bluuebunny/crossref_metadata_2025 huggingface dataset:
Nickel Nanoparticles: Applications and Antimicrobial Role against Methicillin-Resistant Staphylococcus aureus Infections
Authors: Zarenezhad Elham , Abdulabbas Hussein T. , Marzi Mahrokh , Ghazy Esraa , Ekrahi Mohammad , Pezeshki Babak , Ghasemian Abdolmajid , Moawad Amira A.
Published: September 2022

Methicillin-resistant Staphylococcus aureus (MRSA) has evolved vast antibiotic resistance. These strains contain numerous virulence factors facilitating the development of severe infections. Considering the costs, side effects, and time duration needed for the synthesis of novel drugs, seeking efficient alternative approaches for the eradication of drug-resistant bacterial agents seems to be an unmet requirement. Nickel nanoparticles (NiNPs) have been applied as prognostic and therapeutic cheap agents to various aspects of biomedical sciences. Their antibacterial effects are exerted via the disruption of the cell membrane, the deformation of proteins, and the inhibition of DNA replication. NiNPs proper traits include high-level chemical stability and binding affinity, ferromagnetic properties, ecofriendliness, and cost-effectiveness. They have outlined pleomorphic and cubic structures. The combined application of NiNPs with CuO, ZnO, and CdO has enhanced their anti-MRSA effects. The NiNPs at an approximate size of around 50 nm have exerted efficient anti-MRSA effects, particularly at higher concentrations. NiNPs have conferred higher antibacterial effects against MRSA than other nosocomial bacterial pathogens. The application of green synthesis and low-cost materials such as albumin and chitosan enhance the efficacy of NPs for therapeutic purposes.
Impact of Skin Disinfection on Cutaneous Microbiota, before and after Peripheral Venous Catheter Insertion
Authors: Prat Manon , Guenezan Jeremy , Drugeon Bertrand , Burucoa Christophe , Mimoz Olivier , Pichon Maxime
Published: September 2022

Introduction. Patients with invasive medical devices are at high risk for infection. Skin colonization is the initial stage of these infections, leading to the recommendation of practices requiring disinfection using antiseptics. Microbial communities playing a major role in skin health could be impacted by antiseptic procedures. Aim. To characterize and compare the bacterial communities of skin samples from patients before an antisepsis procedure, and after removal of the medical device itself, according to the nature of the antiseptic molecule (povidone iodine or chlorhexidine). Methods. The study focused on alterations in bacterial communities depending on the nature of the antiseptic procedure and type of intravascular device. After amplification of 16S rDNA, libraries (n = 498 samples) were sequenced using MiSeq platform. Results. Using an in-house pipeline (QIIME2 modules), while no alteration in skin microbiota diversity was associated with antiseptic procedure or PVC type, according to culture results (p < 0.05), alterations were at times associated with restricted diversity and higher dissimilarity (p < 0.05). Antiseptic procedures and PVC types were associated with the modification of specific bacterial representations with modulation of the Bacillota/Bacteroidota (Firmicutes/Bacteroidetes) ratio (modulation of C. acnes, Prevotella, Lagierella, and Actinomyces spp.) (p < 0.05). At baseline, the microbiota shows certain bacteria that are significantly associated with future PVC colonization and/or bacteremia (p < 0.05). All of these modulations were associated with altered expression of metabolic pathways (p < 0.05). Discussion. Finally, this work highlights the need to optimize the management of patients requiring intravascular devices, possibly by modulating the skin microbiota.
Exploring the Barriers in the Uptake of the Dutch MRSA ‘Search and Destroy’ Policy Using the Cascade of Care Approach
Authors: Westgeest Annette C. , Schippers Emile F. , Sijbom Martijn , Visser Leo G. , de Boer Mark G. J. , Numans Mattijs E. , Lambregts Merel M. C. ,   on behalf of the MRSA Network Holland West
Published: September 2022

The Dutch ‘search and destroy’ policy consists of screening patients with an increased risk of methicillin-resistant Staphylococcus aureus (MRSA) carriership and subsequent decolonization treatment when carriership is found. Decolonization therapy of individual MRSA carriers is effective. However, the effectiveness of the national ‘search and destroy’ policy is dependent on the entire cascade of care, including identification, referral, and subsequent treatment initiation in MRSA carriers. The aim of this study was to evaluate the leakages in the cascade of MRSA decolonization care. We assessed familiarity with the ‘search and destroy’ policy and the barriers in the uptake of MRSA eradication care using a questionnaire among 114 Dutch general practitioners. The main reasons for treatment were planned hospital visits, occupational reasons, and infections. The main reasons for refraining from eradication treatment were unfamiliarity with the ‘search and destroy’ policy and the assumption that MRSA carriership is often self-limiting. To optimize the continuity of the cascade of care, interventions should be aimed at supporting general practitioners and facilitating treatment and referral.
Vaccinium bracteatum Thunb Extract Inhibits HSV-1 Infection by Regulating ER Stress and Apoptosis
Authors: Kim Buyun , Kwon Eun-Bin , Yang Hye Jin , Li Wei , Hwang Youn-Hwan , Kim Young Soo , Pak Malk Eun , Go Younghoon , Choi Jang-Gi
Published: September 2022

