bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization and Implementation of Cocoa Pod Husk as a Reinforcing Agent to Obtain Thermoplastic Starches and Bio-Based Composite Materials
Authors: Holguín Posso Andrés Mauricio , Macías Silva Juan Carlos , Castañeda Niño Juan Pablo , Mina Hernandez Jose Herminsul , Fajardo Cabrera de Lima Lety del Pilar
Published: June 2024

When the cocoa pod husk (CPH) is used and processed, two types of flour were obtained and can be differentiated by particle size, fine flour (FFCH), and coarse flour (CFCH) and can be used as a possible reinforcement for the development of bio-based composite materials. Each flour was obtained from chopping, drying by forced convection, milling by blades, and sieving using the 100 mesh/bottom according to the Tyler series. Their physicochemical, thermal, and structural characterization made it possible to identify the lower presence of lignin and higher proportions of cellulose and pectin in FFCH. Based on the properties identified in FFCH, it was included in the processing of thermoplastic starch (TPS) from the plantain pulp (Musa paradisiaca) and its respective bio-based composite material using plantain peel short fiber (PPSF) as a reinforcing agent using the following sequence of processing techniques: extrusion, internal mixing, and compression molding. The influence of FFCH contributed to the increase in ultimate tensile strength (7.59 MPa) and higher matrix–reinforcement interaction when obtaining the freshly processed composite material (day 0) when compared to the bio-based composite material with higher FCP content (30%) in the absence of FFCH. As for the disadvantages of FFCH, reduced thermal stability (323.57 to 300.47 °C) and losses in ultimate tensile strength (0.73 MPa) and modulus of elasticity (142.53 to 26.17 MPa) during storage progress were identified. In the case of TPS, the strengthening action of FFCH was not evident. Finally, the use of CFCH was not considered for the elaboration of the bio-based composite material because it reached a higher lignin content than FFCH, which was expected to decrease its affinity with the TPS matrix, resulting in lower mechanical properties in the material.
For Ever and Ever the Perfect Wedding Picture: Converging Religious and Secular Norms and Values in Wedding Photography
Authors: Mäder Marie-Therese
Published: June 2024

The paper examines how stylistic norms of wedding photography express, affirm, adapt, and reshape religious and secular values by combining ethical considerations with qualitative ethnographic observations. The first part offers a critique of the distinction between civil secular and religious weddings in current scholarship. In the second part, the relation between norms and values in an ethics of wedding photos is elaborated. The discussion is illustrated with examples from a study with 27 married couples and their wedding photos. The study reveals two key aspects: In the production of wedding photos, the triangular relation between the couple, their guests, and the location, the so-called locationship, is staged through the lens of the camera. In this triangle, the blending of religious and secular norms and values could be observed. Another significant aspect is how norms and values originating from wedding photography of religious ceremonies continue to impact secular norms and values. It is particularly noteworthy that religion serves as an aesthetic matrix in wedding photography, contributing to a “visual enchantment”, irrespective of whether the ceremony is religious or secular in nature.
The Pursuit of Justice in the Women’s March: Toward an Islamic Liberatory Theology of Resistance
Authors: Anwar Etin
Published: June 2024

The Women’s March on 21 January 2017, opened a new social and political landscape for Muslim women to engage in Islamic liberatory activism. I locate Muslim women’s participation in the marches following the 2017 ‘Muslim travel ban policy’ as a site for discovering the link between the politics of resistance and the utility of Islam as a source for liberation. I argue that Muslim women living in minority and post-secular contexts resort to faith as a source of agentival liberation to address the political rhetoric of anti-Islamic sentiments and policies. The outcome of this research demonstrates (1) how Muslim women activists challenge the Western narratives of being oppressed and explore the ways they want to represent themselves; (2) how Islam serves as a catalyst for theological resistance and how this enhances the role of Muslim women as moral and spiritual agents in transforming their political and social conditions; (3) how the Islamic liberation in the US context historically intersects with Black churches’ resistance toward White racism; and (4) how Muslim women’s agency as spiritual beings is linked to the promotion of justice in the Western liberatory movements. Overall, the article shows how Muslim women resort to their spiritual journey and use such narratives to confront unjust political rhetoric and policies.
Inter-Comparison of SST Products from iQuam, AMSR2/GCOM-W1, and MWRI/FY-3D
Authors: Zhao Yili , Liu Ping , Zhou Wu
Published: June 2024

