bluuebunny/crossref_metadata_2025 huggingface dataset:
Forming Preachers: An Examination of Four Homiletical Pedagogy Paradigms
Authors: Clark E. Trey
Published: March 2024

Teaching preaching effectively in the twenty-first century requires instructors to engage a multiplicity of pedagogical approaches. Unfortunately, there is a paucity of homiletical literature that surveys diverse pedagogical paradigms and practices directly related to preaching. This article takes a step toward filling this void. Specifically, the author argues that embracing varied preaching pedagogical paradigms and practices is essential to foster a more holistic, contextually sensitive, and liberative approach to the formation of preachers. The first part of the article examines three major contemporary homiletical pedagogical approaches that attend to the formation of preachers in interrelated yet distinct ways: teacher-centered, learner-centered, and learning-centered preaching pedagogy. In the second section, building on place-based educational theory, a new paradigm is explored that the author calls place-centered preaching pedagogy. To explicate this paradigm, the article briefly considers four homileticians who, in different ways, reflect aspects of this pedagogy in their teaching: HyeRan Kim-Cragg, Frank A. Thomas, Richard W. Voelz, and Leah D. Schade. The third section offers an assessment of place-centered preaching pedagogy by examining its strengths, weaknesses, and areas for future research. The article ends with a conclusion that revisits the primary aims of the essay and calls for further exploration of the subject.
Assessing Conservation Conditions at La Fortaleza de Kuelap, Peru, Based on Integrated Close-Range Remote Sensing and Near-Surface Geophysics
Authors: Ghezzi Ivan , Kościuk Jacek , Church Warren , VanValkenburgh Parker , Ćmielewski Bartłomiej , Kucera Matthias , Dąbek Paweł B. , Contreras Jeff , Mori Nilsson , Righetti Giovanni , Serafini Stefano , Rojas Carol
Published: March 2024

We combined datasets from multiple research projects and remote sensing technologies to evaluate conservation conditions at La Fortaleza de Kuelap, a pre-Hispanic site in Peru that suffered significant damage under heavy seasonal rains in April 2022. To identify the causes of the collapse and where the monument is at further risk, we modeled surface hydrology using a DTM derived from drone LiDAR data, reconstructed a history of collapses, and calculated the volume of the most recent by fusing terrestrial LiDAR and photogrammetric datasets. In addition, we examined subsurface water accumulation with electrical resistivity, reconstructed the stratification of the monument with seismic refraction, and analyzed vegetation loss and ground moisture accumulation using satellite imagery. Our results point to rainwater infiltration as the most significant source of risk for La Fortaleza’s perimeter walls. Combined with other adverse natural conditions and contemporary conservation interventions, this led to the 2022 collapse. Specialists need to consider these factors when tasked with conserving monuments located in comparable high-altitude perhumid environments. This integration of analytical results demonstrates how multi-scalar and multi-instrumental approaches provide comprehensive and timely assessments of conservation needs.
METEO-DLNet: Quantitative Precipitation Nowcasting Net Based on Meteorological Features and Deep Learning
Authors: Hu Jianping , Yin Bo , Guo Chaoqun
Published: March 2024

Precipitation prediction plays a crucial role in people’s daily lives, work, and social development. Especially in the context of global climate variability, where extreme precipitation causes significant losses to the property of people worldwide, it is urgently necessary to use deep learning algorithms based on radar echo extrapolation for short-term precipitation forecasting. However, there are inadequately addressed issues with radar echo extrapolation methods based on deep learning, particularly when considering the inherent meteorological characteristics of precipitation on spatial and temporal scales. Additionally, traditional forecasting methods face challenges in handling local images that deviate from the overall trend. To address these problems, we propose the METEO-DLNet short-term precipitation prediction network based on meteorological features and deep learning. Experimental results demonstrate that the Meteo-LSTM of METEO-DLNet, utilizing spatial attention and differential attention, adequately learns the influence of meteorological features on spatial and temporal scales. The fusion mechanism, combining self-attention and gating mechanisms, resolves the divergence between local images and the overall trend. Quantitative and qualitative experiments show that METEO-DLNet outperforms current mainstream deep learning precipitation prediction models in natural spatiotemporal sequence problems.
Landsat 9 Thermal Infrared Sensor-2 (TIRS-2) Pre- and Post-Launch Spatial Response Performance
Authors: Eon Rehman , Wenny Brian N. , Poole Ethan , Eftekharzadeh Kay Sarah , Montanaro Matthew , Gerace Aaron , Thome Kurtis J.
Published: March 2024

