bluuebunny/crossref_metadata_2025 huggingface dataset:
Manufacturing Technologies of Polymer Composites—A Review
Authors: Wu Chenchen , Xu Fan , Wang Huixiong , Liu Hong , Yan Feng , Ma Chao
Published: February 2023

Polymer composites have been widely used in the aviation, aerospace, automotive, military, medical, agricultural and industrial fields due to their excellent mechanical properties, heat resistance, flame retardant, impact resistance and corrosion resistance. In general, their manufacturing process is one of the key factors affecting the life cycle of polymer composites. This article provides an overview of typical manufacturing technologies, including surface coating, additive manufacturing and magnetic pulse powder compaction, which are normally used to reduce the failure behaviour of polymer composites in service so that the quality of composite products can be improved. Advanced polymer composite powder manufacturing processes, the processing mechanism and experimental methods are described, and the influence of different manufacturing processes on the moulding quality is revealed. This investigation can provide suitable methods for the selection of manufacturing technology to improve the quality of polymer composite products.
The Energy Absorption Behavior of 3D-Printed Polymeric Octet-Truss Lattice Structures of Varying Strut Length and Radius
Authors: Bolan Matthew , Dean Mackenzie , Bardelcik Alexander
Published: February 2023

We investigate the compressive energy absorption performance of polymeric octet-truss lattice structures that are 3D printed using high-resolution stereolithography. These structures are potential candidates for personal protective equipment, structural, and automotive applications. Two polymeric resins (high-strength/low-ductility and moderate-strength/high-ductility) were used in this work, and a comprehensive uniaxial tensile characterization was conducted to establish an optimal UV curing time. The external octet-truss structure geometry (3″ × 3″ × 3″) was maintained, and four different lattice cell densities (strut length, L) and three different strut radii (R) were printed, UV cured, and compression tested. The compressive stress–strain and energy absorption (EA) behavior were quantified, and the EA at 0.5 strain for the least dense and smallest R structure was 0.02 MJ/m3, while the highest density structure with the largest R was 1.80 MJ/m3 for Resin 2. The structural failure modes varied drastically based on resin type, and it was shown that EA and deformation behavior were related to L, R, and the structures’ relative density (ρ¯). For the ductile resin, an empirical model was developed to predict the EA vs. compressive strain curves based on L and R. This model can be used to design an octet-truss lattice structure based on the EA requirements of an application.
Electrospun Cyclodextrin/Poly(L-lactic acid) Nanofibers for Efficient Air Filter: Their PM and VOC Removal Efficiency and Triboelectric Outputs
Authors: Wanwong Sompit , Sangkhun Weradesh , Jiamboonsri Pimsumon
Published: February 2023

In this work, PLLA and CD/PLLA nanofibers were fabricated using electrospinning and utilized as a particulate matter (PM) and volatile organic compounds (VOCs) filter. The electrospun PLLA and CD/PLLA were characterized with various techniques, including SEM, BET, FTIR, XRD, XPS, WCA, DSC, tensile strength testing, PM and VOCs removal efficiency, and triboelectric performance. The results demonstrated that the best air filter was 2.5 wt%CD/PLLA, which performed the highest filtration efficiencies of 96.84 ± 1.51% and 99.38 ± 0.43% for capturing PM2.5 and PM10, respectively. Its PM2.5 removal efficiency was 16% higher than that of pure PLLA, which were contributed by their higher surface area and porosity. These 2.5 wt%CD/PLLA nanofibers also exhibited the highest and the fastest VOC entrapment. For triboelectric outputs, the 2.5 wt%CD/PLLA-based triboelectric nanogenerator provided the highest electrical outputs as 245 V and 84.70 μA. These give rise to a three-fold enhancement of electrical outputs. These results indicated that the 2.5 wt%CD/PLLA can improve surface charge density that could capture more PM via electrostatic interaction under surrounding vibration. Therefore, this study suggested that 2.5 wt%CD/PLLA is a good candidate for a multifunction nanofibrous air filter that offers efficient PM and VOC removal.
Polymer Membrane Modified with Photocatalytic and Plasmonic Nanoparticles for Self-Cleaning Filters
Authors: Burko Aliaksandr , Zavatski Siarhei , Baturova Arina , Kholiboeva Makhina , Kozina Julia , Kravtsunova Kseniya , Popov Vladimir , Gudok Artem , Dubkov Sergey , Khartov Stanislav , Bandarenka Hanna
Published: February 2023

In this study, we developed a filtering material for facial masks, which is capable of trapping and subsequent inactivation of bacteria under white light emitting diodes (LED) or sunlight irradiation. Such a functionality is achieved via the modification of the composite membrane based on porous polymer with photocatalytic (TiO2) and plasmonic (Ag) nanoparticles. The porous polymer is produced by means of a computer numerical control machine, which rolls a photoresist/thermoplastic mixture into a ~20-µm-thick membrane followed by its thermal/ultraviolet (UV) hardening and porosification. TiO2 nanoparticles are prepared by hydrothermal and sol-gel techniques. Colloidal synthesis is utilized to fabricate Ag nanoparticles. The TiO2 photocatalytic activity under UV excitation as well as a photothermal effect generated by plasmonic Ag nanoparticles subjected to LED irradiation are studied by the assessment of methylene blue (MB) decomposition. We demonstrate that, in contrast to the filter of the standard facial medical mask, the polymer membrane modified with spray-coated TiO2 and Ag nanoparticles prevents the penetration of bacillus subtilis from its top to bottom side and significantly inhibits bacterial growth when exposed to LED or sunlight.
An Overview of the Measurement of Permeability of Composite Reinforcements
Authors: Dei Sommi Andrea , Lionetto Francesca , Maffezzoli Alfonso
Published: February 2023

