bluuebunny/crossref_metadata_2025 huggingface dataset:
Transforming Innovation Systems into Innovation Ecosystems: The Role of Public Policy
Authors: Zheng Xiaoran , Cai Yuzhuo
Published: June 2022

This study investigated the role of public policy in transforming innovation systems into innovation ecosystems. Despite the numerous studies that examined the role of innovation policies in promoting innovation systems and the increasing attention paid to the transition from innovation systems to innovation ecosystems in the literature, research on the role of public policy in facilitating this transition is sparse. To develop an analytical framework that identifies factors to be considered in policies that facilitate the transition towards innovation ecosystems, we synthesised the literature that investigated (1) the role of policy in innovation systems, (2) new features of innovation ecosystems and (3) the relations between (transformative) policies and innovation ecosystems. To identify these factors, we also drew on the concept of policy layering and the neo-Triple Helix model of innovation ecosystems. Specifically, we identified the following factors: the willingness and capacity of innovation actors to develop cross-boundary interactions on a global scale; an institutionalised civil society based on bottom-up media; and the prevailing sustainability ethos in economic, social and environmental dimensions. These can be used to design and evaluate policies that promote sustainable innovation and development as core features of innovation ecosystems.
The Empirical Evidence of EU–Russia Bilateral Trade under Sanctions and Oil Price Shocks
Authors: Garashchuk Anna , Isla Castillo Fernando , Podadera Rivera Pablo
Published: June 2022

After the annexation of Crimea in 2014, many EU–Russia projects such as the concept of Strategic Partnerships, negotiations on the New Basic Agreement, and the abolishment of visa regime, among other important issues, were suspended. On top of that, the parties involved imposed mutual sanctions which seriously damaged bilateral trade relationships. The present article aims to analyse EU–Russia bilateral trade under the sanctions and low oil prices together with such factors as the growth of Russian and the EU’s GDPs per capita, geographical distance between parties and devaluation of Russian currency by applying a gravity model. Moreover, the model allows us to carry out simulations of circumstances as they would likely have unfolded had the sanctions not been imposed and if oil prices had remained at a reasonable level.
Another Prospective on Real Exchange Rate and the Traded Goods Prices: Revisiting Balassa–Samuelson Hypothesis
Authors: Ishaq Maryam , Ghouse Ghulam , Bhatti Muhammad Ishaq
Published: June 2022

This paper proposes a new variant and reinvestigates the validity of the Balassa–Samuelson (BS) hypothesis for nine East and South Asian countries under new specifications. The BS hypothesis is often criticized for one of its fundamental, but oversimplified assumptions related to Purchasing Power Parity (PPP) holding which can be confirmed for cronss-country tradables’ prices, implying nontraded-sector prices are solely responsible for inducing trend deviations in real exchange rate. The assumption, when empirically tested, does not always hold valid, revealing a price difference in tradables for Asian countries against the world (U.S.), a potential driver of their trend in real exchange rate deviations (appreciation). A new approach based on Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) is used to estimate the long-run BS coefficients, while the error correction mechanism is employed to estimate the short-run estimates. These results motivated us to allow for the inexistence of PPP for cross-country tradables; the standard form of the BS model is then tested in its relaxed form using time-series and panel data econometric tests. Despite a relaxing of the BS model in favor of tradables’ price deviation from PPP, the results are not sufficiently supportive of the BS hypothesis. These findings hold strong economic implications for Asia, suggesting that intercountry sectoral productivity bias of regional economies with the world does not necessarily exert substantial effects on their long-run real exchange rates. Additionally, contrary to the core belief of the BS model, intercountry tradables’ price differentials are found to substantially explain real exchange rate movements away from their long-run equilibrium.
The Relationship between Extensive Application of Technology and “Withdrawal from Nature” of Young People
Authors: Yao Song , Liu Kui
Published: June 2022

The aim of this study is to explore the relationship between the extensive application of technology and young people’s “withdrawal from nature”. Among them, “withdrawal from nature” is mainly manifested in a reduced connection with and concern for nature. Two rounds of semi-structured interviews were conducted with 101 young people from China. Thematic analysis was performed to analyze the interview data and resulted in three main themes: the “compensation”, “shifting” and “shielding” effects of technology. More specifically, the application of technology can partially make up for nature’s reduced role in the growth of young people, shift their concerns for ecological problems, and even affect their perception and evaluation of ecological destruction. Thus, it was proved that the application of technology has an impact on young people’s “withdrawal from nature”. This study supplemented the current research on the factors that influence young people’s “withdrawal from nature” and also provided inspiration for better establishing the connection between young people and nature.
Revealing the Coupling Relationship between the Gross Ecosystem Product and Economic Growth: A Case Study of Hubei Province
Authors: Guan Shuai , Liao Qi , Wu Wenjun , Yi Chuan , Gao Yueming
Published: June 2022

