bluuebunny/crossref_metadata_2025 huggingface dataset:
QSAR, Molecular Docking, MD Simulation and MMGBSA Calculations Approaches to Recognize Concealed Pharmacophoric Features Requisite for the Optimization of ALK Tyrosine Kinase Inhibitors as Anticancer Leads
Authors: Jawarkar Rahul D. , Sharma Praveen , Jain Neetesh , Gandhi Ajaykumar , Mukerjee Nobendu , Al-Mutairi Aamal A. , Zaki Magdi E. A. , Al-Hussain Sami A. , Samad Abdul , Masand Vijay H. , Ghosh Arabinda , Bakal Ravindra L.
Published: August 2022

ALK tyrosine kinase ALK TK is an important target in the development of anticancer drugs. In the present work, we have performed a QSAR analysis on a dataset of 224 molecules in order to quickly predict anticancer activity on query compounds. Double cross validation assigns an upward plunge to the genetic algorithm–multi linear regression (GA-MLR) based on robust univariate and multivariate QSAR models with high statistical performance reflected in various parameters like, fitting parameters; R2 = 0.69–0.87, F = 403.46–292.11, etc., internal validation parameters; Q2LOO = 0.69–0.86, Q2LMO = 0.69–0.86, CCCcv = 0.82–0.93, etc., or external validation parameters Q2F1 = 0.64–0.82, Q2F2 = 0.63–0.82, Q2F3 = 0.65–0.81, R2ext = 0.65–0.83 including RMSEtr < RMSEcv. The present QSAR evaluation successfully identified certain distinct structural features responsible for ALK TK inhibitory potency, such as planar Nitrogen within four bonds from the Nitrogen atom, Fluorine atom within five bonds beside the non-ring Oxygen atom, lipophilic atoms within two bonds from the ring Carbon atoms. Molecular docking, MD simulation, and MMGBSA computation results are in consensus with and complementary to the QSAR evaluations. As a result, the current study assists medicinal chemists in prioritizing compounds for experimental detection of anticancer activity, as well as their optimization towards more potent ALK tyrosine kinase inhibitor.
Simultaneous Determination of 21 Sulfonamides in Poultry Eggs Using Ionic Liquid-Modified Molecularly Imprinted Polymer SPE and UPLC–MS/MS
Authors: Suo Decheng , Zhang Su , Song Zhanteng , Wang Shi , Li Yang , Fan Xia
Published: August 2022

An ionic liquid-modified molecularly imprinted polymer (IL-MIP) composite with sulfamethazine as a template molecule and methyl acrylic acid and 1-aminopropyl-3-methylimidazolium bromide as functional monomers was successfully synthesized. The achieved IL-MIP was characterized and evaluated in detail and utilized in the extraction and cleanup of sulfonamides (SAs) in poultry egg samples. The results demonstrated that the IL-MIP possessed a broad reorganization toward SAs and could selectively adsorb 21 kinds of SA compounds. Furthermore, the solid-phase extraction column based on the IL-MIP was used in the extraction and cleanup of 21 SAs in eggs, and the confirmatory detection of SAs was performed using ultraperformance liquid chromatography–tandem mass spectrometry. Under optimum conditions, the limits of detection (LODs) for all SAs ranged from 0.1 ng·g−1 to 1.5 ng·g−1, and the LOD of this method was better than those of the existing methods. The recoveries of SA compounds spiked in egg samples ranged from 84.3% to 105.8%, with low relative standard deviations (<15%). The developed method based on the IL-MIP extraction and cleanup was successfully used in the detection of 21 SAs in more than 100 real poultry egg samples. The results indicated that the proposed method was suitable for detecting 21 SAs in poultry eggs.
β-Cyclodextrin/CMK-8-Based Electrochemical Sensor for Sensitive Detection of Cu2+
Authors: Bao Chengqi , Lu Yan , Liu Jiawei , Gao Yansha , Lu Limin , Liu Shuwu
Published: August 2022

