bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural Fiano Wines Fermented in Stainless Steel Tanks, Oak Barrels, and Earthenware Amphora
Authors: Di Renzo Massimo , Letizia Francesco , Di Martino Catello , Karaulli Julian , Kongoli Renata , Testa Bruno , Avino Pasquale , Guerriero Ettore , Albanese Gianluca , Monaco Mario , Iorizzo Massimo
Published: April 2023

The growing sensitivity toward sustainability is being demonstrated by an increase in sales of natural wines. Natural wines are obtained using exclusively native vines, indigenous yeasts, absence of additives, irregular temperature control during fermentation, and smaller quantities of sulfites even compared to organic wines. In this work, natural wines were obtained from Fiano grape, a historical cultivar of Irpinia (Campania, Italy). The main objective of this study was to compare the chemical and sensory characteristics of natural wines produced using different vessels (10 HL): Test A: stainless steel; Test B: earthenware amphora; Test C: mulberry wood barrel; and Test D: cherry wood barrel without the use of starter yeasts and chemical additives, including sulfites. Our results show a greater concentration of higher alcohols and esters in wines obtained in amphora and wooden barrels. The results of this work reveal that the type of container influences the composition of wine to an important extent. In addition, the Fiano wines obtained have a distinctive sensory profile also due to the ancestral winemaking process used, which did not involve the use of starter yeasts or technological and chemical adjuvants.
Analysis of GNSS Data for Earthquake Precursor Studies Using IONOLAB-TEC in the Himalayan Region
Authors: Joshi Shivani , Kannaujiya Suresh , Joshi Utkarsh
Published: April 2023

Earthquake precursors are the indicators that appear before an earthquake. The release of radon gas, ionospheric disturbances, anomalous animal behavior, and so on are examples of seismic and aseismic events. Ionospheric perturbations can be proved to be a reliable method in earthquake prediction. The GNSS data detect changes in the ionosphere through the time lag of the transmitted GPS signals recorded at the Earth-based receivers. A negative TEC anomaly is caused by the stress released from the rocks before the earthquake, which elevates positive ions or p-holes in the atmosphere and decreases the ions in the ionosphere. A positive TEC anomaly follows this because of the increase in ions in the ionosphere. The ionospheric disruption in the Himalayan region is examined before five random earthquakes. For this, data from 15 separate GNSS stations are investigated using IONOLAB-TEC. A promising total electron content (TEC) data estimate with a temporal resolution of 30 s was analyzed. The results of the TEC data analysis depict the anomaly a month before the five earthquakes, followed by the later perturbation in the earthquake preparation zone. TEC anomalies are enhanced more by the uniform spatial distribution of GNSS stations in the epicentral region than by randomly distributed stations. The results of IONOLAB-TEC and the widely used GPS-TEC software were compared. Owing to its temporal resolution, IONOLAB-TEC has edge over the GPS-TEC software in that it can identify even the slightest negative anomalies before an earthquake.
On the Symbolic Use of Dragons by Jacobus de Voragine and J. R. R. Tolkien
Authors: Peralta Camilo
Published: April 2023

This article focuses on the symbolic use of dragons in several works by J. R. R. Tolkien and The Golden Legend, a popular compilation of saints’ lives by Jacobus de Voragine. In the medieval tradition, as recounted by Voragine, dragons serve as symbols of powerful evil through which the inherent weakness of postlapsarian (“after the Fall”) humans can be emphasized. The sudden, miraculous defeat of dragons also illustrates what is possible through faith and the grace of God, anticipating Tolkien’s notion of eucatastrophe, the unexpected reversal in fortune that characterizes the best fairy tales, which is now recognized as a key component of his own approach to mythopoeia.
Research on the Uncertainty of Landslide Susceptibility Prediction Using Various Data-Driven Models and Attribute Interval Division
Authors: Xing Yin , Chen Yang , Huang Saipeng , Xie Wei , Wang Peng , Xiang Yunfei
Published: April 2023

Two significant uncertainties that are crucial for landslide susceptibility prediction modeling are attribute interval numbers (AIN) division of continuous landslide impact factors in frequency ratio analysis and various susceptibility prediction models. Five continuous landslide impact factor interval attribute classifications (4, 8, 12, 16, 20) and three data-driven models (deep belief networks (DBN), random forest (RF), and neural network (back propagation (BP)) were used for a total of fifteen different scenarios of landslide susceptibility prediction studies in order to investigate the effects of these two factors on modeling and perform a landslide susceptibility index uncertainty analysis (including precision evaluation and statistical law). The findings indicate that: (1) The results demonstrate that for the same model, as the interval attribute value rises from 4 to 8 and finally to 20, the forecast accuracy of landslide susceptibility initially increases gradually, then progressively grows until stable. (2) The DBN model, followed by the RF and BP models, provides the highest prediction accuracy for the same interval attribute value. (3) AIN = 20 and DBN models have the highest prediction accuracy under 15 combined conditions, while AIN = 4 and BP models have the lowest. The accuracy and efficiency of landslide susceptibility modeling are higher when the AIN = 8 and DBN models are combined. (4) The landslide susceptibility index uncertainty predicted by the deeper learning model and the bigger interval attribute value is comparatively low, which is more in line with the real landslide probability distribution features. The conditions that the environmental component attribute interval is divided into eight parts and DBN models are used allow for the efficient and accurate construction of the landslide susceptibility prediction model.
Attention-Embedded Triple-Fusion Branch CNN for Hyperspectral Image Classification
Authors: Zhang Erlei , Zhang Jiayi , Bai Jiaxin , Bian Jiarong , Fang Shaoyi , Zhan Tao , Feng Mingchen
Published: April 2023