The launch of Landsat 9 (L9) on 27 September 2021 marks the ongoing commitment of the Landsat mission to delivering users with calibrated Earth observations for fifty years. The two imaging sensors on L9 are the Thermal Infrared Sensor-2 (TIRS-2) and the Operational Land Imager-2 (OLI-2). Shortly after launch, the image data from OLI-2 and TIRS-2 were evaluated for both radiometric and geometric quality. This paper provides a synopsis of the evaluation of the spatial response of the TIRS-2 instrument. The assessment focuses on determining the instrument’s ability to detect a perfect knife edge. The spatial response was evaluated both pre- and post-launch. Pre-launch testing was performed at NASA Goddard Space Flight Center (GSFC) under flight-like thermal vacuum (TVAC) conditions. On orbit, coastline targets were identified to evaluate the spatial response and compared against Landsat 8 (L8). The pre-launch results indicate that the spatial response of the TIRS-2 sensor is consistent with its predecessor on board L8, with no noticeable decline in image quality to compromise any TIRS science objectives. Similarly, the post-launch analysis shows no apparent degradation of the TIRS-2 focus during the launch and the initial operational timeframe.
Adapting Prediction Models to Bare Soil Fractional Cover for Extending Topsoil Clay Content Mapping Based on AVIRIS-NG Hyperspectral Data
Authors: George Elizabeth Baby , Gomez Cécile , Kumar Nagesh D.
Published: March 2024

The deployment of remote sensing platforms has facilitated the mapping of soil properties to a great extent. However, the accuracy of these soil property estimates is compromised by the presence of non-soil cover, which introduces interference with the acquired reflectance spectra over pixels. Therefore, current soil property estimation by remote sensing is limited to bare soil pixels, which are identified based on spectral indices of vegetation. Our study proposes a composite mapping approach to extend the soil properties mapping beyond bare soil pixels, associated with an uncertainty map. The proposed approach first classified the pixels based on their bare soil fractional cover by spectral unmixing. Then, a specific regression model was built and applied to each bare soil fractional cover class to estimate clay content. Finally, the clay content maps created for each bare soil fractional cover class were mosaicked to create a composite map of clay content estimations. A bootstrap procedure was used to estimate the standard deviation of clay content predictions per bare soil fractional cover dataset, which represented the uncertainty of estimations. This study used a hyperspectral image acquired by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor over cultivated fields in South India. The proposed approach provided modest performances in prediction (Rval2 ranging from 0.53 to 0.63) depending on the bare soil fractional cover class and showed a correct spatial pattern, regardless of the bare soil fraction classes. The model’s performance was observed to increase with the adoption of higher bare soil fractional cover thresholds. The mapped area ranged from 10.4% for pixels with bare soil fractional cover >0.7 to 52.7% for pixels with bare soil fractional cover >0.3. The approach thus extended the mapped surface by 42.4%, while maintaining acceptable prediction performances. Finally, the proposed approach could be adopted to extend the mapping capability of planned and current hyperspectral satellite missions.
Wind Profile Retrieval Based on LSTM Algorithm and Mobile Observation of Brightness Temperature over the Tibetan Plateau
Authors: Chen Bing , Cheng Xinghong , Su Debin , Xu Xiangde , Ma Siying , Hu Zhiqun
Published: March 2024

Stationary or mobile microwave radiometers (MRs) can measure atmospheric temperature, relative humidity, and water vapor density profiles with high spatio-temporal resolution, but cannot obtain the vertical variations of wind field. Based on a dataset of brightness temperatures (TBs) measured with a mobile MR over the Three-River-Source Region of the Tibetan Plateau from 18 to 30 July 2021, we develop a direct retrieval method for the wind profile (WP) based on the Long Short-Term Memory (LSTM) network technique, and obtain the reliable dynamic variation characteristics of the WP in the region. Furthermore, the ground-based radiative transfer model for TOVS (RTTOV-gb) was employed to validate the reliability of the TB observation, and we analyzed the impact of weather conditions, altitude, observational mode, and TB diurnal variation on the accuracy of the TB measurement and the retrieval of the WP. Results show that the TB from the mobile observation (MOTB) on clear and cloudy days are close to those of the simulated TB with the RTTOV-gb model, while TB measurements on rainy days are far larger than the modeled TBs. When compared with radiosonde observations, the WPs retrieved with the LSTM algorithm are better than the ERA5 reanalysis data, especially below 350 hPa, where the root mean square errors for both wind speed and wind direction are smaller than those of ERA5. The major factors influencing WP retrieval include the weather conditions, altitude, observational mode, and TB diurnal variation. Under clear-sky and cloudy conditions, the LSTM retrieval method can reproduce the spatio-temporal evolution of wind field and vertical wind shear characteristics. The findings of this study help to improve our understanding of meso-scale atmospheric dynamic structures, characteristics of vertical wind shear, atmospheric boundary layer turbulence, and enhance the assessment and forecasting accuracy of wind energy resources.
A Remote Sensing Approach to Estimating Cropland Sustainability in the Lateritic Red Soil Region of China
Authors: Duan Dingding , Sun Xiao , Wang Chenrui , Zha Yan , Yu Qiangyi , Yang Peng
Published: March 2024