Liquid composite molding (LCM) is a class of fast and cheap processes suitable for the fabrication of large parts with good geometrical and mechanical properties. One of the main steps in an LCM process is represented by the filling stage, during which a reinforcing fiber preform is impregnated with a low-viscosity resin. Darcy’s permeability is the key property for the filling stage, not usually available and depending on several factors. Permeability is also essential in computational modeling to reduce costly trial-and-error procedures during composite manufacturing. This review aims to present the most used and recent methods for permeability measurement. Several solutions, introduced to monitor resin flow within the preform and to calculate the in-plane and out-of-plane permeability, will be presented. Finally, the new trends toward reliable methods based mainly on non-invasive and possibly integrated sensors will be described.
Removal Efficiency of Insoluble β-Cyclodextrin Polymer from Water–Soluble Carcinogenic Direct Azo Dyes
Authors: Moulahcene Lamia , Skiba Mohamed , Milon Nicolas , Fadila Hammache , Bounoure Frédéric , Lahiani-Skiba Malika
Published: February 2023

A batch system was applied to study the adsorption of three dyes (methyl violet, eriochrom black T and helianthin) from aqueous solution onto β-cyclodextrin polymer, synthesized by using citric acid as a cross linking agent. This polymer lets to adsorb only methyl violet for this effect, several operator variables was checked only with this kind of dye, the removal efficiently increases with increase in adsorbent amount; elevation of temperature lets also to improve the dye adsorption; ionic strength has not effect on dye adsorption process, for the pH we have remarked a slight decrease in removal efficiently with increasing of pH values. Equilibrium study was investigated by applying three models (Langumir, Frendlich and Temkin), results show that Langumir isotherm is the appropriate model. FTIR spectra show the complex inclusion formation which dominates the adsorption mechanism, confirmed by the absence of characteristic peaks of methyl violet in ß-cyclodextrin after adsorption.
Prediction of Molecular Weight of Petroleum Fluids by Empirical Correlations and Artificial Neuron Networks
Authors: Stratiev Dicho , Sotirov Sotir , Sotirova Evdokia , Nenov Svetoslav , Dinkov Rosen , Shishkova Ivelina , Kolev Iliyan Venkov , Yordanov Dobromir , Vasilev Svetlin , Atanassov Krassimir , Simeonov Stanislav , Palichev Georgi Nikolov
Published: February 2023

The exactitude of petroleum fluid molecular weight correlations affects significantly the precision of petroleum engineering calculations and can make process design and trouble-shooting inaccurate. Some of the methods in the literature to predict petroleum fluid molecular weight are used in commercial software process simulators. According to statements made in the literature, the correlations of Lee–Kesler and Twu are the most used in petroleum engineering, and the other methods do not exhibit any significant advantages over the Lee–Kesler and Twu correlations. In order to verify which of the proposed in the literature correlations are the most appropriate for petroleum fluids with molecular weight variation between 70 and 1685 g/mol, 430 data points for boiling point, specific gravity, and molecular weight of petroleum fluids and individual hydrocarbons were extracted from 17 literature sources. Besides the existing correlations in the literature, two different techniques, nonlinear regression and artificial neural network (ANN), were employed to model the molecular weight of the 430 petroleum fluid samples. It was found that the ANN model demonstrated the best accuracy of prediction with a relative standard error (RSE) of 7.2%, followed by the newly developed nonlinear regression correlation with an RSE of 10.9%. The best available molecular weight correlations in the literature were those of API (RSE = 12.4%), Goosens (RSE = 13.9%); and Riazi and Daubert (RSE = 15.2%). The well known molecular weight correlations of Lee–Kesler, and Twu, for the data set of 430 data points, exhibited RSEs of 26.5, and 30.3% respectively.
Can Celecoxib Assay in Preclinical Studies Be Improved?
Authors: Mendes Maria , Sousa João , Pais Alberto , Vitorino Carla
Published: February 2023