Hyperspectral imaging (HSI) is widely used in various fields owing to its rich spectral information. Nonetheless, the high dimensionality of HSI and the limited number of labeled data remain significant obstacles to HSI classification technology. To alleviate the above problems, we propose an attention-embedded triple-branch fusion convolutional neural network (AETF-Net) for an HSI classification. The network consists of a spectral attention branch, a spatial attention branch, and a multi-attention fusion branch (MAFB). The spectral branch introduces the cross-channel attention to alleviate the band redundancy problem in high dimensions, while the spatial branch preserves the location information of features and eliminates interfering image elements by a bi-directional spatial attention module. These pre-extracted spectral and spatial attention features are then embedded into a novel MAFB with large kernel decomposition technique. The proposed AETF-Net achieves multi-attention features reuse and extracts more representative and discriminative features. Experimental results on three well-known datasets demonstrate the superiority of the method AETF-Net.
Study on Factors Affecting Remote Sensing Ecological Quality Combined with Sentinel-2
Authors: Fan Qiang , Shi Yue , Song Xiaonan , Cong Nan
Published: April 2023

Reasonable allocation of urban resources can effectively control changes in ecological quality. This study used Sentinel-2 images, taking urban functional areas as the dividing scale, and combined spatial analysis, statistics, and other relevant methods to explore the factors influencing remote sensing ecological quality in Puxi, Shanghai, China. Landsat-8 and high-resolution Sentinel-2 data fusion achieved more refined remote sensing ecological index (RSEI) distribution data, which is of great significance for ecological quality exploration in small areas; the degree of influence of the selected research factors on the RSEI was spectral index > building > social perception > terrain. The R-value of the soil-adjusted vegetation index (SAVI) was 0.970, and it exerted the strongest influence. The R-value of the average building height was 0.103, indicating that it had the weakest influence. The interactions among the selected factors were mainly two-factor and nonlinear enhancements. Most factor combinations exhibited two-factor enhancement. There were six groups of factor combinations for nonlinear enhancement, of which five were related to the average building height. The results of the present study provide a reference for multi-path ecological quality control in small-area regions.
Continuous Decimeter-Level Positioning in Urban Environments Using Multi-Frequency GPS/BDS/Galileo PPP/INS Tightly Coupled Integration
Authors: Li Xingxing , Shen Zhiheng , Li Xin , Liu Gege , Zhou Yuxuan , Li Shengyu , Lyu Hongbo , Zhang Qian
Published: April 2023

Time- and precision-critical applications, such as autonomous driving, have extremely rigorous standards for continuous high-precision positioning. The importance of precise point positioning (PPP) technology for self-navigation equipment is self-evident by delivering decimeter-/centimeter-level absolute position accuracy in a global coordinate framework. Nevertheless, the prolonged initialization period renders PPP almost too difficult to be widely used for time-critical applications in real transportation scenarios, for example, in city canyons and overpasses. We proposed a method to accomplish continuous decimeter-level positioning by leveraging triple-frequency GNSS observations with an Inertial Navigation System (INS) aiding in urban environments. In the proposed method, the inertial measurements and the original tri-frequency pseudorange and carrier phase measurements are tightly fused in an extended Kalman filter to obtain the optimal state estimate. Afterwards, with precise extra-wide-lane (EWL) and wide-lane (WL) Uncalibrated Phase Delay (UPD) products, the EWL and WL ambiguities can be resolved sequentially to implement instantaneous decimeter-level positioning. Exploiting the short-term high-precision characteristic of the INS, the continuity of the PPP solution can be ameliorated noticeably, and the ability of decimeter-level positioning can be maintained effortlessly throughout the navigation process. With land vehicle data collected, several experiments are undertaken to comprehensively assess the capability of the proposed system in urban scenarios, taking the solution obtained by a commercial post-processing software as the reference. The single-epoch decimeter-level position estimation can be captured instantaneously for WL ambiguity-fixed PPP solutions. Furthermore, for WL ambiguity-fixed PPP/INS-integrated solutions, the position estimation is better than 0.2 m for horizontal components and improved by 40–90% compared with that of the WL ambiguity-fixed PPP solutions. More importantly, the availability rate of positioning accuracy is better than 0.3 m in the horizontal direction and 0.5 m in the up direction reaching 93.91%, whereas it is only 53.78% for WL ambiguity-fixed PPP solutions. Overall, the WL ambiguity-fixed PPP/INS-integrated solutions have the favorable performance to maintain continuous decimeter-level positioning for self-navigation equipment, even if full GNSS outages are encountered.
New Trends in High-Resolution Imagery Processing
Authors: Baiocchi Valerio , Giannone Francesca
Published: April 2023

