bluuebunny/crossref_metadata_2025 huggingface dataset:
Interferometric Radars for Bridge Monitoring: Comparison among X-Bands, Ku-Bands, and W-Bands
Authors: Beni Alessandra , Miccinesi Lapo , Pagnini Lorenzo , Cioncolini Andrea , Shan Jingfeng , Pieraccini Massimiliano
Published: September 2024

Interferometric radars are widely used sensors for structural health monitoring. They are able to perform dynamic measurements of displacement with sub-millimeter precision. Today, the Ku-band is the most common, due to the spread of commercial systems operating in this band. At the same time, the W-band sensors are gaining ever more interest. Other popular systems work in the X-band. Since the characteristics of the measurements dramatically depend on the operative frequency, it is essential to highlight their differences. For instance, higher frequency allows for high displacement resolution, but it is more subject to phase wrapping and decorrelation effects. In this paper, a direct comparison between radars operating in X, Ku, and W-band for bridge monitoring is carried out. The radars provide frequency-modulated continuous-wave signals. Experimental campaigns were performed both in controlled and realistic scenarios (a stayed bridge). The results of the experiments demonstrate that all the three sensors are suitable for performing dynamic structure monitoring despite their differences. It is worth noting that this comparative analysis has highlighted the role of amplitude variation in phase/displacement measurement. Regarding this point, the three different bands exhibit significant differences.
A Small-Scale Landslide in 2023, Leshan, China: Basic Characteristics, Kinematic Process and Cause Analysis
Authors: Cui Yulong , Qian Zhichong , Xu Wei , Xu Chong
Published: September 2024

Sudden mountain landslides can pose substantial threats to human lives and property. On 4 June 2023, a landslide occurred in Jinkouhe District, Leshan City, Sichuan Province, resulting in 19 deaths and 5 injuries. This study, drawing on field investigations, geological data, and historical imagery, elucidates the characteristics and causes of the landslide and conducts a reverse analysis of the landslide movement process using Massflow V2.8 numerical simulation software. The results indicate that rainfall and human engineering activities are key factors that triggered this landslide. Numerical simulation shows that the landslide stopped after 60 s of sliding, with a movement distance of approximately 286 m, a maximum sliding speed of 17 m/s, and a maximum accumulation thickness of 7 m, eventually forming a loose landslide debris accumulation of approximately 5.25 × 103 m3. The findings of this study provide significant reference value for research on landslide movement characteristics and disaster prevention and mitigation in mountainous areas.
Methodology for Performing Bathymetric and Photogrammetric Measurements Using UAV and USV Vehicles in the Coastal Zone
Authors: Specht Mariusz
Published: September 2024

The coastal zone is constantly exposed to marine erosion, rising water levels, waves, tides, sea currents, and debris transport. As a result, there are dynamic changes in the coastal zone topography, which may have negative effects on the aquatic environment and humans. Therefore, in order to monitor the changes in landform taking place in the coastal zone, periodic bathymetric and photogrammetric measurements should be carried out in an appropriate manner. The aim of this review is to develop a methodology for performing bathymetric and photogrammetric measurements using an Unmanned Aerial Vehicle (UAV) and an Unmanned Surface Vehicle (USV) in a coastal zone. This publication shows how topographic and bathymetric monitoring should be carried out in this type of zone in order to obtain high-quality data that will be used to develop a Digital Terrain Model (DTM). The methodology for performing photogrammetric surveys with the use of a drone in the coastal zone should consist of four stages: the selection of a UAV, the development of a photogrammetric flight plan, the determination of the georeferencing method for aerial photos, and the specification as to whether there are meteorological conditions in the studied area that enable the implementation of an aerial mission through the use of a UAV. Alternatively, the methodology for performing bathymetric measurements using a USV in the coastal zone should consist of three stages: the selection of a USV, the development of a hydrographic survey plan, and the determination of the measurement conditions in the studied area and whether they enable measurements to be carried out with the use of a USV. As can be seen, the methodology for performing bathymetric and photogrammetric measurements using UAV and USV vehicles in the coastal zone is a complex process and depends on many interacting factors. The correct conduct of the research will affect the accuracy of the obtained measurement results, the basis of which a DTM of the coastal zone is developed. Due to dynamic changes in the coastal zone topography, it is recommended that bathymetric measurements and photogrammetric measurements with the use of UAV and USV vehicles should be carried out simultaneously on the same day, before or after the vegetation period, to enable the accurate measurement of the shallow waterbody depth.
Enhancing Remote Sensing Water Quality Inversion through Integration of Multisource Spatial Covariates: A Case Study of Hong Kong’s Coastal Nutrient Concentrations
Authors: Zhang Zewei , Li Cangbai , Yang Pan , Xu Zhihao , Yao Linlin , Wang Qi , Chen Guojun , Tan Qian
Published: September 2024