The question of how to balance rapid economic growth with ecosystem pressures has become a key issue in recent years. Using the Tapio decoupling model, the spatial autocorrelation model, and the LMDI decomposition model, we analyzed the spatiotemporal variation in gross ecosystem product (GEP) in Hubei Province, studied the relationship between GEP and economic growth, and analyzed the driving factors of GEP variation. The results show that, during the period 2010–2019, the decoupling coefficient between GEP and economic growth in Hubei Province gradually decreased, while the decoupling relationship changed from weak decoupling to strong decoupling; this change is reflected not only in the decoupling index values of various cities but also in the number of changing cities, so this negative change should attract the attention of policy-makers. In addition, there is a significant local spatial autocorrelation in Hubei Province, mainly distributed in the northwest and southwest of the province, and the trend is becoming increasingly obvious. As the decoupling trend is negative, it is necessary to pay attention to local autocorrelation changes, especially in highly correlated cities, and take action to prevent the further exacerbation of such decoupling to maintain healthy economic and social development. Regarding the driving factors of GEP changes in Hubei Province, cities with strong decoupling and those with weak decoupling have certain differences, and different types of decoupling cities need to adopt different strategies to alleviate pressure on the ecological environment. Cities with a weak decoupling need to address the problem of pollutant emissions associated with industrial upgrading and the positive impact of scientific and technological innovation on the ecological environment. Cities with strong decoupling should not only address pollutant discharge but also improve the area of ecological land. From the perspective of urban development, the high-quality development trend of Wuhan, Yichang, Xiantao, Qianjiang, Xianning, and other cities shows a continuous trend of improvement. Ezhou, Jingzhou, Shennongjia, and other cities need to guard against the loss of ecosystems caused by economic growth.
The Influence of Small-Scale Sporting Events on Participants’ Intentions to Recommend the Host City
Authors: Fernández-Martínez Antonio , Cabello-Manrique David , Roca-Cruz Antonio Francisco , Nuviala Alberto
Published: June 2022

Tourism, including sports tourism, is an important driver of social and economic development. Sports tourism events, and small-scale sporting events in particular, are a powerful resource for promoting tourism in the host city, as a viable way of developing sustainable tourism in the local community. This study aims to analyse the impact of functional quality, outcome quality, satisfaction, and perceived value on intentions to recommend the host city among participants in a small-scale sporting event. A total of 866 runners in a 21-km recreational race participated in this study. A multi-item scale was used and a confirmatory factor analysis of the model was carried out, and the presence of gender differences in the relationships was ascertained using a multigroup analysis. The results revealed a direct effect of functional quality and satisfaction, and an indirect effect of outcome quality and value on intentions to recommend the city. Intention to recommend the city and functional quality showed differences between males and females. In conclusion, managing quality is a key strategy in encouraging participants in small-scale sporting events to recommend the host city.
Development and Validation of a New Questionnaire to Measure Knowledge Level of Street Food Hawkers to Support the Single-Use Plastics Reduction Program in Kelantan, Malaysia
Authors: Abdullah Nur Baizura Aini , Yaacob Nor Azwany , Ismail Ahmad Filza
Published: June 2022

Food hawkers’ knowledge about single-use plastic food containers must be assessed using a valid and reliable tool to improve assessment and evidence collection credibility and to promote environmental sustainability practice. This study aims to develop and validate a new questionnaire to assess the knowledge level of street food hawkers to support the single-use plastics reduction program. Seven experts were involved in the questionnaire process. In the validation process, a cross-sectional study employed the purposive sampling of 660 night-market street food hawkers in a north-eastern state in Peninsular Malaysia, utilising a Google Forms questionnaire with 22 self-administered items. The Content Validity Index (CVI) and Face Validity index (FVI) were used for the construct analysis. The dichotomous response scale was analysed using a two-parameter logistic model of item response theory (2-PL IRT), while marginal reliability used to determine the internal consistency. The I-CVI were calculated for all items with the value ≥ 0.83, except for nine items with I-CVI < 0.83. I-FVI with values of 0.83 or more were acceptable. The 2-PL IRT analyses indicated good psychometric properties considering the discrimination and difficulty index. The marginal reliability value was 0.77. The newly developed questionnaire is a valid and reliable tool to assess the knowledge level of street-food hawkers to support the single-use plastics reduction program.
Application of Clustering Algorithms in the Location of Electric Taxi Charging Stations
Authors: Li Qing , Li Xue , Liu Zuyu , Qi Yaping
Published: June 2022

The reasonable layout of charging stations is an important measure to improve the penetration rate of the electric taxi market. Based on the multi-type clustering algorithm, a widely applicable electric taxi charging stations locating method is proposed. By analyzing the massive gasoline taxi GPS trajectory data, the parking information and charging requirements of electric taxis are extracted, and the research area is divided into reasonable grids. Then, the divided grids are respectively subjected to multiple same-type clustering and multiple multi-type clustering algorithms, so as to help find out the location of the charging station, and a comparative analysis is performed. The empirical analysis shows that the positioning results of the multiple multi-type clustering algorithms are more reasonable than the multiple same-type clustering algorithms, which can effectively prolong the driving distance of electric taxis and save the travel time of drivers.
Analysis on the Spatial Effect of Infrastructure Development on the Real Estate Price in the Yangtze River Delta
Authors: Chen Hanli , Zhang Yu , Zhang Ningxin , Zhou Man , Ding Heping
Published: June 2022

