bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural and Energetic Aspects of Entacapone-Theophylline-Water Cocrystal
Authors: Karagianni Anna , Quodbach Julian , Weingart Oliver , Tsiaxerli Anastasia , Katsanou Vasiliki , Vasylyeva Vera , Janiak Christoph , Kachrimanis Kyriakos
Published: February 2022

Pharmaceutical cocrystals are currently gaining interest among the scientific community, due to their great potential for providing novel crystalline forms with superior properties such as solubility, dissolution rate, bioavailability, and stability. Robust computational tools are valuable tools in the rationalization of cocrystal formation, by providing insight into the intermolecular interactions of multicomponent molecular solids. In this study, various computational techniques based on charge density analysis were implemented to assess structural and energetical perspectives of the interactions responsible for the formation and stability of entacapone-theophylline-water (ETP-THP-water, 1:1:1). Significant non-covalent interactions (NCIs) were identified and evaluated by Hirshfeld surface analysis and density functional theory (DFT) computations, and three-dimensional networks (energy vector diagrams, lattice energy frameworks) were constructed, outlining the crucial stabilizing role of water and the dominance of π-π stacking interactions in the cocrystal. Furthermore, thermal dehydration studies confirmed the strong binding of water molecules in the crystal lattice, as expressed by the high activation energy.
Optimization for Sustainable Train Shunting Services Using DMAIC Cycle
Authors: Alshamlan Mohammed , Alzahrani Aos , BinYousef Musaad , Abdelhadi Abdelhakim , Akkad Khaled , Alyamani Rakan
Published: February 2022

Railway operations is a complicated field that requires a specialized team to operate trains safely and effectively. The focus of this paper was on a Middle Eastern-based railway company to understand the current train shunting process at the north–south passenger line and investigate possible issues in order to resolve them. The aim of this paper is to go through the DMAIC cycle and use it to define, measure, analyze and recommend improvements to enhance and control the current process. The results show that the bottleneck process can be greatly improved and optimized by fixing the root causes identified by the cause and effect diagram, which should positively contribute to increasing the overall performance of train operations and provide more time to maintain the trains.
Will Participatory Guarantee Systems Happen Here? The Case for Innovative Food Systems Governance in the Developed World
Authors: Roggio April M. , Evans Jason R.
Published: February 2022

Participatory guarantee systems (PGS) are locally-rooted agroecological governance mechanisms primarily designed to meet the needs of local producers for product certification and cooperative sales. They have experienced periodic waves of interest in different places throughout the globe. There is a small but rich and growing scholarship devoted to understanding how they are managed, how they are sustained, and what factors predict their success. Interestingly, there is little evidence that they have developed in the United States, which has instead, witnessed the growth of community supported agriculture (CSA), farmer’s markets, food hubs and food policy councils (FPC), although many of these mechanisms have failed to sustain interest and support. Here, we explore the factors that drive the creation of systems in the global South, Europe and other regions, and identify the factors that shape a different trajectory for local agriculture in the United States. We discuss the possibilities for more radical food system transformation in the United States, considering a changing climate, an industrial food system that has prioritized profit over health, and the COVID-19 pandemic. Finally, we conclude by identifying some future pathways for policy reform and research opportunities.
Rewards and Innovation Performance in Manufacturing Small and Medium Enterprises (SMEs)
Authors: Kankisingi Gustave Mungeni , Dhliwayo Shepherd
Published: February 2022

The study investigated types of rewards SMEs offered to intrapreneurs and how these (rewards) contribute to innovation performance (IP). A questionnaire was administered to a sample of 300 SME owner-managers from the industrial spatial distribution areas of Kwa-Zulu Natal province in South Africa. Results show that besides a regular salary offered by 99.5% of the SMEs, fewer than 37.1% of them paid other forms of rewards. The empirical findings show that rewards had an influence on innovation performance. From the 17 rewards awarded to intrapreneurs by SMEs, only “promotion within organisation” and “monetary bonus rewards” had a positive and significant influence on innovation performance. Four other rewards had a significant but negative influence on IP. Rewards are an important tool to encourage crowdsourcing intrapreneurial contribution to IP. Rewards should therefore be strategically selected given the limited financial resources in SMEs. The importance of this study is its focus on SMEs, which are characterised by limited information on the effect of rewards on innovation performance, as well as the efficiency driven economic setting, normally not characterised by “innovation performance”. The study also shows how IP can be crowdsourced through appropriate rewards.
Energiebunker Hamburg—Ecological and Economic Sustainability of a War Relic?
Authors: Drewello Hansjörg , Kulawik Nina
Published: February 2022

The Energiebunker in Hamburg-Wilhelmsburg used to be an abandoned and overgrown flak and air raid bunker—a relic of World War II. After the war, the interior of the bunker was blown up, and only the upper floors and the three- to- four meter thick concrete walls remained. For more than 60 years the building was not in use. The building was transformed during the International Building Exhibition in Hamburg between 2006 and 2013 and is now used to generate renewable electricity and heat for more than 1500 households. This adaptive reuse not only enabled the bunker to be integrated into the redesigned neighborhood, but also to fulfill certain societal needs. The historic building was conserved and given a new sustainable use. Nowadays it is a tourist attraction and a war memorial. This paper explores the economic and environmental sustainability of this transformation. Could this be a second use scenario for other bunker facilities from World War II?
The Effect of Internal Control on Green Innovation: Corporate Environmental Investment as a Mediator
Authors: Ma Xiang , Ock Young-Seok , Wu Fengpei , Zhang Zhenyang
Published: February 2022