The application of remote sensing technology for water quality monitoring has attracted much attention recently. Remote sensing inversion in coastal waters with complex hydrodynamics for non-optically active parameters such as total nitrogen (TN) and total phosphorus (TP) remains a challenge. Existing studies build the relationships between remote sensing spectral data and TN/TP directly or indirectly via the mediation of optically active parameters (e.g., total suspended solids). Such models are often prone to overfitting, performing well with the training set but underperforming with the testing set, even though both datasets are from the same region. Using the Hong Kong coastal region as a case study, we address this issue by incorporating spatial covariates such as hydrometeorological and locational variables as additional input features for machine learning-based inversion models. The proposed model effectively alleviates overfitting while maintaining a decent level of accuracy (R2 exceeding 0.7) during the training, validation and testing steps. The gap between model R2 values in training and testing sets is controlled within 7%. A bootstrap uncertainty analysis shows significantly improved model performance as compared to the model with only remote sensing inputs. We further employ the Shapely Additive Explanations (SHAP) analysis to explore each input’s contribution to the model prediction, verifying the important role of hydrometeorological and locational variables. Our results provide a new perspective for the development of remote sensing inversion models for TN and TP in similar coastal waters.
Research on ELoran Demodulation Algorithm Based on Multiclass Support Vector Machine
Authors: Liu Shiyao , Yan Baorong , Guo Wei , Hua Yu , Zhang Shougang , Lu Jun , Xu Lu , Yang Dong
Published: September 2024

Demodulation and decoding are pivotal for the eLoran system’s timing and information transmission capabilities. This paper proposes a novel demodulation algorithm leveraging a multiclass support vector machine (MSVM) for pulse position modulation (PPM) of eLoran signals. Firstly, the existing demodulation method based on envelope phase detection (EPD) technology is reviewed, highlighting its limitations. Secondly, a detailed exposition of the MSVM algorithm is presented, demonstrating its theoretical foundations and comparative advantages over the traditional method and several other methods proposed in this study. Subsequently, through comprehensive experiments, the algorithm parameters are optimized, and the parallel comparison of different demodulation methods is carried out in various complex environments. The test results show that the MSVM algorithm is significantly superior to traditional methods and other kinds of machine learning algorithms in demodulation accuracy and stability, particularly in high-noise and -interference scenarios. This innovative algorithm not only broadens the design approach for eLoran receivers but also fully meets the high-precision timing service requirements of the eLoran system.
Twenty Years of Thermal Infrared Observations (2004–2024) at Campi Flegrei Caldera (Italy) by the Permanent Surveillance Ground Network of INGV-Osservatorio Vesuviano
Authors: Sansivero Fabio , Vilardo Giuseppe
Published: September 2024

Thermal infrared (TIR) time series images acquired by ground, proximal TIR stations provide valuable data to study evolution of surface temperature fields of diffuse degassing volcanic areas. This paper presents data processing results related to TIR images acquired since 2004 by six ground stations in the permanent thermal infrared surveillance network at Campi Flegrei (TIRNet) set up by INGV-Osservatorio Vesuviano. These results are reported as surface temperature and heat flux time series. The processing methodologies, also discussed in this paper, allow for presentation of the raw TIR image data in a more comprehensible form, suitable for comparisons with other geophysical parameters. A preliminary comparison between different trends in the surface temperature and heat flux values recorded by the TIRNet stations provides evidence of peculiar changes corresponding to periods of intense seismicity at the Campi Flegrei caldera. During periods characterized by modest seismicity, no remarkable evidence of common temperature variations was recorded by the different TIRNet stations. Conversely, almost all the TIRNet stations exhibited common temperature variations, even on a small scale, during periods of significant seismic activity. The comparison between the seismicity and the variations in the surface temperature and heat flux trends suggests an increase in efficiency of heat transfer between the magmatic system and the surface when an increase in seismic activity was registered. This evidence recommends a deeper, multidisciplinary study of this correlation to improve understanding of the volcanic processes affecting the Campi Flegrei caldera.
Towards the Instrumentation of Facemasks Used as Personal Protective Equipment for Unobtrusive Breathing Monitoring of Workers
Authors: Pinnelli Mariangela , Lo Presti Daniela , Silvestri Sergio , Setola Roberto , Schena Emiliano , Massaroni Carlo
Published: September 2024

This study focuses on the integration and validation of a filtering face piece 3 (FFP3) facemask module for monitoring breathing activity in industrial environments. The key objective is to ensure accurate, real-time respiratory rate (RR) monitoring while maintaining workers’ comfort. RR monitoring is conducted through temperature variations detected using temperature sensors tested in two configurations: sensor t1, integrated inside the exhalation valve and necessitating structural mask modifications, and sensor t2, mounted externally in a 3D-printed structure, thus preserving its certification as a piece of personal protective equipment (PPE). Ten healthy volunteers participated in static and dynamic tests, simulating typical daily life and industrial occupational activities while wearing the breathing activity monitoring module and a chest strap as a reference instrument. These tests were carried out in both indoor and outdoor settings. The results demonstrate comparable mean absolute error (MAE) for t1 and t2 in both indoor (i.e., 0.31 bpm and 0.34 bpm) and outdoor conditions (i.e., 0.43 bpm and 0.83 bpm). During simulated working activities, both sensors showed consistency with MAE values in static tests and were not influenced by motion artifacts, with more than 97% of RR estimated errors within ±2 bpm. These findings demonstrate the effectiveness of integrating a smart module into protective masks, enhancing occupational health monitoring by providing continuous and precise RR data without requiring additional wearable devices.
A Blockchain-Based Authentication Mechanism for Enhanced Security
Authors: McCabe Charlotte , Mohideen Althaff Irfan Cader , Singh Raman
Published: September 2024