Evaluating sea surface temperature (SST) products is essential before their application in marine environmental monitoring and related studies. SSTs from the in situ SST Quality Monitor (iQuam) system, Advanced Microwave Scanning Radiometer 2 (AMSR2) aboard the Global Change Observation Mission 1st-Water, and the Microwave Radiation Imager (MWRI) aboard the Chinese Fengyun-3D satellite are intercompared utilizing extended triple collocation (ETC) and direct comparison methods. Additionally, error characteristic variations with respect to time, latitude, SST, sea surface wind speed, columnar water vapor, and columnar cloud liquid water are analyzed comprehensively. In contrast to the prevailing focus on SST validation accuracy, the random errors and the capability to detect SST variations are also evaluated in this study. The result of ETC analysis indicates that iQuam SST from ships exhibits the highest random error, above 0.83 °C, whereas tropical mooring SST displays the lowest random error, below 0.28 °C. SST measurements from drifters, tropical moorings, Argo floats, and high-resolution drifters, which possess random errors of less than 0.35 °C, are recommended for validating remotely sensed SST. The ability of iQuam, AMSR2, and MWRI to detect SST variations diminishes significantly in ocean areas between 0°N and 20°N latitude and latitudes greater than 50°N and 50°S. AMSR2 and iQuam demonstrate similar random errors and capabilities for detecting SST variations, whereas MWRI shows a high random error and weak capability. In comparison to iQuam SST, AMSR2 exhibits a root-mean-square error (RMSE) of about 0.51 °C with a bias of −0.05 °C, while MWRI shows an RMSE of about 1.26 °C with a bias of −0.14 °C.
Contactless X-Band Detection of Steel Bars in Cement: A Preliminary Numerical and Experimental Analysis
Authors: Brancaccio Adriana , Palladino Simone
Published: June 2024

This work presents preliminary experimental results for advancing non-destructive testing methods for detecting steel bars in cement via contactless investigations in the X-band spectrum. This study reveals the field’s penetration into cement, extracting insights into embedded bars through scattered data. Applying a quasi-quadratic inverse scattering technique to numerically simulated data yields promising results, confirming the effectiveness and reliability of the proposed approach. In this realm, using a higher frequency allows for the use of lighter equipment and smaller antennas. Identified areas for improvement include accounting for antenna behavior and establishing the undeformed target morphology and precise orientation. Transitioning from powder-based and sand specimens to real, solid, reinforced concrete structures is expected to alleviate laboratory challenges. Although accurately determining concrete properties such as its relative permittivity and conductivity is essential, it remains beyond the scope of this study. Finally, overcoming these challenges could significantly enhance non-invasive testing, improving structural health monitoring and disaster prevention.
Focus on the Crop Not the Weed: Canola Identification for Precision Weed Management Using Deep Learning
Authors: Mckay Michael , Danilevicz Monica F. , Ashworth Michael B. , Rocha Roberto Lujan , Upadhyaya Shriprabha R. , Bennamoun Mohammed , Edwards David
Published: June 2024

Weeds pose a significant threat to agricultural production, leading to substantial yield losses and increased herbicide usage, with severe economic and environmental implications. This paper uses deep learning to explore a novel approach via targeted segmentation mapping of crop plants rather than weeds, focusing on canola (Brassica napus) as the target crop. Multiple deep learning architectures (ResNet-18, ResNet-34, and VGG-16) were trained for the pixel-wise segmentation of canola plants in the presence of other plant species, assuming all non-canola plants are weeds. Three distinct datasets (T1_miling, T2_miling, and YC) containing 3799 images of canola plants in varying field conditions alongside other plant species were collected with handheld devices at 1.5 m. The top performing model, ResNet-34, achieved an average precision of 0.84, a recall of 0.87, a Jaccard index (IoU) of 0.77, and a Macro F1 score of 0.85, with some variations between datasets. This approach offers increased feature variety for model learning, making it applicable to the identification of a wide range of weed species growing among canola plants, without the need for separate weed datasets. Furthermore, it highlights the importance of accounting for the growth stage and positioning of plants in field conditions when developing weed detection models. The study contributes to the growing field of precision agriculture and offers a promising alternative strategy for weed detection in diverse field environments, with implications for the development of innovative weed control techniques.
EMR-HRNet: A Multi-Scale Feature Fusion Network for Landslide Segmentation from Remote Sensing Images
Authors: Jin Yuanhang , Liu Xiaosheng , Huang Xiaobin
Published: June 2024

Landslides constitute a significant hazard to human life, safety and natural resources. Traditional landslide investigation methods demand considerable human effort and expertise. To address this issue, this study introduces an innovative landslide segmentation framework, EMR-HRNet, aimed at enhancing accuracy. Initially, a novel data augmentation technique, CenterRep, is proposed, not only augmenting the training dataset but also enabling the model to more effectively capture the intricate features of landslides. Furthermore, this paper integrates a RefConv and Multi-Dconv Head Transposed Attention (RMA) feature pyramid structure into the HRNet model, augmenting the model’s capacity for semantic recognition and expression at various levels. Last, the incorporation of the Dilated Efficient Multi-Scale Attention (DEMA) block substantially widens the model’s receptive field, bolstering its capability to discern local features. Rigorous evaluations on the Bijie dataset and the Sichuan and surrounding area dataset demonstrate that EMR-HRNet outperforms other advanced semantic segmentation models, achieving mIoU scores of 81.70% and 71.68%, respectively. Additionally, ablation studies conducted across the comprehensive dataset further corroborate the enhancements’ efficacy. The results indicate that EMR-HRNet excels in processing satellite and UAV remote sensing imagery, showcasing its significant potential in multi-source optical remote sensing for landslide segmentation.
Highly Sensitive Balloon-like Fiber Interferometer Based on Ethanol Coated for Temperature Measurement
Authors: Ding Xin , Lin Qiao , Liu Shen , Zhang Lianzhen , Chen Nan , Zhang Yuping , Wang Yiping
Published: June 2024