The increasing focus on environmental, social, and corporate governance (ESG) has led to a growing interest in how firms’ internal behaviors affect their contributions in promoting sustainable economic development and fulfilling social responsibility. While previous studies have often explored the impact of internal controls on corporate investment decisions, little attention has been paid to the impact of internal controls on corporate green innovation. To this end, we explored the relationship between internal control, environmental investment, and green innovation using data from 2014–2019 for A-share listed companies in Shanghai and Shenzhen, China. The regression results show that there is a significant positive relationship between internal control and corporate green innovation. The improvement of internal control has a significant positive impact on firms’ active adoption of environmental protection investment. Environmental investment plays a partially mediating role in the process of internal control’s influence on green innovation. This implies that the effect of internal control on green innovation further affects green innovation through the indirect effect of environmental investment, in addition to the direct effect. Moreover, through further research, we find that the above influence relationship is significantly present in both heavily polluting and non-heavily polluting enterprises, as well as in state-owned and private enterprises, but is more significant in heavily polluting firms and private firms. Finally, this study responds to the debate on whether internal controls inhibit or promote enterprise innovation. We advocate further research on this issue in the future in terms of the differences in the accountability systems and customs of firms’ decision-making in different countries.
Effects of Deliberate Practice on Blended Learning Sustainability: A Community of Inquiry Perspective
Authors: Chen Rosa Huiju
Published: February 2022

Education for sustainable development has been regarded as a lifelong learning process and an integral part of quality education. To this end, this study aims to examine the implementation of online learning communities and deliberate practice in a blended learning context, to improve English as a foreign language (EFL) students’ learning performance and engagement. Specifically, in addition to the traditional offline courses, the online film clip watching and writing tasks were adopted to ascertain the role of deliberate practice and the dimensions of the community of inquiry (COI) framework were adopted to examine the perceived effectiveness and improved performance. A quantitative study was carried out, involving 67 undergraduate freshman English course students from one university at northeastern Taiwan. The findings of this study indicate that there is statistically significant correlation between the three dimensions of community of inquiry, perceived learning and learning engagement. Moreover, teaching and cognitive presence are more predictive of students’ perceived learning. Finally, this study also illustrates practical implications, to facilitate students’ learning for sustainable development competency in blended learning contexts.
Autonomous Vehicle Overtaking: Modeling and an Optimal Trajectory Generation Scheme
Authors: Yamada Yu , Bakibillah Abu Saleh Md , Hashikura Kotaro , Kamal Md Abdus Samad , Yamada Kou
Published: February 2022

Traffic congestion or accidents may occur as a consequence of the difficulty of performing a safe, comfortable, and efficient overtaking in a timely manner when there is a slow or stopped vehicle, cyclist, or partial lane blockage on the road. Specifically, most drivers find it challenging to overtake a sluggish vehicle on a single-lane road in the presence of vehicles coming from other directions. To resolve such overtaking concerns, this paper proposes a novel optimal trajectory generating scheme for autonomous vehicle overtaking that is both smooth and safe and can be used in a variety of traffic scenarios. The proposed scheme is based on the solution of an optimal predictive problem with the goal of minimizing driving costs while limiting collision risks in the presence of any opposite vehicle on the overtaking lane. The computational burden of the scheme is almost negligible and can be implemented in real-time. The scheme is evaluated in a variety of traffic conditions, including stopped and slow vehicles in the lane, as well as the presence or absence of a nearby opposite vehicle. The simulation results show that the proposed scheme effectively obtains the optimal trajectories even in the difficult overtaking contexts considering various constraints imposed by the road curve, opposite vehicles, and slow preceding vehicles. Finally, the optimal overtaking costs are obtained for various states of the associated vehicles, which provide an indication of the best state to initiate the overtake. The proposed technology can be employed as a fully automated system or an advanced driver assistance system (ADAS) to improve the vehicle flows at challenging driving conditions and enhance transportation sustainability.
Use of Parallel ResNet for High-Performance Pavement Crack Detection and Measurement
Authors: Fan Zhun , Lin Huibiao , Li Chong , Su Jian , Bruno Salvatore , Loprencipe Giuseppe
Published: February 2022