Herpes simplex Type 1 (HSV-1) is a neurotropic virus that infects the peripheral and central nervous system. Usually, after primary infection in epithelial cells, HSV-1 migrates retrograde to the peripheral nervous system (PNS), where it establishes a latent infection. HSV-1 can remain latent in the nervous system, and its reactivation in the brain can rarely cause acute HSV-1 encephalitis, often a life-threatening condition, or asymptomatic reactivations that could lead to neuronal damage and ultimately neurodegenerative disorders. Acyclovir and related nucleoside analogs have been used as therapeutic agents for HSV-1 infection, but resistance to the drug can arise, and the protective effect of HSV-1 on brain cells is limited. Therefore, there is an urgent need for research into safe and effective new antiviral agents that can protect brain cells from the damage that is caused by HSV-1 infection. Vaccinium bracteatum Thunb. (VBT) is widely distributed in Korea and China, and has pharmacological actions such as anti-inflammatory, antioxidant, and antidiabetic activity. Studies on the antiviral effect of VBT on HSV-1 infection have not been reported so far. Therefore, we sought to determine the HSV-1 antiviral effect and molecular mechanism of VBT at the cellular level. We confirmed that VBT repressed the VP16 and IE genes in both Vero and SK-N-SH cells. We also found that the generation of HSV-1 virions was inhibited by VBT treatment. VBT inhibited the activities of the HSV-1-induced endoplasmic reticulum (ER) stressors PERK, ATF4, and CHOP. We confirmed that VBT inhibited the activity of apoptosis factors by regulating the expression of death receptor (DR) after HSV-1 infection. As HSV-1 is closely associated with brain diseases, the study of the antiviral drug effects and mechanism of VBT is meaningful. Further studies using animal models of infection will also be performed to determine the potential of VBT as an antiviral agent.
Methanol Extract of Clavularia inflata Exerts Apoptosis and DNA Damage to Oral Cancer Cells
Authors: Hsu Yin-Yin , Chuang Ya-Ting , Yen Ching-Yu , Cheng Ming-Ya , Chen Ching-Yeu , Cheng Yuan-Bin , Chang Hsueh-Wei
Published: September 2022

Antiproliferation effects of Clavularia-derived natural products against cancer cells have been reported on, but most studies have focused on identifying bioactive compounds, lacking a detailed investigation of the molecular mechanism. Crude extracts generally exhibit multiple targeting potentials for anticancer effects, but they have rarely been assessed for methanol extracts of Clavularia inflata (MECI). This investigation aims to evaluate the antiproliferation of MECI and to examine several potential mechanisms between oral cancer and normal cells. A 24 h MTS assay demonstrated that MECI decreased cell viability in several oral cancer cell lines more than in normal cells. N-acetylcysteine (NAC), an oxidative stress inhibitor, recovered these antiproliferation effects. Higher oxidative stress was stimulated by MECI in oral cancer cells than in normal cells, as proven by examining reactive oxygen species and mitochondrial superoxide. This preferential induction of oxidative stress was partly explained by downregulating more cellular antioxidants, such as glutathione, in oral cancer cells than in normal cells. Consequently, the MECI-generated high oxidative stress in oral cancer cells was preferred to trigger more subG1 population, apoptosis expression (annexin V and caspase activation), and DNA damage, reverted by NAC. In conclusion, MECI is a potent marine natural product showing preferential antiproliferation against oral cancer cells.
Special Issue on Advanced Technologies in Electromagnetic Compatibility
Authors: De Leo Alfredo
Published: September 2022

Electromagnetic Compatibility (EMC) rules the maximum emission levels and the minimum immunity requirements for devices at the scope to ensure their correct interoperability in a real operational environment [...]
Chaos Particle Swarm Optimization Enhancement Algorithm for UAV Safe Path Planning
Authors: Chu Hongyue , Yi Junkai , Yang Fei
Published: September 2022

For safe path planning of unmanned aerial vehicles (UAVs) in a three-dimensional (3D) environment with multiple threats, first, a cost function is introduced according to the terrain constraints and UAV overall performance constraints of the path planning problem. Then, improved nonlinear dynamic inertia weights (INDIW) are introduced into the particle swarm optimization (PSO) algorithm, and when the particles fall into the local optimum, the velocity is perturbed, and the velocity and improved nonlinear dynamic inertia weight PSO (VAINDIWPSO) algorithm are obtained. The algorithm improves the speed of convergence and fitness function value of the PSO algorithm. However, the impact of flyable path optimization is now not obvious. Therefore, to further enhance the overall performance of the VAINDIWPSO algorithm, the adaptive adjustment of the velocity is introduced, the chaotic initialization is carried out, and the improved logistic chaotic map is introduced into the algorithm, and an improved chaotic-VAINDIWPSO (IC-VAINDIWPSO) algorithm is obtained. Then, the corresponding relationship between the algorithm and constraints is used to efficiently search complicated environments and find paths with excessive security and small cost function. The simulation outcomes exhibit that in a complicated environment the IC-VAINDIWPSO algorithm substantially improves the speed of convergence of the algorithm, reduces the fitness function value of the algorithm and the initialization time of the algorithm, and the acquired path is additionally smoother. A near-optimal solution is obtained.
Theoretical and Experimental Investigations on the Ultra-Low-Frequency Broadband of Quasi-Static Metamaterials
Authors: Liu Haixia , He Weitao , Li Lixia , Jia Qi
Published: September 2022