A highly sensitivity balloon-like fiber interferometer based on ethanol coating is presented in this paper. The Mach–Zehnder interferometer is formed by bending a single-mode fiber to a balloon-like structure and nested in the Teflon tube. Then, an ethanol solution was filled into the tube of the balloon-like fiber interferometer by the capillary effect. Due to the high sensitivity of the refractive index (RI) of ethanol solutions to temperature, when the external temperature varies, the optical path difference changes. The change in temperature can be detected by the shift in the interference spectrum. Limited by the size of the balloon-like structure, three kinds of these structures with different sensitive lengths were prepared to select the best parameters. The sensitive lengths were 10, 15 and 20 mm, respectively, and the RI detection performance of each structure in 10~26% NaCl solutions was investigated experimentally. The results show that when the sensitive length is 20 mm, the RI sensitivity of the sensor is the highest, which is 212.88 nm/RIU. Ultimately, the sensitive length filled with ethanol is 20 mm. The experimental results show that the temperature sensitivity of the structure is 1.145 nm/°C in the range of 28.1 °C~35 °C, which is 10.3 times higher than that of an unfilled balloon-like structure (0.111 nm/°C). The system has the advantages of low cost and easy fabrication, which can potentially be used in high-precision temperature monitoring processes.
Computer Vision and Augmented Reality for Human-Centered Fatigue Crack Inspection
Authors: Mojidra Rushil , Li Jian , Mohammadkhorasani Ali , Moreu Fernando , Bennett Caroline , Collins William
Published: June 2024

A significant percentage of bridges in the United States are serving beyond their 50-year design life, and many of them are in poor condition, making them vulnerable to fatigue cracks that can result in catastrophic failure. However, current fatigue crack inspection practice based on human vision is time-consuming, labor intensive, and prone to error. We present a novel human-centered bridge inspection methodology to enhance the efficiency and accuracy of fatigue crack detection by employing advanced technologies including computer vision and augmented reality (AR). In particular, a computer vision-based algorithm is developed to enable near-real-time fatigue crack detection by analyzing structural surface motion in a short video recorded by a moving camera of the AR headset. The approach monitors structural surfaces by tracking feature points and measuring variations in distances between feature point pairs to recognize the motion pattern associated with the crack opening and closing. Measuring distance changes between feature points, as opposed to their displacement changes before this improvement, eliminates the need of camera motion compensation and enables reliable and computationally efficient fatigue crack detection using the nonstationary AR headset. In addition, an AR environment is created and integrated with the computer vision algorithm. The crack detection results are transmitted to the AR headset worn by the bridge inspector, where they are converted into holograms and anchored on the bridge surface in the 3D real-world environment. The AR environment also provides virtual menus to support human-in-the-loop decision-making to determine optimal crack detection parameters. This human-centered approach with improved visualization and human–machine collaboration aids the inspector in making well-informed decisions in the field in a near-real-time fashion. The proposed crack detection method is comprehensively assessed using two laboratory test setups for both in-plane and out-of-plane fatigue cracks. Finally, using the integrated AR environment, a human-centered bridge inspection is conducted to demonstrate the efficacy and potential of the proposed methodology.
5G AI-IoT System for Bird Species Monitoring and Song Classification
Authors: Segura-Garcia Jaume , Sturley Sean , Arevalillo-Herraez Miguel , Alcaraz-Calero Jose M. , Felici-Castell Santiago , Navarro-Camba Enrique A.
Published: June 2024

Identification of different species of animals has become an important issue in biology and ecology. Ornithology has made alliances with other disciplines in order to establish a set of methods that play an important role in the birds’ protection and the evaluation of the environmental quality of different ecosystems. In this case, the use of machine learning and deep learning techniques has produced big progress in birdsong identification. To make an approach from AI-IoT, we have used different approaches based on image feature comparison (through CNNs trained with Imagenet weights, such as EfficientNet or MobileNet) using the feature spectrogram for the birdsong, but also the use of the deep CNN (DCNN) has shown good performance for birdsong classification for reduction of the model size. A 5G IoT-based system for raw audio gathering has been developed, and different CNNs have been tested for bird identification from audio recordings. This comparison shows that Imagenet-weighted CNN shows a relatively high performance for most species, achieving 75% accuracy. However, this network contains a large number of parameters, leading to a less energy efficient inference. We have designed two DCNNs to reduce the amount of parameters, to keep the accuracy at a certain level, and to allow their integration into a small board computer (SBC) or a microcontroller unit (MCU).
Localization Performance Analysis and Algorithm Design of Reconfigurable Intelligent Surface-Assisted D2D Systems
Authors: Wang Mengke , Lv Tiejun , Huang Pingmu , Lin Zhipeng
Published: June 2024