In the process of road pavement health and safety assessment, crack detection plays a pivotal role in a preventive maintenance strategy. Recently, Convolutional Neural Networks (CNNs) have been applied to automatically identify the cracks on concrete pavements. The effectiveness of a CNN-based road crack detection and measurement method depends on several factors, including the image segmentation of cracks with complex topology, the inference of noises with similar texture to the distress, and the sensitivity to thin cracks. The presence of shadows, strong light reflections, and road markings can also severely affect the accuracy in detection and measurement. In this study, a review of the state-of-the-art CNN methods for crack identification is presented, paying attention to existing limitations. Then, a novel deep residual convolutional neural network (Parallel ResNet) is proposed with the aim of creating a high-performance pavement crack detection and measurement system. The challenge and special feature of Parallel ResNet is to remove the noise inference, identifying even thin and complex cracks correctly. The performance of Parallel ResNet has been investigated on two publicly available datasets (CrackTree200 and CFD), comparing it with that of competing methods suggested in the literature. Parallel ResNet reached the maximum scores in Precision (94.27%), Recall (92.52%), and F1 (93.08%) using the CrackTree200 dataset. Similarly, for the CFD dataset the novel method achieved high values in Precision (96.21%), Recall (95.12%), and F1 (95.63%). Based on the crack detection and image recognition results, mathematical morphology was then used to further minimize noise and accurately segment the road diseases, obtaining the outer contours of the connected domain in crack images. Therefore, crack skeletons have been extracted to measure the distress length, width, and area on images of rigid pavements. The experimental results show that Parallel ResNet can effectively minimize noise to obtain the geometry of cracks. The results of crack characteristic measurements are accurate and Parallel ResNet can be assumed as a reliable method in pavement crack image analysis, in order to plan the best road maintenance strategy.
GIS and AHP Based Groundwater Potential Zones Delineation in Chennai River Basin (CRB), India
Authors: Sajil Kumar Pazhuparambil Jayarajan , Elango Lakshmanan , Schneider Michael
Published: February 2022

Groundwater depletion is one of the most critical concerns for users and policymakers. Identifying groundwater potential (low to high) helps properly plan the available groundwater resource. This study has used the possibilities of a geographical information system (GIS), remote sensing and, of course, field data to delineate the groundwater potential zones in the Chennai River Basin (CRB). Thematic layers generated for eleven controlling factors, such as geology, water level, drainage, soil, lineament, rainfall, land use, slope, aspect, geomorphology, and depth to bedrock, were brought into the GIS environment. Then, appropriate weightage was given to each layer using a multi-criteria decision-making technique, namely, the analytic hierarchical process (AHP). A groundwater potential map is generated using weighted overlay analysis, with the following five classes: very poor, poor, moderate, good, and very good. The results were comparable to the actual specific yield data from the field and accuracy was 78.43%. Thus, AHP-aided GIS–RS mapping is a useful tool in groundwater prospecting in this region of the world.
Theoretical and Experimental Analysis on Influence of Natural Airflow on Spent Fuel Heat Removal in Dry Cask Storage
Authors: Ratiko Ratiko , Sumarbagiono Raden , Aisyah Aisyah , Wati Wati , Heriyanto Kuat , Mirawaty Mirawaty , Artiani Pungky Ayu , Purwanto Yuli , Saputra Dwi Luhur Ibnu , Rachmadetin Jaka , Setiawan Risdiyana , Istavara Arifin , Rauf Abdullah Ahmad
Published: February 2022

A key issue contributing to the success of NPP technology is the safe handling of radioactive waste, particularly spent nuclear fuel. According to the IAEA safety standard, the spent fuel must be stored in interim wet storage for several years so the radiation and the decay heat of the spent fuel will decrease to the safe limit values, after which the spent fuel can be moved to dry storage. In this study, we performed a theoretical analysis of heat removal by natural convection airflow in spent nuclear fuel dry storage. The temperature difference between the air inside and outside dry storage produces an air density difference. The air density difference causes a pressure difference, which then generates natural airflow. The result of the theoretical analysis was validated with simulation software and experimental investigation using a reduced-scale dry storage prototype. The dry storage prototype consisted of a dry cask body and two canisters stacked to store materials testing reactor (MTR) spent fuel, which generates decay heat. The cask body had four air inlet vents on the bottom and four air outlet vents at the top. To simulate the decay heat from the spent fuel in the two canisters, the canisters were wrapped with an electric wire heater that was connected to a voltage regulator to adjust the heat power. The theoretical analysis results of this study are relatively consistent with the experimental results, with the mean relative deviation (MRD) values for the prediction of air velocity, the heat rate using natural airflow, and the heat rate using the thermal resistance network equation are +0.76, −23.69, and −29.54%, respectively.
The Topology of Cultural Destinations’ Accessibility: The Case of Attica, Greece
Authors: Kranioti Areti , Tsiotas Dimitrios , Polyzos Serafeim
Published: February 2022