In this work, β-cyclodextrin (β-CD)/mesoporous carbon (CMK-8) nanocomposite was synthesized and used as an electrochemical sensing platform for highly sensitive and selective detection of Cu2+. The morphology and structure of β-CD/CMK-8 were characterized by scanning electron microscope (SEM) and X-ray diffraction (XRD). In addition, the dates from electrochemical impedance spectroscopy (EIS) and Cyclic voltammetry (CV) demonstrated that the β-CD/CMK-8 possessed a fast electronic transfer rate and large effective surface area. Besides this, the β-CD/CMK-8 composite displayed high enrichment ability toward Cu2+. As a result of these impressive features, the β-CD/CMK-8 modified electrode provided a wide linear response ranging from 0.1 ng·L−1 to 1.0 mg·L−1 with a low detection limit of 0.3 ng·L−1. Furthermore, the repeatability, reproducibility and selectivity of β-CD/CMK-8 towards Cu2+ were commendable. The sensor could be used to detect Cu2+ in real samples. All in all, this work proposes a simple and sensitive method for Cu2+ detection, which provides a reference for the subsequent detection of HMIs.
Dietary Diversity and its Association with Nutritional Status, Cardiometabolic Risk Factors and Food Choices of Adults at Risk for Type 2 Diabetes Mellitus in Cape Town, South Africa
Authors: Madlala Samukelisiwe S. , Hill Jillian , Kunneke Ernesta , Kengne Andre P. , Peer Nasheeta , Faber Mieke
Published: August 2022

In South Africa, the nutrition transition has led to unhealthy diets lacking variety, contributing to the rise in overweight, obesity and diet-related noncommunicable diseases. Using baseline screening data of the South African Diabetes Prevention Programme (SA-DPP) study, this study aims to determine the relationship of dietary diversity (DD) with nutritional status, cardiometabolic risk factors and food choices of adults at risk of type 2 diabetes in resource-poor communities around Cape Town. Data of 693 adults, 25–65 years old were analysed. This included socio-demographic information, anthropometric measurements, biochemical assessments, food groups consumed the previous day and consumption frequency of certain foods to reflect food choices. The Minimum Dietary Diversity for Women (MDD-W) indicator was calculated; 70.4% of participants had low DD (<5 food groups). Low DD was associated with elevated serum triglycerides [AOR: 1.49, 95% CI (1.03, 2.15) p = 0.036]. The DD score was positively correlated (although weak) with the unhealthy food score (r = 0.191, p = 0.050) and sugary food score (r = 0.139, p < 0.01). Study participants at risk of diabetes consumed a diet low in DD; however, DD was not associated with nutritional status or cardiometabolic risk factors except for serum triglycerides.
Poxviral ANKR/F-box Proteins: Substrate Adapters for Ubiquitylation and More
Authors: Ingham Robert J. , Loubich Facundo Farynna , Dong Jianing
Published: August 2022

Poxviruses are double-stranded DNA viruses that infect insects and a variety of vertebrate species. The large genomes of poxviruses contain numerous genes that allow these viruses to successfully establish infection, including those that help evade the host immune response and prevent cell death. Ankyrin-repeat (ANKR)/F-box proteins are almost exclusively found in poxviruses, and they function as substrate adapters for Skp1-Cullin-1-F-box protein (SCF) multi-subunit E3 ubiquitin (Ub)-ligases. In this regard, they use their C-terminal F-box domain to bind Skp1, Cullin-1, and Roc1 to recruit cellular E2 enzymes to facilitate the ubiquitylation, and subsequent proteasomal degradation, of proteins bound to their N-terminal ANKRs. However, these proteins do not just function as substrate adapters as they also have Ub-independent activities. In this review, we examine both Ub-dependent and -independent activities of ANKR/F-box proteins and discuss how poxviruses use these proteins to counteract the host innate immune response, uncoat their genome, replicate, block cell death, and influence transcription. Finally, we consider important outstanding questions that need to be answered in order to better understand the function of this versatile protein family.
AG129 Mice as a Comprehensive Model for the Experimental Assessment of Mosquito Vector Competence for Arboviruses
Authors: Baldon Lívia V. R. , de Mendonça Silvana F. , Ferreira Flávia V. , Rezende Fernanda O. , Amadou Siad C. G. , Leite Thiago H. J. F. , Rocha Marcele N. , Marques João T. , Moreira Luciano A. , Ferreira Alvaro G. A.
Published: August 2022