The research on high-precision and all-scenario localization using the millimeter-wave (mmWave) band is of great urgency. Due to the characteristics of mmWave, blockages make the localization task more complex. This paper proposes a cooperative localization system among user equipment (UEs) assisted by reconfigurable intelligent surfaces (RISs), which considers device-to-device (D2D) communication. RISs are used as anchor points, and position estimation is achieved through signal exchanges between UEs. Firstly, we establish a localization model based on this system and derive the UEs’ positioning error bound (PEB) as a performance metric. Then, a UE-RIS joint beamforming design is proposed to optimize channel state information (CSI) with the objective of achieving the minimum PEB. Finally, simulation analysis demonstrates the advantages of the proposed scheme over RIS-assisted base station positioning, achieving centimeter-level accuracy with a 10 dBm lower transmission power.
Confession and Confusion: Misinformation about Religion in the Journalistic Sphere
Authors: Laferrara Valentina , Fernández Maria Carmen , Israel Turim Verónica
Published: June 2024

The media often limit religious coverage to reporting on statements, appointments, opinions, and activities, ignoring in-depth treatment and emphasizing negative news. Media, rather than helping to combat prejudice and promote understanding between communities, have contributed to fuelling intolerance towards religious communities. This study aims to contribute to the understanding of the presence and treatment of religious issues. Through a combination of content analysis focused on Catalan media publications between 1 January 2020 and 31 December 2021, and a focus group with 12 journalists specialized in religious coverage for Catalan newspapers, this research sheds light on the prevailing trends, seeking to answer what is the space of religious content, which can include both content messages produced by religious communities that refer to their own or other faiths and/or content that discusses issues related to religions or religious groups. Occupies in the media agenda, how this content is addressed, and which are the perceptions of journalists regarding the coverage of religious issues. Moreover, we seek to unveil potential actions needed to improve it. The results of this study suggest that there is a tendency to publish limited religious content in the media, potentially shaping perceptions of religion. Furthermore, when religious topics are covered, they focus on Catholicism and Islam, marginalizing other faiths. What is more, stereotypes and misconceptions persist, which could be due to their continued priority to cover scandalous or negative events related to religion.
Enhancing Environmental, Social, and Governance Performance through New Quality Productivity and Green Innovation
Authors: Li Jiaran , Noorliza Karia , Zhang Xiaohan
Published: June 2024

Sustainability practices are increasingly significant in the current business environment, much more so in China with its rapid economic growth. What drives environmental, social, and governance (ESG) performance, especially regarding the impacts of new quality productivity and green innovation, is thus of importance. The study further assesses the impact of new quality productivity and green innovation on ESG performance with listed companies in China. The research is empirical and regresses the data of the Chinese listed companies from 2011 to 2022. The important findings indicate that new quality productivity significantly improves ESG performance. Efficient innovation practice plays a key role in the promotion of corporate sustainability. Green innovation contributes directly to ESG improvement and enhances the effects of new quality productivity on ESG. This moderating effect has proven to be the more important reason why innovation should be well-infused into core business strategies for sustainable optimization. In addition, this study examines the differential impact of new quality productivity across regions, firm types, and development stages, showing that its effectiveness in driving ESG performance is constrained by the geographic location, firm development stage, and industry characteristics. These findings emphasize the importance of incorporating new quality productivity enhancement and green innovation into corporate strategies, providing valuable insights for managers, policymakers, and investors.
Research on Fatigue Characteristics and Prediction of Large-Particle Asphalt Mixtures Based on Four-Point Bending Tests
Authors: Wei Li , Lv Jinlong , Rong Hongliu , Yang Xiaolong
Published: June 2024

Large aggregate asphalt mixtures can absorb noise, reduce water damage, effectively improve the service life of roads, and reduce environmental pressure. In this study, the fatigue characteristics of a large-sized asphalt mixture, LSAM-30, were investigated using four-point bending tests. The fatigue performance of LSAM-30 was compared to that of AC-13 and AC-20 asphalt mixtures across a range of temperatures, frequencies, and strains. The results indicated that the temperature, frequency, and strain significantly affect the fatigue performance of LSAM-30. As the temperature or frequency increased, the disparity in the fatigue performances of LSAM-30, AC-13, and AC-20 became more pronounced. Furthermore, the variations in the strain did not exhibit a clear pattern in the fatigue performance ratio among the three asphalt mixtures, with the ratio changes being minor (<5%). Additionally, an exponential-function-based predictive equation was proposed, showing how the fatigue characteristics of LSAM-30 vary with changes in frequency and temperature.
Exploring the Effects of Urban Development in Ten Chinese Node Cities along the Belt and Road Initiative on Vegetation Net Primary Productivity
Authors: Liu Gaosheng , Pan Jie , Jiang Yuxin , Ye Xinquan , Shao Fan
Published: June 2024