This paper studies the cultural landscape in the prefecture of Attica, Greece, within the context of network science. Tourism is a global and complex phenomenon with a considerable effect on space. Among its diverse forms, cultural tourism stands out, since people often travel to explore different cultures and civilizations. The engagement of different stakeholders in the establishment of policies in regard to tourism development and its relation to cultural heritage demonstrates the need for sustainable spatial planning in cultural tourism areas. According to network science, a modern discipline already contributing to the research in tourism geography, tourism destinations can configure complex spatial networks and be studied in terms of network analysis and statistical mechanics. This paper models the accessibility network of cultural destinations in Attica (ACDN), the capital region of Greece, into a graph, which provides an excellent case study of multilayer network modeling, as is equipped with high quality transportation, accommodation, and cultural infrastructures. The ACDN nodes represent museums and archaeological sites and its edges express possible connections between nodes by different means of transport (car, pedestrian, and public transport). The analysis aims to evaluate the layer’s capacity in the service of the accessibility of the cultural destination tourism market in Greece and reveals two major communities in the structure of ACDN, an urban core and a peripheral, configured by spatial constraints and distinct transportation mode functionality, along with uncovering deficiencies in the public transportation setting of the cultural tourism market of Attica. Overall, this study highlights the requirement for spatial planning and tourism management to be aware of geographical, topological, and functional features of a cultural tourism market and promotes the symbiotic relationship of sustainable tourism development and network science.
Spatial Coherency Model Considering Focal Mechanism Based on Simulated Ground Motions
Authors: Wan Keyu , Sun Xiaodan , Liu Yu , Ren Kang , Sun Xiaoying , Luo Yanqing
Published: February 2022

The spatial coherencies of ground motions are the key to establishing multi-support excitation for large-dimension structures. Most of the existing models were established based on ground motions recorded at dense observation arrays which barely show any detailed information on the focal mechanism. However, in the near field, ground motions are dominated by the source, and so are the spatial coherencies of ground motions. In this paper, a deterministic physics-based method was used to simulate ground motions in the near field for various focal mechanism scenarios. The coherencies of the simulated ground motions were calculated. The Loh coherency model was used to fit the variation in the calculated coherencies for each scenario. The results show that the focal mechanism has a significant effect on the spatial coherencies of simulated ground motions. Finally, the probability density distributions of the parameters, a and b, of the Loh coherency model were obtained, and a coherency model was proposed, based on the Loh coherency model, in which the parameters are taken to be dependent on the focal mechanism.
Retrieval of Nitrogen Content in Apple Canopy Based on Unmanned Aerial Vehicle Hyperspectral Images Using a Modified Correlation Coefficient Method
Authors: Li Meixuan , Zhu Xicun , Li Wei , Tang Xiaoying , Yu Xinyang , Jiang Yuanmao
Published: February 2022

The accurate retrieval of nitrogen content based on Unmanned Aerial Vehicle (UAV) hyperspectral images is limited due to uncertainties in determining the locations of nitrogen-sensitive wavelengths. This study developed a Modified Correlation Coefficient Method (MCCM) to select wavelengths sensitive to nitrogen content. The Normalized Difference Canopy Shadow Index (NDCSI) was applied to remove the shadows from UAV hyperspectral images, thus yielding the canopy spectral information. The MCCM was then used to screen the bands sensitive to nitrogen content and to construct spectral characteristic parameters. Finally, the optimal model for nitrogen content retrieval was established and selected. As a result, the screened sensitive wavelengths for nitrogen content selected were 470, 474, 490, 514, 582, 634, and 682 nm, respectively. Among the nitrogen content retrieval models, the best model was the Support Vector Machine (SVM) model. In the training set, this model outperformed the other models with an R2 of 0.733, RMSE of 6.00%, an nRMSE of 12.76%, and a MAE of 4.49%. Validated by the ground-measured nitrogen content, this model yielded good performance with an R2 of 0.671, an RMSE of 4.73%, an nRMSE of 14.83%, and a MAE of 3.98%. This study can provide a new method for vegetation nutrient content retrieval based on UAV hyperspectral data.
Impact of Nitrogen Application Rates on Upland Rice Performance, Planted under Varying Sowing Times
Authors: Hussain Tajamul , Hussain Nurda , Ahmed Mukhtar , Nualsri Charassri , Duangpan Saowapa
Published: February 2022

Application of suitable nitrogen (N) fertilizer application rate (NR) with respect to sowing time (ST) could help to maximize the performance and productivity of upland rice in Southern Thailand. The 2-year experiments were conducted in the sheds to evaluate the agronomic responses of the upland rice genotype, Dawk Pa–yawm, under various combinations of NR and ST between 2018–2019 and 2019–2020 aimed at obtaining sufficient research evidence for the improved design of long-term field trials in Southern Thailand. As with the initial research, four NR were applied as N0 with no applied N, 1.6 g N pot−1, 3.2 g N pot−1 and 4.8 g N pot−1, and experiments were grown under three ST including early (ST1), medium (ST2) and late sowing (ST3). Results from the experiments indicate that the application of 4.8 g N pot−1 resulted in maximum grain yield under all ST in both years. However, a maximum increase in grain yield was observed under ST2 by 54–101% in 2018–2019 and by 276–339% in 2019–2020. Maximum grain N uptake of 0.57 and 0.82 g pot−1 was also observed at NR 4.8 g N pot−1 under ST2 in both years, respectively. Application of NR 4.8 g N pot−1 resulted in the highest N agronomic efficiency (NAE), nitrogen use efficiency (NUE) and water use efficiency (WUE). However, the performance of yield and yield attributes, N uptake, N use efficiencies and WUE were declined in late sowing (ST3). Significant positive association among yield, yield attributes, N uptake and WUE indicated that an increase in NR up to 4.8 g N pot−1 improved the performance of Dawk Pa–yawm. The results suggest that the application of 4.8 g N pot−1 (90 kg N ha−1) for upland rice being grown during September (ST2) would enhance N use efficiencies, WUE and ultimately improve the yield of upland rice. However, field investigations for current study should be considered prior to general recommendations. Moreover, based on the findings of this study, the importance of variable climatic conditions in the field, and the variability in genotypic response to utilize available N and soil moisture, authors suggest considering more levels of NR and intervals for ST with a greater number of upland rice genotypes to observe variations in field experiments for the precise optimization of NR according to ST.
Steady-State Analysis of Electrical Networks in Pandapower Software: Computational Performances of Newton–Raphson, Newton–Raphson with Iwamoto Multiplier, and Gauss–Seidel Methods
Authors: Vysocký Jan , Foltyn Ladislav , Brkić Dejan , Praksová Renáta , Praks Pavel
Published: February 2022