This paper proposes an I-shaped radial elastic metamaterial with ultra-low-frequency broadband characteristics and studies the propagation characteristics of elastic waves in their quasi-static state. Through the calculation of the dispersion relationship, the frequency response function, and the eigenmode displacement field, it is found that the ultra-low-frequency wide band gap can be generated in the quasi-static metamaterial. The wide band gap is mainly caused by modal transitions. The equivalent mass–spring model reveals the modal changes of the I-shaped radial elastic metamaterial under the surface constraints. Furthermore, by studying the directional vibration displacement field of the finite period structure, it is demonstrated that the mechanism of the ultra-low-frequency broadband (0<Reduced frequency(Ω)<0.20) is the local resonance mechanism. Subsequently, the influence of the geometric and the material parameters on the location and width of the band gap is explored numerically. Finally, based on the model, through the hammer modal experiment, it is proven that the quasi-static structure yields an ultra-low-frequency stop band of 0.1–1012 Hz. The research conclusions can be applied to mechanical engineering fields such as ultra-low-frequency vibration reduction.
XLNet-Based Prediction Model for CVSS Metric Values
Authors: Shi Fan , Kai Shaofeng , Zheng Jinghua , Zhong Yao
Published: September 2022

A plethora of software vulnerabilities are exposed daily, posing a severe threat to the Internet. It is almost impossible for security experts or software developers to deal with all vulnerabilities. Therefore, it is imperative to rapidly assess the severity of the vulnerability to be able to select which one should be given preferential attention. CVSS is now the industry’s de facto evaluation standard, which is calculated with a quantitative formula to measure the severity of a vulnerability. The CVSS formula consists of several metrics related to the vulnerability’s features. Security experts need to determine the values of each metric, which is tedious and time-consuming, therefore hindering the efficiency of severity assessment. To address this problem, in this paper, we propose a method based on a pre-trained model for the prediction of CVSS metric values. More specifically, this method utilizes the XLNet model that is fine-tuned with a self-built corpus to predict the metric values from the vulnerability description text, thus reducing the burden of the assessment procedure. To verify the performance of our method, we compare the XLNet model with other pre-trained models and conventional machine learning techniques. The experimental results show that the method outperforms these models on evaluation metrics, reaching state-of-the-art performance levels.
Optimization of the Power Conversion Efficiency of CsPbIxBr3−x-Based Perovskite Photovoltaic Solar Cells Using ZnO and NiOx as an Inorganic Charge Transport Layer
Authors: Son Hyojung , Jeong Byoung-Seong
Published: September 2022

In this study, we analyzed the maximum power conversion efficiency (PCE) of a photovoltaic cell with an ITO/ZnO/CsPbIxBr3−x/NiOx/Au structure, using ZnO and NiOx as the inorganic charge transport layers and CsPbIxBr3−x as an absorption layer. We optimized the thickness of each layer and investigated the effects of the defect density and interface defect density. To achieve the highest PCE, the optimal thicknesses were 300 nm for the electron transport layer (ZnO), 60 nm for the hole transport layer (NiOx), and 1000 nm for the absorption layer. The absorber defect density was maintained at approximately 1015 cm−3, and the interface defect density was approximately 1011 cm−3. The highest PCE obtained through optimization of each of these factors was 23.07%. These results are expected to contribute to the performance optimization of perovskite solar cells that use inorganic charge carrier transport layers.
Applications of Water Jet Cutting Technology in Agricultural Engineering: A Review
Authors: Cui Dandan , Li Hongwen , He Jin , Wang Qingjie , Lu Caiyun , Hu Hongnan , Cheng Xiupei , Wang Chunlei
Published: September 2022

Cutting is a significant part of agricultural material processing, and the cutting technology determines the quality of agricultural products. Water jet cutting technology is a non-contact and cold cutting technology suitable for cutting agricultural materials. It can realize an environmentally friendly cutting process avoiding such problems as heat generation, sharpening and cleaning blades, and microbial cross-contamination. This paper reviews the current status of water jet cutting of six kinds of agricultural materials, including vegetables, fruits, meats, woods, stems, and soils. By analyzing how to complete different cutting operations, improve cutting ability, or control post-cutting influences, the problems and solutions of water jet cutting of each material are summarized. Then, combined with the application requirements, some suggestions are put forward for developing water jet cutting technology. The results would help researchers determine key information required by cutting agricultural materials and provide a reference for further research on water jet cutting technology in agricultural engineering.
Effect of Soil Damping on the Soil–Pile–Structure Interaction Analyses in Cohesionless Soils
Authors: Alver Ozan , Eseller-Bayat Esra Ece
Published: September 2022