Photogrammetry is a technique that was limited to a few specific sensors and application fields until a few years ago [...]
Comparative Measurements of Astrogeodetic Deflection of the Vertical by Latvian and Swiss Digital Zenith Cameras
Authors: Varna Inese , Willi Daniel , Guillaume Sebastien , Albayrak Müge , Zarins Ansis , Ozen Mustafa
Published: April 2023

Nowadays, zenith telescope-based digital zenith cameras (DZC), such as the COmpact DIgital Astrometric Camera (CODIAC) and VErtical by STArs (VESTA), are used to determine highly precise astrogeodetic deflections of the vertical (DoVs). The CODIAC and VESTA were developed by Eidgenossische Technische Hochschule (ETH) Zurich and University of Latvia, respectively, and only two CODIACs and four VESTAs were produced. The CODIAC has an established accuracy higher than 0.05″, while the accuracy of VESTA is ~0.1″. These two DZCs, which are the most used DZCs of the last decade, were used effectively over many survey campaigns. In this study, we used both the CODIAC and VESTA to conduct simultaneous observations at the School of Management and Engineering Vaud (HEIG-VD) in Yverdon-les-Bains, Switzerland, over five nights in August 2021. Our DZC measurements with CODIAC and VESTA mark the second time that simultaneous parallel observations were made with two different DZCs. Additionally, the VESTA was never tested against another DZC through comparative simultaneous measurements. These comparative measurements between the VESTA and CODIAC allowed for VESTA precision validation and checking the agreement between the two DZCs. The results of repeated, comparative DoV observations over five nights at HEIG-VD revealed a DoV measurement precision of VESTA around 0.13–0.16″ for 15 min long observation session and 0.10–0.13″ for 50 min long observation session. Mean DoV differences between CODIAC and VESTA at HEIG-VD were 0.08″ and −0.06″ for the North–South and East–West components, respectively.
Stratospheric Water Vapor from the Hunga Tonga–Hunga Ha’apai Volcanic Eruption Deduced from COSMIC-2 Radio Occultation
Authors: Randel William J. , Johnston Benjamin R. , Braun John J. , Sokolovskiy Sergey , Vömel Holger , Podglajen Aurelien , Legras Bernard
Published: April 2023

The eruption of the Hunga Tonga–Hunga Ha’apai (HTHH) volcano on 15 January 2022 injected large amounts of water vapor (H2O) directly into the stratosphere. While normal background levels of stratospheric H2O are not detectable in radio occultation (RO) measurements, effects of the HTHH eruption are clearly observed as anomalous refractivity profiles from COSMIC-2, suggesting the possibility of detecting the HTHH H2O signal. To separate temperature and H2O effects on refractivity, we use co-located temperature observations from the Microwave Limb Sounder (MLS) to constrain a simplified H2O retrieval. Our results show enhancements of H2O up to ~2500–3500 ppmv in the stratosphere (~29–33 km) in the days following the HTHH eruption, with propagating patterns that follow the dispersing volcanic plume. The stratospheric H2O profiles derived from RO are in reasonable agreement with limited radiosonde observations over Australia. The H2O profiles during the first few days after the eruption show descent of the plume at a rate of ~−1 km/day, likely due to strong radiative cooling (~−10 K/day) induced by high H2O concentrations; slower descent (~−200 m/day) is observed over the following week as the plume disperses. The total mass of H2O injected by HTHH is estimated as 110 ± 14 Tg from measurements in the early plumes during 16–18 January, which equates to approximately 8% of the background global mass of stratospheric H2O. These RO measurements provide novel quantification of the unprecedented H2O amounts and the plume evolution during the first week after the HTHH eruption.
Study on the Vertical Structure and the Evolution of Precipitation Particle Spectrum Parameters of Stratocumulus Clouds over North China Based on Aircraft Observation
Authors: Xiong Jingyuan , Liu Xiaoli , Wang Jing
Published: April 2023