Celecoxib, a cyclooxygenase-2 inhibitor (COX-2), is attracting considerable interest owing to its potential anticancer activity. The repurposing strategy of this drug, however, requires preclinical assessment involving the use of increasingly improved analytical methods. In this work, a rapid, accurate, precise, and sensitive reversed-phase high-performance liquid chromatography (RP-HPLC) method was developed for the quantification of celecoxib in five mouse matrices (plasma, brain, spleen, liver, and kidney). Chromatographic separation was achieved within 8 min on a reversed-phase C18 column at 35 °C using a mixture of acetonitrile and 2% (v/v) acetic acid (50:50) as mobile phase, at a flow rate of 0.6 mL/min. Celecoxib and curcumin, as the internal standard, were analyzed at 425 nm and 250 nm, respectively. Linearity was observed (r2 ≥ 0.996) in the concentration ranges selected for celecoxib. Overall precision was below 14.9%, and accuracy was between −14.9% and 13.2%. The acceptance criteria specified in FDA and EMA guidelines were met. Celecoxib was reproducibly recovered (≥84%) and showed stability in all biological matrices at room temperature for 24 h. The method was then effectively applied for the quantification of celecoxib to understand in vivo biodistribution following its intraperitoneal administration in mice.
Multi-Dataset Hyper-CNN for Hyperspectral Image Segmentation of Remote Sensing Images
Authors: Liu Li , Awwad Emad Mahrous , Ali Yasser A. , Al-Razgan Muna , Maarouf Ali , Abualigah Laith , Hoshyar Azadeh Noori
Published: February 2023

This research paper presents novel condensed CNN architecture for the recognition of multispectral images, which has been developed to address the lack of attention paid to neural network designs for multispectral and hyperspectral photography in comparison to RGB photographs. The proposed architecture is able to recognize 10-band multispectral images and has fewer parameters than popular deep designs, such as ResNet and DenseNet, thanks to recent advancements in more efficient smaller CNNs. The proposed architecture is trained from scratch, and it outperforms a comparable network that was trained on RGB images in terms of accuracy and efficiency. The study also demonstrates the use of a Bayesian variant of CNN architecture to show that a network able to process multispectral information greatly reduces the uncertainty associated with class predictions in comparison to standard RGB images. The results of the study are demonstrated by comparing the accuracy of the network’s predictions to the images.
Decellularized Porcine Pericardium Enhances Autologous Vascularized Matrix as a Prosthesis for Left Ventricular Full-Wall Myocardial Reconstruction
Authors: Meyer Tanja , Cebotari Serghei , Brandes Gudrun , Hartung Dagmar , Wacker Frank , Theis Monika , Kaufeld Tim , Tudorache Igor , Nolte Ingo , Haverich Axel , Schilling Tobias
Published: February 2023

Regenerative grafts for myocardial reconstruction are often mechanically not stable enough to withstand the left ventricle’s high blood pressure. Hence, decellularized pericardium may serve as a stabilizing structure for biological myocardium prostheses. The efficacy of detergent- and enzyme-based protocols to decellularize porcine pericardium was compared. Then, the decellularized pericardium was employed for a primary cover of a transmural left ventricular defect in minipigs (n = 9). This pericardium patch was applied to mitigate the high-pressure load on an autologous stomach tissue, which was utilized as a regenerative tissue prosthesis. Decellularization of the porcine pericardium with deoxycholic acid (DOA)- and enzyme-based protocols (trypsin/EDTA) removed 90% of the original cells (p < 0.001). The trypsin/EDTA protocol significantly altered the matrix architecture compared to the DOA protocol. There were no infections or clinical signs of graft rejection following the transplantation of the decellularized pericardium and the autologous segment of the stomach in the surviving animals (n = 7). A good left ventricular function could be detected via MRI six months following surgery. The biological integration of the graft into the host’s tissue was found histologically. The stabilization of initially fragile grafts with decellularized pericardium facilitates the application of regenerative myocardial prostheses even on the left ventricle.
Sea Surface Height Estimation from Improved Modified, and Decontaminated Sub-Waveform Retracking Methods over Coastal Areas
Authors: Agar Parisa , Roohi Shirzad , Voosoghi Behzad , Amini Arash , Poreh Davod
Published: February 2023

Coastal zones are challenging areas for sensing by satellite altimeters because reflected signals from non-water surfaces and from calm sea surfaces in small bays and ports inside the radar footprint lead to erroneous powers in return waveforms. Accordingly, these contaminated waveforms do not follow the so-called Brown model in conventional retracking algorithms and fail to derive qualified ranges. Consequently, the estimated water level is erroneous as well. Therefore, selecting an optimized retracker for post-processing waveforms is significantly important to achieve a qualified water level estimation. To find the optimized retracker, we employed a methodology to minimize the effect of erroneous powers on retracked range corrections. To this end, two new approaches were presented, one based on a waveform decontamination method and the other based on a waveform modification method. We considered the first meaningful sub-waveforms in the decontaminated waveforms and in the modified waveforms to be processed with a threshold retracker. To assess their performance, we also retracked the decontaminated and modified full-waveforms. The first meaningful sub-waveform and full-waveform in the original waveforms were retracked to compare the performance of the modified and decontaminated waveform retracking with the original waveform retracking. To compare the results of our sub-waveform retracking algorithms with those of external sub-waveform retracking algorithms, the (Adaptive Leading Edge Sub-waveform) ALES database was also used. In our retracking scenarios, we used the Sentinel-3A SRAL Altimeter to estimate the water levels over the study area within 10 km from the coastlines in both the Persian Gulf and the Bay of Biscay from June 2016 to October 2020. The water levels from processing L2 products were estimated as well. We evaluated our retracking scenarios and L2, as well as the ALES processing results, against the tide gauges. Our analysis showed that within 0–10 km from the coast, the first meaningful sub-waveform of the decontaminated waveforms had the best performance. We reached maximum RMS improvements in this scenario of 53% and 86% over the Persian Gulf and the Bay of Biscay, respectively, in comparison with L2 processing. Over these distances from the coast, the first sub-waveform from the original waveforms and the modified waveforms stayed in the second and third order of performance. The ALES database with an RMS ranging from 13 to 51 cm had a worse performance than all of our sub-waveform retracking scenarios.
A Simplified Coastline Inflection Method for Correcting Geolocation Errors in FengYun-3D Microwave Radiation Imager Images
Authors: Chen Zhuoqi , Xie Jin , Heygster Georg , Chi Zhaohui , Yang Lei , Wu Shengli , Hui Fengming , Cheng Xiao
Published: February 2023