This study explores the spatial effect of infrastructure development on real estate prices in the Yangtze River Delta. It constructs an evaluation system of the infrastructure development level across five dimensions (i.e., transportation, water supply and drainage, energy and power, postal communication, and ecological environment), analyzes the development characteristics of urban infrastructure in the Yangtze River Delta, and uses a spatial panel model to explore how urban infrastructure development affects real estate prices. Results indicate that (1) the overall development level of urban infrastructure in the Yangtze River Delta region shows an upward trend. Significant regional differences exist as the development level of urban infrastructure in the eastern region is ahead of that in the central region; (2) Spatial autocorrelation and real estate prices in the Yangtze River Delta region in infrastructure development and overall levels, respectively, are high; (3) Infrastructure directly affects local real estate market demand and improves the vitality of the housing market in adjacent areas; and (4) Infrastructure construction can significantly promote the rise of urban real estate prices in the eastern region, while this driving effect is not significant in the central region. This research will help the government promote the coordinated development of urban infrastructure and formulate relevant policies for the macro-control of the real estate market in urban agglomerations.
Green Mining Strategy Selection via an Integrated SWOT-PEST Analysis and Fuzzy AHP-MARCOS Approach
Authors: Wu Pan , Zhao Guoyan , Li Yang
Published: June 2022

Deciding on an appropriate development strategy is one of the most crucial aspects of the mining industry’s green transition. This research introduces a novel integrated decision support model that can be applied to analyze various environmental factors and determine development strategies. In this study, a strengths, weaknesses, opportunities, and threats (SWOT) analysis is employed from multiple perspectives, including political, economic, social, and technological (PEST), to assess the internal and external factors that influence green mining. The fuzzy analytic hierarchy process (AHP) is used to analyze the factor weights quantitatively, and the fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method is used to rank and select development strategies. According to the results, “grasp the trend of green development and improve the protection and exploitation level of mineral resources” is found to be the final optimal strategy. Comparative analysis and sensitivity analysis confirmed the accuracy of the model and the case study results.
A Systematic Review of Machine-Translation-Assisted Language Learning for Sustainable Education
Authors: Deng Xinjie , Yu Zhonggen
Published: June 2022

With the rapid development of artificial intelligence, machine translation (MT) has gained popularity in recent years. This study aims to present a systematic review of literature on MT-assisted language learning in terms of main users, theoretical frameworks, users’ attitudes, and the ways in which MT tools are integrated with language teaching and learning. To this end, relevant peer-reviewed articles (n = 26) were selected through the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P) for further analysis. The findings revealed that the main MT users were undergraduate and graduate students. Both teachers and students held mixed attitudes for different reasons. It was also found that MT integration followed four steps, i.e., introduction, demonstration, task assignment, and reflection. The procedures of MT integration could be updated and perfected by introducing other features in the future.
Consumers’ Brand Preferences for Infant Formula: A Grounded Theory Approach
Authors: Tian Yaru , Peng Hua , Dong Xiaoxia , Li Liwang , Zhu Wenqi
Published: June 2022

In recent years, the market pattern of infant formula in China has changed dramatically. The market share of domestic infant formula has exceeded that of imports. The essence of the market share change of domestic and foreign brands is the change of consumers’ brand preferences. To explore which factors affected consumers’ brand preferences, our study conducted a qualitative research method based on the grounded theory, through in-depth interviews with 60 mothers in the Beijing-Tianjin-Hebei region, systematically identifying the factors which affect consumers’ brand preferences for infant formula, which allowed us to establish a theoretical model for them. We found that product characteristics and external environmental factors could directly affect the formation of consumers’ brand preferences, or indirectly through the two intermediary factors of buyers and users. In addition, in the consumption of infant formula, buyers and users were separated, and infants, as actual users, were an important factor that could not be ignored in brand preference.
Spatial Evaluation of Villages and Towns Based on Multi-Source Data and Digital Technology: A Case Study of Suining County of Northern Jiangsu
Authors: Zhang Yuan , Ji Xiang , Sun Liang , Gong Yaxi
Published: June 2022

Based on the research on the current situation and transformation path of the spatial construction of villages and towns in northern Jiangsu, “compactness” and “convenience” are extracted as the elements of spatial evaluation. With multi-source data, comprehensively using ENVI remote sensing image interpretation, GIS spatial analysis, Fragstats landscape index calculation, entropy weight–TOPSIS comprehensive evaluation, and SPSS cluster analysis, a “digital full cycle” of a research framework for the spatial evaluation of villages and towns is built. In this paper, Suining County is taken as the research object, and the spatial construction level of its villages and towns is studied. The research results show that at the county level, the spatial compactness of villages and towns roughly presents the characteristics of an “X” pattern, decreasing from the middle to the four sides, while facility convenience generally presents the characteristics of a right “人” (Chinese character) pattern. At the town level, facility convenience basically presents the pattern characteristics of the “center-node” differentiation structure. The research aims to guide villages and towns to solve the current dilemma of spatial construction, promote the construction of digital villages and towns, and impel the digital transformation of the village and town evaluation system, data, and methods, so as to provide real-time, quantitative, and accurate data and method support for planning and decision-making in villages and towns.
Sustaining Human Nutrition in an Increasingly Urban World
Authors: Valencia Torres Angélica , Tiwari Chetan , Atkinson Samuel F.
Published: June 2022