The understanding of the macro- and micro-structure, particle spectrum parameters, and their evolutions in different parts of stratocumulus clouds based on aircraft observation data, is important basic data for the development of cloud microphysical parameterization schemes and the quantitative retrieval of cloud-precipitation by radar and satellite detections. In this study, a total of ten vertical measurements during three aircraft observations were selected to analyze the vertical distribution of cloud microphysical properties in different parts of stratocumulus clouds in Hebei, North China. It was found that the downdraft in the cumulus cloud area was stronger than that in the stratiform cloud area, with the temperature at the same height higher than that in the stratiform cloud area, and the height of the 0 °C layers was correspondingly higher. In terms of particle spectrum parameters, the intercept and slope parameters of particle spectrum below melting levels in the cumulus part were higher than those in stratiform clouds area in the same weather process. In different vertical detection, it was found that the ice particles have begun to melt in the negative temperature layer near 0 °C level, and there might be sublimation, fragmentation, and aggregation in the melting process of ice phase particles. In addition, the melting process changed the spectral parameters greatly and also changed the correlation between the intercept and slope of the particle spectrum. The slope below the 0 °C level increased with the increase of intercept, which was greater than that above the 0 °C level. The relationship obtained between the intercept parameter of the particle’s spectrum and temperature, and the correlation between the maximum diameter and slope parameter of the particle spectrum, have certain reference significance for cloud physical parameterization and the quantitative retrieval of cloud precipitation by radar and satellite in North China and similar climate background areas.
Evaluation of Absolute Measurements and Normalized Indices of Proximal Optical Sensors as Estimators of Yield in Muskmelon and Sweet Pepper
Authors: Karaca Cihan , Thompson Rodney B. , Peña-Fleitas M. Teresa , Gallardo Marisa , Padilla Francisco M.
Published: April 2023

The generally established protocol for leaf measurement with proximal optical sensors is to use the most recently fully expanded leaf. However, differences in the nitrogen (N) status of lower and upper leaves could possibly be used to enhance optical sensor measurement. Normalized indices that consider both upper and lower leaves have been proposed to improve the assessment of crop N status and yield estimation. This study evaluated whether normalized indices improved the estimation of crop yield from measurements with three different proximal optical sensors: (i) SPAD-502 leaf chlorophyll meter, (ii) Crop Circle ACS 470 canopy reflectance sensor, and (iii) Multiplex fluorescence meter. The study was conducted with sweet pepper (Capsicum annuum L.) and muskmelon (Cucumis melo L.) in plastic greenhouses in Almeria, Spain. Measurements were made on the latest (most recent) leaf (L1), and the second (L2), third (L3) and fourth (L4) fully expanded leaves. Yield estimation models, using linear regression analysis, were developed and validated from the absolute and normalized measurements of the three optical sensors. Overall, the calibration and validation results indicated that the absolute measurements generally had better yield estimation performance than the normalized indices for all the leaves and different leaf profiles. In both species, there was a better performance at the early phenological stages, such as the vegetative and flowering stages, for the absolute and normalized indices for the three optical sensors. Absolute proximal optical sensor measurements on the lower leaves (L2, L3 and L4) slightly improved yield estimation compared to the L1 leaf. Normalized indices that included the L4 leaf (L1–L4) had better yield estimation compared to those using L2 and L3 (e.g., L1–L2 and L1–L3). Of the normalized indices evaluated, the yield performance of the Relative Index (RI), Relative Difference Index (RDI), and Normalized Difference Index (NDI) were very similar, and generally superior to the Difference Index (DI). Overall, the results of this study demonstrated that for three different proximal optical sensors in both muskmelon and sweet pepper (i) normalized indices did not improve yield estimation, and (ii) that absolute measurements on lower leaves (L2, L3 and L4) slightly improved yield estimation performance.
Classification of Land Cover in Complex Terrain Using Gaofen-3 SAR Ascending and Descending Orbit Data
Authors: Wang Hongxia , Yang Haoran , Huang Yabo , Wu Lin , Guo Zhengwei , Li Ning
Published: April 2023

Synthetic aperture radar (SAR) image is an effective remote sensing data source for geographic surveys. However, accurate land cover mapping based on SAR image in areas of complex terrain has become a challenge due to serious geometric distortions and the inadequate separation ability of dual-polarization data. To address these issues, a new land cover mapping framework which is suitable for complex terrain is proposed based on Gaofen-3 data of ascending and descending orbits. Firstly, the geometric distortion area is determined according to the local incident angle, based on analysis of the SAR imaging mechanism, and the correct polarization information of the opposite track is used to compensate for the geometric distortion area, including layovers and shadows. Then, the dual orbital polarization characteristics (DOPC) and dual polarization radar vegetation index (DpRVI) of dual-pol SAR data are extracted, and the optimal feature combination is found by means of Jeffries–Matusita (J-M) distance analysis. Finally, the deep learning method 2D convolutional neural network (2D-CNN) is applied to classify the compensated images. The proposed method was applied to a mountainous region of the Danjiangkou ecological protection area in China. The accuracy and reliability of the method were experimentally compared using the uncompensated images and the images without DpRVI. Quantitative evaluation revealed that the proposed method achieved better performance in complex terrain areas, with an overall accuracy (OA) score of 0.93, and a Kappa coefficient score of 0.92. Compared with the uncompensated image, OA increased by 5% and Kappa increased by 6%. Compared with the images without DpRVI, OA increased by 4% and Kappa increased by 5%. In summary, the results demonstrate the importance of ascending and descending orbit data to compensate geometric distortion and reveal the effectiveness of optimal feature combination including DpRVI. Its simple and effective polarization information compensation capability can broaden the promising application prospects of SAR images.
Modeling the Corn Residue Coverage after Harvesting and before Sowing in Northeast China by Random Forest and Soil Texture Zoning
Authors: Dong Yi , Xuan Fu , Li Ziqian , Su Wei , Guo Hui , Huang Xianda , Li Xuecao , Huang Jianxi
Published: April 2023