Pile foundations in earthquake-prone regions must be analyzed and designed considering the dynamic loads. In the fully nonlinear dynamic analyses, the soil nonlinearity can be considered using the modulus degradation curves in the total-stress approach, and the soil damping is controlled by the unloading/reloading rule. Several researchers have investigated the effect of soil damping on the free-field soil response analyses, but the effect on the soil–pile–structure system response has not been studied thoroughly. In this study, the nonlinear elastic method (hyperbolic model) and the elastoplastic Mohr–Coulomb (MC) models were implemented to investigate the effect of soil damping on the pile and structure response. Dynamic soil–pile–structure interaction analyses were performed by simulating two different centrifuge tests published in the literature, and the analysis results were compared with the centrifuge test results. The analyses with the low-intensity input motions showed that the superstructure accelerations and the bending moments in the single pile were estimated with reasonable accuracy. However, the superstructure accelerations might be underestimated under high-intensity motions, especially in the MC model. Additional analyses were performed under six earthquake records. The constitutive models (MC and hyperbolic) may significantly vary the maximum structural acceleration and pile maximum moments (up to 50%). As a result, the responses of the superstructure and the pile in soil–pile–structure interaction problems are highly dependent on the soil constitutive model that must take the damping into account accurately; in turn, due account must be given to the selection of the constitutive model.
Vibration Reduction of a Timoshenko Beam with Multiple Parallel Nonlinear Energy Sinks
Authors: Zhang Wen-Yong , Niu Mu-Qing , Chen Li-Qun
Published: September 2022

A nonlinear energy sink is a promising device to reduce structural vibrations. In this work, the vibration reduction performances of multiple parallel nonlinear energy sinks attached to a short beam are investigated based on the Timoshenko beam theory. The dynamic equations of a vibration reduction system subjected to a harmonic excitation are established. The frequency responses are analyzed based on Galerkin discretization and the harmonic balance method, and the accuracy is verified by the Runge–Kutta method. An optimization method based on the genetic algorithm is proposed for the number, location, and cubic stiffness of the nonlinear energy sinks. The study reveals that, with the same total mass, multiple parallel nonlinear energy sinks can achieve a larger vibration reduction ratio than a single nonlinear energy sink. The parameter influences of the nonlinear energy sinks are revealed, and unstable responses with large cubic stiffness are presented. The optimal locations of the multiple parallel nonlinear energy sinks are related to low-order modal shapes. A larger reduction ratio on the resonant amplitude can be achieved compared to a uniform distribution of the nonlinear energy sinks. The optimal locations and cubic stiffness are related to the number of nonlinear energy sinks. In the studied case, the optimal number of nonlinear energy sinks was two.
Impact of Concrete Degradation on the Long-Term Safety of a Near-Surface Radioactive Waste Disposal Facility in Korea
Authors: Mutoni Agnes , Kim Juyoul
Published: September 2022

The migration of radionuclides from radioactive waste into the environment poses a public safety concern. Thus, the long-term safety assessment for near-surface disposal sites for radioactive waste in South Korea entails providing reasonable assurance that the annual radiation dose exposure from radionuclide release from the waste repository into the biosphere will not exceed the regulatory limit of 0.1 mSv/yr. At the first near-surface disposal site in Gyeongju, concrete was a crucial component of the engineered barriers designed to contain radionuclides within the disposal site. The ability of concrete to retain radioactive waste within the disposal site is attributed to its high sorption capacity for radionuclides. However, research has shown that the degradation of concrete can affect its radionuclide retention capabilities, which are defined by sorption properties of distribution (Kd) and diffusion (Ds) coefficient parameters. As a result, changes in sorption properties may lead to radionuclides migrating out of the disposal vault. In light of the geochemical deterioration of engineered concrete barriers, this study assesses the long-term safety of near-surface disposal sites. To simulate the impact of concrete degradation on radionuclide migration, we employed RESRAD-OFFSITE’s extended source-term features, which can model the release of radionuclides from radioactive waste shielded by concrete barriers. Using carefully screened published sorption data of four radionuclides (14C, 137Cs, 90Sr and 99Tc) in different stages of concrete degradation, the results indicated that released radioactivity during the most degraded state of concrete will result in a maximum radiation exposure dose of 1.4 × 10−8 mSv/yr from 99Tc which is below the permissible limit of 0.1 mSv per year, thus demonstrating that concrete is a reliable component of the engineered designed barriers for near-surface disposal facilities.
Numerical Investigation of Different Core Topologies in Sandwich-Structured Composites Subjected to Air-Blast Impact
Authors: Walkowiak Marcel , Reinicke Ulf , Anders Denis
Published: September 2022

Air-blast loading is a serious threat to military and civil vehicles, buildings, containers, and cargo. Applications of sandwich-structured composites have attracted increasing interest in modern lightweight design and in the construction of dynamic loading regimes due to their high resistance against blast and ballistic impacts. The functional properties of such composites are determined by the interplay of their face sheet material and the employed core topology. The core topology is the most important parameter affecting the structural behavior of sandwich composites. Therefore, this contribution presents a thorough numerical investigation of different core topologies in sandwich-structured composites subjected to blast loading. Special emphasis is put on prismatic and lattice core topologies displaying auxetic and classical non-auxetic deformation characteristics in order to illustrate the beneficial properties of auxetic core topologies. Their dynamic responses, elastic and plastic deformations, failure mechanisms, and energy absorption capabilities are numerically analyzed and compared. The numerical studies are performed by means of the commercial finite element code ABAQUS/Explicit, including a model for structural failure.
An Efficient Method for Document Correction Based on Checkerboard Calibration Pattern
Authors: Ibrahim Mina , Wagdy Marian , AlHarithi Fahd S. , Qahtani Abdulrahman M. , Elkilani Wail S. , Zarif Sameh
Published: September 2022