Urbanization and economic growth in node cities surged due to the Belt and Road Initiative (BRI), leading to significant environmental changes, notably in vegetation net primary productivity (NPP). Investigating the ecological impact of these urban changes was crucial, despite scarce relevant studies. We employed Sen’s slope estimation and Mann–Kendall trend analysis to study NPP trends (2005–2020) in ten Belt and Road node cities. The Optimized Parameters Geographic Detector Model (OPGD) analyzed factors impacting NPP and their interactions. Results revealed significant NPP variations among the ten cities, ranging from 656.47 gCm−2a−1 to 250.55 gCm−2a−1, with over 79% showing increasing trends. Since 2013, Chongqing, Wuhan, Hefei, Nanchang, and Changsha experienced declining NPP, while the other five cities saw an increase. Natural factors like temperature, precipitation, and DEM predominantly influence rising NPP trends, while anthropogenic factors like land use changes and nighttime light drive NPP decline. Land use changes, with 39.0% explanatory power, primarily affect NPP. After 2013, construction land increased by 117.7 km2 on average, while arable land decreased by 274.8 km2, contributing to decreased vegetation cover NPP. Nighttime lights explained up to 25% of NPP variance. Regions with high nocturnal light values exhibited more developed urbanization but comparatively lower NPP levels.
Mapping Maize Evapotranspiration with Two-Source Land Surface Energy Balance Approaches and Multiscale Remote Sensing Imagery Pixel Sizes: Accuracy Determination toward a Sustainable Irrigated Agriculture
Authors: Costa-Filho Edson , Chávez José L. , Zhang Huihui
Published: June 2024

This study evaluated the performance of remote sensing (RS) algorithms for the estimation of actual maize evapotranspiration (ETa) using different spaceborne, airborne, and proximal multispectral data in a semi-arid climate region to identify the optimal platform that provides the best ETa estimates to improve irrigation water management and help make irrigated agriculture sustainable. The RS platforms used in the study included Landsat-8 (30 m pixel spatial resolution), Sentinel-2 (10 m), Planet CubeSat (3 m), multispectral radiometer or MSR (1 m), and a small uncrewed aerial system or sUAS (0.03 m). Two-source surface energy balance (TSEB) models, implementing the series and parallel surface resistance approaches, were used in this study to estimate hourly maize ETa. The data used in this study were obtained from two maize research sites in Greeley and Fort Collins, CO, USA, in 2020 and 2021. Each research site had different irrigation systems. The Greeley site had a subsurface drip system, while the Fort Collins site had surface irrigation (furrow). Maize ETa predictions were compared to observed maize ETa data from an eddy covariance system installed at each research site. Results indicated that the MSR5 proximal platform (1 m) provided optimal RS data for the TSEB algorithms. The MSR5 “point-based” nadir-looking surface reflectance data and surface radiometric temperature combination resulted in the smallest error when predicting hourly (mm/h) maize ETa. The mean bias and root mean square errors (MBE and RMSE, respectively), when predicting maize hourly ETa using the MSR5 sensor data, were equal to −0.02 (−3%) ± 0.07 (11%) mm/h MBE ± RMSE and −0.02 (−3%) ± 0.09 (14%) mm/h for the TSEB parallel and series approaches, respectively. The poorest performance, when predicting hourly TSEB maize ETa, was from Landsat-8 (30 m) multispectral data combined with its original thermal data, since the errors were −0.03 (−5%) ± 0.16 (29%) mm/h and −0.07 (−13%) ± 0.15 (29%) mm/h for the TSEB parallel and series approaches, respectively. These results indicate the need to develop methods to improve the quality of the RS data from sub-optimal platforms/sensors/scales/calibration to further advance sustainable irrigation water management.
Evaluating Mineral Matter Dynamics within the Peatland as Reflected in Water Composition
Authors: Pezdir Valentina , Serianz Luka , Gosar Mateja
Published: June 2024

Peatland hydrology plays an important role in preserving or changing the record in any consideration of past atmospheric deposition records in peat bogs. The Šijec bog, located on the Pokljuka plateau in Slovenia, is one of the largest ombrotrophic peatlands. We sampled the surface pools, pore water, drainage from the peatland, and karst streams not connected to the peatland. Additionally, we sampled the precipitation, as ombrotrophic peatlands receive mineral matter solely from the atmosphere. The results of the evaluation of the chemical and isotopic composition indicated different origins of dissolved mineral matter in different water types. The components originating from the bedrock and surrounding soils (Ca, Mg, Al, Si, Sr) predominated in the streams. The chemical composition of the peatland drainage water revealed the significant removal of major components from the peatland, particularly elements like Al, Fe, and REE, and metals that are readily dissolved in an acidic environment or mobile in their reduced state. Despite their solubility, concentrations of metals (As, Cr, Cu, Fe, Ni, Pb, Ti) and REE in surface pools remained higher than in the drainage due to incomplete elimination from the peatland. The composition of pore water reflects variations among the W and E parts of the peatland, indicating a heterogenous hydrological structure with different dynamics, such as an additional source of water at approximately 90 cm depth in the NW part. The chemical composition and isotope signature (18O and 2H) of pore water additionally indicated a heterogeneous recharge with residence times of less than a year. The overall analysis indicated a predominantly ombrotrophic type and a small part in the NW area of the peatland as a minerotrophic type of peat.
Research on the Optimization Path of Regional Innovation “Dualization” Effect Based on System Dynamics
Authors: Hou Renyong , Xiao Jiaxing , Zhu Baoji , Peng Weihua , Dan Haijian
Published: June 2024

