suicide includes the ingestion of drugs combined with drowning. A case of acute intoxication by Bisoprolol and drowning is reported. The dead body of a 40-year-old woman was discovered on a river side, soon after her husband found a suicide note at home. In the woman’s vehicle four empty boxes of Bisoprolol, a widely used beta blocker, were also found. Main autopsy findings were consistent with drowning and represented by plume of froth at the mouth and nostrils with frothy fluid also in the airways, water into the stomach, and a remarkable pulmonary edema as a result of fluid aspiration. Toxicological analyses were performed on peripheral blood, urine and gastric content samples using liquid and gas chromatography, coupled with mass spectrometry. Toxicological results were negative for ethanol and other common drugs of abuse. High levels of bisoprolol were found in blood (7.54 mg/L), far exceeding the therapeutic range, in the urine (1.14 mg/L), and gastric content (13.12 mg/L). Bisoprolol intoxication was assessed as a relevant contributing condition to the immediate cause of death represented by drowning. Although Bisoprolol would certainly have a heart-depressing effect, it is not possible to determine if the victim fell unconscious or if she simply collapsed into the water with a secondary drowning.
Investigation of Irrigation Water Requirement and Evapotranspiration for Water Resource Management in Southern Punjab, Pakistan
Authors: Hussain Sajjad , Mubeen Muhammad , Nasim Wajid , Fahad Shah , Ali Musaddiq , Ehsan Muhammad Azhar , Raza Ali
Published: January 2023

Water scarcity and water quality degradation are exacerbated by climate change in all countries, including Pakistan. The use of water in agriculture is one of the most predominant resources, so reducing consumption and improving resource management is of utmost importance. In the past few decades, excessive irrigation has led to severe water scarcity and reduced water quality. This study determined the irrigation requirements for cotton, rice, and wheat, using the CROPWAT model in Southern Punjab (Multan District). In the study area, evapotranspiration ranged from 1.8 to 10.24 mm/day, while effective rainfall ranged from 2 to 31.3 mm. Rice, cotton, and wheat each required 996.4, 623.3, and 209.5 mm of irrigation, respectively. Among rice, cotton, and wheat, the total net irrigation was 72.4, 67.8, and 44.1 mm, respectively, while the total gross irrigation was 103.5, 99.8, and 63 mm. The CROPWAT model showed a moderately useful result for identifying irrigation needs in Southern Punjab. The study emphasizes the need for groundwater harvesting and water management technologies to implement a water management system that reduces water shortages.
Improving Governance of Tenure in Policy and Practice: Agrarian and Environmental Transition in the Mekong Region and Its Impacts on Sustainability Analyzed through the ‘Tenure-Scape’ Approach
Authors: Jansen Louisa J.M. , Kalas Patrick P.
Published: January 2023

Land relations in the Mekong Region are marked by the densely populated and intensively cultivated lowlands and the more extensive settlement and cultivation areas in the uplands. Land-use changes in the lowlands and uplands are interlinked and are a key process of agrarian and environmental transition. The ‘tenure-scape’ approach is introduced as a qualitative analysis combining integrated landscape approaches, governance and rights-based approaches, while underlining the centrality of legitimate tenure rights, limitations and obligations. This approach is used to analyze the impact of the Green Revolution and the global commodity boom, in particular the growth of rubber and coffee, on sustainability in the Mekong countries, i.e., Cambodia, Lao People’s Democratic Republic, Myanmar and Viet Nam. The way forward points to the use of the elements of the ‘tenure-scape’ approach to re-valuate the potential contribution of smallholder farmers to the wider physical and societal landscape. The ultimate goal is to go from transition to transformation toward a more secure, equitable future for those at risk of being excluded from effective access to, use of, and control over land, fisheries, forests and water resources, which are providing the basis for their livelihoods if the concession model of land-based investments were to be continued.
Introducing the Smart City to Children: Lessons Learned from Hands-On Workshops in Classes
Authors: Clarinval Antoine , Simonofski Anthony , Henry Julie , Vanderose Benoît , Dumas Bruno
Published: January 2023