The complex interaction between social, economic, and environmental processes coupled with transformations of the landscape primarily driven by urbanization have impacts on the access, availability, and distribution, of food. This has resulted in a global micronutrient deficiency and hunger. Given rapid urbanization and population growth, a more sustainable food system is necessary to feed more urban populations and provide adequate nutrition, especially in developing countries. Existing frameworks for modelling urban-environment interactions contain components related to food security, however, lack the specificity needed to evaluate the effects of land use decisions and agricultural production strategies on the health of local populations measured through metrics such as nutritional output. The research presented here proposes an urban nutrition (UN) extension to the previously published urban ecological economic system by developing a focused component that simulates scenarios of different degrees of urbanization and agricultural production techniques to improve the nutritional output of agricultural land, while considering the conservation of soil. This simulation approach was subsequently applied to the Toluca Metropolitan Zone, Mexico. Results showed that nutritional output would greatly increase when adding a variety of crops, even in scenarios where agricultural land is limited. The proposed extension can be used by decision makers worldwide to evaluate how landscape configurations and agricultural production systems affect the nutritional needs of the local population while fostering sustainable practices.
Combined Use of Biochar with 15Nitrogen Labelled Urea Increases Rice Yield, N Use Efficiency and Fertilizer N Recovery under Water-Saving Irrigation
Authors: Haque Ahmad Numery Ashfaqul , Uddin Md. Kamal , Sulaiman Muhammad Firdaus , Amin Adibah Mohd , Hossain Mahmud , Solaiman Zakaria M. , Aziz Azharuddin Abd , Mosharrof Mehnaz
Published: June 2022

Biochar is a potential carbon-rich soil amendment that improves the physicochemical properties of soil, besides acting as a controlled release fertilizer. An experiment was conducted to investigate the effect of biochars on rice yield, fertilizer use efficiency and recovery under water-saving irrigation by 15N isotopic tracer study. Two types of irrigation as alternate wetting and drying (AWD) and continuous flooding (CF), and four types of biochar treatments such as rice husk biochar (RHB) with 15N urea, oil palm empty fruit bunch biochar (EFBB) with 15N urea, 15N urea alone and control, were applied to assess their impact on rice. About 4% reduced grain yield with 18% improved water productivity was achieved by the AWD regime over the CF, whereas RHB and EFBB significantly increased rice yield compared to unamended soil. RHB and EFBB enhanced the water productivity up to 25.3%. The fertilizer N uptake and recovery were boosted by RHB and EFBB up to 18.8% and 24.5%, respectively. RHB and EFBB accelerated the agronomic use efficiency and partial factor productivity of N (up to 21% and 8%, respectively). RHB and EFBB profoundly enhanced the pH, the total C and N and the available N (NH4+ and NO3−) of the post-harvest soil. This study suggests that adding RHB and EFBB with urea improves fertilizer N utilization and soil N retention, and their combination with AWD could enhance rice yield with better water productivity due to their porous structure and controlled N release capacity.
Do Vaccination Attitudes Mediate the Link between Critical Consciousness and COVID-19 Vaccination Behaviour? A Cross-Sectional Study
Authors: Assante Gabriela Monica , Candel Octav Sorin
Published: June 2022

Critical consciousness development represents a building block in the formation of health-related attitudes and behaviours. One of the most studied health-related behaviours in the previous year is COVID-19 vaccination behaviour. The present study examines critical consciousness, COVID-19 vaccination attitudes and vaccination behaviour in a consistent sample of young adults (N = 1185). Participants were residents of Romania, aged 18 to 41 years. The Critical Consciousness Scale—Short Form (CCS-S) and the Vaccination Attitudes Examination (VAX) Scale were used. The results demonstrate the mediating role of two types of vaccination attitude—lack of confidence in the promoted vaccine benefits and worries about unforeseen effects—in the relationship between critical reflection and vaccination behaviour. Communication is fundamental in an initiative aimed at changing behaviour. When shaping a health-related campaign, communication and dialogue must be horizontal and characterised by empathy and mutual recognition to determine favourable health-related behaviour.
Maxillary Sinus Pleomorphic Adenoma: A Systematic Review
Authors: Chęciński Maciej , Nowak Zuzanna
Published: June 2022