Arboviruses (an acronym for “arthropod-borne virus”), such as dengue, yellow fever, Zika, and Chikungunya, are important human pathogens transmitted by mosquitoes. These viruses impose a growing burden on public health. Despite laboratory mice having been used for decades for understanding the basic biological phenomena of these viruses, it was only recently that researchers started to develop immunocompromised animals to study the pathogenesis of arboviruses and their transmission in a way that parallels natural cycles. Here, we show that the AG129 mouse (IFN α/β/γ R−/−) is a suitable and comprehensive vertebrate model for studying the mosquito vector competence for the major arboviruses of medical importance, namely the dengue virus (DENV), yellow fever virus (YFV), Zika virus (ZIKV), Mayaro virus (MAYV), and Chikungunya virus (CHIKV). We found that, after intraperitoneal injection, AG129 mice developed a transient viremia lasting several days, peaking on day two or three post infection, for all five arboviruses tested in this study. Furthermore, we found that the observed viremia was ample enough to infect Aedes aegypti during a blood meal from the AG129 infected mice. Finally, we demonstrated that infected mosquitoes could transmit each of the tested arboviruses back to naïve AG129 mice, completing a full transmission cycle of these vector-borne viruses. Together, our data show that A129 mice are a simple and comprehensive vertebrate model for studies of vector competence, as well as investigations into other aspects of mosquito biology that can affect virus–host interactions.
Design and Analysis of Highly Sensitive LSPR-Based Metal–Insulator–Metal Nano-Discs as a Biosensor for Fast Detection of SARS-CoV-2
Authors: Taghipour Ata , Heidarzadeh Hamid
Published: August 2022

For over 2 years, the coronavirus has been the most urgent challenge to humanity, and the development of rapid and accurate detection methods is crucial to control these viruses. Here, a 3D FDTD simulation of Au/SiO2/Au metal–insulator–metal (MIM) nanostructures as a biosensor was performed. The strong coupling between the two plasmonic interfaces in the Au/SiO2/Au cavity helped us to obtain relatively higher sensitivity. The attachment of SARS-CoV-2 changed the refractive index, which was used to detect SARS-CoV-2. Due to the higher overlapping of plasmonic mode with the environment of nano-discs, a higher sensitivity of 312.8 nm/RIU was obtained. The peak wavelength of the proposed structure shifted by approximately 47 nm when the surrounding medium refractive index changed from 1.35 (no binding) to 1.5 (full binding). Consequently, the SPR peak intensity variation can be used as another sensing mechanism to detect SARS-CoV-2. Finally, the previously reported refractive index changes for various concentrations of the SARS-CoV-2 S-glycoprotein solution were used to evaluate the performance of the designed biosensor.
Oxidative Stress Mitigation by Chitosan Nanoparticles in Durum Wheat Also Affects Phytochemicals and Technological Quality of Bran and Semolina
Authors: Picchi Valentina , Calzone Antonella , Gobbi Serena , Paccani Sara , Lo Scalzo Roberto , Marti Alessandra , Faoro Franco
Published: August 2022

In our previous work, durum wheat cv. Fabulis was grown over two consecutive seasons (2016–2017 and 2017–2018) in an experimental field in the north of Italy. With the aim of mitigating oxidative stress, plants were subjected to four treatments (deionized water, CHT 0.05 mg/mL, CHT-NPs, and CHT-NPs-NAC) three times during the experiment. Chitosan nanoparticles (CHT-NPs) reduced symptom severity on wheat leaves and positively influenced the final grain yield. The present work aimed at investigating whether CHT treatments and particularly N-acetyl cysteine (NAC)-loaded or -unloaded CHT-NPs, while triggering plant defense mechanisms, might also vary the nutritional and technological quality of grains. For this purpose, the grains harvested from the previous experiment were analyzed for their content in phytochemicals and for their technological properties. The results showed that CHT increased the polyphenol and tocopherol content and the reducing capacity of bran and semolina, even if the positive effect of the nano-formulation remained still unclear and slightly varied between the two years of cultivation. The positive effect against oxidative stress induced by the chitosan treatments was more evident in the preservation of both the starch pasting properties and gluten aggregation capacity, indicating that the overall technological quality of semolina was maintained. Our data confirm the role of chitosan as an elicitor of the antioxidant defense system in wheat also at the grain level.
Comparative Transcriptome Analysis of Deep-Rooting and Shallow-Rooting Potato (Solanum tuberosum L.) Genotypes under Drought Stress
Authors: Qin Tianyuan , Sun Chao , Kazim Ali , Cui Song , Wang Yihao , Richard Dormatey , Yao Panfeng , Bi Zhenzhen , Liu Yuhui , Bai Jiangping
Published: August 2022