At the core of every system for the efficient control of the network steady-state operation is the AC-power-flow problem solver. For local distribution networks to continue to operate effectively, it is necessary to use the most powerful and numerically stable AC-power-flow problem solvers within the software that controls the power flows in these networks. This communication presents the results of analyses of the computational performance and stability of three methods for solving the AC-power-flow problem. Specifically, this communication compares the robustness and speed of execution of the Gauss–Seidel (G–S), Newton–Raphson (N–R), and Newton–Raphson method with Iwamoto multipliers (N–R–I), which were tested in open-source pandapower software using a meshed electrical network model of various topologies. The test results show that the pandapower implementations of the N–R method and the N–R–I method are significantly more robust and faster than the G–S method, regardless of the network topology. In addition, a generalized Python interface between the pandapower and the SciPy package was implemented and tested, and results show that the hybrid Powell, Levenberg–Marquardt, and Krylov methods, a quasilinearization algorithm, and the continuous Newton method can sometimes achieve better results than the classical N–R method.
Project Management for Corporate Events: A Set of Tools to Manage Risk and Increase Quality Outcomes
Authors: Dounavi Louiza-Elpida , Dermitzakis Emmanouil , Chatzistelios Georgios , Kirytopoulos Konstantinos
Published: February 2022

The events industry is a project-based industry where sustainable development has been of ever-increasing interest over the last decade. In this regard, the importance of managing risks and delivering quality outcomes in corporate events and the events industry in general cannot be overstated. This paper aims to contribute to the enhancement of project management processes and quality of corporate events, with a focus on risk management. For this purpose, a set of semi-structured interviews with event managers was conducted and thematic analysis was used to qualitatively analyse the research data gathered. Data analysis resulted in the development of a set of tools and methods that have the potential to assist corporate event managers in the project risk management process. This set comprises of a work breakdown structure (WBS) template, a risk breakdown structure (RBS), and a set of risk treatment and mitigation strategies for corporate events. These tools are innovative in the sense that they are based on and correspond to the phases of the event life-cycle rather than individual management domains, have not been developed in unison before, and can be utilized collectively for greater benefits realization.
Net Promoter Score (NPS) and Customer Satisfaction: Relationship and Efficient Management
Authors: Baquero Asier
Published: February 2022

The NPS index is used in the hotel industry to measure customer loyalty and, by extension, customer satisfaction. Many hotel companies set their annual budget based on this index and include it, together with annual economic results, for evaluation when deciding on a potential management bonus. For managers in some companies, achieving a high NPS becomes nearly as important as achieving strong economic results. The purpose of this research is to deepen the study of the NPS index by analysing the existing relationship that the model has with customer satisfaction, focusing on the following main areas of a hotel: reception, cleanliness and room comfort, and gastronomy. To do so, this study uses fuzzy set qualitative comparative analysis (fsQCA). New evidence of value is offered based on the analysis of a sample of six hotels (4 and 5*) located in the Balearic Islands, Spain (Mallorca, Minorca, and Ibiza). In total, 557 surveys were completed in August 2021 and 571 surveys were completed in August 2020, and therefore both sample groups were impacted by a Black Swan (BS) event, the COVID-19 pandemic, in two different stages of its trajectory. The results suggest that in the study sample, the key factor in achieving a high NPS was (1) gastronomy in 2021 (after more than one year of the COVID-19 pandemic), and (2) cleanliness and room comfort in 2020 (at the beginning of the COVID-19 pandemic). These results offer insights for hotel managers, as well as for academics who can develop new lines of research on the subject.
Changes over Time Matter: A Cycle of Participatory Sustainability Assessment of Organic Coffee in Chiapas, Mexico
Authors: Jiménez-Ortega Aldo Daniel , Aguilar Ibarra Alonso , Galeana-Pizaña J. Mauricio , Núñez Juan Manuel
Published: February 2022