Smart cities are receiving a lot of attention from researchers and practitioners as they are considered potential solutions to challenges (e.g., traffic congestion and waste management) faced by cities. As a result, the term “smart city” is recurring in political discourses and the news. Moreover, smart cities are transitioning from strong and technological orientations toward inclusive and participative orientations, and citizens are expected to take an active part in their design. However, the smart city concept remains obscure to the majority of the public; although many participation methods exist for adults, few have been implemented for children, who remain on the sidelines. Our objective is to address the lack of research on innovative initiatives to (1) educate children on the smart city concept and (2) include them in citizen participation dynamics. To achieve this, we propose a novel hands-on workshop where children learn about the smart city concept, are challenged with a collective urban planning exercise and develop a digital citizen participation method. This paper describes the workshop conducted and reports on lessons learned from its evaluation; the workshop involved 299 children from the ages of 12 to 14. It showed success in improving the children’s understanding of the smart city concept. We then propose future inclusive smart city research directions grounded in the evaluation results and the feedback received from multiple practitioners.
Efficient Phosphate Removal from Wastewater by Ca-Laden Biochar Composites Prepared from Eggshell and Peanut Shells: A Comparison of Methods
Authors: Liu Xiaoqi , Lv Jialong
Published: January 2023

Biochar is currently widely used as the adsorbent for phosphorus (P) removal from wastewater. Cheap and green modified materials and efficient preparation methods are the key to obtain efficient and economical engineering biochar. Conventional salt solution and chemical impregnation are common methods for preparing engineered biochar. However, this preparation method is not environmentally friendly or cheap due to the price of salt solutions and the solvent treatment process for chemical impregnation. In this article, Ca-laden biochar was prepared using peanut shells as carbon base materials and discarded eggshells as calcium source. Two methods (ball milling and chemical impregnation) of building the Ca-laden biochar were compared from the perspective of the characterization of biochar, the adsorption performance and the economic cost. The composition and structure of biochar were analyzed by the element content, functional group, X-ray diffraction, energy spectrum and electron microscope scanning etc. The adsorption behavior of biochar was tested in different environments (pH and temperature). The results revealed that the capacity of P adsorption by the Ca-modified biochar was higher than the adsorption by raw biochar, and that the prepared Ca-laden biochar has a wide working environment. Moreover, the Ca-laden biochar prepared by ball milling has a higher specific surface area and more porosity. The Ca-modified biochar through ball milling has a higher amount of adsorbed P than that of through chemical impregnation. This work not only creates a novel method for making excellent P adsorbents, but also offers an environmentally friendly use for agricultural eggshells and peanut shells.
Thermal, Acoustic, and Hygrothermal Properties of Recycled Bovine Leather Cutting Waste-Based Panels with Different Compositions
Authors: Merli Francesca , Fiorini Costanza Vittoria , Barbanera Marco , Pietroni Giorgia , Spaccini Francesco , Buratti Cinzia
Published: January 2023

This study aims to investigate the thermo-acoustic and hygrothermal properties of innovative panels made of leather waste produced by a bag factory from a circular economy perspective. Their performance was compared with other residual-based insulation panels. The leather scraps were chipped and three boards were fabricated by means of a mold with different compositions, adding adhesive glue. In order to improve the sustainability aspects, a sample was assembled by using a water-based polyurethane glue, in addition to the two panels with vinyl glue. Panels were tested for thermal, acoustic, and hygrothermal performance. Thermal conductivity values in the range of 0.064–0.078 W/mK at 10 °C were measured depending on the composition and the adhesive. A slight thermal performance deterioration occurs when using the natural water-based glue. The samples were characterized by good performance both in terms of sound absorption coefficient (Noise Reduction Coefficient NRC = 0.21–0.28) and Transmission Loss, up to 59 dB values. Water vapor resistance factor values in the 35–48 range were obtained, close to the values of standard materials, such as expanded polystyrene and polyurethane.
Digital Transformation, Top Management Team Heterogeneity, and Corporate Innovation: Evidence from A Quasi-Natural Experiment in China
Authors: Zhang Qincheng , Yang Mingzeng
Published: January 2023

Digitalization has brought great changes to economic and social development, and corporate digital transformation has gradually become the focus of academic attention. We explore the economic impacts of digital transformation from the perspective of corporate innovation utilizing a sample of China’s A-share listed manufacturing firms from 2008 to 2020, depending on the quasi-natural experiment of “Integration of Informatization & Industrialization”. Using the difference-in-differences (DID) model, we document that the growth of innovation considerably tends to rise via corporate digital transformation, and top management team (TMT) heterogeneity plays a positively moderating role in this process. The findings are still reliable after the parallel trend test, PSM-DID, placebo test, and the test of excluding alternative explanations. Extended analyses find that the innovation incentive effect of digital transformation will enhance corporate value in the later stage. Our findings not only contribute to the advancement of the study in digital transformation, but also offer theoretical support and useful advice for furthering corporate digitalization and upgrading the mechanism for creative growth.
Effect of Chinese Currency Appreciation on Investments in Renewable Energy Projects in Countries along the Belt and Road
Authors: Wang Huazhang , Ergu Daji , Zai Wenjiao
Published: January 2023