The selection and breeding of deep rooting and drought-tolerant varieties has become a promising approach for improving the yield and adaptability of potato (Solanum tuberosum L.) in arid and semiarid areas. Therefore, the discovery of root-development-related genes and drought tolerance signaling pathways in potato is important. In this study, we used deep-rooting (C119) and shallow-rooting (C16) potato genotypes, with different levels of drought tolerance, to achieve this objective. Both genotypes were treated with 150 mM mannitol for 0 h (T0), 2 h (T2), 6 h (T6), 12 h (T12), and 24 h (T24), and their root tissues were subjected to comparative transcriptome analysis. A total of 531, 1571, 1247, and 3540 differentially expressed genes (DEGs) in C16 and 1531, 1108, 674, and 4850 DEGs in C119 were identified in T2 vs. T0, T6 vs. T2, T12 vs. T6, and T24 vs. T12 comparisons, respectively. Gene expression analysis indicated that a delay in the onset of drought-induced transcriptional changes in C16 compared with C119. Functional enrichment analysis revealed genotype-specific biological processes involved in drought stress tolerance. The metabolic pathways of plant hormone transduction and MAPK signaling were heavily involved in the resistance of C16 and C119 to drought, while abscisic acid (ABA), ethylene, and salicylic acid signal transduction pathways likely played more important roles in C119 stress responses. Furthermore, genes involved in root cell elongation and division showed differential expression between the two genotypes under drought stress. Overall, this study provides important information for the marker-assisted selection and breeding of drought-tolerant potato genotypes.
Quality Characteristics, Anthocyanin Stability and Antioxidant Activity of Apple (Malus domestica) and Black Chokeberry (Aronia melanocarpa) Juice Blends
Authors: Nour Violeta
Published: August 2022

Black chokeberries are a valuable source of anthocyanins and other phenolic compounds, but they are underutilized due to their unpalatable astringent taste. The aim of this study was to determine the potential of using black chokeberry juice as a health-promoting ingredient in apple juice with a view to develop a new functional food product and to increase the dietary consumption of bioactive compounds. Mixed juices were prepared from apple (A) juice and black chokeberry (BC) juice at 95:5 (ABC5), 90:10 (ABC10), 85:15 (ABC15), and 80:20 (ABC20) volumetric ratios. Comparative studies on the effect of heat treatment (90 °C, 10 min) and storage (four months, 20 °C) on the physicochemical and antioxidant properties of apple, black chokeberry, and mixed juices were carried out. The soluble solids content, titratable acidity, total phenolic, total anthocyanin and ascorbic acid content, and antioxidant activity increased while the total soluble solids/titratable acidity ratio decreased with increasing addition levels of BC juice. Mixing A juice with BC juice at 95:5 and 90:10 volumetric ratios improved the color and enhanced the palatability and general acceptability of the juice. The percentage losses of anthocyanins and polyphenols registered after heat treatment and storage increased with increasing addition levels of BC juice.
Extending the Shelf Life of Fresh Khalal Barhi Dates via an Optimized Postharvest Ultrasonic Treatment
Authors: Abdelkarim Diaeldin O. , Mohamed Ahmed Isam A. , Ahmed Khaled A. , Younis Mahmoud , Yehia Hany M. , Zein El-Abedein Assem I. , Alhamdan Abdulla
Published: August 2022

The Barhi date is a high-quality date cultivar whose fruits (dates) are plucked and eaten fresh when they reach the Khalal maturity stage due to their sweetness, crispiness, and yellow skin color. After harvesting, Khalal Barhi fruits rapidly matured to the Rutab stage, where their tissues become soft and their skin color browner. This results in a decrease in their market value and customer demand. This study aims at investigating the effectiveness of the postharvest ultrasonic treatment in conserving the physical, microbial, and nutritional quality of Barhi fruits and extending their shelf life. To achieve the goals of the present work, the response surface methodology (RSM) was used for the optimization of the ultrasonic intensity (50, 100, 150, and 200 W/cm2) and application time (5, 10, 15, and 20 min) to preserve the Barhi dates high quality features for varied storage temperatures (1, 5, 15, and 25 °C) and duration (1, 6, 16, and 21 days). In RSM, a four-factors-mixed-levels central composite rotatable design (CCRD) was applied to optimize the ultrasound treatment and storage environments for better-quality physical [total soluble solids (TSS), firmness, and total color changes (ΔE)], microbial [total viable count (TVC)], nutritional [total phenolic content (TPC), DPPH antiradical activity, glucose, and fructose] features of Barhi dates. The outcomes showed that ultrasound intensity and its application time, storage temperature, and storage period influence the physical, microbial, and nutritional quality attributes in different magnitudes. The ideal settings for lessening the changes in the physical attributes, eliminating the microbial growth, and improving the nutritional quality attributes were 140 W/cm2, 5.2 min, 20.9 °C, and 21 days for ultrasound intensity, ultrasound exposure duration, storage temperature, and storage duration, respectively. In conclusion, this study proved the potential application of ultrasound for persevering the excellence aspects of Barhi dates and identified the ideal ultrasound environments for maintaining the physical, microbial, and nutritional quality features of Barhi dates during extended storing.
Activated Carbon Modified by Ester Hydrolysis of Ethyl Acetate for Water Vapor Adsorption Enhancement
Authors: Xu Jinping , Zhang Hailin , Ji Xu , Lan Qing , Fan Quanhai
Published: August 2022

