bluuebunny/crossref_metadata_2025 huggingface dataset:
Cognizant Fiber-Reinforced Polymer Composites Incorporating Seamlessly Integrated Sensing and Computing Circuitry
Authors: Jaradat Mohammed , Duran Jorge Loredo , Murcia Daniel Heras , Buechley Leah , Shen Yu-Lin , Christodoulou Christos , Taha Mahmoud Reda
Published: November 2023

Structural fiber-reinforced polymer (FRP) composite materials consisting of a polymer matrix reinforced with layers of high-strength fibers are used in numerous applications, including but not limited to spacecraft, vehicles, buildings, and bridges. Researchers in the past few decades have suggested the necessary integration of sensors (e.g., fiber optic sensors) in polymer composites to enable health monitoring of composites’ performance over their service lives. This work introduces an innovative cognizant composite that can self-sense, compute, and implement decisions based on sensed values. It is a critical step towards smart, resilient infrastructure. We describe a method to fabricate textile sensors with flexible circuitry and a microcontroller within the polymer composite, enabling computational operations to take place in the composite without impacting its integrity. A microstructural investigation of the sensors showed that the amount of oxidative agent and soaking time of the fabric play a major role in the adsorption of polypyrrole (PPy) on fiberglass (FG). XPS results showed that the 10 g ferric chloride solution with 6 h of soaking time had the highest degree of protonation (28%) and, therefore, higher adsorption of PPy on FG. A strain range of 30% was achieved by examining different circuitry and sensor designs for their resistance and strain resolution under mechanical loading. A microcontroller was added to the circuit and then embedded within a composite material. This composite system was tested under flexural loading to demonstrate its self-sensing, computing, and actuation capabilities. The resulting cognizant composite demonstrated the ability to read resistance values and measure strain using the embedded microcontroller and autonomously actuate an LED light when the strain exceeds a predefined limit of 2000 µε. The application of the proposed FRP system would provide in situ monitoring of structural composite components with autonomous response capabilities, as well as reduce manufacturing, production, and maintenance costs.
Numerical Study on the Influence of Different Operating Conditions on Mixing Uniformity of the Helical Gear Pump Mixer
Authors: Li Xuetong , Zhang Lili , Zhang Yongliang
Published: November 2023

The uniformity of the gelatin solution and water mixing process is a critical factor in the performance of helical gear pump mixers that affects pump efficiency. In this study, we investigate the impact of water inlet velocity and rotational speed on the helical gear pump mixer. A numerical model of the helical gear pump mixer is established using Simerics MP+ 5.2.15 software. By varying the water inlet velocity from 0.159 m/s to 1.272 m/s and the rotational speed from 8 rpm to 50 rpm, we obtained volume fraction distributions of water in different sections of the helical gear pump mixer. The simulation results show that the high water inlet velocity causes the water and gelatin solution in the mixing tank to not mix fully. When the inlet speed is 0.318 m/s, the mixing uniformity of the gelatin solution and water in the mixing tank is effectively promoted, and the maximum volume fraction of water in the water-rich region is reduced by 70.24%. In poor water regions, the maximum volume fraction of water increased by 9.25 times. Furthermore, within a certain range, increasing the rotational speed of the helical gear pump promotes the faster transport of water to the back of the mixing tank, leading to reduced non-uniformity in the gelatin solution and water mixing process. These findings provide valuable insights for enhancing mixing uniformity in helical gear pump mixers.
A Laboratory-Scale Numerical Investigation of the Effect of Confinement Conditions on the Mechanical Responses of Coal under Various Saturation Conditions
Authors: Wang Huping , Wang Zhao , Ding Sanqing , Jin Chao , Zhang Xiaogang , Liu Langtao
Published: November 2023

Deep coal seams are generally preferred for CO2 sequestration, during which the saturation fluids and high-stress condition involved can significantly alter the mechanical attributes of coal. To understand the effect of stress conditions on the mechanical properties of coal during CO2 sequestration, a finite element model was developed and subsequently validated using experimental data. The results indicate that coal strength increases from 10.35% for a 5 MPa CO2-saturated sample to 114.54% for an 8 MPa CO2 + water-saturated sample as the confining pressure rises from 0 to 30 MPa, due to reduced porosity. However, this effect diminishes with higher confining pressures as dilation decreases. The critical confining pressure determined in this study is approximately 20 MPa, at which all samples exhibit similar failure strength (around 48.50 MPa). Moreover, the strengthening effect caused by applied stress is especially pronounced in CO2-saturated samples, particularly in those saturated with super-critical CO2 and CO2 + water. This suggests that the reduction in coal strength resulting from the adsorption of saturation fluids can be counterbalanced by the strength gain resulting from applied stress. The aforementioned results highlight the effectiveness of injecting high-pressure super-critical CO2 into deep coal seams for carbon sequestration purposes.
Squamotransitional Cell Carcinoma of the Uterine Cervix with Ovarian Metastasis and Benign Brenner Tumor: A Case Report
Authors: Yordanov Angel , Karaivanov Milen , Ivanov Ivan , Kostov Stoyan , Todorova Venelina , Iliev Ilko , Tzoneva Eva , Strateva Diana
Published: November 2023