Passwords are the first line of defence against preventing unauthorised access to systems and potential leakage of sensitive data. However, the traditional reliance on username and password combinations is not enough protection and has prompted the implementation of technologies such as two-factor authentication (2FA). While 2FA enhances security by adding a layer of verification, these techniques are not impervious to threats. Even with the implementation of 2FA, the relentless efforts of cybercriminals present formidable obstacles in securing digital spaces. The objective of this work is to implement blockchain technology as a form of 2FA. The findings of this work suggest that blockchain-based 2FA methods could strengthen digital security compared to conventional 2FA methods.
Impact of a Precision Intervention for Vascular Health in Middle-Aged and Older Postmenopausal Women Using Polar Heart Rate Sensors: A 24-Week RCT Study Based on the New Compilation of Tai Chi (Bafa Wubu)
Authors: Wang Xiaona , Han Yanli , Li Haojie , Wang Xin , Wang Guixian
Published: September 2024

(1) Background: This study utilized a 24-week intervention incorporating heart rate sensors for real-time monitoring of intervention training, aiming to comprehensively assess the effects of Tai Chi on vascular endothelial function, atherosclerosis progression, and lipid metabolism. The insights gained may inform personalized non-pharmacological interventions to enhance the management of cardiovascular health in this population to provide sustainable benefits and improve quality of life. (2) Methods: Forty postmenopausal middle-aged and elderly women were randomly assigned to an exercise or control group. The exercise group underwent a 24-week Tai Chi (BaFa WuBu) training intervention with real-time heart rate monitoring using Polar sensors. Pre- and post-intervention assessments included body composition, blood pressure, vascularity, and blood parameters measured with the Inbody 720, Vascular Endothelial Function Detector, and Arteriosclerosis. Data were analyzed using SPSS 26.0 and mixed-design ANOVA to assess the effects of time, group, and their interactions on study outcomes. (3) Results: After training through 24 weeks of Tai Chi (BaFa WuBu) intervention, compared with the control group, systolic blood pressure in the exercise group was significantly lower (p < 0.05), and the difference between left and right arm pulse pressure, left and right ankle mean arterial pressure, left and right side baPWV, left and right side ABI, TC, TG, LDL, and blood pressure viscosity were all very significantly lower (p < 0.01), and the diastolic blood pressure was significantly higher (p < 0.05). Compared with baseline values in the exercise group, systolic blood pressure, right and left arm pulse pressure difference, right and left ankle mean arterial pressure, right and left side baPWV, right and left side ABI, TC, TG, LDL, and blood pressure viscosity decreased very significantly (p < 0.01) and diastolic blood pressure and FMD increased very significantly (p < 0.01) in the exercise group after the intervention. (4) Conclusions: In our study, a 24-week Tai Chi (BaFa WuBu) program significantly improved vascular health in middle-aged and older postmenopausal women. This simplified Tai Chi form is gentle and effective, ideal for older adults. Regular practice led to reduced vascular obstruction, improved lipid metabolism, and enhanced vascular endothelial function, crucial for preventing vascular diseases. The real-time heart rate sensors used were pivotal, enabling precise monitoring and adjustment of exercise intensity, thereby enhancing the study’s scientific rigor and supporting Tai Chi (BaFa WuBu) as a beneficial therapeutic exercise.
A Novel End-to-End Deep Learning Framework for Chip Packaging Defect Detection
Authors: Zhou Siyi , Yao Shunhua , Shen Tao , Wang Qingwang
Published: September 2024

As semiconductor chip manufacturing technology advances, chip structures are becoming more complex, leading to an increased likelihood of void defects in the solder layer during packaging. However, identifying void defects in packaged chips remains a significant challenge due to the complex chip background, varying defect sizes and shapes, and blurred boundaries between voids and their surroundings. To address these challenges, we present a deep-learning-based framework for void defect segmentation in chip packaging. The framework consists of two main components: a solder region extraction method and a void defect segmentation network. The solder region extraction method includes a lightweight segmentation network and a rotation correction algorithm that eliminates background noise and accurately captures the solder region of the chip. The void defect segmentation network is designed for efficient and accurate defect segmentation. To cope with the variability of void defect shapes and sizes, we propose a Mamba model-based encoder that uses a visual state space module for multi-scale information extraction. In addition, we propose an interactive dual-stream decoder that uses a feature correlation cross gate module to fuse the streams’ features to improve their correlation and produce more accurate void defect segmentation maps. The effectiveness of the framework is evaluated through quantitative and qualitative experiments on our custom X-ray chip dataset. Furthermore, the proposed void defect segmentation framework for chip packaging has been applied to a real factory inspection line, achieving an accuracy of 93.3% in chip qualification.
Enhancing Unmanned Aerial Vehicle Security: A Zero-Knowledge Proof Approach with Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge for Authentication and Location Proof
Authors: Koulianos Athanasios , Paraskevopoulos Panagiotis , Litke Antonios , Papadakis Nikolaos K.
Published: September 2024