Crop residue cover is vital for reducing soil erosion and improving soil fertility, which is an important way of conserving tillage to protect the black soil in Northeast China. How much the crop residue covers on cropland is of significance for black soil protection. Landsat-8 and Sentinel-2 images were used to estimate corn residue coverage (CRC) in Northeast China in this study. The estimation model of CRC was established for improving CRC estimation accuracy by the optimal combination of spectral indices and textural features, based on soil texture zoning, using the random forest regression method. Our results revealed that (1) the optimization C5 of spectral indices and textural features improves the CRC estimation accuracy after harvesting and before sowing with determination coefficients (R2) of 0.78 and 0.73, respectively; (2) the random forest improves the CRC estimation accuracy after harvesting and before sowing with R2 of 0.81 and 0.77, respectively; (3) considering the spatial heterogeneity of the soil background and the usage of soil texture zoning models increase the accuracy of CRC estimation after harvesting and before sowing with R2 of 0.84 and 0.81, respectively. In general, the CRC estimation accuracy after harvesting was better than that before sowing. The results revealed that the corn residue coverage in most of the study area was 0.3 to 0.6 and was mainly distributed in the Songnen Plain. By the estimated corn residue coverage results, the implementation of conservation tillage practices is identified, which is vital for protecting the black soil in Northeast China.
Feasibility Study for the Development of a Low-Cost, Compact, and Fast Sensor for the Detection and Classification of Microplastics in the Marine Environment
Authors: Cocciaro Bruno , Merlino Silvia , Bianucci Marco , Casani Claudio , Palleschi Vincenzo
Published: April 2023

The detection and classification of microplastics in the marine environment is a complex task that implies the use of delicate and expensive instrumentation. In this paper, we present a preliminary feasibility study for the development of a low-cost, compact microplastics sensor that could be mounted, in principle, on a float of drifters, for the monitoring of large marine surfaces. The preliminary results of the study indicate that a simple sensor equipped with three infrared-sensitive photodiodes can reach classification accuracies around 90% for the most-diffused floating microplastics in the marine environment (polyethylene and polypropylene).
IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring
Authors: Young Fraser , Mason Rachel , Morris Rosie E. , Stuart Samuel , Godfrey Alan
Published: April 2023

Walking/gait quality is a useful clinical tool to assess general health and is now broadly described as the sixth vital sign. This has been mediated by advances in sensing technology, including instrumented walkways and three-dimensional motion capture. However, it is wearable technology innovation that has spawned the highest growth in instrumented gait assessment due to the capabilities for monitoring within and beyond the laboratory. Specifically, instrumented gait assessment with wearable inertial measurement units (IMUs) has provided more readily deployable devices for use in any environment. Contemporary IMU-based gait assessment research has shown evidence of the robust quantifying of important clinical gait outcomes in, e.g., neurological disorders to gather more insightful habitual data in the home and community, given the relatively low cost and portability of IMUs. The aim of this narrative review is to describe the ongoing research regarding the need to move gait assessment out of bespoke settings into habitual environments and to consider the shortcomings and inefficiencies that are common within the field. Accordingly, we broadly explore how the Internet of Things (IoT) could better enable routine gait assessment beyond bespoke settings. As IMU-based wearables and algorithms mature in their corroboration with alternate technologies, such as computer vision, edge computing, and pose estimation, the role of IoT communication will enable new opportunities for remote gait assessment.
Age-Related Changes in Episodic Processing of Scenes: A Functional Activation and Connectivity Study
Authors: Miyakoshi Makoto , Archer Josephine Astrid , Wu Chiao-Yi , Nakai Toshiharu , Chen Shen-Hsing Annabel
Published: April 2023

The posterior-to-anterior shift in aging (PASA) effect is seen as a compensatory model that enables older adults to meet increased cognitive demands to perform comparably as their young counterparts. However, empirical support for the PASA effect investigating age-related changes in the inferior frontal gyrus (IFG), hippocampus, and parahippocampus has yet to be established. 33 older adults and 48 young adults were administered tasks sensitive to novelty and relational processing of indoor/outdoor scenes in a 3-Tesla MRI scanner. Functional activation and connectivity analyses were applied to examine the age-related changes on the IFG, hippocampus, and parahippocampus among low/high-performing older adults and young adults. Significant parahippocampal activation was generally found in both older (high-performing) and young adults for novelty and relational processing of scenes. Younger adults had significantly greater IFG and parahippocampal activation than older adults, and greater parahippocampal activation compared to low-performing older adults for relational processing—providing partial support for the PASA model. Observations of significant functional connectivity within the medial temporal lobe and greater negative left IFG-right hippocampus/parahippocampus functional connectivity for young compared to low-performing older adults for relational processing also supports the PASA effect partially.
Pointing Error Correction for a Moving-Platform Electro-Optical Telescope Using an Optimized Parameter Model
Authors: He Yan , Zhang Yahui , Feng Xiaohua , Deng Shuwei , Wang Zhiwen
Published: April 2023