Background: Pleomorphic adenoma (PA), also known as a mixed tumor, is a neoplasm of the glandular tissue. The maxillary sinus (MS) is an atypical location of PA; however, as an empty cavity inside the bone, it predisposes tumors to develop unnoticed. The aim of the following systematic review was to identify and characterize the diagnostics and prognosis of maxillary sinus pleomorphic adenoma (MSPA). Methods: The cases of MSPA that underwent treatment and were observed for possible recurrence were qualified for the review. The medical databases were searched using the following engines: ACM, BASE, Google Scholar and PubMed. The risk of bias was assessed using the JBI Critical Appraisal Tool for Case Reports. The extracted data were tabulated and summarized in a descriptive manner. Results: To the best knowledge of the authors, only seven cases of MSPA were described in the last 20 years. Relapse occurred in three of these cases and malignant transformation occurred in two. The longest recorded time without recurrence was 4 years. The size of the detected MSPA in the largest dimension ranged in various cases from 40 to 60 mm, with an average of 48 mm. Discussion: All but one of the seven included reports showed flaws during the risk of bias assessment. Only in two of seven reported cases was there no reason to suspect that the tumor had penetrated the sinus from the oral or nasal cavity. The MS is disadvantageous as a location as tumors occupying the entire volume of the sinus are often diagnosed. Recurrences and malignant transformations seem to be frequent and often remain undetected for a prolonged period. Other information: This research received no external funding. OSF Registries number: 8KVGM.
Differential Response to Cytotoxic Drugs Explains the Dynamics of Leukemic Cell Death: Insights from Experiments and Mathematical Modeling
Authors: Guzev Ekaterina , Bunimovich-Mendrazitsky Svetlana , Firer Michael A.
Published: June 2022

This study presents a framework whereby cancer chemotherapy could be improved through collaboration between mathematicians and experimentalists. Following on from our recently published model, we use A20 murine leukemic cells transfected with monomeric red fluorescent proteins cells (mCherry) to compare the simulated and experimental cytotoxicity of two Federal Drug Administration (FDA)-approved anticancer drugs, Cytarabine (Cyt) and Ibrutinib (Ibr) in an in vitro model system of Chronic Lymphocytic Leukemia (CLL). Maximum growth inhibition with Cyt (95%) was reached at an 8-fold lower drug concentration (6.25 μM) than for Ibr (97%, 50 μM). For the proposed ordinary differential equations (ODE) model, a multistep strategy was used to estimate the parameters relevant to the analysis of in vitro experiments testing the effects of different drug concentrations. The simulation results demonstrate that our model correctly predicts the effects of drugs on leukemic cells. To assess the closeness of the fit between the simulations and experimental data, RMSEs for both drugs were calculated (both RMSEs < 0.1). The numerical solutions of the model show a symmetrical dynamical evolution for two drugs with different modes of action. Simulations of the combinatorial effect of Cyt and Ibr showed that their synergism enhanced the cytotoxic effect by 40%. We suggest that this model could predict a more personalized drug dose based on the growth rate of an individual’s cancer cells.
Dimensionality Reduction, Modelling, and Optimization of Multivariate Problems Based on Machine Learning
Authors: Alswaitti Mohammed , Siddique Kamran , Jiang Shulei , Alomoush Waleed , Alrosan Ayat
Published: June 2022

Simulation-based optimization design is becoming increasingly important in engineering. However, carrying out multi-point, multi-variable, and multi-objective optimization work is faced with the “Curse of Dimensionality”, which is highly time-consuming and often limited by computational burdens as in aerodynamic optimization problems. In this paper, an active subspace dimensionality reduction method and the adaptive surrogate model were proposed to reduce such computational costs while keeping a high precision. In this method, the active subspace dimensionality reduction technique, three-layer radial basis neural network approach, and polynomial fitting process were presented. For the model evaluation, a NASA standard test function problem and RAE2822 airfoil drag reduction optimization were investigated in the experimental design problem. The efficacy of the method was proved by both the experimental examples in which the adaptive surrogate model in a dominant one-dimensional active subspace is given and the optimization efficiency was improved by two orders. Furthermore, the results show that the constructed surrogate model reduced dimensionality and alleviated the complexity of conventional multivariate surrogate modeling with high precision.
A Characterization for the Neighbor-Distinguishing Index of Planar Graphs
Authors: Huo Jingjing , Li Mingchao , Wang Ying
Published: June 2022

Symmetry, such as structural symmetry, color symmetry and so on, plays an important role in graph coloring. In this paper, we use structural symmetry and color symmetry to study the characterization for the neighbor-distinguishing index of planar graphs. Let G be a simple graph with no isolated edges. The neighbor-distinguishing edge coloring of G is a proper edge coloring of G such that any two adjacent vertices admit different sets consisting of the colors of their incident edges. The neighbor-distinguishing index χa′(G) of G is the smallest number of colors in such an edge coloring of G. It was conjectured that if G is a connected graph with at least three vertices and G≠C5, then χa′(G)≤Δ+2. In this paper, we show that if G is a planar graph with maximum degree Δ≥13, then Δ≤χa′(G)≤Δ+1, and, further, χa′(G)=Δ+1 if and only if G contains two adjacent vertices of maximum degree.
Determination of “Neutral”–“Pain”, “Neutral”–“Pleasure”, and “Pleasure”–“Pain” Affective State Distances by Using AI Image Analysis of Facial Expressions
Authors: Prossinger Hermann , Hladký Tomáš , Boschetti Silvia , Říha Daniel , Binter Jakub
Published: June 2022