Coordinated regional development is an important issue for China in the new era, and the influence of innovation ability on regional economic development is increasing, but the current regional innovation is characterized by an increasingly obvious “dualization” effect. In this paper, by constructing innovation efficiency, science and technology innovation, innovation culture, and innovation policy as the four key subsystems of regional innovation effect, and using system dynamics to establish a regional innovation effect model, Wuhan and Enshi as the representatives of central city and non-central city, selecting the data from 2014 to 2021, and adopting different parameters to simulate the evolution trend of the innovation effect, it is concluded that the growth rate of industrial enterprises and the intensity of R&D expenditures have increased, and the innovation effect has become more and more obvious, which is the most important issue in the new era of China’s development. It is also concluded that the growth rate of industrial enterprises and the intensity of R&D expenditure are the key factors influencing the innovation effect of central and non-central cities, and suggestions are made for optimizing the “dualization” effect of regional innovation.
Effect of Common Ions in Agricultural Additives on the Retention of Cd, Cu, and Cr in Farmland Soils
Authors: Zhou Xu , Cao Hongbin
Published: June 2024

The anions and cations in agricultural additives have crucial impacts on the retention of toxic heavy metals (HMs) in soil. However, the influence of these ions on the adsorption and desorption of Cd, Cr, and Cu in soil has not been clarified in previous studies. This study investigated the adsorption behavior of HMs, common anions, and dissolved organic matter (DOM) in alkaline soil from farmland under different experimental conditions. Nitrates, sulfates, and chlorides were used as HM sources to investigate the effects of different experimental anion environments on batch adsorption experiments and fluorescence quenching titration experiments. Batch sorption experiments showed that the sorption of Cd2+ was inhibited by the concomitant presence of Cr3+ and Cu2+, and the presence of Cl− and SO42− inhibited the binding of HMs to the soil matrix compared to NO3−. The fluorescence quenching titration with HMs suggested that SO42− significantly enhances the binding ability of Cr3+ to DOM in solution, which may be the reason SO42− inhibited Cr3+ retention in soil. These results provide detailed insights into the interactions of HMs with DOM and anions, which is of great significance for the targeted application of pesticides and HMs’ transport and removal in farmland soils.
Determining the Location of Shared Electric Micro-Mobility Stations in Urban Environment
Authors: Jaber Ahmed , Ashqar Huthaifa , Csonka Bálint
Published: June 2024

Locating shared electric micro-mobility stations in urban environments involves balancing multiple objectives, including accessibility, profitability, sustainability, operational costs, and social considerations. This study investigates traveler preferences regarding shared electric micro-mobility stations, focusing on factors influencing their location decisions. The study used the Analytic Hierarchy Process (AHP) model to analyze the criteria and determine their relative importance in influencing the location decisions of shared electric micro-mobility stations as evaluated by experts in transportation fields. The examined criteria are proximity to public transportation, accessibility to key destinations, demographics (e.g., age, and income), safety, land use, and pedestrian and cyclist infrastructure. Using the AHP model, the importance and ranking of each criterion were established. Results indicate that the availability and quality of sidewalks and bike lanes in the vicinity, along with the proximity to popular destinations like shopping centers and tourist attractions, emerge as the most influential criteria. The least important criteria were the demographics such as the young age percentage in the area and the average income of the surrounding population. These findings underscore the critical importance of well-maintained infrastructure for pedestrian and cyclist mobility, as well as the need for convenient access to high-traffic areas. Such insights provide valuable guidance for informed decision making regarding the optimal placement of shared electric micro-mobility stations.
Risk of Post-COVID-19 Uveitis and Risk Modification by Vaccination: A Nationwide Retrospective Cohort Study
Authors: Kim Jiyeong , Ahn Seong Joon
Published: June 2024

This study aimed to evaluate the risk of uveitis, one of the most common ocular manifestations of COVID-19, in individuals with a history of uveitis and COVID-19 infection while discriminating the effects of COVID-19 infection and vaccinations. We analyzed nationwide data from 235,228 individuals with a history of uveitis prior to COVID-19 infection and evaluated incidences and hazard ratios (HRs) of post-COVID-19 uveitis for different post-infection periods, including early- (within 30 days) and delayed-onset ones. The cumulative incidences of post-infection uveitis at 3, 6, and 12 months were calculated as 8.5%, 11.8%, and 14.0%, respectively. The HR of post-COVID-19 uveitis was 1.21 (95% confidence interval [CI]: 1.07–1.37) and was particularly higher in the early-onset period (1.42, 95% CI: 1.24–1.61). Vaccinated individuals showed a modestly elevated risk of uveitis relative to pre-infection, while unvaccinated ones exhibited substantially higher risks in the early-onset period: the HR of post-infection uveitis before vaccination was 3.61 (95% CI: 1.35-9.66), whereas after vaccination, it was 1.21 (95% CI: 1.05–1.39). COVID-19 infection was associated with a higher risk of uveitis, which was mitigated by vaccination. Vigilance in the monitoring of uveitis is warranted for recently COVID-19-infected individuals with a history of uveitis, particularly unvaccinated individuals.
Research on Intelligent Chemical Dosing System for Phosphorus Removal in Wastewater Treatment Plants
Authors: Lu Xi , Huang Song , Liu Haichen , Yang Fengwei , Zhang Ting , Wan Xinyu
Published: June 2024