This paper discusses how to incorporate the changes within an agroecosystem into sustainability assessment. We measured the sustainability of 86 organic coffee producers located in 4 municipalities of Sierra Madre of Chiapas, Mexico. Based on the MESMIS framework, a set of indicators was selected. A sustainability index was constructed using the multi-criteria decision method known as the analytical hierarchy process in a broad participatory process with producers and cooperatives. Likewise, classification of producers was carried out through land use transitions in their lands between 1999 and 2019 using satellite imagery. A variance analysis between classes was performed to identify statistical differences. The results show that producers who expand their coffee plantations into forested areas have more sustainability levels than those producers who convert agricultural activities into coffee plantations and producers with both transitions in coffee expansion-conversion. The indicators of labor efficiency, benefit-to-cost ratio, price, remnant of primary vegetation, recovery of production from natural phenomena, family succession, and producer land area showed statistical differences between classes. These results are relevant because sustainability assessment is an action-oriented method. Therefore, the contribution of this study can help guide recommendations for specific groups of producers.
Assessing the Impact of Technology Assessment, Responsible Research and Innovation and Sustainability Research: Towards a Common Methodological Approach
Authors: Ladikas Miltos , Hahn Julia , Huang Lei
Published: February 2022

The missions of Technology Assessment (TA), Responsible Research and Innovation (RRI) and Sustainability Research (SR) are similar in their relationship to Science, Technology and Innovation (STI). Although adopting different terminology, the three research fields show great conceptual and methodological overlaps, as all three react to societal demands and policy needs via common tools. The impact of TA, RRI and SR is linked directly, but its assessment requires new thinking in terms of common conceptual and methodological approaches. The paper provides an overview of the current discussion on societal impact assessment and identifies areas of particular interest for the three fields. It describes the current discussions on impact assessment and impact indicators in each field and undertakes a bibliometric analysis that shows clear inter-relationships in terms of thematic focus and a common emphasis on impact in all three fields. Following this analysis, the paper argues for a common impact assessment methodology for TA, RRI and SR, under the notion of resonance and based on the concepts of anticipation, reflection and inclusion.
Effects of Environmental Regulation on Green Total Factor Productivity: An Evidence from the Yellow River Basin, China
Authors: Mao Jinhuang , Wu Qiong , Zhu Meihong , Lu Chengpeng
Published: February 2022

Based on the data of 59 prefecture-level cities in the Yellow River Basin from 2011 to 2019, this paper uses the Slack Based Measure-Global Malmquist Luenberger (SBM-GML) model to measure green total factor productivity (GTFP) of the cities. Under the space–time concept of the Basin, heterogeneity analysis of the upper, middle and lower reaches of the Yellow River Basin is conducted. On this basis, a panel Tobit model is constructed to analyze the impact of environmental regulation on GTFP in the whole basin, upstream region, middle region and downstream region. The results show that the intensity of environmental regulation in the Yellow River Basin increases gradually, which is the highest in the lower reaches, followed by the middle reaches; spatially, the intensity of environmental regulation shows a certain aggregation trend. The green economic growth is realized in the whole basin, and the green technology progress effect is the driving factor of GTFP. The GTFP distribution in the upstream region is relatively concentrated, showing a slow upward trend. The distribution of GTFP in the middle reaches is discrete, and the annual difference is large. In the downstream region, it shows a trend of decline first and then increase. Environmental regulation promotes GTFP in the whole basin, upper, middle and lower reaches, accompanied by certain spatial differences. The Yellow River Basin breaks through the cost effect brought by environmental regulation and triggers technological innovation, thereby enhancing GTFP; the “Porter hypothesis” has been verified in the Yellow River Basin.
Geometric and Topological Bases of a New Classification of Wood Vascular Tissues, Part 2: Classification of Vessels According to Their Grouping
Authors: Bardarov Nikolai , Christoff Nicole , Todorov Vladislav
Published: February 2022

The arrangement of vessels and their grouping is unique in most tree species. When observing tiny, microscopic samples of wood, the arrangement of the wood vessels forms a characteristic and repetitive pattern, which is largely determined by the tree species, but it is also influenced by the site conditions as well as its location in the tree. The present study is part of a project aimed at applying computer vision and computer recognition methods to present a more general and comprehensive group classification of wood vessels. Quantitative descriptions of the grouping of vessels, as a rule, have so far been used mainly to reveal characteristic deviations from the typical structure of wood, for example, due to extreme site conditions. Therefore, they are applicable but not sufficient for the present study and need in-depth revision. A classification of vessels is presented depending on their mutual position, and more precisely, the groups of adjacent vessels are determined using quantitative methods. The quantitative indicators used for this purpose are based on the diameter and other quantitative indicators of the vessels’ arrangements. The proposed classification, although based on a long-known classification scheme in structural wood science, allows for the more precise definition of the classes of a grouping of adjacent vessels in a cross-section as a necessary step towards the wider use of the methods of machine recognition of wood.
The Innovation of the Cashierless Store: A Preliminary Analysis in Italy
Authors: Gazzola Patrizia , Grechi Daniele , Martinelli Ilaria , Pezzetti Roberta
Published: February 2022