Introduction: Cervical cancer is the fourth most common malignancy in women and the fourth leading cause of death among women. The main histological types of cervical cancer are squamous cell carcinoma—75% of all cases; adenocarcinoma—10–25%; and all other rare variants including adenosquamous carcinoma and neuroendocrine carcinoma. Squamotransitional cervical cancer is an extremely rare and poorly studied subtype of squamous cell carcinoma. Case report: We present a case of a 64-year-old female patient with early-stage squamotransitional carcinoma. A metastasis was observed in the left ovary and the left fallopian tube and a benign Brenner tumor in the right ovary. Discussion: Although it is believed that this cervical cancer subtype shares the same risk factors and prognosis as squamous cell carcinoma, it is more likely to metastasize and recur. It is not unusual for spread to exist within nearby structures like the cervix and adnexa. It is impossible to tell which is the predominant focus from the immunoprofile of the lesions. Practically speaking, the best course of action in these situations is to rule out the presence of a primary tumor in the urinary tract before clarifying the condition of the cervix, uterus, and adnexal tissues. The presence of a Brenner tumor raises the possibility of a connection between the tumor’s differentiation from a cell population and potential urothelial differentiation. Conclusion: Squamotransitional cervical cancer is a rare tumor with a poorly studied clinical behavior. Despite a shortage of information in the literature, it should be regarded as a more aggressive variety of squamous cell carcinoma and, as such, should be treated and followed up more aggressively. This case is the first described with involvement of the cervix, endometrium, and adnexal structures and a concomitant Brenner tumor.
Evaluation of Multiple Satellite, Reanalysis, and Merged Precipitation Products for Hydrological Modeling in the Data-Scarce Tributaries of the Pearl River Basin, China
Authors: Gao Zhen , Tang Guoqiang , Jing Wenlong , Hou Zhiwei , Yang Ji , Sun Jia
Published: November 2023

Satellite and reanalysis precipitation estimates of high quality are widely used for hydrological modeling, especially in ungauged or data-scarce regions. To improve flood simulations by merging different precipitation inputs or directly merging streamflow outputs, this study comprehensively evaluates the accuracy and hydrological utility of nine corrected and uncorrected precipitation products (TMPA-3B42V7, TMPA-3B42RT, IMERG-cal, IMERG-uncal, ERA5, ERA-Interim, GSMaP, GSMaP-RNL, and PERSIANN-CCS) from 2006 to 2018 on a daily timescale using the Coupled Routing and Excess Storage (CREST) hydrological model in two flood-prone tributaries, the Beijiang and Dongjiang Rivers, of the Pearl River Basin, China. The results indicate that (1) all the corrected precipitation products had better performance (higher CC, CSI, KGE’, and NSCE values) than the uncorrected ones, particularly in the Beijiang River, which has a larger drainage area; (2) after re-calibration under Scenario II, the two daily merged precipitation products (NSCE values: 0.73–0.87 and 0.69–0.82 over the Beijiang and Dongjiang Rivers, respectively) outperformed their original members for hydrological modeling in terms of BIAS and RMSE values; (3) in Scenario III, four evaluation metrics illustrated that merging multi-source streamflow simulations achieved better performance in streamflow simulation than merging multi-source precipitation products; and (4) under increasing flood levels, almost all the performances of streamflow simulations were reduced, and the two merging schemes had a similar performance. These findings will provide valuable information for improving flood simulations and will also be useful for further hydrometeorological applications of remote sensing data.
Unimodular Waveform Design for the DFRC System with Constrained Communication QoS
Authors: Huang Chao , Zhou Qingsong , Huang Zhongrui , Li Zhihui , Xu Yibo , Zhang Jianyun
Published: November 2023

In this study, we investigated two waveform design problems for a dual-functional radar communication (DFRC) system, taking into consideration different constrained communication quality-of-service (QoS) requirements. Our objective was to minimize the mean-square error (MSE) of radar beampattern matching as the cost function. To this end, the multi-user interference (MUI) energy constraint and constructive interference (CI) constraint were, respectively, formulated to ensure the communication QoS. It is important to note that we designed a strict per-user MUI energy constraint at each sampling moment to achieve more accurate control over communication performance. Additionally, we introduced a constant-modulus constraint to optimize the efficiency of the radio frequency (RF) amplifier. To tackle the nonconvex waveform design problems encountered, we employed the alternative direction methods of multipliers (ADMM) technique. This allowed us to decompose the original problem into two solvable subproblems, which were then solved using the majorization–minimization (MM) method and geometrical structure. Finally, we obtained extensive simulation results which demonstrate the effectiveness and superiority of the proposed algorithm.
Soil Texture Mapping in Songnen Plain of China Using Sentinel-2 Imagery
Authors: Zheng Miao , Wang Xiang , Li Sijia , Zhu Bingxue , Hou Junbin , Song Kaishan
Published: November 2023