Whether the phosphorus removal chemical in wastewater treatment plants (WWTPs) can be accurately dosed not only affects the compliance of the effluent total phosphorus but also has a huge impact on sludge production and energy consumption during the wastewater treatment process. For the effluent from the secondary sedimentation tank of a wastewater treatment plant in southern China, based on experimental screening of the optimal pH value, chemical types and concentrations of chemicals, coagulation time, etc., a dynamic dosage prediction feedforward model for chemical phosphorus removal agents in the effluent from the secondary sedimentation tank of the WWTPs was developed to predict the most economical dosage of the chemicals. Meanwhile, combined with the adaptive fuzzy neural network P feedback control algorithm, dynamic real-time control of chemical dosing was achieved. Through micro-control design, a software model for signal collection and feedback in a specific phosphorus removal scenario was formed, and an automatic control system for chemical dosing was ultimately developed for a WWTP in a city in southern China. After stable operation for two months, the system achieved a 100% compliance rate for effluent total phosphorus (TP) concentration and a 67% improvement in effluent stability, helping the wastewater treatment plant achieve stable and precise control of the phosphorus removal process in the secondary sedimentation tank effluent, which is conducive to further promoting its implementation of low-carbon pathways.
Demonstration of Proactive Algaecide Treatments Targeting Overwintering Cyanobacteria in Sediments of an Urban Pond
Authors: Calomeni-Eck Alyssa , McQueen Andrew , Kinley-Baird Ciera , Smith Elizabeth , Growcock Benjamin , Decker Katlynn , Hampton Schad , Stahl Anthony , Boyer Marvin , Clyde Gerard
Published: June 2024

Most cyanobacteria that form harmful algal blooms (HABs) in inland waterbodies can overwinter in sediments. This field demonstration within an urban pond was conducted to bolster a database on the novel use of algaecide treatments to proactively target overwintering cyanobacteria located in sediments prior to HAB formation. In March 2023, a peroxide-based algaecide was applied to sediments of a water feature located in urban Kansas City, Kansas, and cyanobacteria responses were measured over subsequent weeks and months. Multiple lines of evidence were used to discern the impacts of proactive treatments on overwintering cells in sediments and HAB severity throughout the growing season. Although results of the measured cyanobacterial responses were mixed, three of five lines of evidence indicated proactive algaecide treatments were effective at decreasing the transfer of cyanobacteria to the water column and HAB severity during months when HABs tended to occur. Microcystin concentrations immediately post-treatment (hours) remained at the analytical detection limit (0.10 µg/L) and were below USEPA risk-based thresholds, highlighting the benefits of application prior to the exponential growth phase of toxin-producing cyanobacteria. These results expand the dataset and methodology for field-scale proactive algaecide applications targeting overwintering cyanobacterial cells in sediment to mitigate and delay HAB development.
Conceptual Model Based on Groundwater Dynamics in the Northern Croatian Dinaric Region at the Transition from the Deep Karst and Fluviokarst
Authors: Boljat Ivana , Terzić Josip , Duić Željko , Lukač Reberski Jasmina , Selak Ana
Published: June 2024

The Dinaric karst in the north differs from the rest of the karst in Croatia in terms of karstification depth. The infiltrating precipitation drains in cascades from deeply karstified mountainous areas to the shallow or fluviokarst, forming the tributaries of the Kupa River. Time series analyses were conducted on a 5-year dataset to elucidate the hydrogeological conceptual model of the area and clarify disparate findings from tracer tests under varying hydrological conditions. The flow duration curve, autocorrelation functions, and recession curves were used to evaluate the spring discharge variability, the karstification degree, and the karst aquifer’s size. The crosscorrelation function and temperature dynamics were employed to assess the spring’s response to recharge and the hydrogeological system behavior. Comparative analysis with previous studies was conducted to contextualize the obtained results. The research outcomes delineated several key findings: (i) the deep karst zone is less developed than the shallow karst zone; (ii) groundwater exchange is significantly faster in shallow karst; (iii) groundwater divides in the Kapela Mountain are zonal; (iv) the homogenization of groundwater occurs during periods of high water levels; (v) fast water exchange transpires without concurrent groundwater temperature homogenization; and (vi) a definition of the boundary between deep and fluviokarst in Croatia.
Review of the Mechanism and Methodology of Water Demand Forecasting in the Socio-Economic System
Authors: Fang Xudong , Liu Jinhua , Zhou Min , Zhang Hui , Zhao Jing
Published: June 2024

As global water scarcity becomes increasingly acute, water demand forecasting has emerged as a critical component in water resource management and planning. This review aims to comprehensively survey and analyze the current state of research, existing issues, and development trends in the field of water demand forecasting. Presently, there are numerous studies on water demand forecasting; however, most of the forecasting results tend to be overestimated. On the mechanistic level, research has gradually shifted from considering single factors to accounting for the complex influences of multiple factors. This paper summarizes the mechanism of water demand from the three levels of agriculture, industry, and residential life. In terms of forecasting methods, various techniques have been explored and applied, particularly new methods based on artificial intelligence and machine learning, which have demonstrated significant advantages in improving forecasting accuracy and handling nonlinear relationships. Despite the notable progress and practical achievements in water demand forecasting, several challenges and issues remain. Future research should focus on diversifying methodologies, comprehensively considering multiple influencing factors, further refining forecasting models and technical systems, strengthening uncertainty and risk management, and emphasizing practical applications and policy guidance.
Numerical Investigation of Different Stepped Spillway Geometries over a Mild Slope for Safe Operation Using Multi-Phase Model
Authors: Pandey Binaya Raj , K C Megh Raj , Crookston Brian , Zenz Gerald
Published: June 2024