(1) Background: In addition to verbalizations, facial expressions advertise one’s affective state. There is an ongoing debate concerning the communicative value of the facial expressions of pain and of pleasure, and to what extent humans can distinguish between these. We introduce a novel method of analysis by replacing human ratings with outputs from image analysis software. (2) Methods: We use image analysis software to extract feature vectors of the facial expressions neutral, pain, and pleasure displayed by 20 actresses. We dimension-reduced these feature vectors, used singular value decomposition to eliminate noise, and then used hierarchical agglomerative clustering to detect patterns. (3) Results: The vector norms for pain–pleasure were rarely less than the distances pain–neutral and pleasure–neutral. The pain–pleasure distances were Weibull-distributed and noise contributed 10% to the signal. The noise-free distances clustered in four clusters and two isolates. (4) Conclusions: AI methods of image recognition are superior to human abilities in distinguishing between facial expressions of pain and pleasure. Statistical methods and hierarchical clustering offer possible explanations as to why humans fail. The reliability of commercial software, which attempts to identify facial expressions of affective states, can be improved by using the results of our analyses.
Novel COVID-19 Diagnosis Delivery App Using Computed Tomography Images Analyzed with Saliency-Preprocessing and Deep Learning
Authors: Tello-Mijares Santiago , Woo Fomuy
Published: June 2022

This app project was aimed to remotely deliver diagnoses and disease-progression information to COVID-19 patients to help minimize risk during this and future pandemics. Data collected from chest computed tomography (CT) scans of COVID-19-infected patients were shared through the app. In this article, we focused on image preprocessing techniques to identify and highlight areas with ground glass opacity (GGO) and pulmonary infiltrates (PIs) in CT image sequences of COVID-19 cases. Convolutional neural networks (CNNs) were used to classify the disease progression of pneumonia. Each GGO and PI pattern was highlighted with saliency map fusion, and the resulting map was used to train and test a CNN classification scheme with three classes. In addition to patients, this information was shared between the respiratory triage/radiologist and the COVID-19 multidisciplinary teams with the application so that the severity of the disease could be understood through CT and medical diagnosis. The three-class, disease-level COVID-19 classification results exhibited a macro-precision of more than 94.89% in a two-fold cross-validation. Both the segmentation and classification results were comparable to those made by a medical specialist.
Photon-Counting Detector CT Virtual Monoengergetic Images for Cochlear Implant Visualization—A Head to Head Comparison to Energy-Integrating Detector CT
Authors: Waldeck Stephan , Overhoff Daniel , Alizadeh Leona , Becker Benjamin V. , Port Matthias , Froelich Matthias F. , Brockmann Marc A. , Schumann Sven , Vogl Thomas J. , Schoenberg Stefan O. , Schmidt Sandra
Published: June 2022

Cochlear implants (CIs) are the primary treatment method in patients with profound sensorineural hearing loss. Interpretation of postoperative imaging with conventional energy-integrating detector computed tomography (EID-CT) following CI surgery remains challenging due to metal artifacts. Still, the photon-counting detector (PCD-CT) is a new emerging technology with the potential to eliminate these problems. This study evaluated the performance of virtual monoenergetic (VME) EID-CT images versus PCD-CT in CI imaging. In this cadaveric study, two temporal bone specimens with implanted CIs were scanned with EID-CT and PCD-CT. The images were assessed according to the visibility of interelectrode wire, size of electrode contact, and diameter of halo artifacts. The visibility of interelectrode wire sections was significantly higher when reviewing PCD-CT images. The difference in diameter measurements for electrode contacts between the two CT scanner modalities showed that the PCD-CT technology generally led to significantly larger diameter readings. The larger measurements were closer to the manufacturer’s specifications for the CI electrode. The size of halo artifacts surrounding the electrode contacts did not differ significantly between the two imaging modalities. PCT-CT imaging is a promising technology for CI imaging with improved spatial resolution and better visibility of small structures than conventional EID-CT.
Effects of Chronic Inhalation of Electronic Cigarette Vapor Containing Nicotine on Neurobehaviors and Pre/Postsynaptic Neuron Markers
Authors: Alasmari Fawaz , Alotibi Farraj M. , Alqahtani Faleh , Alshammari Tahani K. , Kadi Aban A. , Alghamdi Abdullah M. , Allahem Bassil S. , Alasmari Abdullah F. , Alsharari Shakir D. , Al-Rejaie Salim S. , Alshammari Musaad A.
Published: June 2022