This paper proposes a new optimized parameter model that enhances the pointing accuracy of moving-platform electro-optical telescopes (MPEOTs). The study begins by comprehensively analyzing the error sources, including the telescope and the platform navigation system. Next, a linear pointing correction model is established based on the target positioning process. To eliminate multicollinearity, stepwise regression is applied to obtain the optimized parameter model. The experimental results show that the MPEOT corrected by this model outperforms the mount model, with pointing errors of less than 50 arcsec for approximately 23 h. In the three tests conducted, the modified azimuth error(s) (RMS) were 14.07″, 12.71″, and 28.93″, and the elevation error(s) (RMS) were 12.94″, 12.73″, and 28.30″, respectively.
A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton
Authors: Kiobia Denis O. , Mwitta Canicius J. , Fue Kadeghe G. , Schmidt Jason M. , Riley David G. , Rains Glen C.
Published: April 2023

Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT techniques in detecting, classifying, and counting cotton insect pests and corresponding beneficial insects. The effectiveness and limitations of AI and IoT techniques in various cotton agricultural settings were comprehensively reviewed. This review indicates that insects can be detected with an accuracy of between 70 and 98% using camera/microphone sensors and enhanced deep learning algorithms. However, despite the numerous pests and beneficial insects, only a few species were targeted for detection and classification by AI and IoT systems. Not surprisingly, due to the challenges of identifying immature and predatory insects, few studies have designed systems to detect and characterize them. The location of the insects, sufficient data size, concentrated insects on the image, and similarity in species appearance are major obstacles when implementing AI. Similarly, IoT is constrained by a lack of effective field distance between sensors when targeting insects according to their estimated population size. Based on this study, the number of pest species monitored by AI and IoT technologies should be increased while improving the system’s detection accuracy.
Analysis of Gun Crimes in New York City
Authors: Sarasa-Cabezuelo Antonio
Published: April 2023

Violence involving firearms in the USA is a very important problem. As a consequence, a large number of crimes of this type are recorded every year. However, the solutions proposed have not managed to reduce the number of this type of crime. One of the cities with a large number of violent crimes is New York City. The number of crimes is not homogeneous and depends on the district where they occur. This paper proposes to study the information about the crimes in which firearms are involved with the aim of characterizing the factors on which the occurrence of this type of crime depends, such as the levels of poverty and culture. Since the districts are not homogeneous, the information has been analyzed at the district level. For this, data from the open data portal of the city of New York have been used and machine-learning techniques have been used. The results have shown that the variables on which they depend are different in each district.
Experimental Study on Synergistic Extraction for Separating Manganese and Iron from Waste Ternary Battery Leaching Solution
Authors: Peng Xuebin , Shi Lei , Yang Zhen , Lin Lin , Qu Tao
Published: April 2023

In this paper, the key factors and the mechanism of the extraction of iron and manganese from the sulfuric acid leaching solution of waste ternary lithium-ion batteries were studied by combining P204 and N235 extractors. The experimental results showed that the optimal organic phase composition was 25% P204 + 15% N235 + 60% sulfonated kerosene, and the optimal pH of the pre-extraction solution was in the range of 3.0–3.5. Under the conditions of an extraction temperature of 25–35 °C and an extraction ratio of O/A = 1/1 and after mixing for 5 min, the removal rate of Mn and Fe exceeded 99%. Under the same extraction conditions, the extraction effect of the P204-N235 composite extractant on Mn and Fe was better than that of P204 alone. logD-log[P204] showed that the formulas of the Mn and Fe extracts were MnR2(HR) and FeR2(HR), respectively. The logD-pH diagram showed that only one free H+ was released for each metal ion during extraction, and extraction occurred via a cation exchange reaction.
An Intense Bout of Acute Aerobic Exercise, but Not a Carbohydrate Supplement, Improves Cognitive Task Performance in a Sample of Black, Indigenous, and People of Color (BIPOC) Student Athletes
Authors: van der Weyden Megan Sax , Martin Joel , Rodriguez Jose , Boolani Ali
Published: April 2023