Passive microwave (PMW) sensors are popularly applied to Earth observations. However, the satellite PMW radiometer data sometimes have non-negligible errors in geolocation. Coastline inflection methods (CIMs) are widely used to improve geolocation errors of PMW images. However, they commonly require accuracy satellite flight parameters, which are difficult to obtain by users. In this study, a simplified coastline inflection method (SCIM) is proposed to correct the geolocation errors without demanding for the satellite flight parameters. SCIM is applied to improve geolocation errors of FengYun-3D (FY-3D) Microwave Radiation Imager (MWRI) brightness temperature images from 2018 and 2019. It reduces the geolocation errors of MWRI images to 0.15 pixels in the along-track and cross-track direction. This means reductions of 75% and 86% of the geolocation errors, respectively. The mean brightness temperature differences between the ascending and descending MWRI images are reduced by 34%, demonstrating the improved geolocation accuracy of SCIM. The corrected images are also used to estimate Arctic sea ice concentration (SIC). By comparing with SICs retrieved from the un-corrected images, the root mean square error (RMSE) and mean absolute error (MAE) of the SICs from the corrected images are reduced from 13.7% to 10.2% and 8.9% to 6.9%, respectively. The mean correlation coefficient (R) increases from 0.91 to 0.95. All these results indicate that SCIM can reduce geolocation errors of satellite-based PMW images significantly. As SCIM is very simple and easy to be applied, it could be a useful method for users of PMW images.
Forage Mass Estimation in Silvopastoral and Full Sun Systems: Evaluation through Proximal Remote Sensing Applied to the SAFER Model
Authors: Luns Hatum de Almeida Samira , Brunno Costa Souza Jarlyson , Furlan Nogueira Sandra , Ricardo Macedo Pezzopane José , Heriberto de Castro Teixeira Antônio , Bosi Cristiam , Adami Marcos , Zerbato Cristiano , Carlos de Campos Bernardi Alberto , Bayma Gustavo , Pereira da Silva Rouverson
Published: February 2023

The operational slowness in the execution of direct methods for estimating forage mass, an important variable for defining the animal stocking rate, gave rise to the need for methods with faster responses and greater territorial coverage. In this context, the aim of this study was to evaluate a method to estimate the mass of Urochloa brizantha cv. BRS Piatã in shaded and full sun systems, through proximal sensing applied to the Simple Algorithm for Evapotranspiration Retrieving (SAFER) model, applied with the Monteith Radiation Use Efficiency (RUE) model. The study was carried out in the experimental area of Fazenda Canchim, a research center of Embrapa Pecuária Sudeste, São Carlos, SP, Brazil (21°57′S, 47°50′W, 860 m), with collections of forage mass and reflectance in the silvopastoral systems animal production and full sun. Reflectance data, as well as meteorological data obtained by a weather station installed in the study area, were used as input for the SAFER model and, later, for the radiation use efficiency model to calculate the fresh mass of forage. The forage collected in the field was sent to the laboratory, separated, weighed and dried, generating the variables of pasture total dry mass), total leaf dry mass, leaf and stalk dry mass and leaf area index. With the variables of pasture, in situ, and fresh mass, obtained from SAFER, the training regression model, in which 80% were used for training and 20% for testing the models. The SAFER was able to promisingly express the behavior of forage variables, with a significant correlation with all of them. The variables that obtained the best estimation performance model were the dry mass of leaves and stems and the dry mass of leaves in silvopastoral and full sun systems, respectively. It was concluded that the association of the SAFER model with the proximal sensor allowed us to obtain a fast, precise and accurate forage estimation method.
A Circum-Arctic Monitoring Framework for Quantifying Annual Erosion Rates of Permafrost Coasts
Authors: Philipp Marius , Dietz Andreas , Ullmann Tobias , Kuenzer Claudia
Published: February 2023