UAVs are increasingly being used in various domains, from personal and commercial applications to military operations. Ensuring the security and trustworthiness of UAV communications is crucial, and blockchain technology has been explored as a solution. However, privacy remains a challenge, especially in public blockchains. In this work, we propose a novel approach utilizing zero-knowledge proof techniques, specifically zk-SNARKs, which are non-interactive cryptographic proofs. This approach allows UAVs to prove their authenticity or location without disclosing sensitive information. We generated zk-SNARK proofs using the Zokrates tool on a Raspberry Pi, simulating a drone environment, and analyzed power consumption and CPU utilization. The results are promising, especially in the case of larger drones with higher battery capacities. Ethereum was chosen as the public blockchain platform, with smart contracts developed in Solidity and tested on the Sepolia testnet using Remix IDE. This novel proposed approach paves the way for a new path of research in the UAV area.
Measurement Method of Stress in High-Voltage Cable Accessories Based on Ultrasonic Longitudinal Wave Attenuation
Authors: Su Jingang , Zhang Peng , Huang Xingwang , Pang Xianhai
Published: September 2024

High-voltage cables are the main arteries of urban power supply. Cable accessories are connecting components between different sections of cables or between cables and other electrical equipment. The stress in the cold shrink tube of cable accessories is a key parameter to ensure the stable operation of the power system. This paper attempts to explore a method for measuring the stress in the cold shrink tube of high-voltage cable accessories based on ultrasonic longitudinal wave attenuation. Firstly, a pulse ultrasonic longitudinal wave testing system based on FPGA is designed, where the ultrasonic sensor operates in a single-transmit, single-receive mode with a frequency of 3 MHz, a repetition frequency of 50 Hz, and a data acquisition and transmission frequency of 40 MHz. Then, through experiments and theoretical calculations, the transmission and attenuation characteristics of ultrasonic longitudinal waves in multi-layer elastic media are studied, revealing an exponential relationship between ultrasonic wave attenuation and the thickness of the cold shrink tube. Finally, by establishing a theoretical model of the radial stress of the cold shrink tube, using the thickness of the cold shrink tube as an intermediate variable, an effective measurement of the stress of the cold shrink tube was achieved.
An Improved YOLOv8 OBB Model for Ship Detection through Stable Diffusion Data Augmentation
Authors: Feng Sang , Huang Yi , Zhang Ning
Published: September 2024

Unmanned aerial vehicles (UAVs) with cameras offer extensive monitoring capabilities and exceptional maneuverability, making them ideal for real-time ship detection and effective ship management. However, ship detection by camera-equipped UAVs faces challenges when it comes to multi-viewpoints, multi-scales, environmental variability, and dataset scarcity. To overcome these challenges, we proposed a data augmentation method based on stable diffusion to generate new images for expanding the dataset. Additionally, we improve the YOLOv8n OBB model by incorporating the BiFPN structure and EMA module, enhancing its ability to detect multi-viewpoint and multi-scale ship instances. Through multiple comparative experiments, we evaluated the effectiveness of our proposed data augmentation method and the improved model. The results indicated that our proposed data augmentation method is effective for low-volume datasets with complex object features. The YOLOv8n-BiFPN-EMA OBB model we proposed performed well in detecting multi-viewpoint and multi-scale ship instances, achieving the mAP (@0.5) of 92.3%, the mAP (@0.5:0.95) of 77.5%, a reduction of 0.8 million in model parameters, and a detection speed that satisfies real-time ship detection requirements.
One-Dimensional ZnO Nanorod Array Grown on Ag Nanowire Mesh/ZnO Composite Seed Layer for H2 Gas Sensing and UV Detection Applications
Authors: Wang Fang-Hsing , Li An-Jhe , Liu Han-Wen , Kang Tsung-Kuei
Published: September 2024

Photodetectors and gas sensors are vital in modern technology, spanning from environmental monitoring to biomedical diagnostics. This paper explores the UV detection and gas sensing properties of a zinc oxide (ZnO) nanorod array (ZNA) grown on silver nanowire mesh (AgNM) using a hydrothermal method. We examined the impact of different zinc acetate precursor concentrations on their properties. Results show the AgNM forms a network with high transparency (79%) and low sheet resistance (7.23 Ω/□). A sol–gel ZnO thin film was coated on this mesh, providing a seed layer with a hexagonal wurtzite structure. Increasing the precursor concentration alters the diameter, length, and area density of ZNAs, affecting their performance. The ZNA-AgNM-based photodetector shows enhanced dark current and photocurrent with increasing precursor concentration, achieving a maximum photoresponsivity of 114 A/W at 374 nm and a detectivity of 6.37 × 1014 Jones at 0.05 M zinc acetate. For gas sensing, the resistance of ZNA-AgNM-based sensors decreases with temperature, with the best hydrogen response (2.71) at 300 °C and 0.04 M precursor concentration. These findings highlight the potential of ZNA-AgNM for high-performance UV photodetectors and hydrogen gas sensors, offering an alternative way for the development of future sensing devices with enhanced performance and functionality.
Designing of Airspeed Measurement Method for UAVs Based on MEMS Pressure Sensors
Authors: Chen Zhipeng , Li Haojie , Yu Hang , Zhao Yuan , Ma Jing , Zhang Chuanhao , Zhang He
Published: September 2024