To improve water vapor adsorption, this study employed oxalic acid–ethyl acetate acidic hydrolysis to modify honeycomb activated carbon and introduce hydrophilic functional groups. Scanning electron microscopy (SEM), Boehm titration, Fourier transform infrared spectroscopy (FT-IR), and an automatic surface area analyzer (BET) were used to characterize the microscopic morphology, surface functional groups, specific surface area, and pore size changes. The results showed that, when the concentration of oxalic acid is 0.0006 mol/cm3, the specific surface area is 179.06 m2/g. After hydrolysis with ethyl acetate, the original functional groups became more abundant, while the number of total acidic functional groups on the surface grew from 0.497 mmol/g to 1.437 mmol/g. The static water vapor adsorption experiments were conducted on modified activated carbon under constant temperature and humidity conditions. Compared with unmodified activated carbon, the activated carbon modified with 0.0006 mol/cm3 oxalic acid increased the adsorption capacity of water vapor by 15.7%. The adsorption capacity of activated carbon after being combined with 0.0006 mol/cm3 oxalic acid and ester hydrolysis modification increased by 37.1%. At the same temperature, the adsorption capacity increased with a higher relative humidity. At the same relative humidity, the adsorption capacity decreased as the temperature rose. Therefore, this modification method may provide clues for the application of enhancing the hygroscopic ability of activated carbon.
A Review of Event Deposits in Lake Sediments
Authors: Sabatier Pierre , Moernaut Jasper , Bertrand Sebastien , Van Daele Maarten , Kremer Katrina , Chaumillon Eric , Arnaud Fabien
Published: August 2022

Event deposits in lake sediments provide invaluable chronicles of geodynamic and climatic natural hazards on multi-millennial timescales. Sediment archives are particularly useful for reconstructing high-impact, low-frequency events, which are rarely observed in instrumental or historical data. However, attributing a trigger mechanism to event deposits observed in lake sediments can be particularly challenging as different types of events can produce deposits with very similar lithological characteristics, such as turbidites. In this review paper, we summarize the state of the art on event deposits in paleolimnology. We start by describing the sedimentary facies typical of floods, glacial lake outburst floods, avalanches, hurricanes, earthquakes, tsunamis, volcanic eruptions, and spontaneous delta collapses. We then describe the most indicative methods that can be applied at the scale of lake basins (geophysical survey, multiple coring) and on sediment cores (sedimentology, inorganic and organic geochemistry, biotic approach). Finally, we provide recommendations on how to obtain accurate chronologies on sediment cores containing event deposits, and ultimately date the events. Accurately identifying and dating event deposits has the potential to improve hazard assessments, particularly in terms of the return periods, recurrence patterns, and maximum magnitudes, which is one of the main geological challenges for sustainable worldwide development.
Scene Changes Understanding Framework Based on Graph Convolutional Networks and Swin Transformer Blocks for Monitoring LCLU Using High-Resolution Remote Sensing Images
Authors: Yang Sihan , Song Fei , Jeon Gwanggil , Sun Rui
Published: August 2022

High-resolution remote sensing images with rich land surface structure can provide data support for accurately understanding more detailed change information of land cover and land use (LCLU) at different times. In this study, we present a novel scene change understanding framework for remote sensing which includes scene classification and change detection. To enhance the feature representation of images in scene classification, a robust label semantic relation learning (LSRL) network based on EfficientNet is presented for scene classification. It consists of a semantic relation learning module based on graph convolutional networks and a joint expression learning framework based on similarity. Since the bi-temporal remote sensing image pairs include spectral information in both temporal and spatial dimensions, land cover and land use change monitoring can be improved by using the relationship between different spatial and temporal locations. Therefore, a change detection method based on swin transformer blocks (STB-CD) is presented to obtain contextual relationships between targets. The experimental results on the LEVIR-CD, NWPU-RESISC45, and AID datasets demonstrate the superiority of LSRL and STB-CD over other state-of-the-art methods.
Clustering Optimization for Triple-Frequency Combined Observations of BDS-3 Based on Improved PSO-FCM Algorithm
Authors: Qian Zhaoyong , Cao Yuhua , Sun Xiaoshuang , Ni Lei , Wang Zhiyu , Chen Xiaowei
Published: August 2022