This study demonstrates a circum-Arctic monitoring framework for quantifying annual change of permafrost-affected coasts at a spatial resolution of 10 m. Frequent cloud coverage and challenging lighting conditions, including polar night, limit the usability of optical data in Arctic regions. For this reason, Synthetic Aperture RADAR (SAR) data in the form of annual median and standard deviation (sd) Sentinel-1 (S1) backscatter images covering the months June–September for the years 2017–2021 were computed. Annual composites for the year 2020 were hereby utilized as input for the generation of a high-quality coastline product via a Deep Learning (DL) workflow, covering 161,600 km of the Arctic coastline. The previously computed annual S1 composites for the years 2017 and 2021 were employed as input data for the Change Vector Analysis (CVA)-based coastal change investigation. The generated DL coastline product served hereby as a reference. Maximum erosion rates of up to 67 m per year could be observed based on 400 m coastline segments. Overall highest average annual erosion can be reported for the United States (Alaska) with 0.75 m per year, followed by Russia with 0.62 m per year. Out of all seas covered in this study, the Beaufort Sea featured the overall strongest average annual coastal erosion of 1.12 m. Several quality layers are provided for both the DL coastline product and the CVA-based coastal change analysis to assess the applicability and accuracy of the output products. The predicted coastal change rates show good agreement with findings published in previous literature. The proposed methods and data may act as a valuable tool for future analysis of permafrost loss and carbon emissions in Arctic coastal environments.
A TinyML Deep Learning Approach for Indoor Tracking of Assets
Authors: Avellaneda Diego , Mendez Diego , Fortino Giancarlo
Published: February 2023

Positioning systems have gained paramount importance for many different productive sector; however, traditional systems such as Global Positioning System (GPS) have failed to offer accurate and scalable solutions for indoor positioning requirements. Nowadays, alternative solutions such as fingerprinting allow the recognition of the characteristic signature of a location based on RF signal acquisition. In this work, a machine learning (ML) approach has been considered in order to classify the RSSI information acquired by multiple scanning stations from TAG broadcasting messages. TinyML has been considered for this project, as it is a rapidly growing technological paradigm that aims to assist the design and implementation of ML mechanisms in resource-constrained embedded devices. Hence, this paper presents the design, implementation, and deployment of embedded devices capable of communicating and sending information to a central system that determines the location of objects in a defined environment. A neural network (deep learning) is trained and deployed on the edge, allowing the multiple external error factors that affect the accuracy of traditional position estimation algorithms to be considered. Edge Impulse is selected as the main platform for data standardization, pre-processing, model training, evaluation, and deployment. The final deployed system is capable of classifying real data from the installed TAGs, achieving a classification accuracy of 88%, which can be increased to 94% when a post-processing stage is implemented.
A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer
Authors: Brancato Valentina , Brancati Nadia , Esposito Giusy , La Rosa Massimo , Cavaliere Carlo , Allarà Ciro , Romeo Valeria , De Pietro Giuseppe , Salvatore Marco , Aiello Marco , Sangiovanni Mara
Published: February 2023

Breast Cancer (BC) is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. The Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67 antigen are the most examined markers depicting BC heterogeneity and have been shown to have a strong impact on BC prognosis. Radiomics can noninvasively predict BC heterogeneity through the quantitative evaluation of medical images, such as Magnetic Resonance Imaging (MRI), which has become increasingly important in the detection and characterization of BC. However, the lack of comprehensive BC datasets in terms of molecular outcomes and MRI modalities, and the absence of a general methodology to build and compare feature selection approaches and predictive models, limit the routine use of radiomics in the BC clinical practice. In this work, a new radiomic approach based on a two-step feature selection process was proposed to build predictors for ER, PR, HER2, and Ki67 markers. An in-house dataset was used, containing 92 multiparametric MRIs of patients with histologically proven BC and all four relevant biomarkers available. Thousands of radiomic features were extracted from post-contrast and subtracted Dynamic Contrast-Enanched (DCE) MRI images, Apparent Diffusion Coefficient (ADC) maps, and T2-weighted (T2) images. The two-step feature selection approach was used to identify significant radiomic features properly and then to build the final prediction models. They showed remarkable results in terms of F1-score for all the biomarkers: 84%, 63%, 90%, and 72% for ER, HER2, Ki67, and PR, respectively. When possible, the models were validated on the TCGA/TCIA Breast Cancer dataset, returning promising results (F1-score = 88% for the ER+/ER− classification task). The developed approach efficiently characterized BC heterogeneity according to the examined molecular biomarkers.
K-Anonymity Privacy Protection Algorithm for Multi-Dimensional Data against Skewness and Similarity Attacks
Authors: Su Bing , Huang Jiaxuan , Miao Kelei , Wang Zhangquan , Zhang Xudong , Chen Yourong
Published: February 2023

Currently, a significant focus has been established on the privacy protection of multi-dimensional data publishing in various application scenarios, such as scientific research and policy-making. The K-anonymity mechanism based on clustering is the main method of shared-data desensitization, but it will cause problems of inconsistent clustering results and low clustering accuracy. It also cannot defend against several common attacks, such as skewness and similarity attacks at the same time. To defend against these attacks, we propose a K-anonymity privacy protection algorithm for multi-dimensional data against skewness and similarity attacks (KAPP) combined with t-closeness. Firstly, we propose a multi-dimensional sensitive data clustering algorithm based on improved African vultures optimization. More specifically, we improve the initialization, fitness calculation, and solution update strategy of the clustering center. The improved African vultures optimization can provide the optimal solution with various dimensions and achieve highly accurate clustering of the multi-dimensional dataset based on multiple sensitive attributes. It ensures that multi-dimensional data of different clusters are different in sensitive data. After the dataset anonymization, similar sensitive data of the same equivalence class will become less, and it eventually does not satisfy the premise of being theft by skewness and similarity attacks. We also propose an equivalence class partition method based on the sensitive data distribution difference value measurement and t-closeness. Namely, we calculate the sensitive data distribution’s difference value of each equivalence class and then combine the equivalence classes with larger difference values. Each equivalence class satisfies t-closeness. This method can ensure that multi-dimensional data of the same equivalence class are different in multiple sensitive attributes, and thus can effectively defend against skewness and similarity attacks. Moreover, we generalize sensitive attributes with significant weight and all quasi-identifier attributes to achieve anonymous protection of the dataset. The experimental results show that KAPP improves clustering accuracy, diversity, and anonymity compared to other similar methods under skewness and similarity attacks.
Detection of Green Asparagus in Complex Environments Based on the Improved YOLOv5 Algorithm
Authors: Hong Weiwei , Ma Zenghong , Ye Bingliang , Yu Gaohong , Tang Tao , Zheng Mingfeng
Published: February 2023