Airspeed measurement is crucial for UAV control. To achieve accurate airspeed measurements for UAVs, this paper calculates airspeed data by measuring changes in air pressure and temperature. Based on this, a data processing method based on mechanical filtering and the improved AR-SHAKF algorithm is proposed to indirectly measure airspeed with high precision. In particular, a mathematical model for an airspeed measurement system was established, and an installation method for the pressure sensor was designed to measure the total pressure, static pressure, and temperature. Secondly, the measurement principle of the sensor was analyzed, and a metal tube was installed to act as a mechanical filter, particularly in cases where the aircraft has a significant impact on the gas flow field. Furthermore, a time series model was used to establish the sensor state equation and the initial noise values. It also enhanced the Sage–Husa adaptive filter to analyze the unavoidable error impact of initial noise values. By constraining the range of measurement noise, it achieved adaptive noise estimation. To validate the superiority of the proposed method, a low-complexity airspeed measurement device based on MEMS pressure sensors was designed. The results demonstrate that the airspeed measurement device and the designed velocity measurement method can effectively calculate airspeed with high measurement accuracy and strong interference resistance.
A Machine Learning Approach for Path Loss Prediction Using Combination of Regression and Classification Models
Authors: Iliev Ilia , Velchev Yuliyan , Petkov Peter Z. , Bonev Boncho , Iliev Georgi , Nachev Ivaylo
Published: September 2024

One of the key parameters in radio link planning is the propagation path loss. Most of the existing methods for its prediction are not characterized by a good balance between accuracy, generality, and low computational complexity. To address this problem, a machine learning approach for path loss prediction is presented in this study. The novelty is the proposal of a compound model, which consists of two regression models and one classifier. The first regression model is adequate when a line-of-sight scenario is fulfilled in radio wave propagation, whereas the second one is appropriate for non-line-of-sight conditions. The classification model is intended to provide a probabilistic output, through which the outputs of the regression models are combined. The number of used input parameters is only five. They are related to the distance, the antenna heights, and the statistics of the terrain profile and line-of-sight obstacles. The proposed approach allows creation of a generalized model that is valid for various types of areas and terrains, different antenna heights, and line-of-sight and non line-of-sight propagation conditions. An experimental dataset is provided by measurements for a variety of relief types (flat, hilly, mountain, and foothill) and for rural, urban, and suburban areas. The experimental results show an excellent performances in terms of a root mean square error of a prediction as low as 7.3 dB and a coefficient of determination as high as 0.702. Although the study covers only one operating frequency of 433 MHz, the proposed model can be trained and applied for any frequency in the decimeter wavelength range. The main reason for the choice of such an operating frequency is because it falls within the range in which many wireless systems of different types are operating. These include Internet of Things (IoT), machine-to-machine (M2M) mesh radio networks, power efficient communication over long distances such as Low-Power Wide-Area Network (LPWAN)—LoRa, etc.
A Statistical Methodology for Evaluating Asymmetry after Normalization with Application to Genomic Data
Authors: Leiva Víctor , Corzo Jimmy , Vergara Myrian E. , Ospina Raydonal , Castro Cecilia
Published: September 2024

This study evaluates the symmetry of data distributions after normalization, focusing on various statistical tests, including a few explored test named Rp. We apply normalization techniques, such as variance stabilizing transformations, to ribonucleic acid sequencing data with varying sample sizes to assess their effectiveness in achieving symmetric data distributions. Our findings reveal that while normalization generally induces symmetry, some samples retain asymmetric distributions, challenging the conventional assumption of post-normalization symmetry. The Rp test, in particular, shows superior performance when there are variations in sample size and data distribution, making it a preferred tool for assessing symmetry when applied to genomic data. This finding underscores the importance of validating symmetry assumptions during data normalization, especially in genomic data, as overlooked asymmetries can lead to potential inaccuracies in downstream analyses. We analyze postmortem lateral temporal lobe samples to explore normal aging and Alzheimer’s disease, highlighting the critical role of symmetry testing in the accurate interpretation of genomic data.
Tomato Plant Residues, a Sustainable Fiber Source for Cardboard Packaging
Authors: Gregor-Svetec Diana , Vodnik Žan , Gale Tea , Kavčič Urška
Published: September 2024

Cardboard packaging is a good example of sustainable material use, yet even more sustainable solutions are available, such as replacing wood fibers with those from alternative sources like agricultural waste. In our research, we produced paperboard from fibers obtained from waste tomato stems using a pilot paper machine, and its basic, surface, and mechanical properties were then determined. Additionally, we produced corrugated cardboard from the tomato fiber-based paperboard and analyzed its performance under different environmental conditions. A comparative analysis was made with commercial corrugated cardboard to determine the differences in mechanical properties and the quality of the prints made using the flexographic printing technique. The results indicated that the properties of tomato fiber-based paperboard and corrugated cardboard are sufficient for many packaging applications. Analyses showed that the mechanical properties of both commercial and corrugated cardboard produced from tomato stems were affected by the environmental conditions, while the change in print quality was minor. Exposure to high humidity had a much greater effect than exposure to low temperature. High humidity lowered the tensile and bursting strength and resistance to compression, resulting in decreased strength and stiffness, while low temperature had a less severe effect. Nevertheless, corrugated cardboard made from tomato-based paperboard can be used for storage of fresh produce locally, as well as for transport packaging, provided the transport box is designed to address its poor stacking strength. The print quality of this cardboard is also suitable for transport packaging, and the readability of the UHF RFID tags remains satisfactory. The findings of this study have significant implications for the development of sustainable materials. The successful use of tomato stems, a waste product from agriculture, in the production of corrugated cardboard supports the circular economy by turning waste into a valuable resource.
Environmental Life Cycle Assessment of Innovative Ejectors Plant Technology for Sediment By-Pass in Harbours and Ports
Authors: Pellegrini Marco , Saccani Cesare , Guzzini Alessandro
Published: September 2024