Spatiotemporal assessment and a comprehensive understanding of cropland sustainability are prerequisites for ensuring food security and promoting sustainable development. However, a remote sensing-based approach framework that is suitable for large-scale and high-precision assessment and can reflect the overall sustainability of cropland has not yet been developed. This study considered a typical lateritic red soil region of Guangdong Province, China, as an example. Cropland sustainability was examined from three aspects: natural capacity, management level, and food productivity. Ten typical indicators, including soil organic matter, pH, irrigation guarantee capability, multiple cropping index, and food productivity, among others, were constructed using remote sensing technology and selected to represent these three aspects. Based on the indicator system, we assessed the spatiotemporal patterns of cropland sustainability from 2010 to 2020. The results showed that the natural capacity, management level, and food productivity of cropland had improved over the 10 years. The cropland sustainability score increased from 67.95 to 69.08 over this period. The sustainability scores for 68.64% of cropland were increased and were largely distributed in the eastern and western region of the study area. The croplands with declining sustainability scores were mostly distributed in the central region. The prefecture-level regions differed in cropland sustainability, with Zhongshan, Zhuhai, and Qingyuan cities exhibiting the highest values, and Zhanjiang the lowest. Exploring the underlying mechanisms of cropland sustainability and proposing improvement measures can guide decision-making, cropland protection, and efficient utilization, especially in similar lateritic red soil regions of the world.
PixRevive: Latent Feature Diffusion Model for Compressed Video Quality Enhancement
Authors: Wang Weiran , Jing Minge , Fan Yibo , Weng Wei
Published: March 2024

In recent years, the rapid prevalence of high-definition video in Internet of Things (IoT) systems has been directly facilitated by advances in imaging sensor technology. To adapt to limited uplink bandwidth, most media platforms opt to compress videos to bitrate streams for transmission. However, this compression often leads to significant texture loss and artifacts, which severely degrade the Quality of Experience (QoE). We propose a latent feature diffusion model (LFDM) for compressed video quality enhancement, which comprises a compact edge latent feature prior network (ELPN) and a conditional noise prediction network (CNPN). Specifically, we first pre-train ELPNet to construct a latent feature space that captures rich detail information for representing sharpness latent variables. Second, we incorporate these latent variables into the prediction network to iteratively guide the generation direction, thus resolving the problem that the direct application of diffusion models to temporal prediction disrupts inter-frame dependencies, thereby completing the modeling of temporal correlations. Lastly, we innovatively develop a Grouped Domain Fusion module that effectively addresses the challenges of diffusion distortion caused by naive cross-domain information fusion. Comparative experiments on the MFQEv2 benchmark validate our algorithm’s superior performance in terms of both objective and subjective metrics. By integrating with codecs and image sensors, our method can provide higher video quality.
A Review on Traversability Risk Assessments for Autonomous Ground Vehicles: Methods and Metrics
Authors: Benrabah Mohamed , Orou Mousse Charifou , Randriamiarintsoa Elie , Chapuis Roland , Aufrère Romuald
Published: March 2024

Evaluating the risk associated with operations is an essential element of safe planning and an essential prerequisite in mobile robotics. This issue is very broad, with numerous definitions emerging in the recent literature adapting different application scenarios and leading to different algorithmic approaches. In this review, we will investigate how the state-of-the-art approaches define the traversability risk, particularly for mobile robots, whereby we classify existing risk-aware navigation algorithms according to their characterization of risk. Subsequently, we will overview the formulations of risk assessment along a path using traversability grid maps since it is essential for a mobile robot to evaluate its path to predict potential hazards. Finally, we will discuss the consistency of commonly used risk metrics in robotics. The aim of the review is to offer a comprehensive overview to newcomers in the field, to provide a structured reference for practitioners, and to also inspire future developments.
Optically Controlled Gain Modulation for Microwave Metasurface Antennas
Authors: Tripon-Canseliet Charlotte , Della Giovampaola Cristian , Pavy Nicolas , Chazelas Jean , Maci Stefano
Published: March 2024

Over the past decade, metasurfaces (MTSs) have emerged as a highly promising platform for the development of next-generation, miniaturized, planar devices across a wide spectrum of microwave frequencies. Among their various applications, the concept of MTS-based antennas, particularly those that are based on surface wave excitation, represents a groundbreaking advancement with significant implications for communication technologies. However, existing literature primarily focuses on MTS configurations printed on traditional substrates, largely overlooking the potential benefits of employing photosensitive substrates. This paper endeavors to pioneer this novel path. We present a specialized design of a modulated MTS printed on a silicon substrate, which acts as a photosensitive Ka-band surface wave antenna. Remarkably, the gain of this antenna can be time-modulated, achieving a variance of up to 15 dB, under low-power (below 1 W/cm²) optical illumination at a wavelength of 971 nm. This innovative approach positions the antenna as a direct transducer, capable of converting an optically modulated signal into a microwave-modulated radiated signal, thus offering a new dimension in antenna technology and functionality.
Relationship between Body Posture Assessed by Dynamic Baropodometry and Dental Occlusion in Patients with and without Dental Pathology
Authors: Carda-Navarro Isabel , Lacort-Collado Lidia , Fernández-Ehrling Nadia , Lanuza-Garcia Alicia , Ferrer-Torregrosa Javier , Guinot-Barona Clara
Published: March 2024