Foreign investment in renewable energy generation projects is a critical part of the Belt and Road Initiative. Under the background of the market economy, the electric energy will participate in power market competition among the countries along the line, and the sales revenue will be settled in the local currency. The exchange rate of the countries along the Belt and Road fluctuates frequently and widely, thereby posing significant risks to the investment income of the projects. To address this problem, this paper proposes the concept of Ek as the effective exchange rate expressed by the on-grid price, investment cost per kilowatt electricity generation equipment, and annual operating cost rate of unit power generation capacity. Moreover, this paper presents a model of power generation cost, income, and earning expressed by the real exchange rate. The flexibility formula of the fluctuation of power generation cost, income, profit, and internal rate of return relative(IRR) to Ek is derived, and the effect of exchange rate level and fluctuation on projects is analyzed. With the wind power projects invested by China in Pakistan taken as an example, the trend during the entire life cycle is calculated. The changes in net profit rate, IRR, and levelized cost of energy (LCOE) are calculated under Chinese currency appreciation of 10%, 20%, and 35% and 5% and 10% reduction of investment cost per unit. As the Chinese currency appreciates and the project IRR declines significantly, LCOE decreases slightly, but this decrease is not sufficient to compensate for the losses caused by the decline in IRR. The following effective measures are proposed to deal with the exchange rate fluctuation of foreign renewable energy generation projects: building energy Internet, reducing project cost, and using Chinese currency as the settlement currency. In this paper, a solution is provided for investments in renewable energy projects in regions where exchange rates fluctuate greatly.
An Alternative Rural Housing Management Tool Empowered by a Bayesian Neural Classifier
Authors: Song Mingzhi , Zhu Zheng , Wang Peipei , Wang Kun , Li Zhenqi , Feng Cun , Shan Ming
Published: January 2023

In developing countries, decision-making regarding old rural houses significantly relies on expert site investigations, which are criticized for being resource-demanding. This paper aims to construct an efficient Bayesian classifier for house safety and habitability risk evaluations, enabling people with none-civil-engineering backgrounds to make judgements comparable with experts so that house risk levels can be checked regularly at low costs. An initial list of critical risk factors for house safety and habitability was identified with a literature review and verified by expert discussions, field surveys, and Pearson’s Chi-square test of independence with 864 questionnaire samples. The model was constructed according to the causal mechanism between the verified factors and quantified using Bayesian belief network parameter learning. The model reached relatively high accuracy rates, ranging from 91.3% to 100.0% under different situations, including crosschecks with unused expert judgement samples with full input data, crosschecks with unused expert judgement samples with missing input data, and those involving local residents’ judgement. Model sensitivity analyses revealed walls; purlins and roof trusses; and foundations as the three most critical factors for safety and insulation and waterproofing; water and electricity; and fire safety for habitability. The identified list of critical factors contributes to the rural house evaluation and management strategies for developing countries. In addition, the established Bayesian classifier enables regular house checks on a regular and economical basis.
Thermal Assessment of Dielectric Microspacer Technology Using an Advanced Three-Dimensional Simulation Model
Authors: Zeneli Myrto , Bellucci Alessandro , Sabbatella Gianfranco , Fotopoulou Maria , Apostolopoulos Vasilis , Stamatopoulos Panagiotis , Trucchi Daniele M. , Nikolopoulos Aristeidis , Rakopoulos Dimitrios
Published: January 2023

Dielectric microspacers (DMS) are a novel micro-technology that can be used to achieve a fixed micron/sub-micron gap distance between two separated surfaces, such as the emitter (cathode) and the PV cell (anode) of a near-field thermophotovoltaic converter (TPV). One of the system’s challenges is the flow of undesirable excess thermal energy from the cathode to the anode that might cause the PV cell to overheat. This work investigates the possibility of integrating this technology into a hybrid thermionic-photovoltaic (TIPV) converter operating at ultra-high temperatures (>1000 °C) without any risk of collector’s overheating, which might lead to its mechanical failure. A steady-state 3-D CFD model was developed in Fluent v17.1 solver to assess the system’s thermal behavior when the two electrodes were separated by a distance of 8–10 μm. The heat transfer through conduction across the system components and the net photon/electron flux between the two electrodes were simulated. Different cathode temperatures within the range of 1500–2500 K and various DMS shapes (capillary, cylindrical), patterns (e.g., ring-shaped) and sizes were studied. Results show that thermal performance is not affected by the DMS pattern, even for thermal conductivities of 80 W/(m·K), whereas the possibility of mechanical failure is considerable for Tcathode > 2000 K.
Education Stakeholders’ Viewpoints about an ESD Competency Framework: Q Methodology Research
Authors: Chaaban Youmen , Du Xiangyun , Lundberg Adrian , Abu-Tineh Abdullah
Published: January 2023