The retail sector, under the pressure of digitalization and technological innovation, has experienced profound changes in the last decade, and retailers have had to cope with these changes by implementing new business models and competitive strategies with the aim of satisfying the consumers’ needs. In the last few decades, the sector has been affected by different new trends, from the birth of supermarkets to the advent of e-commerce, up to the introduction of cashierless stores. The latter represents a new category of store that is totally computer-based and digitalized, in which the use of cameras, sensors and self-shelves minimizes human interaction. Amazon pioneered this emerging concept, with the launch of Amazon Go, but other start-up companies are rapidly entering the cashierless retail market and embracing the challenge. The purpose of this paper is to analyze the knowledge of Italian consumers of cashierless shops, and the relevance of different factors related to this new kind of shops. A questionnaire was sent to a sample of more than 1000 consumers to identify and evaluate the actual situation and knowledge of this phenomenon, which is not yet diffuse in Italy. A statistical analysis, regarding both their knowledge about cashierless stores and the customer experience, is provided to discuss the most relevant factors affecting the customers’ perceptions and attitudes, with a comparison per gender and type of users. The results of the provided analysis reveal that the phenomenon is very little known, and this is certainly influenced by the lack of these stores in Italy.
Anatomy-Aware Inference of the 3D Standing Spine Posture from 2D Radiographs
Authors: Bayat Amirhossein , Pace Danielle F. , Sekuboyina Anjany , Payer Christian , Stern Darko , Urschler Martin , Kirschke Jan S. , Menze Bjoern H.
Published: February 2022

An important factor for the development of spinal degeneration, pain and the outcome of spinal surgery is known to be the balance of the spine. It must be analyzed in an upright, standing position to ensure physiological loading conditions and visualize load-dependent deformations. Despite the complex 3D shape of the spine, this analysis is currently performed using 2D radiographs, as all frequently used 3D imaging techniques require the patient to be scanned in a prone position. To overcome this limitation, we propose a deep neural network to reconstruct the 3D spinal pose in an upright standing position, loaded naturally. Specifically, we propose a novel neural network architecture, which takes orthogonal 2D radiographs and infers the spine’s 3D posture using vertebral shape priors. In this work, we define vertebral shape priors using an atlas and a spine shape prior, incorporating both into our proposed network architecture. We validate our architecture on digitally reconstructed radiographs, achieving a 3D reconstruction Dice of 0.95, indicating an almost perfect 2D-to-3D domain translation. Validating the reconstruction accuracy of a 3D standing spine on real data is infeasible due to the lack of a valid ground truth. Hence, we design a novel experiment for this purpose, using an orientation invariant distance metric, to evaluate our model’s ability to synthesize full-3D, upright, and patient-specific spine models. We compare the synthesized spine shapes from clinical upright standing radiographs to the same patient’s 3D spinal posture in the prone position from CT.
Dynamical Symmetry and the Thermofield State at Large N
Authors: Jevicki Antal , Liu Xianlong , Yoon Junggi , Zheng Junjie
Published: February 2022

We discuss thermofield double QFT at real time, in the large N limit. First, we establish a (dynamical) symmetry, which we argue holds in general for the real-time portion of the Schwinger–Kelydish contour. At large N, this symmetry is seen to generate a one-parameter degeneracy of stationary collective solutions. The construction is explicitly worked out on an example of the O(N) vector QFT. As a nontrivial application, we describe the construction of the corresponding (large N) thermofield double state in real-time collective formalism.
Viruses Infecting Greenhood Orchids (Pterostylidinae) in Eastern Australia
Authors: Chao Hsu-Yao , Clements Mark A. , Mackenzie Anne M. , Dietzgen Ralf G. , Thomas John E. , Geering Andrew D. W.
Published: February 2022

The Australasian biogeographic realm is a major centre of diversity for orchids, with every subfamily of the Orchidaceae represented and high levels of endemism at the species rank. It is hypothesised that there is a commensurate diversity of viruses infecting this group of plants. In this study, we have utilised high-throughput sequencing to survey for viruses infecting greenhood orchids (Pterostylidinae) in New South Wales and the Australian Capital Territory. The main aim of this study was to characterise Pterostylis blotch virus (PtBV), a previously reported but uncharacterised virus that had been tentatively classified in the genus Orthotospovirus. This classification was confirmed by genome sequencing, and phylogenetic analyses suggested that PtBV is representative of a new species that is possibly indigenous to Australia as it does not belong to either the American or Eurasian clades of orthotospoviruses. Apart from PtBV, putative new viruses in the genera Alphaendornavirus, Amalgavirus, Polerovirus and Totivirus were discovered, and complete genome sequences were obtained for each virus. It is concluded that the polerovirus is likely an example of an introduced virus infecting a native plant species in its natural habitat, as this virus is probably vectored by an aphid, and Australia has a depauperate native aphid fauna that does not include any species that are host-adapted to orchids.
Zika Virus Immunoglobulin G Seroprevalence among Young Adults Living with HIV or without HIV in Thailand from 1997 to 2017
Authors: Choyrum Sirinath , Wangsaeng Nantawan , Nechba Anouar , Salvadori Nicolas , Saisom Rumpaiphorn , Achalapong Jullapong , Putiyanun Chaiwat , Sabsanong Prapan , Sangsawang Suraphan , Patamasingh Na Ayudhaya Orada , Jourdain Gonzague , Ngo-Giang-Huong Nicole , Khamduang Woottichai
Published: February 2022