Portable digital devices such as PDAs and camera phones are the easiest and most widely used methods to preserve and collect information. Capturing a document image using this method always has warping issues, especially when capturing pages from a book and rolled-up documents. In this article, we propose an effective method to correct the warping of the captured document image. The proposed method uses a checkerboard calibration pattern to calculate the world and image points. A radial distortion algorithm is used to handle the warping problem based on the computed image and world points. The proposed method obtained an error rate of 3% using a document de-warping dataset (CBDAR 2007). The proposed method achieved a high level of quality compared with other previous methods. Our method fixes the problem of warping in document images acquired with different levels of complexity, such as poor lighting, low quality, and different layouts.
Evidence-Based Software Engineering: A Checklist-Based Approach to Assess the Abstracts of Reviews Self-Identifying as Systematic Reviews
Authors: Boaye Belle Alvine , Zhao Yixi
Published: September 2022

A systematic review allows synthesizing the state of knowledge related to a clearly formulated research question as well as understanding the correlations between exposures and outcomes. A systematic review usually leverages explicit, reproducible, and systematic methods that allow reducing the potential bias that may arise when conducting a review. When properly conducted, a systematic review yields reliable findings from which conclusions and decisions can be made. Systematic reviews are increasingly popular and have several stakeholders to whom they allow making recommendations on how to act based on the review findings. They also help support future research prioritization. A systematic review usually has several components. The abstract is one of the most important parts of a review because it usually reflects the content of the review. It may be the only part of the review read by most readers when forming an opinion on a given topic. It may help more motivated readers decide whether the review is worth reading or not. But abstracts are sometimes poorly written and may, therefore, give a misleading and even harmful picture of the review’s contents. To assess the extent to which a review’s abstract is well constructed, we used a checklist-based approach to propose a measure that allows quantifying the systematicity of review abstracts i.e., the extent to which they exhibit good reporting quality. Experiments conducted on 151 reviews published in the software engineering field showed that the abstracts of these reviews had suboptimal systematicity.
Analysis of the Characteristics and Cause Analysis of Soil Salt Space Based on the Basin Scale
Authors: Lu Li , Li Sheng , Gao Yuan , Ge Yanyan , Zhang Yun
Published: September 2022

The analysis of water-soluble salts in the soil is an important basic work for the development and research of the salinity monitoring and salinization control of saline soils, aiming at the complexity of the development of soil salinization in oases in arid and semi-arid areas. Based on the regionalization theory, GPS positioning technology was adopted in this paper to conduct fixed point sampling of the Weigan River Basin oasis from April to May 2020. Soil sampling levels were between 0 m and 0.25 m, between 1 m and 2 m, and between 2 m and 3 m, respectively, and soil physical and chemical properties were analyzed and tested from May to June 2022. The spatial variability of soil salinity at different depths in the Weigan River Basin oasis was quantitatively studied by GIS and geostatistics, and the results show that: (1) the soil salinity of each layer in the Weigan River Basin oasis was generally high, with an average value of 1.27%, 0.87%, and 0.79%, respectively, and a variation coefficient between 1.023 and 1.265, showing strong variability. (2) A reasonable number of soil sampling should be based on the 95% confidence level and 20% relative error. Therefore, the number of soil samples in the corresponding layers should not be less than 89, 70, and 91. (3) Optimal fitting models of soil salinity at the layers between 0 m and 0.25 m and between 1 m and 2 m were both spherical models, while the optimal fitting model of soil salinity at the layer between 2 m and 3 m was an exponential model. Soil salinity at different depths is affected by random factors and structural factors. Soil salinity at the layer between 0 m and 0.25 m showed moderate spatial correlation, while soil salinity at the layers between 1 m and 2 m and between 2 m and 3 m showed strong spatial correlation. (4) Three layers of soil salinity had obvious anisotropy, and the maximum variation direction was northwest–southeast. The nested model can overcome the influence of directionality on the fitting of soil salinity variation function in the layer between 0 m and 0.25 m and improve the spatial interpolation accuracy. (5) In terms of spatial pattern, the area of high soil salinity was located along the Tarim River and at the edge of oasis (i.e., desert–oasis ecotone). On the whole, the salinity shows a gradual increasing trend from the inner part of the oasis (i.e., cultivation area) to the edge of the oasis, and from the northwest to the southeast. (6) The spatial distribution pattern of soil salinity in the study area was mainly affected by the differences in topography, groundwater level, and water quality, while agricultural activities intensified the formation of the distribution pattern, reflecting the complexity of the development of soil physical and chemical properties in arid and semi-arid areas. This study provided a reference for the improvement, management, and rational utilization of saline soil in the Weigan River Basin oasis.
An Improved Method Based on EEMD-LSTM to Predict Missing Measured Data of Structural Sensors
Authors: Chen Zengshun , Yuan Chenfeng , Wu Haofan , Zhang Likai , Li Ke , Xue Xuanyi , Wu Lei
Published: September 2022