The triple-frequency linear combination method can provide combinations with different characteristics and is one of the important methods to improve the performance of navigation services. Due to the large number of combinations and different combination performances, combinatorial clustering optimization is very important, and the efficiency of manual screening is very low. Firstly, based on the basic model, the objective equations are derived. Secondly, based on the fuzzy c-means (FCM) algorithm, three improved PSO-FCM algorithms are proposed, namely the S-PSO-FCM algorithm, L-PSO-FCM algorithm, and LOG-PSO-FCM algorithm. Thirdly, according to the different combination characteristics, the two datasets whose combined coefficients sum to 0 and 1 are emphatically discussed. Finally, the effectiveness of the improved PSO-FCM algorithms is studied based on the public dataset and the measured BeiDou-3 navigation satellite system (BDS-3) data of short baseline, long baseline, and ultra-long baseline. The results show that the performance of the proposed algorithm is better than that of the FCM algorithm, especially in short baseline and long baseline cases.
Evaluation of SAR and Optical Data for Flood Delineation Using Supervised and Unsupervised Classification
Authors: Foroughnia Fatemeh , Alfieri Silvia Maria , Menenti Massimo , Lindenbergh Roderik
Published: August 2022

Precise and accurate delineation of flooding areas with synthetic aperture radar (SAR) and multi-spectral (MS) data is challenging because flooded areas are inherently heterogeneous as emergent vegetation (EV) and turbid water (TW) are common. We addressed these challenges by developing and applying a new stepwise sequence of unsupervised and supervised classification methods using both SAR and MS data. The MS and SAR signatures of land and water targets in the study area were evaluated prior to the classification to identify the land and water classes that could be delineated. The delineation based on a simple thresholding method provided a satisfactory estimate of the total flooded area but did not perform well on heterogeneous surface water. To deal with the heterogeneity and fragmentation of water patches, a new unsupervised classification approach based on a combination of thresholding and segmentation (CThS) was developed. Since sandy areas and emergent vegetation could not be classified by the SAR-based unsupervised methods, supervised random forest (RF) classification was applied to a time series of SAR and co-event MS data, both combined and separated. The new stepwise approach was tested for determining the flood extent of two events in Italy. The results showed that all the classification methods applied to MS data outperformed the ones applied to SAR data. Although the supervised RF classification may lead to better accuracies, the CThS (unsupervised) method achieved precision and accuracy comparable to the RF, making it more appropriate for rapid flood mapping due to its ease of implementation.
LiDAR Reveals the Process of Vision-Mediated Predator–Prey Relationships
Authors: Fu Yanwen , Xu Guangcai , Gao Shang , Feng Limin , Guo Qinghua , Yang Haitao
Published: August 2022

Exploring the processes of interspecific relationships is crucial to understanding the mechanisms of biodiversity maintenance. Visually detecting interspecies relationships of large mammals is limited by the reconstruction accuracy of the environmental structure and the timely detection of animal behavior. Hence, we used backpack laser scanning (BLS) to reconstruct the high-resolution three-dimensional environmental structure to simulate the process of a predator approaching its prey, indicating that predator tigers would reduce their visibility by changing their behavior. Wild boars will nibble off about 5m of branches around the nest in order to create better visibility around the nest, adopting an anti-predation strategy to detect possible predators in advance. Our study not only points out how predator–prey relationships are affected by visibility as the environment mediates it, but also provides an operable framework for exploring interspecific relationships from a more complex dimension. Finally, this study provides a new perspective for exploring the mechanisms of biodiversity maintenance.
Electromagnetic Interference Effects of Continuous Waves on Memristors: A Simulation Study
Authors: Ma Guilei , Man Menghua , Zhang Yongqiang , Liu Shanghe
Published: August 2022

As two-terminal passive fundamental circuit elements with memory characteristics, memristors are promising devices for applications such as neuromorphic systems, in-memory computing, and tunable RF/microwave circuits. The increasingly complex electromagnetic interference (EMI) environment threatens the reliability of memristor systems. However, various EMI signals’ effects on memristors are still unclear. This paper selects continuous waves (CWs) as EMI signals. It provides a deeper insight into the interference effect of CWs on the memristor driven by a sinusoidal excitation voltage, as well as a method for investigating the EMI effect of memristors. The optimal memristor model is obtained by the exhaustive traversing of the possible model parameters, and the interference effect of CWs on memristors is quantified based on this model and the proposed evaluation metrics. Simulation results indicate that CW interference may affect the switching time, dynamic range, nonlinearity, symmetry, time to the boundary, and variation of memristance. The specific interference effect depends on the operating mode of the memristor, the amplitude, and the frequency of the CW. This research provides a foundation for evaluating EMI effects and designing electromagnetic protection for memristive neuromorphic systems.
An Adaptive Algorithm for Multipath Mitigation in GNSS Positioning with Android Smartphones
Authors: Benvenuto Lorenzo , Cosso Tiziano , Delzanno Giorgio
Published: August 2022