Body biomechanics and dental occlusion are related, but this interaction is not fully elucidated. The aim of this study was to investigate the association between body posture and occlusion in patients with and without dental pathology. A cross-sectional study was carried out with 29 patients divided into a control group and a group with pathology (malocclusions). Body posture was evaluated by dynamic baropodometry, analyzing parameters such as the line of gait and the anteroposterior and lateral position of the center of pressure (CoP). Occlusion was classified radiographically according to the sagittal skeletal relationship. Results showed significant differences in mean position phase line between groups (p = 0.01–0.02), with means of 115.85 ± 16.98 mm vs. 95.74 ± 24.47 mm (left side) and 109.03 ± 18.03 mm vs. 91.23 ± 20.80 mm (right side) for controls and pathologies, respectively. The effect size was large (Cohen’s d 0.97 and 0.92). There were no differences in the anteroposterior (p = 0.38) or lateral (p = 0.78) position of the CoP. In gait analysis, significant differences were observed in left (548.89 ± 127.50 N vs. 360.15 ± 125.78 N, p < 0.001) and right (535.71 ± 131.57 N vs. 342.70 ± 108.40 N, p < 0.001) maximum heel strength between groups. The results suggest an association between body posture and occlusion, although further studies are needed to confirm this relationship. An integrated postural and occlusal approach could optimize the diagnosis and treatment of dental patients.
A Deep Learning Model for Markerless Pose Estimation Based on Keypoint Augmentation: What Factors Influence Errors in Biomechanical Applications?
Authors: Ruescas-Nicolau Ana V. , Medina-Ripoll Enrique , de Rosario Helios , Sanchiz Navarro Joaquín , Parrilla Eduardo , Juan Lizandra María Carmen
Published: March 2024

In biomechanics, movement is typically recorded by tracking the trajectories of anatomical landmarks previously marked using passive instrumentation, which entails several inconveniences. To overcome these disadvantages, researchers are exploring different markerless methods, such as pose estimation networks, to capture movement with equivalent accuracy to marker-based photogrammetry. However, pose estimation models usually only provide joint centers, which are incomplete data for calculating joint angles in all anatomical axes. Recently, marker augmentation models based on deep learning have emerged. These models transform pose estimation data into complete anatomical data. Building on this concept, this study presents three marker augmentation models of varying complexity that were compared to a photogrammetry system. The errors in anatomical landmark positions and the derived joint angles were calculated, and a statistical analysis of the errors was performed to identify the factors that most influence their magnitude. The proposed Transformer model improved upon the errors reported in the literature, yielding position errors of less than 1.5 cm for anatomical landmarks and 4.4 degrees for all seven movements evaluated. Anthropometric data did not influence the errors, while anatomical landmarks and movement influenced position errors, and model, rotation axis, and movement influenced joint angle errors.
RU-SLAM: A Robust Deep-Learning Visual Simultaneous Localization and Mapping (SLAM) System for Weakly Textured Underwater Environments
Authors: Wang Zhuo , Cheng Qin , Mu Xiaokai
Published: March 2024

Accurate and robust simultaneous localization and mapping (SLAM) systems are crucial for autonomous underwater vehicles (AUVs) to perform missions in unknown environments. However, directly applying deep learning-based SLAM methods to underwater environments poses challenges due to weak textures, image degradation, and the inability to accurately annotate keypoints. In this paper, a robust deep-learning visual SLAM system is proposed. First, a feature generator named UWNet is designed to address weak texture and image degradation problems and extract more accurate keypoint features and their descriptors. Further, the idea of knowledge distillation is introduced based on an improved underwater imaging physical model to train the network in a self-supervised manner. Finally, UWNet is integrated into the ORB-SLAM3 to replace the traditional feature extractor. The extracted local and global features are respectively utilized in the feature tracking and closed-loop detection modules. Experimental results on public datasets and self-collected pool datasets verify that the proposed system maintains high accuracy and robustness in complex scenarios.
A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature
Authors: Mata-Romero Marcela E. , Simental-Martínez Omar A. , Guerrero-Osuna Héctor A. , Luque-Vega Luis F. , Lopez-Neri Emmanuel , Ornelas-Vargas Gerardo , Castañeda-Miranda Rodrigo , Martínez-Blanco Ma. del Rosario , Nava-Pintor Jesús Antonio , García-Vázquez Fabián
Published: March 2024

The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.
Subspace Identification of Bridge Frequencies Based on the Dimensionless Response of a Two-Axle Vehicle
Authors: Quan Yixin , Zeng Qing , Jin Nan , Zhu Yipeng , Liu Chengyin
Published: March 2024