Teachers are considered key drivers of the education for sustainable development (ESD) agenda. They play a critical role in ensuring the attainment of sustainability goals, yet require early opportunities to acquire the necessary knowledge, skills, and attitudes, which will enable them to foster ESD. Therefore, this study documented the development and evaluation of a framework consisting of the core competencies that pre-service teachers need to achieve ESD in Qatar. Framed by complexity theory, the competency framework was developed into a Q-sample, which was then evaluated by multiple education stakeholders, including teacher educators, professional development specialists, ministry specialists, and teachers. The results of the Q-analysis indicated six diverse viewpoints and revealed a lack of overarching consensus statements among the viewpoints. Several statements were also considered controversial as different participants revealed contrasting views in regard to their importance for pre-service teachers. Implications for practice using the competency framework as a dynamic communication and reflection blueprint for implementing ESD are discussed.
The Role of Stakeholders in Creating Mobility in Logistics Systems of Polish Cities
Authors: Przybylska Edyta , Kramarz Marzena , Dohn Katarzyna
Published: January 2023

The basis for developing logistics solutions in cities is to know the requirements and expectations of current and potential transport users and for decision makers to strive to meet them. In building an urban logistics strategy, it is therefore necessary to take into account different stakeholder groups. Building stakeholder relations should be aimed at involving them in the development of a sustainable transport policy for the city. It should be noted, however, that the importance of stakeholders in transport policy is diverse. This assumption was made in the paper, which aimed to identify the role of the various groups of urban logistics stakeholders in the sustainable movement of people. This challenge is subordinated to the methodology proposed in the paper, which combines the analysis of urban logistics stakeholders and the assignment of roles to them in the pursuit of sustainable flows of people in the city with the identification of tasks in which stakeholders characterized by a particular role should be involved. Achieving the stated goal required collaboration with experts. Research on the roles of stakeholders, as well as the tasks in which they should be involved, was conducted in Polish cities. Infrastructure managers, small mobility organisers, public safety organisations and public transport organisations turned out to be the development leaders who, as a result, were recommended to be included in most tasks by local government units of Polish cities. What deserves special attention in the results obtained, on the other hand, is the role of the unpredictable main player, which is other cities.
Analysis of a Combined Solar Drying System for Wood-Chips, Sawdust, and Pellets
Authors: Kumar Baibhaw , Szepesi Gábor , Szamosi Zoltán , Krámer Gyula
Published: January 2023

The future of conventional fuels has limited sustainability and creates disquietude because of the ubiquitous energy crisis worldwide. The judicious use of biomass or wood-based fuels is inevitable. The quality of wood fuels depends on the moisture content, and subsequently, solar drying solutions can play a vital role in adequately storing and controlling moisture in the fuels. In the present study, a novel forced convection cabinet-type solar dryer was developed and investigated for its thermal performance. An artificial neural network (ANN model) was created to predict the final moisture content of the drying system. The drying behavior of three distinct wood fuels, i.e., woodchips, sawdust, and pellets, was kept under observation to plot the drying curve based on their calculated moisture ratio. The dryer reached a maximum temperature of 60 °C while maintaining a temperature gradient of 10–20 °C. The maximum thermal energy and exergy efficiency was recorded as 55% and 51.1%, respectively. The ANN-optimized model was found suitable with reasonable values of coefficient of correlation (R) for the model.
Towards a Value Co-Creation Process in Collaborative Environments for TVET Education
Authors: Badawi Salem , Drăgoicea Monica
Published: January 2023