We present a solution for improving the robustness of GNSS positioning with Android devices. The proposed method combines an acquisition phase performed in a dedicated Android app (thus working on the edge) and a processing phase, based on a modified version of the open source library RTKLIB, performed on a dedicated server. The processing phase applies an improved version of the RTK library based on an adaptive algorithm for mitigating the multipath effect on satellite radio signals received by smartphone’s antennas. The algorithm is built on top of an extended version of the sigma-epsilon model in which weights associated to observables potentially affected by multipath errors are computed using logged data. In the paper, we will focus our attention on the architecture of the proposed solution and discuss preliminary experimental results obtained with the resulting system.
Assessing Electroencephalography as a Stress Indicator: A VR High-Altitude Scenario Monitored through EEG and ECG
Authors: Aspiotis Vasileios , Miltiadous Andreas , Kalafatakis Konstantinos , Tzimourta Katerina D. , Giannakeas Nikolaos , Tsipouras Markos G. , Peschos Dimitrios , Glavas Euripidis , Tzallas Alexandros T.
Published: August 2022

Over the last decade, virtual reality (VR) has become an increasingly accessible commodity. Head-mounted display (HMD) immersive technologies allow researchers to simulate experimental scenarios that would be unfeasible or risky in real life. An example is extreme heights exposure simulations, which can be utilized in research on stress system mobilization. Until recently, electroencephalography (EEG)-related research was focused on mental stress prompted by social or mathematical challenges, with only a few studies employing HMD VR techniques to induce stress. In this study, we combine a state-of-the-art EEG wearable device and an electrocardiography (ECG) sensor with a VR headset to provoke stress in a high-altitude scenarios while monitoring EEG and ECG biomarkers in real time. A robust pipeline for signal clearing is implemented to preprocess the noise-infiltrated (due to movement) EEG data. Statistical and correlation analysis is employed to explore the relationship between these biomarkers with stress. The participant pool is divided into two groups based on their heart rate increase, where statistically important EEG biomarker differences emerged between them. Finally, the occipital-region band power changes and occipital asymmetry alterations were found to be associated with height-related stress and brain activation in beta and gamma bands, which correlates with the results of the self-reported Perceived Stress Scale questionnaire.
Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets
Authors: Yin Hao , Li Dongguang , Wang Yue , Hong Xiaotong
Published: August 2022

In preparation for the battlefields of the future, using unmanned aerial vehicles (UAV) loaded with multisensors to track dynamic targets has become the research focus in recent years. According to the air combat tracking scenarios and traditional multisensor weighted fusion algorithms, this paper contains designs of a new data fusion method using a global Kalman filter and LSTM prediction measurement variance, which uses an adaptive truncation mechanism to determine the optimal weights. The method considers the temporal correlation of the measured data and introduces a detection mechanism for maneuvering of targets. Numerical simulation results show the accuracy of the algorithm can be improved about 66% by training 871 flight data. Based on a mature refitted civil wing UAV platform, the field experiments verified the data fusion method for tracking dynamic target is effective, stable, and has generalization ability.
A Sensor and Machine Learning-Based Sensory Management Recommendation System for Children with Autism Spectrum Disorders
Authors: Deng Lingling , Rattadilok Prapa
Published: August 2022

Sensory processing issues are one of the most common issues observed in autism spectrum disorders (ASD). Technologies that could address the issue serve a more and more important role in interventions for ASD individuals nowadays. In this study, a sensory management recommendation system was developed and tested to help ASD children deal with atypical sensory responses in class. The system employed sensor fusion and machine learning techniques to identify distractions, anxious situations, and the potential causes of these in the surroundings. Another novelty of the system included a sensory management strategy making a module based on fuzzy logic, which generated alerts to inform teachers and caregivers about children’s states and risky environmental factors. Sensory management strategies were recommended to help improve children’s attention or calm children down. The evaluation results suggested that the use of the system had a positive impact on children’s performance and its design was user-friendly. The sensory management recommendation system could work as an intelligent companion for ASD children that helps with their in-class performance by recommending management strategies in relation to the real-time information about the children’s environment.
Detection of Water pH Using Visible Near-Infrared Spectroscopy and One-Dimensional Convolutional Neural Network
Authors: Li Dengshan , Li Lina
Published: August 2022