Time history testing using a shaking table is one of the most widely used methods for assessing the dynamic response of structures. In shaking-table experiments and on-site monitoring, acceleration sensors are facing problems of missing data due to the fact of measurement point failures, affecting the validity and accuracy of assessing the structural dynamic response. The original measured signals are decomposed by ensemble empirical mode decomposition (EEMD), and the widely used deep neural networks (DNNs), gated recurrent units (GRUs), and long short-term memory networks (LSTMs) are used to predict the subseries of the decomposed original measured signal data to help model and recover the irregular, periodic variations in the measured signal data. The raw acceleration data of a liquefied natural gas (LNG) storage tank in shaking-table experiments were used as an example to compare and discuss the method’s performance for the complementation of missing measured signal data. The results of the measured signal data recovery showed that the hybrid method (EEMD based) proposed in this paper had a higher complementary performance compared with the traditional deep learning methods, while the EEMD-LSTM exhibited the best missing data complementary accuracy among all models. In addition, the effect of the number of prediction steps on the prediction accuracy of the EEMD-LSTM model is also discussed. This study not only provides a method to fuse EEMD and deep learning models to predict measured signal’ missing data but also provides suggestions for the use of EEMD-LSTM models under different conditions.
A Combined Method for Preparation of Landslide Susceptibility Map in Izmir (Türkiye)
Authors: KINCAL Cem , KAYHAN Hakan
Published: September 2022

Landslide susceptibility maps (LSMs) have been used frequently by researchers for many years in prediction of the occurrence of landslides. Since many landslides have occurred there in the past, Izmir, which is the third largest city of Türkiye, was selected for landslide susceptibility assessment using geographical information systems (GIS) and remote sensing (RS) techniques. The aim of this study is to create a better landslide susceptibility map (LSM) for the Izmir metropolitan area and its surroundings by minimizing the shortcomings of some of the commonly used methods. For this purpose, four different LSMs were prepared using the logistic regression (LR), analytical hierarchy process (AHP), frequency ratio (FR) and index of entropy (IOE) methods with susceptibility classes ranging from extremely low to extremely high. These four maps were then overlaid. The highest susceptibility class was chosen for each pixel to form a combined landslide susceptibility map (CLSM). The final CLSM is a thematic map presenting landslide susceptibility using five different classes. The geo-environmental factors selected for use in this analysis were slope angle, slope aspect, lithology, slope curvature, elevation, density of discontinuity, stream power index (SPI), land use and distance from stream. Finally, the areas under receiver-operating characteristic (ROC) curves were employed to compare the predictive capability of the five models used. Overall, the Combined Method (CM) (AUC = 0.887) performed very well for landslide susceptibility assessment. Out of all the models, the IOE model (AUC = 0.841) had a slightly lower predictive capability than the CM model, and AHP (AUC = 0.816) was better than FR (AUC = 0.738) and LR (AUC = 0.727). It was observed that, compared to rural areas, residential areas of Izmir city are particularly susceptible to landslides.
Enhancing Channelized Feature Interpretability Using Deep Learning Predictive Modeling
Authors: Mad Sahad Salbiah , Tan Nian Wei , Sajid Muhammad , Jones Ernest Austin , Abdul Latiff Abdul Halim
Published: September 2022

Automating geobodies using insufficient labeled training data as input for structural prediction may result in missing important features and a possibility of overfitting, leading to low accuracy. We adopt a deep learning (DL) predictive modeling scheme to alleviate detection of channelized features based on classified seismic attributes (X) and different ground truth scenarios (y), to imitate actual human interpreters’ tasks. In this approach, diverse augmentation method was applied to increase the accuracy of the model after we were satisfied with the refined annotated ground truth dataset. We evaluated the effect of dropout as a training regularizer and facies’ spatial representation towards optimized prediction results, apart from conventional hyperparameter tuning. From our findings, increasing batch size helps speedup training speed and improve performance stability. Finally, we demonstrate that the designed Convolutional Neural Network (CNN) is capable of learning channelized variation from complex deepwater settings in a fluvial-dominated depositional environment while producing outstanding mean Intersection of Union (IoU) (95%) despite utilizing 6.4% from the overall dataset and avoiding overfitting possibilities.
A Novel Hybrid Whale-Chimp Optimization Algorithm for Structural Damage Detection
Authors: Chen Zhen , Zhang Kun , Chan Tommy H. T. , Li Xiaoke , Zhao Shunbo
Published: September 2022

Damage detection of structures based on swarm intelligence optimization algorithms is an effective method for structural damage detection and key parts of the field of structural health monitoring. Based on the chimp optimization algorithm (ChOA) and the whale optimization algorithm, this paper proposes a novel hybrid whale-chimp optimization algorithm (W-ChOA) for structural damage detection. To improve the identification accuracy of the ChOA, the Sobol sequence is adopted in the population initialization stage to make the population evenly fill the entire solution space. In addition, to improve the local search ability of the traditional ChOA, the bubble-net hunting mechanism and the random search mechanism of the whale optimization algorithm are introduced into the position update process of the ChOA. In this paper, the validity and applicability of the proposed method are illustrated by a two-story rigid frame model and a simply supported beam model. Simulations show that the presented method has much better performance than the ChOA, especially in dealing with multiple damage detection cases. The W-ChOA has good performance in both overcoming misjudgment and improving computational efficiency, which should be a preferred choice in adoption for structural damage detection.
Indigenous Agency in Australian Bark Painting
Authors: Geissler Marie
Published: September 2022