Soil texture is a key physical property that affects the soil’s ability to retain moisture and nutrients. As a result, it is of extreme importance to conduct remote sensing monitoring of soil texture. Songnen Plain is located in the black soil belt of Northeast China. The development of satellite imagery in remote sensing technology enables the rapid monitoring of large areas. This study aimed to map the surface soil texture of cultivated land in Songnen Plain using Sentinel-2 images and Random Forest (RF) algorithm. We conducted this study by collecting 354 topsoil (0–20 cm) samples in Songnen Plain and evaluating the effectiveness of the bands and spectral indices of Sentinel-2 images and RF algorithm in predicting soil texture (sand, silt, and clay fractions). The results demonstrated that the 16 covariates were moderately and highly correlated with soil texture. And, Band11 of Sentinel-2 images could be used as the corresponding band of soil texture. For sand fraction, the Sentinel-2 images and RF algorithm’s Coefficient of Determination (R2) and Root Mean Square Error (RMSE) were 0.77 and 10.48%, respectively, and for silt fraction, they were 0.75 and 9.38%. Sand fraction decreased from southwest to northeast in Songnen Plain, while silt and clay fractions increased. We found that the Songnen Plain was affected by water erosion and wind erosion, in the northeast and southwest, respectively, providing reference for the implementation of Conservation Tillage policies. The outcome of the study can provide reference for future soil texture mapping with a high resolution.
Evaluation of Tree-Growth Rate in the Laurentides Wildlife Reserve Using GEDI and Airborne-LiDAR Data
Authors: Parra Adriana , Simard Marc
Published: November 2023

Loss of forest cover and derived effects on forest ecosystems services has led to the establishment of land management policies and forest monitoring systems, and consequently to the demand for accurate and multitemporal data on forest extent and structure. In recent years, spaceborne Light Detection and Ranging (LiDAR) missions, such as the Global Ecosystem Dynamics Investigation (GEDI) instrument, have facilitated the repeated acquisition of data on the vertical structure of vegetation. In this study, we designed an approach incorporating GEDI and airborne LiDAR data, in addition to detailed forestry inventory data, for estimating tree-growth dynamics for the Laurentides wildlife reserve in Canada. We estimated an average tree-growth rate of 0.32 ± 0.23 (SD) m/year for the study site and evaluated our results against field data and a time series of NDVI from Landsat images. The results are in agreement with expected patterns in tree-growth rates related to tree species and forest stand age, and the produced dataset is able to track disturbance events resulting in the loss of canopy height. Our study demonstrates the benefits of using spaceborne-LiDAR data for extending the temporal coverage of forestry inventories and highlights the ability of GEDI data for detecting changes in forests’ vertical structure.
A Method of Extracting the SWH Based on a Constituted Wave Slope Feature Vector (WSFV) from X-Band Marine Radar Images
Authors: Wei Yanbo , Wang Yujie , He Chendi , Song Huili , Lu Zhizhong , Wang Hui
Published: November 2023

The shadow statistical method (SSM) used for extracting the significant wave height (SWH) from X-band marine radar images was further investigated because of its advantage of not requiring an external reference for calibration. Currently, a fixed shadow segmentation threshold is utilized to extract the SWH from a radar image based on the SSM. However, the retrieval accuracy of the SWH is not ideal for low wind speeds since the echo intensity of sea waves rapidly decays over distance. In order to solve this problem, an adaptive shadow threshold, which varies with echo intensity over distance and can accurately divide the radar image into shadow and nonshadow areas, is adopted to calculate the wave slope (WS) based on the texture feature of the edge image. Instead of using the averaged WS, the wave slope feature vector (WSFV) is constructed for retrieving the SWH since the illumination ratio and the calculated WS in the azimuth are different for shore-based radar images. In this paper, the SWH is calculated based on the constructed WSFV and classical support vector regression (SVR) technology. The collected 222 sets of X-band marine radar images with an SWH range of 1.0∼3.5 m and an average wind speed range of 5∼10 m/s were utilized to verify the performance of the proposed approach. The buoy record, which was deployed during the experiment, was used as the ground truth. For the proposed approach, the mean bias (BIAS) and the mean absolute error (MAE) were 0.03 m and 0.14 m when the ratio of the training set to the test set was 1:1. Compared to the traditional SSM, the correlation coefficient (CC) of the proposed approach increased by 0.27, and the root mean square error (RMSE) decreased by 0.28 m.
Fusion of Audio and Vibration Signals for Bearing Fault Diagnosis Based on a Quadratic Convolution Neural Network
Authors: Yan Jin , Liao Jian-bin , Gao Jin-yi , Zhang Wei-wei , Huang Chao-ming , Yu Hong-liang
Published: November 2023

In this paper, a quadratic convolution neural network (QCNN) using both audio and vibration signals is utilized for bearing fault diagnosis. Specifically, to make use of multi-modal information for bearing fault diagnosis, the audio and vibration signals are first fused together using a 1 × 1 convolution. Then, a quadratic convolution neural network is applied for the fusion feature extraction. Finally, a decision module is designed for fault classification. The proposed method utilizes the complementary information of audio and vibration signals, and is insensitive to noise. The experimental results show that the accuracy of the proposed method can achieve high accuracies for both single and multiple bearing fault diagnosis in the noisy situations. Moreover, the combination of two-modal data helps improve the performance under all conditions.
Stress Level Detection Based on the Capacitive Electrocardiogram Signals of Driving Subjects
Authors: Škorić Tamara
Published: November 2023