Background: There are contradictory findings in the literature on whether an acute bout of aerobic exercise leads to a post-exercise improvement in cognitive function (CF). Moreover, participants used in the published literature are not representative of the racial make-up of sport or tactical populations. Methods: A randomized crossover design was incorporated, with participants randomly consuming water or a carbohydrate sports drink within the first 3 min of a graded maximal exercise test (GMET) conducted in a laboratory. Twelve self-identified African American participants, (seven males, five females, age = 21.42 ± 2.38 years, height = 174.94 ± 12.55 cm, mass = 82.45 ± 33.09 kg) completed both testing days. Participants completed the CF tests immediately pre- and post-GMET. CF was assessed with the Stroop color and word task (SCWT) and concentration task grid (CTG). Participants completed the GMET when they reported a score of 20 on the Borg ratings of perceived exertion scale. Results: Time to complete the SCWT incongruent task (p < 0.001) and CTG performance (p < 0.001) significantly improved post-GMET in both conditions. VO2max was positively correlated with pre- and post-GMET SCWT performance. Conclusions: The findings of our study suggest that an acute bout of maximal exercise significantly improves CF. Additionally, cardiorespiratory fitness is positively associated with CF in our sample of student athletes from a historically Black college and university.
Low Pre-Season Hamstring-to-Quadriceps Strength Ratio Identified in Players Who Further Sustained In-Season Hamstring Strain Injuries: A Retrospective Study from a Brazilian Serie A Team
Authors: Veeck Filipe , Ruas Cassio V. , Pinto Matheus Daros , Grazioli Rafael , Cardoso Gustavo Pacheco , Albuquerque Thiago , Schipper Lucas , Valente Henrique Gonçalves , Santos Victor H. , Dornelles Márcio , Rabaldo Paulo , Rocha Clarice S. , Baroni Bruno Manfredini , Cadore Eduardo Lusa , Pinto Ronei Silveira
Published: April 2023

A common pre-season injury prevention assessment conducted by professional football clubs is the hamstring-to-quadriceps (H:Q) strength ratio calculated by peak torque (PT). However, it is debatable whether players that present low pre-season H:Q ratios are more susceptible to further sustaining in-season hamstring strain injuries (HSI). Based upon retrospective data from a Brazilian Serie A football squad, a particular season came to our attention as ten out of seventeen (~59%) professional male football players sustained HSI. Therefore, we examined the pre-season H:Q ratios of these players. H:Q conventional (CR) and functional (FR) ratios, and the respective knee extensor/flexor PT from the limbs of players further sustaining in-season HSI (injured players, IP) were compared to the proportional number of dominant/non-dominant limbs from uninjured players (UP) in the squad. FR and CR were ~18–22% lower (p < 0.01), whereas quadriceps concentric PT was ~25% greater for IP than UP (p = 0.002). Low scores of FR and CR were correlated (p < 0.01) with high levels of quadriceps concentric PT (r = −0.66 to −0.77). In conclusion, players who sustained in-season HSI had lower pre-season FR and CR compared to UP, which appears to be associated with higher levels of quadriceps concentric torque than hamstring concentric or eccentric torque.
European Citizens’ Worries and Self-Responsibility towards Climate Change
Authors: Mata Fernando , Jesus Meirielly Santos , Cano-Díaz Concha , Dos-Santos Maria
Published: April 2023

Attitudes and perceptions about climate change (CC) are crucial to public engagement and support in the promotion of mitigating actions and sustainable lifestyles embracing the United Nations’ sustainable development goals. This study aimed to investigate how worried are European citizens about CC, and what is their willingness to assume self-responsibility in its mitigation. We used the European Social Survey, namely the answers to the questions “How worried are you about climate change?” and “To what extent do you feel a personal responsibility to try to CC?” and have related them with demography and individual perception of the society and its policies. We fit two statistical models to each of the questions studied and found the following: Model 1—people that trust in scientists are more worried about CC, people satisfied with the national government are more worried about CC, women are more worried about CC than men, and older and more educated people are also more worried about CC; Model 2—Women have higher levels of self-responsibility, people that trust in scientists feel more responsibility when satisfied with the economy and the health system of the country, and older people that trust in scientists also have more responsibility.
Validation of an Instrument on Perceptions of Heritage Education through Structural Equation Modeling
Authors: Sánchez-Ibáñez Raquel , Cimino Alfonso
Published: April 2023

The aim of this paper is to analyze the validity of a questionnaire designed to analyze teachers’ perceptions of how heritage is taught. The methodology used is quantitative with a non-experimental design based on a Likert-type questionnaire. The sample is non-probabilistic and consists of 132 primary education teachers from the region of Agrigento (Sicily, Italy). For the data analysis, a structural equation model has been employed. The results show that the validated questionnaire explains the variability of 60% of the surveyed teachers. The teachers identify three teaching approaches in accordance with the theoretical approach of the research: a traditional approach based on the memorization of contents, with which 58% of the teachers identified; a student-based model focused on active learning strategies (23%); and an intermediate model (21%). Consequently, a renewal can be appreciated in the teaching of heritage that can encourage the promotion of training with regard to heritage education and the use of an active teaching methodology. Finally, the instrument has been validated and shown to be appropriate, which implies that the conclusions drawn from applying the model serve to explain teachers’ perceptions of heritage teaching.
What Factors Determine the Academic Orientation in Moroccan Higher Education?
Authors: Sellamy Khadija , Fakhri Youssef , Moumen Aniss
Published: April 2023