As an essential reference to bridge dynamic characteristics, the identification of bridge frequencies has far-reaching consequences for the health monitoring and damage evaluation of bridges. This study proposes a uniform scheme to identify bridge frequencies with two different subspace-based methodologies, i.e., an improved Short-Time Stochastic Subspace Identification (ST-SSI) method and an improved Multivariable Output Error State Space (MOESP) method, by simply adjusting the signal inputs. One of the key features of the proposed scheme is the dimensionless description of the vehicle–bridge interaction system and the employment of the dimensionless response of a two-axle vehicle as the state input, which enhances the robustness of the vehicle properties and speed. Additionally, it establishes the equation of the vehicle biaxial response difference considering the time shift between the front and the rear wheels, theoretically eliminating the road roughness information in the state equation and output signal effectively. The numerical examples discuss the effects of vehicle speeds, road roughness conditions, and ongoing traffic on the bridge identification. According to the dimensionless speed parameter Sv1 of the vehicle, the ST-SSI (Sv1 < 0.1) or MOESP (Sv1 ≥ 0.1) algorithm is applied to extract the frequencies of a simply supported bridge from the dimensionless response of a two-axle vehicle on a single passage. In addition, the proposed methodology is applied to two types of long-span complex bridges. The results show that the proposed approaches exhibit good performance in identifying multi-order frequencies of the bridges, even considering high vehicle speeds, high levels of road surface roughness, and random traffic flows.
Targeted Offline Two-Dimensional HPLC and UHPLC-Orbitrap-MS Combined with Molecular Networking Reveal the Effect of Processing on Chemical Constituents of Xuetong (the Stem of Kadsura heteroclita)
Authors: Yuan Hanwen , Su Wei , Liang Ling , Xie Qingling , Lyu Mengying , Yu Huanghe , Li Bin , Wang Wei
Published: March 2024

Xuetong, the dried stem of Kadsura heteroclita (Roxb.) Craib, is a traditional Tujia medicine extensively used to treat rheumatoid arthritis (RA). All traditional Chinese medicines (TCMs) necessitate a processing stage called “Paozhi” before clinical application. However, there is a dearth of research concerning the processing methods employed for Xuetong. To investigate the impact of vinegar and wine processing on the chemical constituents of Xuetong, this study devised a targeted offline two-dimensional (2D) high-performance liquid chromatography (HPLC) and ultra-high-performance liquid chromatography-orbitrap mass spectrometry (UHPLC-orbitrap-MS) method. By incorporating various MS data-processing techniques, such as molecular networking technology, fragment-ion similarity searching (FISh), online and offline database matching, and fragmentation pattern analysis, a total of 158 components were identified in Xuetong. Among them, 14 were verified by comparison with the reference standards. Notably, aside from triterpenoids and lignans, catechin derivatives were found to be the predominant constituents of Xuetong, and their levels exhibited a significant decrease following processing. This method significantly improved peak capacity and resolution, overcoming the limitations of 1D LC in simultaneously analyzing highly polar catechin derivatives and less polar triterpenoids and lignans. Moreover, the developed method shows promise for Xuetong’s quality control.
Integrated Absorption–Adsorption Process for Waste-Free Decontamination of Gases from Sulfur Dioxide, Part 2: CFD Modeling and Experimental Investigation of a Bubble-Cap Tray
Authors: Apostolov Apostol , Panyovska Stela , Stefanov Stefan , Dzhonova-Atanasova Daniela , Razkazova-Velkova Elena , Michev Stefan
Published: March 2024

There are many technologies for removal of sulfur dioxide (SO2) from flue gases. They are intrinsic part of the efforts for sustainability of energy production as they reduce the harmful impact of fossil fuel combustion on the environment by minimizing one of the main air pollutants. A wide range of methods use alkaline absorbents. In most cases, the products obtained from the absorption process have to undergo further oxidation, which increases the cost of carrying out the process. As a final result, the sulfates obtained (Na2SO4 and CaSO4) have limited practical application and there is a problem with their disposal. Scientific and engineering efforts have been directed towards the development of a practically waste-free technology for gas purification from SO2. An absorption–adsorption method is proposed, which comprises absorption of SO2 in water with simultaneous adsorption of the resultant sulfurous acid (H2SO3) from the aqueous solution with a synthetic anion-exchange resin. Regeneration of the adsorbent is accomplished with a dilute solution of ammonia (NH3), followed by decomposition of the resulting ammonium sulfite ((NH4)2SO3) with nitric acid (HNO3). The products of the processes are pure gaseous (liquefied) SO2 and an aqueous solution of ammonium nitrate (NH4NO3). Sulfur dioxide has a wide range of applications in the chemical industry; ammonium nitrate is a product with a variety of commercial uses as well, the most common of which is as a soil fertilizer. The new absorption–adsorption method offers a practically waste-free technology. The basic unit of this technology is a bubble-cap tray column where the absorption–adsorption process is carried out in an aqueous suspension of a synthetic anion-exchange resin. This work presents a CFD simulation of the flow on the bubble-cap tray. A physical model of the column is constructed, which contains a bubble-cap tray fabricated by 3D printing. As a result of this experimental study, new data on the tray pressure drop, gas holdup, and the kinetics of the absorption–adsorption process were obtained.
Decoupling Economic Growth from Carbon Emissions in the Yangtze River Economic Belt of China: From the Coordinated Regional Development Perspective
Authors: Fu Jiasha , Wang Fan , Guo Jin
Published: March 2024