The automotive industry and scientific community are making efforts to develop innovative solutions that would increase successful driver performance in preventing crashes caused by drivers’ health and concentration. High stress is one of the causes of impaired driver performance. This study investigates the ability to classify different stress levels based on capacitive electrocardiogram (cECG) recorded during driving by unobtrusive acquisition systems with different hardware implementations. The proposed machine-learning model extracted only four features, based on the detection of the R peak, which is the most reliably detected characteristic point even in inferior quality cECG. Another criterion for selecting the features is their low computational complexity, which enables real-time application. The proposed method was validated on three open data sets recorded during driving: electrocardiogram (ECG) recorded by electrodes with direct skin contact (high quality); cECG recorded without direct skin contact through clothes by electrodes built into a portable multi-modal cushion (middle quality); and cECG recorded through the clothes without direct skin contact by electrodes built into a car seat (lowest quality). The proposed model achieved a high accuracy of 100% for high-quality ECG, 96.67% for middle-quality cECG, and 98.08% for the lower-quality cECG.
Shadow Effect for Small Insect Detection by W-Band Pulsed Radar
Authors: Hernández Rosas Miguel , Espinosa Flores-Verdad Guillermo , Peregrina Barreto Hayde , Liedo Pablo , Altamirano Robles Leopoldo
Published: November 2023

In radar entomology, one primary challenge is detecting small species (smaller than 5 cm) since these tiny insects reflect radiation that can be poorly observable and, therefore, difficult to interpret. After a literature search on radar entomology, this research found few works where it has been possible to sense insects with dimensions smaller than 5 cm using radars. This paper describes different methodologies to detect Mediterranean fruit flies with 5–6 mm sizes using a pulsed W-band radar and presents the experimental results that validate the procedures. The article’s main contribution is the successful detection of Mediterranean fruit flies employing the shadow effect on the backscattered radar signal, achieving an 11% difference in received power when flies are present. So far, according to the information available and the literature search, this work is the first to detect small insects less than 1 cm long using a pulsed radar in W-Band. The results show that the proposed shadow effect is a viable alternative to the current sensors used in smart traps, as it allows not only detection but also counting the number of insects in the trap.
Soil Particle Size Thresholds in Soil Spectroscopy and Its Effect on the Multivariate Models for the Analysis of Soil Properties
Authors: Barra Issam , El Moatassem Tarik , Kebede Fassil
Published: November 2023

This study focused on one of the few but critical sample preparations required in soil spectroscopy (i.e., grinding), as well as the effect of soil particle size on the FTIR spectral database and the partial least squares regression models for the prediction of eight soil properties (viz., TC, TN, OC, sand, silt, clay, Olsen P, and CEC). Fifty soil samples from three Moroccan region were used. The soil samples underwent three preparations (drying, grinding, sieving) to obtain, at the end of the sample preparation step, three ranges of particle size, samples with sizes < 500 µm, samples with sizes < 250 µm, and a third range with particles < 125 µm. The multivariate models (PLSR) were set up based on the FTIR spectra recorded on the different obtained samples. The correlation coefficient (R2) and the root mean squared error of cross validation (RMSECV) were chosen as figures of merit to assess the quality of the prediction models. The results showed a general trend in improving the R2 as the finer particles were used (from <500 µm to 125 µm), which was clearly observed for TC, TN, P2O5, and CEC, whereas the cross-validation errors (RMSECV) showed an opposite trend. This confirmed that fine soil grinding improved the accuracy of predictive models for soil properties diagnosis in soil spectroscopy.
Tailor-Made Development Pathways: A Framework to Enhance Active Participation of Youth in Agriculture
Authors: Madende Primrose , Henning Johannes I. F. , Jordaan Henry
Published: November 2023

The development of youth to actively engage in agriculture could address the persistent youth unemployment problem. For youth to actively engage in agriculture, adequate access to key productive resources is necessary. The main aim of this article is to develop and validate tailor-made development pathways based on the characteristics of four youth typologies, addressing the constrained access to key livelihood capitals, and to enhance the participation of youth in agriculture. The pathways are developed based on the Modified Sustainable Livelihood Framework (MSLF), which includes six livelihood capitals, namely, physical, natural, social, financial, human and psychological capitals. Four pathways were developed and named Business-oriented, Gender-oriented, Occupation-oriented and Livestock-oriented. Through focus group discussions, the pathways were validated to determine whether they can be used successfully to facilitate the participation of youths in agriculture. The results confirm that tailor-made development pathways can be used to develop youth characterised by the typology that informed that pathway, to actively engage in agriculture. The implementation of support strategies to support youth in agriculture, should therefore, be guided by the specific needs of different typologies. This allows for the coordination and coherence of youth support initiatives to enhance access to resources, which can yield improvements to desired development outcomes compared to initiatives implemented as piecemeals.
Boosting Ensemble Learning for Freeway Crash Classification under Varying Traffic Conditions: A Hyperparameter Optimization Approach
Authors: Almahdi Abdulla , Al Mamlook Rabia Emhamed , Bandara Nishantha , Almuflih Ali Saeed , Nasayreh Ahmad , Gharaibeh Hasan , Alasim Fahad , Aljohani Abeer , Jamal Arshad
Published: November 2023