Sedimentation is the natural process of sediment transportation and deposition in quiescent water conditions. Sedimentation can affect the functionality of ports, harbours and navigation channels by reducing water depth, making navigation difficult, if not impossible. Different solutions are available to guarantee infrastructure functionality against sedimentation, with maintenance dredging being the most widely adopted. Alternative technologies for dredging have been developed and tested to reduce the environmental concerns related to dredging operations. Among other solutions, applying a sediment by-pass system based on a jet pump emerged as one of the most promising. While the existing literature covers the techno-economic aspects of sediment by-pass systems, the environmental impacts must be better evaluated and assessed. This paper aims to resolve this gap by evaluating, through the ReCiPe2016 life cycle assessment (LCA) methodology, the environmental impact of an innovative sediment by-pass system called an “ejectors plant”. The LCA results are based on the demonstrator established in Cervia Harbour in Italy, which was extensively monitored for 15 months during its operation. This paper shows how energy consumption during the operation phase highly affects the considered midpoint and endpoint categories. For example, the GWP100 of the ejectors plant, considering the Italian electricity mix, equals 1.75 million tons of equivalent CO2 over 20 years, while under a low-carbon scenario, it is reduced to 0.17. In that case, material consumption in the construction phase becomes dominant, thus highlighting the importance of eco-innovation of ejectors plants to minimise oxidant formation. Finally, this paper compares the ejectors plant and traditional dredging through environmental LCA. The ejectors plant had a lower impact in all categories except for GWP-related categories. The sensitivity analysis showed how such a conclusion may be mitigated by considering different electricity mixes and maintenance dredging working cycles.
How Do the Representatives of Small and Micro Restaurants Perceive Food Waste in Their Own Restaurant? Empirical Evidence from The Netherlands
Authors: Masurel Enno , van Montfort Kees , Nederhorst Anne
Published: September 2024

The focus of this paper is on the generation of food waste by small and micro restaurants, specifically on the perceptions of representatives of these restaurants. Do they perceive this generation of food waste as problematic, and do they perceive that they have enough knowledge about how to minimize this generated food waste? With data from a sample of 200 Dutch restaurants, which were collected through surveys and analyzed with regression analysis, we came to two key findings. The first key finding is that our respondents hardly perceive the food waste that is generated in their own restaurant as problematic. The second key finding is that they perceive they have limited knowledge about how to minimize the food waste that is generated in their own restaurant. The main influencing factor for both perceptions appeared to be the actual level of food waste generated in their own restaurant. This paper continues with a number of recommendations for future research, to apply other research techniques and to study other sectors as well. The paper ends with practical recommendations for the representatives of the small and micro restaurants, as the findings of this paper suggest a need for targeted educational and training programs to enhance food waste management in their restaurants, contributing to broader sustainability goals.
Spatiotemporal Variations in MODIS EVI and MODIS LAI and the Responses to Meteorological Drought across Different Slope Conditions in Karst Mountain Regions
Authors: Yang Mei , He Zhonghua , Pi Guining , You Man
Published: September 2024

Based on monthly MODIS EVI and LAI data from 2001 to 2020, combined with the Standardized Precipitation Evapotranspiration Index (SPEI), this study employs Theil–Sen trend analysis, Mann–Kendall (MK) test, Hurst index analysis, and correlation analysis to comparatively analyze the overall vegetation trends, spatial distribution characteristics, and future trends of different vegetation types in Guizhou Province under varying slope conditions. The study also explores the response of vegetation to SPEI at different time scales across different slopes. The results indicate the following: (1) From 2001 to 2020, the average values of EVI (0.34%/a) and LAI (1.4%/a) during the growing season exhibited an increasing trend, with the improved vegetation areas primarily concentrated in the western region of Guizhou, while the degradation areas were mainly located in the central and eastern regions. (2) Under different slope conditions, EVI generally showed slight improvement, while LAI exhibited significant improvement, with dry-lands experiencing the largest changes. Future trends indicate continuous improvement, but the proportion of vegetation improvement area decreases with increasing slope. When the slope is less than 5°, the proportion of vegetation improvement area is the highest. (3) The positive correlation between EVI, LAI, and SPEI at different time scales is stronger than the negative correlation, with the strongest correlations observed when the slope is less than 5°. When the slope exceeds 35°, the relationship between vegetation and drought response is almost unaffected by the slope. These findings provide a scientific basis for vegetation growth monitoring and the study of climate change and vegetation interactions in Guizhou Province.
Bi-Objective Inventory Policy with Comprehensive Environmental Factors Formulation and Service Level Constraints
Authors: Giacomelli Marco , Pilati Francesco , Brunelli Matteo
Published: September 2024