Nicotine-exposed animal models exhibit neurobehavioral changes linked to impaired synaptic plasticity. Previous studies highlighted alterations in neurotransmitter levels following nicotine exposure. Vesicular glutamate transporter (VGLUT1) and vesicular gamma-aminobutyric acid (GABA) transporter (VGAT) are essential for the transport and release of glutamate and GABA, respectively, from presynaptic neurons into synapses. In our work, an e-cigarette device was used to deliver vapor containing nicotine to C57BL/6J mice for four weeks. Novel object recognition, locomotion, and Y-maze tests were performed to investigate the behavioral parameters. Protein studies were conducted to study the hippocampal expression of VGLUT1, VGAT, and postsynaptic density protein 95 (PSD95) as well as brain cytokine markers. Long-term memory and locomotion tests revealed that e-cigarette aerosols containing nicotine modulated recognition memory and motor behaviors. We found that vapor exposure increased VGLUT1 expression and decreased VGAT expression in the hippocampus. No alterations were found in PSD95 expression. We observed that vapor-containing nicotine exposure altered certain brain cytokines such as IFNβ-1 and MCP-5. Our work provides evidence of an association between neurobehavioral changes and altered hippocampal VGLUT1 and VGAT expression in mice exposed to e-cigarette vapors containing nicotine. Such exposure was also associated with altered neurobehaviors, which might affect neurodegenerative diseases.
Characteristics of Environmentally Persistent Free Radicals in PM2.5 and the Influence of Air Pollutants in Shihezi, Northwestern China
Authors: He Feifei , Lu Jianjiang , Li Zhuoying , Li Min , Liu Zilong , Tong Yanbin
Published: June 2022

Environmentally persistent free radicals (EPFRs) are a kind of hazardous substance that exist stably in the atmosphere for a long time. EPFRs combined with fine particulate matter (PM2.5) can enter the human respiratory tract through respiration, causing oxidative stress and DNA damage, and they are also closely related to lung cancer. In this study, the inhalation risk for EPFRs in PM2.5 and factors influencing this risk were assessed using the equivalent number of cigarette tar EPFRs. The daily inhalation exposure for EPFRs in PM2.5 was estimated to be equivalent to 0.66–8.40 cigarette tar EPFRs per day. The concentration level and species characteristics were investigated using electron paramagnetic resonance spectroscopy. The concentration of EPFRs in the study ranged from 1.353–4.653 × 1013 spins/g, and the types of EPFRs were mainly oxygen- or carbon-centered semiquinone-type radicals. Our study showed that there is a strong correlation between the concentrations of EPFRs and conventional pollutants, except for sulfur dioxide. The major factors influencing EPFR concentration in the atmosphere were temperature and wind speed; the higher the temperature and wind speed, the lower the concentration of EPFRs. The findings of this study provide an important basis for further research on the formation mechanism and health effects of EPFRs.
In Situ Measurements of Domestic Water Quality and Health Risks by Elevated Concentration of Heavy Metals and Metalloids Using Monte Carlo and MLGI Methods
Authors: Senoro Delia B. , de Jesus Kevin Lawrence M. , Nolos Ronnel C. , Lamac Ma. Rowela L. , Deseo Khainah M. , Tabelin Carlito B.
Published: June 2022

The domestic water (DW) quality of an island province in the Philippines that experienced two major mining disasters in the 1990s was assessed and evaluated in 2021 utilizing the heavy metals pollution index (MPI), Nemerow’s pollution index (NPI), and the total carcinogenic risk (TCR) index. The island province sources its DW supply from groundwater (GW), surface water (SW), tap water (TP), and water refilling stations (WRS). This DW supply is used for drinking and cooking by the population. In situ analyses were carried out using an Olympus Vanta X-ray fluorescence spectrometer (XRF) and Accusensing Metals Analysis System (MAS) G1 and the target heavy metals and metalloids (HMM) were arsenic (As), barium (Ba), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), nickel (Ni), and zinc (Zn). The carcinogenic risk was evaluated using the Monte Carlo (MC) method while a machine learning geostatistical interpolation (MLGI) technique was employed to create spatial maps of the metal concentrations and health risk indices. The MPI values calculated at all sampling locations for all water samples indicated a high pollution. Additionally, the NPI values computed at all sampling locations for all DW samples were categorized as “highly polluted”. The results showed that the health quotient indices (HQI) for As and Pb were significantly greater than 1 in all water sources, indicating a probable significant health risk (HR) to the population of the island province. Additionally, As exhibited the highest carcinogenic risk (CR), which was observed in TW samples. This accounted for 89.7% of the total CR observed in TW. Furthermore, all sampling locations exceeded the recommended maximum threshold level of 1.0 × 10−4 by the USEPA. Spatial distribution maps of the contaminant concentrations and health risks provide valuable information to households and guide local government units as well as regional and national agencies in developing strategic interventions to improve DW quality in the island province.
Development and In Vitro Validation of Antibacterial Paints Containing Chloroxylenol and Terpineol
Authors: Querido Micaela Machado , Paulo Ivo , Hariharakrishnan Sriram , Rocha Daniel , Barbosa Nuno , Gonçalves Diogo , Galhano dos Santos Rui , Bordado João Moura , Teixeira João Paulo , Pereira Cristiana Costa
Published: June 2022