Freeway crashes represent a significant and persistent threat to road safety, resulting in both loss of life and extensive property damage. Effectively addressing this critical issue requires a comprehensive understanding of the factors contributing to these incidents and the ability to accurately predict crash severity under different traffic conditions. This study aims to improve the accuracy of crash classification by incorporating key traffic-related variables such as braking, weather conditions, and speed. To validate the effectiveness of proposed model, we utilize real-world crash data from Flint, Michigan. To achieve the objective, we employ an innovative Boosting Ensemble Learning approach, leveraging five advanced ensemble learning models: Gradient Boosting, Cat Boost, XGBoost, LightGBM, and SGD. Through the application of hyperparameter optimization techniques, we further enhance the performance of these models, improving their predictive capabilities. Our evaluation results demonstrated the effectiveness of our approach, with Gradient Boosting algorithms achieving an accuracy rate of up to 96% in crash classification. This research provides valuable insights into the potential of using Boosting Ensemble Learning as a tool for accurately and efficiently classifying freeway crashes across a spectrum of traffic conditions. Additionally, it sheds light on the nuanced variations in crash mechanisms observed when employing diverse ensemble learning models. The findings of this study underscore the significance of hyperparameter optimization as a critical factor in elevating the predictive precision of freeway crashes.
Enhanced Ant Colony Optimization for Vehicular Ad Hoc Networks Using Fittest Node Clustering
Authors: Bijalwan Akhilesh , Hussain Iqram , Purohit Kamlesh Chandra , Kumar M. Anand
Published: November 2023

Vehicular ad hoc networks (VANETs) are a rapidly evolving field at the intersection of intelligent transportation systems, emphasizing the need for a stable and scalable VANET topology to accommodate growing vehicular densities. The intricate challenge of route selection calls for advanced clustering protocols to bolster road safety and message routing. This research introduces a novel approach to intelligent clustering routing protocols, leveraging heuristic-based solutions built upon an enhanced ant colony optimizer (ACO) framework. The study unfolds in two stages: the creation of a dynamic search space model and the election of cluster heads (CHs). The innovative dynamic aware transmission range parallel Euclidean distance (DA-TRPED) technique establishes a dynamic search space using the parallel Euclidean distance (PED) concept. This approach evaluates vehicular nodes by estimating PED values, reducing the search process’s complexity. Subsequently, an intelligent cluster head is selected by enhancing the dynamic evaporation factor (DEF) within the ACO technique. The experimental validation of the DA-TRPED technique takes place in NS2 simulations, demonstrating superior performance compared to conventional ACO. This enhancement is evident in metrics such as packet delivery, packet drop, throughput, end-to-end delay, and the lifetime analysis of clustered nodes. The proposed approach holds promise for optimizing VANETs, enhancing their stability and scalability while promoting road safety and efficient message routing.
Framework for Dynamic Circular Economy in the Building Industry: Integration of Blockchain Technology and Multi-Criteria Decision-Making Approach
Authors: Movaffaghi Hamid , Yitmen Ibrahim
Published: November 2023

The building industry is one of the most resource-intensive sectors in industrialized countries, requiring a shift from a linear to a more sustainable circular economic model. Nevertheless, there are several major challenges, such as the management of information regarding used materials and products, the lack of cross-sector documentation tools, and sales operations for implementing a dynamic circular economy in the building industry. To overcome these challenges, blockchain technology for documentation, tracing used materials and products, and the use of multi-criteria decision-making approaches for the ranking and selection of optimal used materials and products have emerged as crucial facilitators, with the potential to address the technological, organizational, environmental, and economic requirements. The purpose of this study is to develop a theoretical framework of a digital platform ecosystem for implementing a dynamic circular economy in the building industry through the integration of blockchain technology and a multi-criteria decision-making approach built upon their synergy. The priority order of two alternatives of used materials and products was determined according to the AHP method, leading to selection of the most sustainable alternative. This research study contributes to dynamic circular economies by (1) facilitating cross-sector information transparency and the tracing of used materials and products from their sources to their end-of-life stages and through (2) the ranking and selection of used materials and products based on their overall properties.
Determining the Optimal Sample Size for Assessing Crown Damage on Color Infrared (CIR) Aerial Photographs
Authors: Kolić Jelena , Pernar Renata , Seletković Ante , Jazbec Anamarija , Ančić Mario
Published: November 2023