Decoupling economic growth from carbon emissions is crucial for combating the climate crisis and promoting green development. However, a uniform approach to climate mitigation exacerbates regional disharmony. As a microcosm of China’s regional heterogeneity, the Yangtze River Economic Belt (YREB) is helpful in exploring regional collaborative climate governance. This paper uses the Thiel index, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) decomposition approach to explore the decoupling of economic growth from carbon emissions in YREB from 2005 to 2019. Results indicate that the carbon intensity difference is mainly from the difference within middle-rising provinces (MRP) and western less-developed provinces (WLP). YREB exhibits strong decoupling overall, but it is not sustained. The economic growth effect significantly promotes carbon emissions, which is more prominent in MRP. The energy intensity effect plays a vital role in restraining carbon emissions. The emission factor effect signals an improved energy structure in WLP. Regional coordination is needed to achieve green development; thus, provinces should set differentiated carbon emission reduction targets, and more potent tools are recommended in major carbon emitters.
Unpacking Smart Campus Assessment: Developing a Framework via Narrative Literature Review
Authors: Polin Ken , Yigitcanlar Tan , Washington Tracy , Limb Mark
Published: March 2024

The emergence of the smart campus approach for university campuses addresses the digital transformation needs of higher education institutions, driven by the increasing capability and popularity of digital technologies like artificial intelligence and the internet of things. While existing research has laid a foundation for conceptualizing smart campuses and developing implementation frameworks, a significant gap remains in understanding how to assess a university campus’s ‘smartness’ effectively. The lack of a robust assessment framework makes it challenging to gauge the effectiveness of smart campus initiatives and identify areas for improvement. This study aims to bridge this research gap by identifying key indicators for evaluating the ‘smartness’ of university campuses. Using a narrative literature review method, the study comprehensively reviews the recent literature on smart campuses, organizational management, and societal applications, focusing on identifying pertinent indicators. By incorporating insights from different domains, the study presents a holistic understanding of the indicators necessary for assessing the ‘smartness’ of university campuses through the proposed smart campus assessment framework. The framework and the insights generated inform researchers and decision-makers in assessing and monitoring the effectiveness of smart campuses.
Public Housing Stock between Recovery and Sustainability: The Case of Tor Bella Monaca in Rome
Authors: Cangelli Eliana , Conteduca Michele , Behnam Kia Elnaz , Zaiter Hassan , Fonti Valerio
Published: March 2024

The buildings and construction sector is responsible for 37% of energy-related CO2 emissions and over 34% of energy demand globally. The redevelopment of the existing residential building stock has become a consolidated policy of the European Commission to implement the objectives of economic recovery and energy transition towards climate neutrality by 2050. This paper illustrates the design experimentation conducted by the Sapienza University team on the recovery of the public housing compartment R5 in Tor Bella Monaca, Rome. The research proposes an original methodology that is ideally replicable for regenerating large public housing districts built on the outskirts of major European cities, characterised by significant technological and social degradation and energy deficiency. This paper provides an overview of the interventions and an evaluation of the method and set of tools developed in drafting the Technical and Economic Feasibility Study at both the neighbourhood and building levels. This contribution is addressed to researchers and public and private organisations dealing with the complexity of the social housing recovery topic, emphasising overall sustainability aspects of interventions in terms of typological and energy refurbishment of buildings, re-activation of open spaces and enhancement of landscape components, and envisioning new services through participatory methods that promote social inclusion.
New Approach of Normal and Shear Stress Components for Multiple Curvilinear Holes Which Weakened a Flexible Plate
Authors: Alharbi Faizah M. , Alhendi Nafeesa G.
Published: March 2024

In this article, a thin infinite flexible plate weakened by multiple curvilinear holes is considered. The strength shapes are mapped outside a unit circle with the assistance of particular conformal mapping under certain conditions. The mathematical model that governs the rounded forces of the current physical problem is the boundary value problem of elastic media. This study is applicable to many phenomena throughout nature, like tunnels, caves, and excavations in soil or rock. The Cauchy method for complex variables is used to get the closed forms of Gaursat functions and change the problem to a second-type integrodifferential equation with a Cauchy kernel, which is used for a large area of the contact problems. Then, the normal and shear stress components that act on the model are derived. Afterward, some of the physical applications are studied, and different stress components at specific values in each application are calculated and plotted using Maple 2023.
Pseudo-Finsler Radially Symmetric Spaces
Authors: Ionel Marianty , Javaloyes Miguel Ángel
Published: March 2024