The establishment of self-disinfecting surfaces is an important method to avoid surface contamination. Recently, paints with antimicrobial properties have been developed to be applied on different surfaces, avoiding contamination with pathogens. In this work, self-disinfecting paints containing Chloroxylenol (CLX), Terpineol (TRP), and a mixture of both substances were developed. The goal was to evaluate and validate these paints using international standards for eventual commercialization and application in scenarios where surface contamination represents a problem. The paints were challenged with five different bacteria, Gram-positive and Gram-negative, before and after a scrub resistance test, where the long-term efficacy of the paints was evaluated. The antibacterial activity assessment was performed following ISO 22196 and JIS Z2801. In general, the paints showed very promising results, demonstrating their antibacterial activity, before and after scrub resistance test. The paint incorporating the mixture of CLX and TRP (CLX+TRP) stood out by revealing consistent results of antibacterial activity both before and after the scrub resistance test for most of the tested bacteria. The cytotoxicity of the developed paints was assessed in vitro by performing tests by direct contact with a human skin cell line, HaCaT, and testes on extracts with HaCaT and a pulmonary cell line, A549. The methodologies for cytotoxicity assessment were developed based in ISO 10993. For genotoxicity assessment, alkaline comet assay was conducted on both cell lines. The cytotoxicity assessment revealed promising results with the paints, demonstrating values of cellular viability above 70% and values of lactate dehydrogenase (LDH) leakage below 30%. The genotoxic assessment also revealed acceptable values of primary DNA damage for the developed antibacterial paints. In general, the selected methodologies presented good potential to be applied in the validation of both efficacy and safety of the antimicrobial paints, aiming to be applied in real scenarios.
Ecological Integrity Impairment and Habitat Fragmentation for Neotropical Macroinvertebrate Communities in an Agricultural Stream
Authors: Echeverría-Sáenz Silvia , Ugalde-Salazar Rocío , Guevara-Mora Meyer , Quesada-Alvarado Francisco , Ruepert Clemens
Published: June 2022

The Volcán River watershed in the south Pacific of Costa Rica comprises forests, small urban settlements, cattle fields, and intensive agriculture (mostly pineapple and sugarcane). The ecological integrity and quality of its waters was assessed from 2011–2013 and 2018–2019 by means of physical–chemical parameters (pH, conductivity, temperature, DO, DBO, nitrate, total phosphorus, and pesticide residues) and benthic macroinvertebrate (MI) sampling in eight sites (Volcán, Cañas, and Ángel Rivers, and Peje and Maura streams), resulting in high ecological integrity in all sites except the Peje stream, which is polluted with nitrates and pesticides. Only in this stream was there a marked seasonal variation in the abundance of 16 MI families including Leptohyphidae, Leptophlebiidae, Philopotamidae, Glossossomatidae, and Corydalidae, among others, whose presence was limited exclusively to the dry season (December to April), disappearing from the stream in the rainy season, with corresponding peaks in nitrate (max 20.3 mg/L) and pesticides (mainly herbicides and organophosphate insecticides). The characteristics of the watershed, with large areas of forest and excellent water quality, allow for the re-colonization of organisms into the Peje stream; however, those organisms are incapable of development and growth, providing evidence of a contaminant-driven habitat fragmentation in this stream during the rainy season.
Contrasting Scaling Properties of Near-Sun Sub-Alfvénic and Super-Alfvénic Regions
Authors: Alberti Tommaso , Benella Simone , Carbone Vincenzo , Consolini Giuseppe , Quattrociocchi Virgilio , Stumpo Mirko
Published: June 2022

Scale-invariance has rapidly established itself as one of the most used concepts in space plasmas to uncover underlying physical mechanisms via the scaling-law behavior of the statistical properties of field fluctuations. In this work, we characterize the scaling properties of the magnetic field fluctuations in a sub-alfvénic region in contrast with those of the nearby super-alfvénic zone during the ninth Parker Solar Probe perihelion. With our observations, (i) evidence of an extended self-similarity (ESS) for both the inertial and the sub-ion/kinetic regimes during both solar wind intervals is provided, (ii) a multifractal nature of field fluctuations is observed across inertial scales for both solar wind intervals, and (iii) a mono-fractal structure of the small-scale dynamics is reported. The main novelty is that a universal character is found at the sub-ion/kinetic scale, where a unique rescaling exponent describes the high-order statistics of fluctuations during both wind intervals. Conversely, a multitude of scaling symmetries is observed at the inertial scale with a similar fractal topology and geometrical structures between the magnetic field components in the ecliptic plane and perpendicular to it, in contrast with a different level of intermittency, more pronounced during the super-alfvénic interval rather than the sub-alfvénic one, along the perpendicular direction to the ecliptic plane. The above features are interpreted in terms of the possible underlying heating and/or acceleration mechanisms in the solar corona resulting from turbulence and current sheet formation.