The appropriate design and operation of spillways are critical for dam safety. To enhance design practices and gain insights into flow hydraulics, both experimental and numerical modeling are commonly employed. In this study, we conducted a numerical investigation of flow over a mildly sloping (1V:3H) stepped spillway with various step geometries using a multi-phase mixture model with dispersed interface tracking in ANSYS Fluent. The model was validated against experimental data from Utah State University, focusing on water surface profiles over the crest, velocities, and air concentrations. The validated numerical model was used to simulate flow over different step geometries (i.e., 0.2 m H uniform Step, 0.1 m H uniform step, non-uniform steps, adverse slope steps, and stepped pool) for a range of discharges from 0.285 m3/s/m to 1.265 m3/s/m. While flow depths over the crest and velocities in the chute compared well with experimental results, air concentrations exhibited some deviation, indicating numerical limitations of the solver. The shift in the location of the inception point was found to be mainly influenced by a higher flow rate than the different design configurations over an identical mild slope. The downstream non-linear flow velocity curve with different flow rates indicated less effectiveness of the step roughness over a high flow rate as a result of the reduction in relative roughness. The theoretical velocity ratio indicated the least reduction in downstream velocity with the stepped pooled spillway due to the formation of a “stagnant pool”. A higher negative-pressure region due to flow separation at the vertical face of the steps was obtained by adverse slope steps, which shows that the risk of cavitation is higher over the adverse slope step spillway. Turbulent kinetic energy (TKE) was found to be higher for uniform 0.2 m H steps due to the strong mixing of flow over the steps. The least TKE was found at the steps of the stepped pool spillway due to the formation of a “stagnant pool”. Uniform 0.2 m H steps achieved the maximum energy dissipation efficiency, whereas the stepped pool spillway obtained the least energy dissipation efficiency, introducing higher flow velocity at the stilling basin with a higher residual head. The adverse slope and non-uniform steps were found to be more effective than the uniform 0.1 m H steps and stepped pool spillway. The application of uniform steps of higher drop height and length could achieve higher TKE over the steps, reducing the directional flow velocity, which reduces the risk of potential damage.
A Study on Wild and Domestic Animal Detection for Farm Protection by using Computer Vision
Authors: Shilaskar Swati , Bhatlawande Shripad , Kharade Parth , Khade Sanket , Walekar Karan
Published: June 2024

Crop protection against wild animal intrusion has become a pressing challenge with significant social and economic implications, particularly in agricultural-dependent nations like India. In response, an innovative AI-driven surveillance system is designed to detect and determine potential threats from animals to farm environments. The system accurately identifies and classifies animals in farm images by leveraging advanced computer vision techniques and machine learning algorithms, including Support Vector Machines, K-Means clustering, Random Forest, Decision Trees, and Logistic Regression. The model generalizes effectively by analyzing a diverse dataset comprising various animal species. Key features such as accuracy, precision, recall, F1-score, and confusion matrices are employed to assess model performance comprehensively. The results showcase high accuracy across multiple algorithms. The proposed system offers a promising solution to protect crops, minimize losses, and foster harmonious coexistence between farming and wildlife. The results demonstrate good accuracy for various algorithms: 92.75% for Logistic Regression, 86.47% for Decision Trees, 95.65% for Random Forests, and 94.20% for Support Vector Machines. This highlights how reliable the system is in classifying animals, providing a viable way to safeguard crops, reduce losses, and promote peaceful cohabitation between agriculture and wildlife.
Avram Iancu, the National Hero: Controversial Aspects
Authors:   Babeş-Bolyai University and  George Bariþiu Institute of History, Cluj-Napoca, Bolovan Ioan , Șipoș Sorin ,   University of Oradea
Published: June 2024

In Romanian historiography, few specialists have investigated Iancu’s life after 1852. Even Silviu Dragomir, in his 1924 monograph, went only as far as the year 1852 with his research. In time, however, two points of view emerged about Iancu’s last years (between 1852, when the emperor visited the Apuseni Mountains, and 1872, when Iancu died). For Silviu Dragomir, the behaviour of the leader of the Motzen after 1852 can be explained by a neuro-psychic disease caused by the pressure experienced during the Revolution, the great responsibilities he took, and the treatment of the Motzen and their leaders by the Austrians after the Revolution. Most historians considered the refusal of the leader of the Motzen to meet the emperor the first sign of a mental disease, but there are also testimonies that rule out madness. It is our contention that Iancu’s “disorders” from 1852 to 1872 which his contemporaries talk about are in fact more or less serious bouts of depression, lasting shorter or longer spans of time, and therefore to label Avram Iancu “a madman” nowadays, as well as in the past, is doing a huge injustice to the memory of an exemplary leader.