An improved YOLOv5 algorithm for the efficient recognition and detection of asparagus with a high accuracy in complex environments was proposed in this study to realize the intelligent machine harvesting of green asparagus. The coordinate attention (CA) mechanism was added to the backbone feature extraction network, which focused more attention on the growth characteristics of asparagus. In the neck part of the algorithm, PANet was replaced with BiFPN, which enhanced the feature propagation and reuse. At the same time, a dataset of asparagus in complex environments under different weather conditions was constructed, and the performance variations of the models with distinct attention mechanisms and feature fusion networks were compared through experiments. Experimental results showed that the mAP@0.5 of the improved YOLOv5 model increased by 4.22% and reached 98.69%, compared with the YOLOv5 prototype network. Thus, the improved YOLOv5 algorithm can effectively detect asparagus and provide technical support for intelligent machine harvesting of asparagus in different weather conditions and complex environments.
Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts
Authors: Baleani Alessia , Paone Nicola , Gladines Jona , Vanlanduit Steve
Published: February 2023

The focus of this study is to design a backlit vision instrument capable of measuring surface roughness and to discuss its metrological performance compared to traditional measurement instruments. The instrument is a non-contact high-magnification imaging system characterized by short inspection time which opens the perspective of in-line implementation. We combined the use of the modulation transfer function to evaluate the imaging conditions of an electrically tunable lens to obtain an optimally focused image. We prepared a set of turned steel samples with different roughness in the range Ra 2.4 µm to 15.1 µm. The layout of the instrument is presented, including a discussion on how optimal imaging conditions were obtained. The paper describes the comparison performed on measurements collected with the vision system designed in this work and state-of-the-art instruments. A comparison of the results of the backlit system depends on the values of surface roughness considered; while at larger values of roughness the offset increases, the results are compatible with the ones of the stylus at lower values of roughness. In fact, the error bands are superimposed by at least 58% based on the cases analyzed.
Temperature Compensation for Reusable Piezo Configuration for Condition Monitoring of Metallic Structures: EMI Approach
Authors: Baral Sushmita , Negi Prateek , Adhikari Sailesh , Bhalla Suresh
Published: February 2023

This paper presents a novel algorithm for compensating the changes in conductance signatures of a piezo sensor due to the temperature variation employed in condition monitoring using the electro-mechanical impedance (EMI) approach. It is crucial to consider the changes in an EMI signature due to temperature before using it for comparison with the baseline signature. The shifts in the signature due to temperature can be misinterpreted as damages to the structure, which might also result in a false alarm. In the present study, the compensation values are calculated based on experiments on piezo sensors both in a free boundary condition and in a bonded condition on a metallic host structure. The values were further validated experimentally for damage detection on a large 2D steel plate structure. The variation in first natural frequency values for the unbonded piezo sensor at different temperatures has been used to develop the compensation algorithms. Whereas, in the case of the bonded sensor, the shift in structural peaks has been used. The developed compensation relations showed promising results in damage detection. Lastly, a finite element-based study has also been performed, supporting the experimental findings. The outcome of this study will aid in the compensation of the signatures in the structure due to temperature variation in the conductance signature.
Connections between the Academic Achievement, Vocational Selection, and Careers of Pilots
Authors: Rimša Vytautas , Radzevičienė Aldona , Latvėnas Mantvydas
Published: February 2023

Research demonstrates that a pilot should have specific skills and abilities. Therefore, professional aptitude tests developed by AGAI are used to select the best graduates for the pilot profession. This research investigates the connections between pilots’ academic achievement, vocational selection, and careers. The sample comprises 52 subjects who started studying in 2009, 2010, and 2011. They were evaluated based on their maturity examinations, vocational selection, academic achievement, and professional career. We observed that the average scores for the pilots’ Lithuanian language, mathematics, and physics maturity examinations are statistically significantly higher (p < 0.05) than the average scores of Lithuanian school graduates. The vast majority of the enrolled students completed their studies and began work in their field of specialty. The academic achievement of those working as pilots (a person who has completed 5 years of pilot studies and works as a captain or first officer) differ in that their average scores in physical study subjects are statistically significantly higher. The graduates who received higher study scores during this study show a statistically significant frequency in their employment as pilots (2–4 quartile). These research findings show that academic achievement and vocational selection are characteristics of those who work as pilots.
Field Investigation into Tree Fates from Recent Apple Tree Decline: Abrupt Hydraulic Failure Versus Gradual Hydraulic Loss
Authors: Xu Hao , Hannam Kirsten D. , MacDonald Jesse L. , Ediger Danielle
Published: February 2023