As firms and consumers engage with environmental issues, decisions for inventory control need to entail this perspective of sustainability. Most green inventory models employ methods such as carbon caps or taxes for dealing with environmental sustainability. This problem can be more generally tackled via an explicit estimation of the environmental drivers of maintaining inventory in a warehouse, paired with the economic perspective within a transparent multi-objective optimization framework. With this goal, this paper builds on a detailed estimation of environmental and cost factors for a continuous-review inventory policy. The bi-objective problem is tackled by keeping the objective functions separate. In particular, the modeling of greenhouse gas emission or cost performance factors for the inventory encompasses factors that can depend on the decision variables, taking into account aspects such as warehouse location, building characterization, energy usage, and transport requirements. The effects of the emission drivers on the multi-objective optimization decisions are analyzed, considering that the problem can be constrained by multiple service level measures. Stockout response can be multifaceted and different service level measures capture different aspects of inventory shortages, affecting the resulting efficient solutions differently. The results highlight the impact of aspects such as warehouse location and supply capacity on solutions for the multi-objective inventory problem. Managerial decisions are thus influenced by warehousing and supply attributes via a traceable link to specific cost and emission determinants.
Meralgia Paresthetica: Neurolysis or Neurectomy?
Authors: Carrassi Erika , Basso Elisabetta , Maistrello Lorenzo , Zanette Giampietro , Ferraresi Stefano
Published: September 2024

Meralgia paresthetica is a compressive neuropathy of the lateral femoral cutaneous nerve. Surgery is the gold standard for severe cases. However, no high-quality evidence exists on which strategy is best: decompression or neurectomy. Data of a consecutive series of 52 patients treated for meralgia paresthetica over 25 years (1997–2022) were retrospectively collected from medical records and telephone interviews. In total, 27 women and 25 men were operated on; 11 patients had iatrogenic meralgia paresthetica. Decompression was performed on 47 patients, and neurectomy in 8 cases (5 primary neurectomies plus 3 failed neurolysis). Out of the patients who underwent decompression, 41 (87.2%) benefited from the treatment; 3 had pain relief, but no benefit on paresthesia; and 3 reported pain persistence. The latter required neurectomy to resolve symptoms. The eight patients who underwent neurectomy experienced symptom relief but had an obvious anesthetic area persisting over years. Complications were rare (3.8%): a groin hematoma in the post-operative course and an inguinal herniation 6 months after surgery. Surgery, be it neurolysis or neurectomy, offers excellent results with low risks. Decompression has been proven to be adequate in almost all patients, avoiding the side effects of neurectomy. The latter should be confined to failed decompression or to iatrogenic meralgia.
Radiomic Analysis of Treatment Effect for Patients with Radiation Necrosis Treated with Pentoxifylline and Vitamin E
Authors: Patel Jimmy S. , Salari Elahheh , Chen Xuxin , Switchenko Jeffrey , Eaton Bree R. , Zhong Jim , Yang Xiaofeng , Shu Hui-Kuo G. , Sudmeier Lisa J.
Published: September 2024

Background: The combination of oral pentoxifylline (Ptx) and vitamin E (VitE) has been used to treat radiation-induced fibrosis and soft tissue injury. Here, we review outcomes and perform a radiomic analysis of treatment effects in patients prescribed Ptx + VitE at our institution for the treatment of radiation necrosis (RN). Methods: A total of 48 patients treated with stereotactic radiosurgery (SRS) had evidence of RN and had MRI before and after starting Ptx + VitE. The radiation oncologist’s impression of the imaging in the electronic medical record was used to score response to treatment. Support Vector Machine (SVM) was used to train a model of radiomics features derived from radiation necrosis on pre- and 1st post-treatment T1 post-contrast MRIs that can classify the ultimate response to treatment with Ptx + VitE. Results: A total of 43.8% of patients showed evidence of improvement, 18.8% showed no change, and 25% showed worsening RN upon imaging after starting Ptx + VitE. The median time-to-response assessment was 3.17 months. Nine patients progressed significantly and required Bevacizumab, hyperbaric oxygen therapy, or surgery. Patients who had multiple lesions treated with SRS were less likely to show improvement (p = 0.037). A total of 34 patients were also prescribed dexamethasone, either before (7), with (16), or after starting (11) treatment. The use of dexamethasone was not associated with an improved response to Ptx + VitE (p = 0.471). Three patients stopped treatment due to side effects. Finally, we were able to develop a machine learning (SVM) model of radiomic features derived from pre- and 1st post-treatment MRIs that was able to predict the ultimate treatment response to Ptx + VitE with receiver operating characteristic (ROC) area under curve (AUC) of 0.69. Conclusions: Ptx + VitE appears safe for the treatment of RN, but randomized data are needed to assess efficacy and validate radiomic models, which may assist with prognostication.
Uptake, Elimination and Metabolism of Brominated Dibenzofurans in Mice
Authors: Tue Nguyen Minh , Kimura Eiki , Maekawa Fumihiko , Goto Akitoshi , Uramaru Naoto , Kunisue Tatsuya , Suzuki Go
Published: September 2024