We introduce the concept of radially symmetric pseudo-Finsler spaces, which generalize the notion of symmetric Finsler spaces, and prove that this concept is equivalent to the preservation of flag curvature by parallel transport together with reversibility. As a consequence, reversible pseudo-Finsler manifolds with constant flag curvature are radially symmetric.
On the Breaking of the U(1) Peccei–Quinn Symmetry and Its Implications for Neutrino and Dark Matter Physics
Authors: Civitarese Osvaldo
Published: March 2024

The Standard Model of electroweak interactions is based on the fundamental SU(2)weak × U(1)elect representation. It assumes massless neutrinos and purely left-handed massive W± and Z0 bosons to which one should add the massless photon. The existence, verified experimentally, of neutrino oscillations poses a challenge to this scheme, since the oscillations take place between at least three massive neutrinos belonging to a mass hierarchy still to be determined. One should also take into account the possible existence of sterile neutrino species. In a somehow different context, the fundamental nature of the strong interaction component of the forces in nature is described by the, until now, extremely successful representation based on the SU(3)strong group which, together with the confining rule, give a description of massive hadrons in terms of quarks and gluons. To this is added the minimal U(1) Higgs group to give mass to the otherwise massless generators. This representation may also be challenged by the existence of both dark matter and dark energy, of still unknown composition. In this note, we shall discuss a possible connection between these questions, namely the need to extend the SU(3)strong × SU(2)weak × U(1)elect to account for massive neutrinos and dark matter. The main point of it is related to the role of axions, as postulated by Roberto Peccei and Helen Quinn. The existence of neutral pseudo-scalar bosons, that is, the axions, has been proposed long ago by Peccei and Quinn to explain the suppression of the electric dipole moment of the neutron. The associated U(1)PQ symmetry breaks at very high energy, and it guarantees that the interaction of other particles with axions is very weak. We shall review the axion properties in connection with the apparently different contexts of neutrino and dark matter physics.
Control and Analysis of a Hybrid-Rotor Bearingless Switched Reluctance Motor with One-Phase Full-Period Suspension
Authors: Liu Zeyuan , Wu Xingcheng , Zhang Wenfeng , Yang Yan , Liu Chengzi
Published: March 2024

In the traditional control scheme of a 12/8-pole bearingless switched reluctance motor (BSRM), radial force and torque are usually controlled as a compromise due to the conflict between their effective output areas. Additionally, each phase requires individual power circuits and is excited in turn to produce a continuous levitation force, resulting in high power device requirements and high controller costs. This paper discusses a 12/8-pole single-winding hybrid-rotor bearingless switched reluctance motor (HBSRM) with a hybrid rotor consisting of cylindrical and salient-pole lamination segments. The asymmetric rotor of the HBSRM slightly increases the complexity of its structure and magnetic circuit, but makes it possible to generate the desired radial force at any rotor angular position. A control scheme for the HBSRM is developed to utilize the independent excitation of the four windings in one phase to generate the desired levitation force at any rotor angular position, and it requires only half the number of power circuits used in the conventional control scheme of a 12/8-pole single-winding BSRM. Different from the average torque chosen to be controlled in traditional methods, this scheme directly regulates the instantaneous total torque produced by all excited phases together and presents a current algorithm to optimize the torque contribution of each phase so as to reduce torque pulsation, and the improved performance of this bearingless motor is finally validated by simulation analysis.
Conformally Invariant Gravity and Gravitating Mirages
Authors: Berezin Victor , Ivanova Inna
Published: March 2024

The action of an ideal fluid in Euler variables with a variable number of particles is used for the phenomenological description of the processes of particle creation in strong external fields. It has been demonstrated that the conformal invariance of the creation law imposes quite strict restrictions on the possible types of sources. It is shown that combinations with the particle number density in the creation law can be interpreted as dark matter within the framework of this model.
Direct Evidence of Powassan Virus Vertical Transmission in Ixodes scapularis in Nature
Authors: Lange Rachel E. , Prusinski Melissa A. , Dupuis Alan P. , Ciota Alexander T.
Published: March 2024

Powassan virus (POWV) is a tick-borne flavivirus endemic in North America and Russia. Experimental infections with POWV have confirmed horizontal, transstadial, vertical, and cofeeding transmission routes for potential virus maintenance. In the field, vertical transmission has never been observed. During New York State tick-borne pathogen surveillance, POWV RNA and/or infectious POWV was detected in five pools of questing Ixodes scapularis larvae. Additionally, engorged female I. scapularis adults were collected from hunter-harvested white-tailed deer (Odocoileus virginianus) in a region with relatively high tick infection rates of POWV and allowed to oviposit under laboratory conditions. POWV RNA was detected in three female adult husks and one pool of larvae from a positive female. Infectious virus was isolated from all three RNA-positive females and the single positive larval pool. The detection of RNA and infectious virus in unfed questing larvae from the field and larvae from replete females collected from the primary tick host implicates vertical transmission as a potential mechanism for the maintenance of POWV in I. scapularis in nature, and elucidates the potential epidemiological significance of larval ticks in the transmission of POWV to humans.
Acalculous Cholecystitis as a Complication of Primary Epstein-Barr Virus Infection: A Case-Based Scoping Review of the Literature
Authors: Tsiakalos Aristotelis , Schinas Georgios , Karatzaferis Aggelos , Rigopoulos Emmanouil Angelos , Pappas Christos , Polyzou Eleni , Dimopoulou Effrosyni , Dimopoulos George , Akinosoglou Karolina
Published: March 2024