In the last decade, a sporadic tree health syndrome affecting high-density apple plantings in North America has become known as Rapid Apple Decline (RAD) or Sudden Apple Decline (SAD). The affected apple trees were typically grafted on small dwarfing rootstocks, often displayed necrosis at the graft union, and suffered from sudden mortality that occurred over 2–3 weeks amid the growing season or a gradual decline. In 2019 and 2020, we conducted a multi-site investigation in the south Okanagan, British Columbia, Canada, to assess the stem hydraulic characteristics, stomatal conductance, leaf δ13C‰, and fruit dry matter accumulation of the declining trees during disease progression. In trees that died, mortality appeared to be associated with severe disruption in xylem water transport at the damaged graft union, followed by abrupt hydraulic failure. In contrast, symptomatic trees that did not die exhibited the moderately declined plant water relations and a reduction in fruit dry matter accumulation followed by either further deterioration or eventual recovery. This pattern indicates the risk of carbohydrate depletion over gradual hydraulic decline and the importance of timely horticultural remedies. In the present study, we discuss potential horticultural practices to mitigate hydraulic dysfunctions and enhance crop tolerance.
Plant Toxins as Potential Alternatives to Botulinum Toxin for Eye-Movement Disorder Therapy
Authors: Bortolotti Massimo , Zanello Andrea , Serra Lorenzo , Biscotti Francesco , Polito Letizia , Bolognesi Andrea
Published: February 2023

The most successful alternative to traditional surgery for ocular muscle spasm treatment is the intramuscular injection of botulinum toxin (BTX), which allows the maintenance of the muscle dynamics and the absence of scars. However, the main BTX disadvantage is its nonpermanent effect. A possible way for overcoming this obstacle could be represented by the enzymatic surgery using plant toxins known as ribosome-inactivating proteins (RIPs). In this paper, two highly toxic RIPs, namely, ricin and stenodactylin, were considered in a preliminary study for their possible use in the treatment of strabismus and oculofacial dystonias, as alternatives to BTX. Both RIPs showed a strong cytotoxic effect against rhabdomyosarcoma cell lines and myotube differentiated cells, with stenodactylin being about 10-fold more toxic than ricin. Moreover, stenodactylin showed a much higher cytotoxicity on myoblasts than on rhabdomyosarcoma cells. In our experimental conditions, stenodactylin did not damage conjunctival cells. Despite the limitations due to in vitro experiments, our data show that the high cytotoxicity of stenodactylin allows the use of a very low dose and, consequently, of very low injection volumes. This can represent a great advantage in the case of in vivo locoregional treatment. Furthermore, it is possible to modulate the chemoablation of myocytes while destroying myoblasts, thus reducing regenerative phenomena. The risk of cytotoxicity to surrounding tissues would be strongly reduced by the low injected volume and the relative resistance of conjunctival cells. In conclusion, our data suggest that stenodactylin and ricin could represent potential candidates to substitute BTX in ocular dystonia therapy.
The Influence of Geopolitical Risk on International Direct Investment and Its Countermeasures
Authors: Yu Miaozhi , Wang Na
Published: February 2023

Recent years have seen frequent geopolitical conflicts and the world economy has fallen into a recession. In order to explore how wars, terrorist attacks and international tensions affect foreign direct investment (FDI), this paper uses the fixed-effect model to investigate the impact of geopolitical risks on FDI flows in 41 countries during 2003–2020 from the perspective of market seeking, natural resource seeking and strategic resource seeking. The results show that, on the whole, geopolitical risks can significantly inhibit the inflow of foreign direct investment and hinder the development of domestic economy. The market size, natural resources and science and technology of the host country are important factors to attract foreign investment. Trade dependence has a moderating effect on the negative impact of geopolitical risks. Countries that depend on international trade may eliminate geopolitical frictions through economic cooperation. The impact of geopolitical risk is heterogeneous in countries with different levels of economic development. The impact of geopolitical risk on foreign direct investment in developed economies is not significant.
Correction: Rimano et al. The Environmental Impact of Organizations: A Pilot Test from the Packaging Industry Based on Organizational Life Cycle Assessment. Sustainability 2021, 13, 11402
Authors: Rimano Michela , Simboli Alberto , Taddeo Raffaella , Del Grosso Michele , Raggi Andrea
Published: February 2023

The authors would like to make the following corrections about the published paper [...]
Italy vs. Poland: A Comparative Analysis of Regional Planning System Attitudes toward Adaptation to Climate Changes and Green Infrastructures
Authors: Ledda Antonio , Kubacka Marta , Calia Giovanna , Bródka Sylwia , Serra Vittorio , De Montis Andrea
Published: February 2023