One of the priorities in sustainable forest management is monitoring the health status of trees and stands. From the aspect of remote sensing (RS), the best way of doing this is by interpreting color infrared (CIR) aerial photographs; however, this raises the issue of sample size. For this reason, to apply this method in practice, it is indispensable to determine an appropriate sample size to ensure sufficient reliability of the health status assessment of trees in CIR aerial photographs. This research was conducted in lowland forests of pedunculate oak in Croatia. To determine damage in the photographs of the main tree species, a systematic sample with varying dot grid densities—100 × 100 m, 200 × 200 m, 300 × 300 m, 500 × 500 m, 1000 × 1000 m—was used with combinations of different numbers of interpreted trees per sample. Damage indicators were also calculated based on tree distributions obtained by interpreting four trees, two trees and one tree in different sample sizes. The results of the testing showed that there were no statistically significant differences between different sample densities and numbers of interpreted trees in relation to mean damage assessment. Regardless of the fact that there were no statistically significant differences during damage assessment, it was found that by lowering sample densities, starting with 200 × 200 m, the number of trees and the number of sample points per particular sub-compartment significantly decreased, and so did the desired accuracy. Consequently, the participation (distribution) of particular species and damage degrees in the sample were lost, which significantly affected the overall tree health assessment. In contrast, grid densities of 100 × 100 m with one interpreted tree at the raster point proved to be the optimal sample size. This confirms the fact found in earlier research, that is, that the selected sample should have several spatially well-distributed points with a smaller number of trees in the point, and samples with larger numbers of trees in a smaller number of points should be avoided.
Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey
Authors: Kayral İhsan Erdem , Sarı Tuğba , Tandoğan Aktepe Nisa Şansel
Published: November 2023

Accurate forecasting of tourism demand and income holds paramount importance for both the tourism industry and the national economy. This study aims to address several objectives: (1) specify the best forecasting model in the prediction of tourist arrival volumes and tourism income for Turkey; (2) assess the degree of impact exerted by various determinants on the tourism forecasts; (3) generate forecasts for tourist arrival volumes and tourism income using the most suitable models; and (4) examine potential scenarios illustrating the ramifications of the Russia-Ukraine war on tourist arrival volumes and tourism income. The forecasting models employed in this study encompass a comprehensive set of statistical methods, including ETS, ARIMA, TRAMO-SEATS, X13, X11, STL, Grey, and their combinations with ANN. In the ANN models, exogenous variables such as the global financial crisis, the Turkey-Russia warplane crash crisis, the COVID-19 pandemic, and USD/TRY exchange rates are incorporated. The results unveil the identification of five superior models: ETS, Grey, hybrid ETS-ANN, hybrid Grey-ANN, and hybrid ARIMA-ANN models, which exhibit the lowest MAPE and sMAPE values. Forecasts for the forthcoming quarters are examined under two scenarios: assuming the continuity or cessation of the Russia-Ukraine war. Comparative analysis of the relative effects of exogenous variables indicates that COVID-19 has the most substantial impact on tourist arrival volumes, and tourism income is primarily influenced by the USD/TRY exchange rate.
A Novel Individual Carbon Emission Evaluation and Carbon Trading Model for Low-Carbon University Campuses
Authors: Hao Junhong , Ye Xialin , Yu Chenfei , Liu Jiayuan , Ruan Yimin , Zhang Yingxin , Hong Feng , Zhang Dongyue
Published: November 2023

Individual carbon accounting and trading is significant for building and achieving low-/zero-carbon university campuses. This manuscript examines various aspects of individual carbon trading on campus, such as assessing personal carbon emissions, students’ willingness to participate in individual carbon trading on campus, and its influencing factors, policy setting, and emission reduction benefits. Based on the Theory of Planned Behavior, this manuscript uses the conditional process analysis method and conducts a questionnaire survey on a university campus in Beijing to evaluate individuals’ carbon emissions on campus and explore their willingness to trade personal carbon. Moreover, a system dynamics approach is adopted to propose a simulation model of individual carbon trading on the campus and assess its feasibility and emission reduction benefits. The results indicate an average annual emission reduction of 8.18% per person, providing a theoretical foundation to implement and promote the individual carbon trading pilot on campus. These findings highlight the potential benefits of individual carbon trading policies that may effectively reduce carbon emissions on university campuses.
Examining Sustainability Alignment of Supplier Selection Criteria during Industrial Revolutions
Authors: Modarress-Fathi Batoul , Ansari Al , Ansari Alexander
Published: November 2023

Suppliers have evolved alongside industrial revolutions induced by their selection criteria for over two centuries. While sustainability has remained a pledge in their inter-creditor agreements, the claims of 11,000 scientists regarding the Earth’s colossal pollution and the calls of 196 nations to reach net-zero emissions by 2030 have accentuated concerns regarding the sustainability of supply selection criteria. Twenty supply selection criteria and seventy associated indicators were identified in industrial revolutions. The identified criteria and indicators were forwarded to 250 volunteers with expertise in the supply chain across six industries. Maintaining confidentiality, the volunteers were first requested to rank the criteria and related indicators concerning the three pillars of sustainability, the environmental, economic, and social, using The second request was to mark the percentage of influence of economic criteria and the related indicators on environmental and social sustainability. The third request was to state their professional views on sustainability during the industrial revolutions. Statistical analyses of the responses suggested that the identified supplier selection criteria were not equally driven by economic, environmental, and social sustainability. Supply chain professionals supported the statistical analysis and confirmed that the economic indicators dominating the selection of suppliers were significantly higher than the environmental and social criteria. They also confirmed that economic indicators have negatively impacted environmental and social sustainability during industrial revolutions. They recommended that transitioning into sustainable supply chains requires shifting emphasis from economic to environmental and social sustainability.
Stakeholder Participation for Nature-Based Solutions: Inspiration for Rural Area’s Sustainability in China
Authors: Liu Huihui , Martens Pim
Published: November 2023