In the early years of the discovery of Indigenous bark paintings in Australia, anthropologists regarded this artform as part of a static and unchanging tradition. Inspired by the images of Arnhem Land rock art and ceremonial body design, the bark paintings were innovatively adapted by Indigenous Australians for the bark medium. Today, this art is recognised for its dynamism and sophistication, offering a window into how the artists engaged with the world. Within the context of recent art and anthropological scholarship, the paiFntings are understood as artefacts of Indigenous ‘agency’. They are products of the intentional action of artists through which power is enacted and from which change has followed. This paper reveals how the paintings were influential to their audiences and the discourses arising from their display through the agency of the artists who made them, and the curators who selected them. It underlines how Indigenous agency associated with the aesthetic and semantics values of bark painting has been and continues to be a powerful mechanism for instigating cultural, social, economic and political change. As such, it points to the wealth of Indigenous agency yet to be documented in the other collections of bark painting that are held in institutions in Australia and throughout the world.
Inferences of a Mixture Bivariate Alpha Power Exponential Model with Engineering Application
Authors: Alotaibi Refah , Nassar Mazen , Ghosh Indranil , Rezk Hoda , Elshahhat Ahmed
Published: September 2022

The univariate alpha power exponential (APE) distribution has several appealing characteristics. It behaves similarly to Weibull, Gamma, and generalized exponential distributions with two parameters. In this paper, we consider different bivariate mixture models starting with two independent univariate APE models, and, in the latter case, starting from two dependent APE models. Several useful structural properties of such a mixture model (under the assumption of two independent APE distribution) are discussed. Bivariate APE (BAPE), in short, modelled under the dependent set up are also discussed in the context of a copula-based construction. Inferential aspects under the classical and under the Bayesian paradigm are considered to estimate the model parameters, and a simulation study is conducted for this purpose. For illustrative purposes, a well-known motor data is re-analyzed to exhibit the flexibility of the proposed bivariate mixture model.
Functional Identification of Arthrinium phaeospermum Effectors Related to Bambusa pervariabilis × Dendrocalamopsis grandis Shoot Blight
Authors: Fang Xinmei , Yan Peng , Luo Fengying , Han Shan , Lin Tiantian , Li Shuying , Li Shujiang , Zhu Tianhui
Published: September 2022

The shoot blight of Bambusa pervariabilis × Dendrocalamopsis grandis caused by Arthrinium phaeospermum made bamboo die in a large area, resulting in serious ecological and economic losses. Dual RNA-seq was used to sequence and analyze the transcriptome data of A. phaeospermum and B. pervariabilis × D. grandis in the four periods after the pathogen infected the host and to screen the candidate effectors of the pathogen related to the infection. After the identification of the effectors by the tobacco transient expression system, the functions of these effectors were verified by gene knockout. Fifty-three differentially expressed candidate effectors were obtained by differential gene expression analysis and effector prediction. Among them, the effectors ApCE12 and ApCE22 can cause programmed cell death in tobacco. The disease index of B. pervariabilis × D. grandis inoculated with mutant ΔApCE12 and mutant ΔApCE22 strains were 52.5% and 47.5%, respectively, which was significantly lower than that of the wild-type strains (80%), the ApCE12 complementary strain (77.5%), and the ApCE22 complementary strain (75%). The tolerance of the mutant ΔApCE12 and mutant ΔApCE22 strains to H2O2 and NaCl stress was significantly lower than that of the wild-type strain and the ApCE12 complementary and ApCE22 complementary strains, but there was no difference in their tolerance to Congo red. Therefore, this study shows that the effectors ApCE12 and ApCE22 play an important role in A. phaeospermum virulence and response to H2O2 and NaCl stress.
Magnetic Nanoparticle-Based Electrochemical Sensing Platform Using Ferrocene-Labelled Peptide Nucleic Acid for the Early Diagnosis of Colorectal Cancer
Authors: Hanoglu Simge Balaban , Man Ezgi , Harmanci Duygu , Tozan Ruzgar Serife , Sanli Serdar , Keles Nazim Arda , Ayden Atakan , Tuna Bilge Guvenc , Duzgun Ozgul , Ozkan Omer Faruk , Dogan Soner , Ghorbanizamani Faezeh , Moulahoum Hichem , Guler Celik Emine , Evran Serap , Timur Suna
Published: September 2022