European spatial planners deal with two major concerns: adaptation to climate changes (ACC) and the design and management of green infrastructures (GIs). ACC calls for the renewal of spatial planning with constant appeals to the need to adequately prepare for extreme climate events. GIs deliver ecosystem services (ES), which consist of beneficial functions to living beings in terms of, for example, helping people adapt to climate change. An effective implementation of adaptation measures at the regional and sub-regional scale is based on an efficient and prompt spatial planning system and GIs management. In this paper, we aim at comparing the attitudes of Italian and Polish spatial planning systems with respect to the integration of concepts related to ACC and GIs. We describe commonalities and differences between the two spatial planning frameworks by scrutinizing regional plans adopted in Sardinia (Italy) and Wielkopolska (Poland). We found out a scarce consideration of both ACC and GIs planning and management. The findings suggest that the regional spatial planning tools need to be updated to be fully satisfactory in terms of ACC and GIs concepts.
On the Performance of Diffuse Ceiling Ventilation in Classrooms: A Pre-Occupancy Study at a School in Southern Sweden
Authors: Ogbuagu Too-Chukwu Cyracus , Linden Elisabet , MacCutcheon Douglas , Nilsson Erling , Persson Torbjorn , Kabanshi Alan
Published: February 2023

The implementation and application of diffused ceiling ventilation (DCV) is gradually gaining momentum, especially in Denmark, Finland, and the Netherlands. In countries such as Sweden, the application is limited despite the favorable conditions for implementation. The current study investigates the performance of DCV and mixing ventilation in a pre-occupancy field study for newly renovated classrooms in Southern Sweden. Two classrooms at the school were installed with diffuse ceiling ventilation while the rest had mixing ventilation. The objective of the study was to compare and evaluate the ventilation performance in terms of indoor environmental quality parameters such as thermal comfort, air quality indexes, airflow, and temperature distribution. Pre-occupancy measurements were performed in two classrooms with similar room characteristics, with one room running under mixing ventilation and the other under DCV. Constant temperature anemometers, thermocouples, and INNOVA thermal comfort were used to measure the indoor air speeds, temperature, and thermal comfort, respectively. Tracer gas measurements, with SF6, were performed to assess air quality. Additionally acoustic measurements were conducted to assess the acoustic benefits of DCV on reducing ventilation noise. The results demonstrate that DCV offers similar indoor environmental conditions to mixing ventilation but has better acoustic performance especially on reducing the ventilation noise. Indoor environmental conditions were very homogeneous under DCV with mixing ventilation showing tendencies for short circuit ventilation. This study demonstrates that DCV has a potential for implementation in Swedish schools with minimal system modification on existing ventilation and air distribution systems.
Vertical Greenery Systems in Commercial Complexes: Development of an Evaluation Guideline
Authors: Wu Yimeng , Wang Zhendong , Wang Hao
Published: February 2023

Building vertical greenery has become an effective measure to solve the contradiction between the shortage of urban greenery and the increasing demand for greenery. However, the lack of direct economic benefits dampens motivation for its development. As a vital development mode for high-density cities worldwide, commercial complexes are the most appropriate buildings to support greenery because of economic agglomeration and resource integration. An important reason for whether or not commercial complex greenery is constructed is the need for an evaluation system. To bridge this research gap, we propose a holistic evaluation guideline for commercial complex greenery. First, a list of related sustainable rating systems from the academic literature and official websites was compiled and reviewed to identify and compare their referential features. Second, the limitations of these evaluation systems in assessing the greenery of commercial complexes were explored using a case study. Third, the features of commercial complex greenery were introduced through field research and interviews. Finally, a holistic evaluation guideline for vertical greenery systems in commercial complexes was proposed, including logical thinking for the evaluation system of the dimension–indicator–quantitative method, the creation of innovative evaluation indicators, the establishment of a database, the assignment of weights to different dimensions and indicators, and the construction of an evaluation mechanism for the whole life cycle. This research demonstrates the significance of an evaluation process for commercial complex greenery systems, proposes a refined guideline for its development, and rationally grasps the development direction from a macro perspective.
When Event Social Sustainability Is Tarnished by Scandal: Long-Term Community Perceptions of the 2002 Winter Olympics Bid Scandal and Legacy
Authors: June Haylie M. , Kernan Ashley R. , Sumsion Rachel M. , Cope Michael R. , Sanders Scott R. , Ward Carol
Published: February 2023

Due to the increasing number of events around the world, event sustainability is an area of research relevant across disciplines. Research has found that event sustainability encompasses economic, environmental, and social legacies. However, events may face unforeseen challenges, sometimes even major scandals. How do these scandals impact residents and the sustainable legacy of the mega-event? As a historical case study, we explore social aspects of event sustainability in the wake of the 2002 Winter Olympics bid scandal, where it was reported that the Salt Lake Olympic Committee (SLOC) bribed members of the International Olympic Committee (IOC) to secure votes in favor of Salt Lake City hosting the 2002 Winter Olympic. Despite the bribery scandal, the Salt Lake City Games were considered a success by the media and members of the SLOC and IOC. Specifically, the present study investigates local residents’ perceptions of the scandal before, during, and after the Olympics using data gathered from 1999 to 2018 in Heber Valley, Utah. We find that time is a significant predictor of residents’ feelings toward the scandal. Further, feelings towards the Olympics, community desirability, race, and biological sex are also significant predictors. These findings lead us to conclude that the effects of the scandal on the Olympics’ sustainable legacy fade away over time.