Due to the current pressure of rural modernization and industrialization, rural areas are facing social and environmental challenges such as a lack of cultural identity, low democratic participation, and the destruction of landscape ecology, especially in China, a large and representative developing country. The nature-based solutions (NbS) approach states that achieving the multiple benefits of nature for health and well-being requires wider stakeholder collaboration and integration of nature into the policies. Although many scholars have argued that NbS have a significant positive contribution to sustainability in rural areas, there is still a lack of clear pathways for NbS to guide farmer participation and address environmental issues. This paper first summarizes the theoretical research and practical experience of stakeholder participation for NbS through a systematic review. The literature analysis is mainly conducted from five perspectives: policies, benefits, challenges, methods, and frameworks. Combined with the “farmers as the main body” principle of China’s rural revitalization strategy, this study proposes to (1) stimulate farmers’ awareness of environmental protection; (2) enhance farmers’ participation and sense of ownership; (3) enhance farmers’ ability to take action to improve the ecological environment; and (4) integrate eco-design into their lives, make environmental protection education deeply rooted in people’s hearts, and cultivate green farmers.
Alternative Integrated Ethanol, Urea, and Acetic Acid Processing Routes Employing CCU: A Prospective Study through a Life Cycle Perspective
Authors: Miranda Denis da Silva , Martins Luise Prado , Teles Beatriz Arioli de Sá , Cunha Isadora L. C. , Menezes Natália de Almeida , Sakamoto Hugo , Kulay Luiz
Published: November 2023

Despite the importance of inputs such as urea, ethanol, and acetic acid for the global production of food, energy, and chemical bases, manufacturing these substances depends on non-renewable resources, generating significant environmental impacts. One alternative to reducing these effects is to integrate production processes. This study compares the cumulative environmental performance of individual production routes for ethanol, urea, and acetic acid with that of an integrated complex designed based on Industrial Ecology precepts. Life Cycle Assessment was used as a metric for the impact categories of Global Warming Potential (GWP) and Primary Energy Demand (PED). The comparison occurred between the reference scenario, which considers individual processes, and six alternative integrated arrangements that vary in the treatment given to a stream concentrated in fuels generated in the Carbon Capture and Usage system that serves the processing of acetic acid. The study showed that process integration is recommended in terms of PED, whose contributions were reduced by 46–63% compared to stand-alone processes. The impacts of GWP are associated with treating the fuel stream. If it is treated as a co-product and environmental loads are allocated in terms of energy content, gains of up to 44% can be expected. On the other hand, if the stream is a waste, the complex’s GWP becomes more aggressive than the baseline scenario by 66%.
The Influence of Social Norms and Environmental Regulations on Rural Households’ Pesticide Packaging Waste Disposal Behavior
Authors: Zhang Yuhan , Zhang Mengling , Weng Zhenlin , Gao Xueping , Liao Wenmei
Published: November 2023

The agricultural ecological environment provides an important resource guarantee for social development. The extensive management mode of agriculture in China has not fundamentally changed; the contradiction between production and governance is still prominent, and the management of agricultural surface pollution has a long way to go. Based on the data from 572 rural households in Jiangxi province, this paper uses the Ordered Logit, 2SLS, and the moderation effect model to analyze the mechanism between social norms (SNs) and rural households’ (RHs) disposal of pesticide packaging waste (PPW) and to test the moderation effect of environmental regulation (ER) in the influence path of SN to RHs’ disposal of PPW. The results show that (1) descriptive norms and directive norms promote RHs not littering PPW; the probability of RHs not littering PPW increases by 4.0% for each unit decrease in descriptive norms, and the probability of RHs not littering PPW increases by 12.1% when there are directive norms, but the directive norms are more significant than the descriptive norms. Consistent conclusions were obtained after the robustness test and endogeneity treatment. (2) Reputational incentives strengthen the promotional effect of directive norms on RHs’ behavior of not littering PPW; punitive regulations hinder the promotional effect of descriptive norms on RHs’ behavior of not littering PPW. Based on the findings of the study, the following policy recommendations are put forward: Actively cultivate SNs and give full play to their role in promoting RHs’ choice of the disposal behavior of PPW; improve the role of ER in regulating RHs’ choice of the disposal behavior of PPW; guide the ER and SNs to work in coordination.
Studying Alumina–Water Nanofluid Two-Phase Heat Transfer in a Novel E-Shaped Porous Cavity via Introducing New Thermal Conductivity Correlation
Authors: Armaghani Taher , Sepehrnia Mojtaba , Molana Maysam , Nour Manasik M. , Safari Amir
Published: November 2023