Polybrominated dibenzofurans (PBDFs) are major brominated dioxins in the environment, but information on their bioaccumulation potential and toxicokinetics is limited. This study conducted oral exposure experiments with C57BL/6J mice to investigate the uptake ratios, distribution in the liver, plasma and brain, metabolism, and elimination kinetics of four bromine/chlorine-substituted dibenzofurans (TrBDF: 2,3,8-tribromo, TeBDF: 2,3,7,8-tetrabromo, PeBDF: 1,2,3,7,8-pentabromo, TrBCDF: 2,3,7-tribromo-8-chloro) in comparison with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). The hepatic uptake ratios of 2,3,7,8-substituted dibenzofurans were lower than that of TCDD (up to 84% of the administered doses) and decreased with the number of Br substitutions (42%, 33%, and 29% for TrBCDF, TeBDF, and PeBDF, respectively). The brain uptake ratios of these dibenzofurans were less than 0.05%, and the plasma-to-brain transfer ratio also decreased with the Br number. All 2,3,7,8-substituted compounds were eliminated from the liver following first-order kinetics, with half-times in the order of TrBCDF (5.6 days) < TeBDF (8.8 days) ≈ TCDD (8.7 days) < PeBDF (13 days). The non-2,3,7,8-substituted TrBDF was poorly retained in the liver (<0.01% of the dose at 1 day) and rapidly eliminated following two-phase kinetics. All dibenzofurans were metabolised into monohydroxylated products in the liver, but the contribution of this metabolic pathway to hepatic elimination was only significant for TrBDF. As the toxic effects of dioxin-like compounds are influenced by their biological persistence, the slow elimination of TrBCDF, TeBDF, and PeBDF observed in this study suggests that exposure risk of brominated dibenzofurans may be underestimated using the toxic equivalency factors of the less persistent chlorinated analogues.
The Divergent Effect of Different Infant Vaccination Schedules of the 13-Valent Pneumococcal Conjugate Vaccine on Serotype-Specific Immunological Memory
Authors: Tzovara Irene , Papadatou Ioanna , Tzanoudaki Marianna , Piperi Christina , Kanaka-Gantenbein Christina , Spoulou Vana
Published: September 2024

Pneumococcal vaccination schedules are traditionally assessed based on the antibody response. The Memory B Cell (MBC) response has been less studied, despite its role in the magnitude and longevity of protection. We compared the immune response to different vaccination schedules with the 13-valent Pneumococcal Conjugate Vaccine (PCV13) and investigated the relationship between MBCs and the antibody response. Total and pneumococcal serotype (PS)-specific MBCs, their subsets and PS-specific IgG antibodies induced by a 3 + 0 (group A), 2 + 1 (group B) or 3 + 1 (group C) schedule in healthy infants were studied before and 1 month after the last PCV13. The relatively immature IgM+IgD+ MBC subset was the predominant subset in all groups but was larger in group A compared to group B and group C, indicating that age might be a significant parameter of the composition of the MBC pool. PS-specific MBCs at baseline were higher in group A, but they increased significantly only in the groups receiving the booster schedules (groups B and C). PS-specific IgM-only MBCs at baseline positively corelated with the antibody response and the PS-specific swIg MBCs post-immunization. Our findings illustrate the importance of a booster dose for the enrichment of PS-specific immunological memory. IgM-only MBCs and swIg MBCs may serve as additional correlates of vaccine-induced protection.
Effects of Rotavirus NSP4 on the Immune Response and Protection of Rotavirus-Norovirus Recombinant Subunit Vaccines in Different Immune Pathways
Authors: Hu Jingping , Wu Jinyuan , Cao Han , Luan Ning , Lin Kangyang , Zhang Haihao , Gao Dandan , Lei Zhentao , Li Hongjun , Liu Cunbao
Published: September 2024

Diarrheal disease continues to be a major cause of global morbidity and mortality among children under 5 years of age. To address the current issues associated with oral attenuated rotavirus vaccines, the study of parenteral rotavirus vaccines has promising prospects. In our previous study, we reported that rotavirus nonstructural protein 4 (NSP4) did not increase the IgG antibody titer of co-immune antigen but did have a protective effect against diarrhea via the intramuscular injection method. Here, we explored whether NSP4 can exert adjuvant effects on mucosal immune pathways. In this study, we immunized mice via muscle and nasal routes, gavaged them with the rotavirus Wa strain or the rotavirus SA11 strain, and then tested the protective effects of immune sera against both viruses. The results revealed that the serum-specific VP8* IgG antibody titers of the mice immunized via the nasal route were much lower than those of the mice immunized by intramuscular injection, and the specific IgA antibodies were almost undetectable in the bronchoalveolar lavage fluid (BALF). NSP4 did not increase the titer of specific VP8* antibodies in either immune pathway. Therefore, in the two vaccines (PP-NSP4-VP8* and PP-VP8*+NSP4) used in this study, NSP4 was unable to perform its potential adjuvant role through the mucosal immune pathway. Instead, NSP4 was used as a co-immunized antigen to stimulate the mice to produce specific binding antibodies that play a protective role against diarrhea.