Primary Epstein-Barr virus (EBV) infection manifests with diverse clinical symptoms, occasionally resulting in severe complications. This scoping review investigates the rare occurrence of acute acalculous cholecystitis (AAC) in the context of primary EBV infection, with a focus on understanding its prevalence, clinical features, and underlying mechanisms. The study also explores EBV infection association with Gilbert syndrome, a condition that potentially exacerbates the clinical picture. Additionally, a case report of an 18-year-old female presenting with AAC and ascites secondary to EBV infection enhances the review. A comprehensive literature review was conducted, analyzing reported cases of AAC secondary to EBV infection. This involved examining patient demographics, clinical presentations, laboratory findings, and outcomes. The search yielded 44 cases, predominantly affecting young females. Common clinical features included fever, cervical lymphadenopathy, tonsillitis/pharyngitis, and splenomegaly. Laboratory findings highlighted significant hepatic involvement. The review also noted a potential link between AAC in EBV infection and Gilbert syndrome, particularly in cases with abnormal bilirubin levels. AAC is a rare but significant complication of primary EBV infection, primarily observed in young females, and may be associated with Gilbert syndrome. This comprehensive review underscores the need for heightened clinical awareness and timely diagnosis to manage this complication effectively.
The Adaptation Time to the Extender as a Crucial Step for an Accurate Evaluation of Ram Sperm Quality during the Liquid Storage
Authors: Neila-Montero Marta , Alvarez Mercedes , Riesco Marta F. , Soriano-Úbeda Cristina , Montes-Garrido Rafael , Palacin-Martinez Cristina , de Paz Paulino , Anel Luis , Anel-Lopez Luis
Published: March 2024

Accurate assessment of ram sperm quality is crucial to optimizing assisted reproductive technologies in sheep. However, semen preservation can induce sperm due to osmotic, biochemical, and thermal stress. Stabilizing sperm with a suitable cooling rate and adaptation period to the extender could mitigate these effects for a more reliable evaluation. This study aimed to determine: (1) the best time to assess ram sperm quality, and (2) the factor responsible for the altered state of ram sperm during the first hours of liquid storage. In Experiment 1, ejaculated sperm were diluted and assessed for sperm motility and functionality at four preservation times: 0, 3, 6, and 24 h as sperm damage control. Both sperm motility and functionality improved after 6 h. Experiment 2 investigated the factor responsible for sperm quality change by testing the interactions of seminal plasma and extender with sperm from epididymides independently and in combination. The evaluation of sperm was performed as in Experiment 1. Sperm in groups containing the extender showed altered motility at 0 and 24 h, and lower functionality at 0 h. Thus, we could assume that extender addition initially alters ram sperm, causing sublethal damage that is reversible after 3 to 6 h of semen preservation. In conclusion, ram sperm require an adaptation time of 3 to 6 h to the extender before an accurate quality assessment can be conducted. This has practical implications for reproduction centers, enabling better workflow organization and optimal expression of ram sperm attributes when cervical artificial insemination is routinely performed.
Monitoring the Water Quality Distribution Characteristics in the Huaihe River Basin Based on the Sentinel-2 Satellite
Authors: Shi Xuanshuo , Qiu Zhongfeng , Hu Yunjian , Zhao Dongzhi , Zhao Aibo , Lin Hui , Zhan Yating , Wang Yu , Zhang Yuanzhi
Published: March 2024

Remote sensing technology plays a crucial role in the rapid and wide-scale monitoring of water quality, which is of great significance for water pollution prevention and control. In this study, the downstream and nearshore areas of the Huaihe River Basin were selected as the study area. By utilizing spectral information from standard solution measurements in the laboratory and in situ water quality data matched with satellite spatiotemporal data, inversion models for total phosphorus (TP) and ammonia nitrogen (NH3-N) water quality parameters were developed. The validation results using field measurements demonstrated that the inversion models performed well, with coefficients of determination (R2) of 0.7302 and 0.8024 and root mean square errors of 0.02614 mg/L and 0.0368 mg/L for total phosphorus and ammonia nitrogen, respectively. By applying the models to Sentinel-2 satellite images from 2022, the temporal and spatial distribution characteristics of total phosphorus and ammonia nitrogen concentrations in the study area were obtained. The ammonia nitrogen concentration ranged from 0.05 to 0.30 mg/L, while the total phosphorus concentration ranged from 0.10 to 0.40 mg/L. Overall, the distribution appeared to be stable. The southern region of the Guan River estuary showed slightly higher water quality parameter concentrations compared to the northern region, while the North Jiangsu Irrigation Main Canal estuary was affected by the dilution of river water, resulting in lower concentrations in the estuarine area.