Diagnostic biomarkers based on epigenetic changes such as DNA methylation are promising tools for early cancer diagnosis. However, there are significant difficulties in directly and specifically detecting methylated DNA regions. Here, we report an electrochemical sensing system based on magnetic nanoparticles that enable a quantitative and selective analysis of the methylated septin9 (mSEPT9) gene, which is considered a diagnostic marker in early stage colorectal cancer (CRC). Methylation levels of SEPT9 in CRC samples were successfully followed by the selective recognition ability of a related peptide nucleic acid (PNA) after hybridization with DNA fragments in human patients’ serums and plasma (n = 10). Moreover, this system was also adapted into a point-of-care (POC) device for a one-step detection platform. The detection of mSEPT9 demonstrated a limit of detection (LOD) value of 0.37% and interference-free measurement in the presence of branched-chain amino acid transaminase 1 (BCAT1) and SRY box transcription factor 21 antisense divergent transcript 1 (SOX21-AS1). The currently proposed functional platform has substantial prospects in translational applications of early CRC detection.
Automatic Modeling for Concrete Compressive Strength Prediction Using Auto-Sklearn
Authors: Shi M. , Shen Weigang
Published: September 2022

Machine learning is widely used for predicting the compressive strength of concrete. However, the machine learning modeling process relies on expert experience. Automated machine learning (AutoML) aims to automatically select optimal data preprocessing methods, feature preprocessing methods, machine learning algorithms, and hyperparameters according to the datasets used, to obtain high-precision prediction models. However, the effectiveness of modeling concrete compressive strength using AutoML has not been verified. This study attempts to fill the above research gap. We construct a database comprising four different types of concrete datasets and compare one AutoML algorithm (Auto-Sklearn) against five ML algorithms. The results show that Auto-Sklearn can automatically build an accurate concrete compressive strength prediction model without relying on expert experience. In addition, Auto-Sklearn achieves the highest accuracy for all four datasets, with an average R2 of 0.953; the average R2 values of the ML models with tuned hyperparameters range from 0.909 to 0.943. This study verifies for the first time the feasibility of AutoML for concrete compressive strength prediction, to allow concrete engineers to easily build accurate concrete compressive strength prediction models without relying on a large amount of ML modeling experience.
Can Adjuvant HPV Vaccination Be Helpful in the Prevention of Persistent/Recurrent Cervical Dysplasia after Surgical Treatment?—A Literature Review
Authors: Michalczyk Kaja , Misiek Marcin , Chudecka-Głaz Anita
Published: September 2022

Cervical cancer formation is preceded by precursor lesions, including low-grade squamous intraepithelial lesions (LSILs) and high-grade squamous intraepithelial lesions (HSILs), which are usually diagnosed in women of reproductive age. Despite the recent advanced diagnostic and treatment methods, including colposcopy, the loop electrosurgical excision procedure (LEEP), and surgical conization, the recurrence or residual disease affects as many as 6.6% of patients. The lesions are often associated with human papilloma virus (HPV) infection. As HPV persistence is the leading and only modifiable factor affecting the risk of progression of CIN lesions into high-grade cervical dysplasia and cancer, it has been proposed to conduct adjuvant vaccination in patients treated for high-grade cervical dysplasia. To date, no vaccine has been approved for therapeutic use in patients diagnosed with HSILs; however, attempts have been made to determine the use of HPV prophylactic vaccination to reduce recurrent HSILs and prevent cervical cancer. The aim of this review was to analyze the up-to-date literature concerning the possible use of secondary human papilloma virus (HPV) vaccination as an adjuvant method to surgical treatment in patients diagnosed with cervical HSILs. Adjuvant HPV vaccination after surgical treatment may reduce the risk of recurrent cervical dysplasia.
Enriched Riceberry Bran Oil Exerts Chemopreventive Properties through Anti-Inflammation and Alteration of Gut Microbiota in Carcinogen-Induced Liver and Colon Carcinogenesis in Rats
Authors: Phannasorn Warunyoo , Pharapirom Aroonrat , Thiennimitr Parameth , Guo Huina , Ketnawa Sunantha , Wongpoomchai Rawiwan
Published: September 2022

Riceberry has recently been acknowledged for its beneficial pharmacological effects. Riceberry bran oil (RBBO) exhibited anti-proliferation activity in various cancer cell lines. However, animal studies of RBBO on anti-carcinogenicity and its molecular inhibitory mechanism have been limited. This study purposed to investigate the chemopreventive effects of RBBO on the carcinogen-induced liver and colorectal carcinogenesis in rats. Rats were injected with diethylnitrosamine (DEN) and 1,2-dimethylhydrazine (DMH) and further orally administered with RBBO equivalent to 100 mg/kg body weight of γ-oryzanol 5 days/week for 10 weeks. RBBO administration suppressed preneoplastic lesions including hepatic glutathione S-transferase placental form positive foci and colorectal aberrant crypt foci. Accordingly, RBBO induced hepatocellular and colorectal cell apoptosis and reduced pro-inflammatory cytokine expression. Interestingly, RBBO effectively promoted the alteration of gut microbiota in DEN- and DMH-induced rats, as has been shown in the elevated Firmicutes/Bacteroidetes ratio. This outcome was consistent with an increase in butyrate in the feces of carcinogen-induced rats. The increase in butyrate reflects the chemopreventive properties of RBBO through the mechanisms of its anti-inflammatory properties and cell apoptosis induction in preneoplastic cells. This would indicate that RBBO containing γ-oryzanol, phytosterols, and tocols holds significant potential in the prevention of cancer.