The appearance of the COVID disruption has proved the need for rapid innovations in education, with new value proposition(s) able to capture the new activities involving value co-creation in the education service systems. This paper introduces a conceptual framework for skills building in collaborative TVET online communities that integrates the Collaborative Knowledge Sharing Environment (CKSEnv), an ontology-based collaborative development of knowledge-intensive services, as a possible main driver for value co-creation amongst actors in the after-pandemic TVET education. CKSEnv’s usability and usefulness in achieving its goals is evaluated. Quantitative and qualitative data collected through interviews have revealed respondents’ interest in topics such as the sustainability, usefulness, usability, value co-creation, and technical functionality of the proposed development. Both the utility and simplicity proved to have the most significant impact on CKSEnv adoption and usage. A new service design artifact is created, the smart service model canvas in the TVET online communities, to explain the new value co-creation process, which is able to fill gaps in describing the role of ICT in supporting the TVET training cycle. This research may ground further explorations related to the development of TVET online communities, while the CKSEnv is still in the evaluation stage. The practical implications of this study express the need for new value co-creation processes with specific activities that use technology-driven innovations, able to establish such newly created value, through smart educational services.
Environmental Noise Impact Assessment for Large-Scale Surface Mining Operations in Serbia
Authors: Pantelic Uros , Lilic Petar , Cvjetic Aleksandar , Lilic Nikola
Published: January 2023

Noise emissions are a significant environmental impact caused by the mining industry in all technological phases of surface mining, mineral processing, and waste disposal. This paper presents the role of noise impact assessment and control in large-scale surface mining operations. Mine planning develops the model of mining operations, ore excavation, and waste dumping scheduling and processing rates, including spatial distribution of mining activities. Such a level of mine planning requires an environmental impact assessment study. This can be achieved by applying noise impact assessment models. The described approach can be used to verify the effectiveness of the proposed protection measures to reduce or eliminate the identified negative impacts. This paper presents a case study of environmental noise impact assessment and control at the Serbia Zijin Copper DOO Bor mine, encompassing the analysis of the noise protection measures efficiency within the planning of large-scale mining operations at the open-pit mine Veliki Krivelj.
The Role of Organizational Efforts in Mitigating the Adverse Effects of Workplace Mistreatment on Attitudinal Responses
Authors: Park Jongsoo
Published: January 2023

Despite increasing attention to workplace mistreatment in organizations, few studies have investigated the consequences of such negative experiences on employees. Using the Canadian Public Service Employee Survey (PSES) data (about 80,000 observations), this study examines the relationships between workplace mistreatment and outcomes at work and the moderating role of organizational efforts in preventing and handling workplace mistreatment among Canadian federal government employees. Empirical results of an OLS regression and logit model document that perceived workplace mistreatment, in terms of workplace harassment and discrimination, is negatively related to job satisfaction and continuance organizational commitment and positively related to turnover intention. The analysis also shows that the linkages between workplace mistreatment and the three outcomes were weaker when organizational efforts aimed at dealing with workplace mistreatment were perceived to be high. Implications of these results for research and practice are discussed.
Identifying the Factors Contributing to Freeway Crash Severity Based on Discrete Choice Models
Authors: Cheng Wen , Ye Fei , Wang Changshuai , Bai Jiping
Published: January 2023

The freeway’s operation safety has attracted wide attention. In order to mitigate the losses brought on by traffic accidents on freeways, discrete choice models were constructed based on the statistical analysis method to quantitatively analyze the significance and magnitude of the impact of multiple dimensional factors on crash severity. Based on 1154 accidents that occurred on Zhejiang Province’s Hang-Jin-Qu Fressway from 2013 to 2018, the distribution characteristics of crash severity were analyzed. The dependent variable was the crash injury severity, which was categorized into property damage only (PDO), injury, and fatal. As independent variables, 15 candidate variables representing four aspects, including driver, vehicle, road, and environmental conditions, were chosen. Considering the ordered characteristics of the variables, the models developed included the ordered logit, the generalized ordered logit, and the partial proportional odds models. The Brant test found that the previous two models had difficulty dealing with the problem of partial variables that did not fit the parallel-lines assumption, and the conclusions were finally discussed through the partial proportional odds model results. The findings indicate that 11 factors have significant consequences. Five variables, namely “mountainous”, “female”, “driving experience 2- years”, “large vehicle responsible”, and “vehicle not going straight”, violated the parallel-lines assumption. Female drivers and drivers aged 55+ years were more likely to suffer injuries and fatalities in collisions with guardrails and other objects. Large vehicles being involved and vehicles not going straight enhanced the likelihood of injury and fatal outcomes when drivers had 2- years of experience. Wet-skid road conditions enhanced the likelihood of injury accidents, and driving at nighttime without lighting increased the likelihood of fatal accidents. Departments responsible for traffic management can take full account of these variations and develop focused proposals for improvement.