Zika virus (ZIKV) epidemiological data in Thailand are limited. We assessed ZIKV IgG seroprevalence among young adults during 1997–2017 and determined factors associated with ZIKV IgG seropositivity. This retrospective laboratory study included randomly selected subjects aged 18–25 years participating in large clinical studies conducted in Thailand during 1997–2017. Stored plasma samples were analyzed for ZIKV IgG using an ELISA test (Anti-Zika Virus IgG, EUROIMMUN, Lübeck, Germany). Sociodemographic, clinical and laboratory data were used in univariable and multivariable analyses to identify factors associated with ZIKV IgG positivity. Of the 1648 subjects included, 1259 were pregnant women, 844 were living with HIV and 111 were living with HBV. ZIKV IgG seroprevalence was similar among the HIV-infected and -uninfected pregnant women (22.8% vs. 25.8%, p-value = 0.335) and was overall stable among the pregnant women, with a 25.2% prevalence. Factors independently associated with ZIKV IgG positivity included an age of 23–25 years as compared to 18–20 years, an HIV RNA load below 3.88 log10 copies/mL and birth in regions outside northern Thailand. Our study shows that a large proportion of the population in Thailand probably remains susceptible to ZIKV infection, which could be the ground for future outbreaks. Continued surveillance of ZIKV spread in Thailand is needed to inform public health policies.
Antibody Response to SARS-CoV-2 Infection and Vaccination in COVID-19-naïve and Experienced Individuals
Authors: Uprichard Susan L. , O’Brien Amornrat , Evdokimova Monika , Rowe Cynthia L. , Joyce Cara , Hackbart Matthew , Cruz-Pulido Yazmin E. , Cohen Courtney A. , Rock Michelle L. , Dye John M. , Kuehnert Paul , Ricks Keersten M. , Casper Marybeth , Linhart Lori , Anderson Katrina , Kirk Laura , Maggiore Jack A. , Herbert Andrew S. , Clark Nina M. , Reid Gail E. , Baker Susan C.
Published: February 2022

Understanding the magnitude of responses to vaccination during the ongoing SARS-CoV-2 pandemic is essential for ultimate mitigation of the disease. Here, we describe a cohort of 102 subjects (70 COVID-19-naïve, 32 COVID-19-experienced) who received two doses of one of the mRNA vaccines (BNT162b2 (Pfizer–BioNTech) and mRNA-1273 (Moderna)). We document that a single exposure to antigen via infection or vaccination induces a variable antibody response which is affected by age, gender, race, and co-morbidities. In response to a second antigen dose, both COVID-19-naïve and experienced subjects exhibited elevated levels of anti-spike and SARS-CoV-2 neutralizing activity; however, COVID-19-experienced individuals achieved higher antibody levels and neutralization activity as a group. The COVID-19-experienced subjects exhibited no significant increase in antibody or neutralization titer in response to the second vaccine dose (i.e., third antigen exposure). Finally, we found that COVID-19-naïve individuals who received the Moderna vaccine exhibited a more robust boost response to the second vaccine dose (p = 0.004) as compared to the response to Pfizer–BioNTech. Ongoing studies with this cohort will continue to contribute to our understanding of the range and durability of responses to SARS-CoV-2 mRNA vaccines.
Duration of Hepatitis B Vaccine-Induced Protection among Medical Students and Healthcare Workers following Primary Vaccination in Infancy and Rate of Immunity Decline
Authors: Phattraprayoon Nanthida , Kakheaw Jirapa , Soonklang Kamonwan , Cheirsilpa Kunsuda , Ungtrakul Teerapat , Auewarakul Chirayu , Mahanonda Nithi
Published: February 2022

Since the introduction of hepatitis B virus (HBV) vaccines, the numbers of HBV infections and complications have significantly decreased. However, the evidence on whether primary vaccination of infants confers lifelong immunity varies. We aimed to assess long-term immunity among healthcare workers and medical students, and the rate of decline of HBV surface antigen antibodies (anti-HBs). Hepatitis B status among participants born after 1 January 1992 was reviewed at Chulabhorn Royal Academy, Thailand. Participants were stratified by intervals since primary vaccination. HBV immunity was determined and analyzed as anti-HBs decline rate in participants with multiple follow-ups. A total of 464 participants were analyzed, with a median age of 23. Protective immunity against HBV (anti-HBs ≥ 10 mIU/mL) at 16–20, 21–25 and 26–28 years post-primary vaccination was 28%, 51.7% and 60%, respectively. The overall declining rate of anti-HBs was −42.39 mIU/mL per year. Participants with anti-HBs levels of >100–1000 mIU/mL at baseline had a faster decline rate than those with anti-HBs levels of 10–100 mIU/mL. Primary vaccination may not provide lifelong protection since HBV immunity deteriorates over time. Individuals with higher initial HBV immunity levels may experience a faster decline rate.