Guidance is a dynamic process that takes place throughout our lives based on various interactions with the environment. Academic and professional guidance is the most important step in a young person’s life, enabling them to make decisions about education, training, employment, and helping them to develop a career. This stage presents a problem for many high school and university students who feel disoriented in front of the plethora of courses offered. In this context, several researchers have conducted a series of studies to explain the important axes that influence this guidance process. In this work, we will present an overview of the subject of our exploratory research, “the academic orientation of Moroccan students”. Then we will see the methodology that follows in order to perform a qualitative analysis of interviews using the NVIVO software. Later, we will prove that creating a good orientation will contribute in one way or another to better employability. Then, based on the theory of planned behavior, we will propose a theoretical model of the factors explaining the students’ orientation.
Monitoring of the Surfactants in Surface Waters in Slovakia and the Possible Impact of COVID-19 Pandemic on Their Presence
Authors: Lobotková Martina , Hybská Helena , Turčániová Eszter , Salva Jozef , Schwarz Marián , Hýrošová Tatiana
Published: April 2023

In order to keep the home and occupational environment clean and non-infectious, the consumption of cleaners and disinfectants, including cosmetics, is increasing. Excessive use of these products results in their accumulation in the aquatic environment. Conventional wastewater treatment plants are unable to effectively remove the emergent pollutants, including personal care products. This article is focused on the monitoring of the presence of personal care products in surface waters in two river basins in the Slovak Republic, in terms of the surfactant content. Ecotoxicological evaluation of the selected samples from the monitored river basins was performed by an acute toxicity test using the test organism Daphnia magna. The monitoring results indicate the presence of personal care products in the aquatic environment which poses an ecological and environmental risk. Monitoring in the Hron and Nitra river basins confirmed contamination with the surfactants, to which the measures related to the COVID-19 pandemic contributed. The content of the surfactants in personal care products is significant, and their impact on the aquatic environment is not sufficiently monitored.
Evidence of Multi-Source Data Fusion on the Relationship between the Specific Urban Built Environment and Urban Vitality in Shenzhen
Authors: Zhang Pei , Zhang Tao , Fukuda Hiroatsu , Ma Moheng
Published: April 2023

Urban vitality is the key element of sustainable urban development. This paper aims to explore the relationship between urban vitality and the existing built-up environment of the city of Shenzhen. The regression models with multi-source geographic datasets from 2021–2022 were applied to assess Shenzhen in three dimensions: economic, social, and cultural. The results show that Shenzhen’s vitality originates from multiple popular centers. Dense road networks, abundant transportation, and commercial, recreational, entertainment, sports, and leisure facilities are positive indicators of vitality, while urban villages and residential areas have the opposite effect. The model can explain 59% of vitality changes. This paper proposes a quantifiable and replicable adaptation framework for urban villages that combines urban form with data vitality assessment in order to deepen our understanding of urban villages and offer theoretical justifications for long-term urban regeneration. The findings also suggest that spatial differences should be taken into account when formulating urban regeneration responses to make them more targeted. Overall, this paper provides valuable insights for urban planners, policymaker and researchers interested in promoting sustainable urban development through vitality-based urban regeneration.
Does the Opening of High-Speed Railway Promote Corporate Digital Transformation?
Authors: Xin Xiao-Hui , Ou Guo-Li , Zhu Ruo-Yu
Published: April 2023

As China’s economy enters the digital era, guiding enterprises to conduct better digital transformations has become an urgent problem to be solved. In this regard, this paper builds a multiperiod DID model to empirically examine the impact of opening a high-speed railway (HSR) on corporate digital transformation by matching the data of HSR with the data of Shanghai and Shenzhen A-share listed companies from 2008 to 2019. It was found that (1) the opening of an HSR can significantly improve corporate digital transformation, and this finding still held after considering endogeneity issues and various robustness tests. (2) A heterogeneity analysis showed that the promoting effect of opening an HSR on corporate digital transformation was mainly found in nonstate enterprises, high-tech enterprises, and enterprises located in cities with low initial transportation endowment. (3) A mechanistic analysis found that opening an HSR can promote corporate digital transformation by promoting senior staff mobility, increasing industry competition, and enhancing financial agglomeration. This paper not only enriches the research related to the economic consequences of opening an HSR, but it also has important implications for guiding enterprises to successfully conduct corporate digital transformations.
Spatial Distribution of Soil Water and Salt in a Slightly Salinized Farmland
Authors: Ke Zengming , Liu Xiaoli , Ma Lihui , Jiao Feng , Wang Zhanli
Published: April 2023

It is important to study the mechanisms associated with the spatial distribution of soil water and salt to control soil salinization and promote the sustainable development of farmland. Six plots in a slight farmland with different spatial locations were selected to determine the spatial distribution of soil water and salt and their correlation using the multifractal method. Each plot was applied using the grid method (15 m × 15 m, 3600 m2), where each sampling site was located at the center point coordinates. The 0–20 and 20–40 cm soil layers were sampled.The spatial variability of the soil water and salt were 1.41 and 1.73 fold higher in the upstream farmland than in the downstream farmland. The spatial variability of the soil water and salt was significantly correlated. In addition, the spatial variability of the soil water and salt significantly correlated in the 0–20 and 20–40 cm layers. The spatial distribution of both soil water and salt in the entire soil layer had similar characteristics at this sampling scale. Our results provide a theoretical basis to study the interactive mechanisms associated with the distribution of soil water and salt.