Investigating natural convection heat transfer of nanofluids in various geometries has garnered significant attention due to its potential applications across several disciplines. This study presents a numerical simulation of the natural convection heat transfer and entropy generation process in an E-shaped porous cavity filled with nanofluids, implementing Buongiorno’s simulation model. Analyzing the behavior of individual nanoparticles, or even the entire nanofluid system at the molecular level, can be extremely computationally intensive. Symmetry is a fundamental concept in science that can help reduce this computational burden considerably. In this study, nanofluids are frequently conceived of as a combination of water and Al2O3 nanoparticles at a concentration of up to 4% by volume. A unique correlation was proposed to model the effective thermal conductivity of nanofluids. The average Nusselt number, entropy production, and Rayleigh number have been illustrated to exhibit a decreasing trend when the volume concentration of nanoparticles inside the porous cavity rises; the 4% vol. water–alumina NFs yield 17.35% less average Nu number compared to the base water.
The Therapeutic Effect of Botulinum Toxin Type A on Trigeminal Neuralgia: Are There Any Differences between Type 1 versus Type 2 Trigeminal Neuralgia?
Authors: Tereshko Yan , Valente Mariarosaria , Belgrado Enrico , Dalla Torre Chiara , Dal Bello Simone , Merlino Giovanni , Gigli Gian Luigi , Lettieri Christian
Published: November 2023

Background: Botulinum toxin type A is an effective treatment for trigeminal neuralgia. Moreover, its efficacy in type 2 trigeminal neuralgia and comparative studies between type 1 and type 2 trigeminal neuralgia (TN) still need to be improved. Methods: We treated 40 TN patients with onabotulinumtoxinA; 18 had type 1 TN, and 22 had type 2 TN. We compared the baseline pain score with the Visual Analogue Scale (VAS) and paroxysm frequency (number per week) at the baseline with those obtained at 1-month and 3-month follow-ups. Nonetheless, we compared the baseline Penn Facial Pain Scale with the scores obtained at the 1-month follow-up. Results: BoNT/A effectively reduced pain intensity and frequency at the 1-month and 3-month follow-ups. Moreover, the type 1 TN and type 2 TN groups had baseline pain scores of 7.8 ± 1.65 and 8.4 ± 1.1, respectively. Pain significantly improved (p < 0.001) in both groups to 3.1 ± 2.3 (type 1 TN) and 3.5 ± 2.3 (type 2 TN) at the 1-month follow-up and to 3.2 ± 2.5 (type 1 TN) and 3.6 ± 2.5 (type 2 TN) at the 3-month follow-up. There was no difference between the two groups (p 0.345). The baseline paroxysm frequencies (number per week) were 86.7 ± 69.3 and 88.9 ± 62.2 for the type 1 and type 2 TN groups, respectively; they were significantly reduced in both groups at the 1-month and 3-month follow-ups without significant differences between the two groups (p 0.902). The Pain Facial Pain Scale improved at the 1-month follow-up, and no significant differences were found between the two groups. There was a strong correlation between background pain and paroxysm pain intensity (r 0.8, p < 0.001). Conclusions: Botulinum toxin type A effectively reduced the pain, paroxysm frequency, and PFPS scores of type 1 and type 2 trigeminal neuralgia patients without statistically significant differences. Facial asymmetry was the only adverse event.
Structural Similarities, in Relation with the Cross-Reactivity, of Hymenoptera Allergenic Dipeptidyl Peptidases IV—An Overall Comparison Including a New Dipeptidyl Peptidase IV Sequence from Vespa velutina
Authors: Monsalve Rafael I. , Lombardero Manuel , Christensen Lars H. , Núñez-Acevedo Beatriz , González-de-Olano David , Sobrino-García Miriam , Castillo-Loja Rosita M. , Bravo Susana B. , Alonso-Sampedro Manuela , Vidal Carmen
Published: November 2023

(1) Background: Dipeptidyl Peptidases IV (DPPIVs), present in many organisms, are minor components in the venoms of Hymenoptera, where they have been identified as cross-reactive allergenic molecules. Considering that the structure of homologous DPPIVs is well characterized, we aimed to explain which regions have higher similarity among these proteins and present a comparison among them, including a new Vespa velutina DPPIV sequence. Moreover, two cases of sensitization to DPPIVs in wasp- and honeybee-sensitized patients are presented. (2) Methods: Proteomic analyses have been performed on the venom of the Asian hornet Vespa velutina to demonstrate the sequence of its DPPIV (allergen named Vesp v 3, with sequence accession number P0DRB8, and with the proteomic data available via ProteomeXchange with the identifier PXD046030). A comparison performed through their alignments and analysis of the three-dimensional structure showed a region with higher similarity among Hymenoptera DPPIVs. Additionally, ImmunoCAP™ determinations (including specific inhibition experiments), as well as IgE immunoblotting, are performed to demonstrate the allergenicity of Api m 5 and Ves v 3. (3) Results and Conclusions: The data presented demonstrate that the similarities among Hymenoptera DPPIVs are most likely localized at the C-terminal region of these enzymes. In addition, a higher similarity of the Vespa/Vespula DPPIVs is shown. The clinical cases analyzed demonstrated the allergenicity of Api m 5 and Ves v 3 in the sera of the allergic patients, as well as the presence of this minor component in the preparations used in venom immunotherapy.