pH is an important parameter for water quality detection. This study proposed a novel calibration regression strategy based on a one-dimensional convolutional neural network (1D-CNN) for water pH detection using visible near-infrared (Vis-NIR) spectroscopy. Two groups of Vis-NIR spectral analysis experiments of water pH detection were employed to evaluate the performance of 1D-CNN. Two conventional multivariate regression calibration methods, including partial least squares (PLS) and least squares support vector machine (LS-SVM), were introduced for comparative analysis with 1D-CNN. The successive projections algorithm (SPA) was adopted to select the feature variables. In addition, the learning mechanism of 1D-CNN was interpreted through visual feature maps by convolutional layers. The results showed that the 1D-CNN models obtained the highest prediction accuracy based on full spectra for the two experiments. For the spectrophotometer experiment, the root mean square error of prediction (RMSEP) was 0.7925, and the determination coefficient of prediction (Rp2) was 0.8515. For the grating spectrograph experiment, the RMSEP was 0.5128 and the Rp2 was 0.9273. The convolutional layers could automatically preprocess the spectra and effectively extract the spectra features. Compared with the traditional regression methods, 1D-CNN does not need complex spectra pretreatment and variable selection. Therefore, 1D-CNN is a promising regression approach, with higher prediction accuracy and better modeling convenience for rapid water pH detection using Vis-NIR spectroscopy.
Selecting the Most Important Features for Predicting Mild Cognitive Impairment from Thai Verbal Fluency Assessments
Authors: Metarugcheep Suppat , Punyabukkana Proadpran , Wanvarie Dittaya , Hemrungrojn Solaphat , Chunharas Chaipat , Pratanwanich Ploy N.
Published: August 2022

Mild cognitive impairment (MCI) is an early stage of cognitive decline or memory loss, commonly found among the elderly. A phonemic verbal fluency (PVF) task is a standard cognitive test that participants are asked to produce words starting with given letters, such as “F” in English and “ก” /k/ in Thai. With state-of-the-art machine learning techniques, features extracted from the PVF data have been widely used to detect MCI. The PVF features, including acoustic features, semantic features, and word grouping, have been studied in many languages but not Thai. However, applying the same PVF feature extraction methods used in English to Thai yields unpleasant results due to different language characteristics. This study performs analytical feature extraction on Thai PVF data to classify MCI patients. In particular, we propose novel approaches to extract features based on phonemic clustering (ability to cluster words by phonemes) and switching (ability to shift between clusters) for the Thai PVF data. The comparison results of the three classifiers revealed that the support vector machine performed the best with an area under the receiver operating characteristic curve (AUC) of 0.733 (N = 100). Furthermore, our implemented guidelines extracted efficient features, which support the machine learning models regarding MCI detection on Thai PVF data.
Model-Based Estimates for Farm Labor Quantities
Authors: Chen Lu , Cruze Nathan B. , Young Linda J.
Published: August 2022

The United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) conducts the Farm Labor Survey to produce estimates of the number of workers, duration of the workweek, and wage rates for all agricultural workers. Traditionally, expert opinion is used to integrate auxiliary information, such as the previous year’s estimates, with the survey’s direct estimates. Alternatively, implementing small area models for integrating survey estimates with additional sources of information provides more reliable official estimates and valid measures of uncertainty for each type of estimate. In this paper, several hierarchical Bayesian subarea-level models are developed in support of different estimates of interest in the Farm Labor Survey. A 2020 case study illustrates the improvement of the direct survey estimates for areas with small sample sizes by using auxiliary information and borrowing information across areas and subareas. The resulting framework provides a complete set of coherent estimates for all required geographic levels. These methods were incorporated into the official Farm Labor publication for the first time in 2020.
Regional Sustainability of Logistics Efficiency in China along the Belt and Road Initiative Considering Carbon Emissions
Authors: Ye Chong , Chen Nuo , Weng Shuangyu , Xu Zeyu
Published: August 2022

The Belt and Road Initiative puts higher requirements for the logistics industry. As one of the most energy-consuming industries, logistics is a high-carbon emission industry. Its impact on the environment cannot be ignored. In this context, how to respond to the “Belt and Road” under the concept of sustainable development, to promote the logistics industry to achieve “low consumption, low emissions, high efficiency” of regional sustainability, has become the most important development of China’s logistics industry. Therefore, based on previous research, this paper establishes an input–output index system and uses the SBM-DEA model and Malmquist index model to analyze the efficiency of low-carbon logistics in 17 provinces from 2006 to 2020, explore the overall level of the logistics and the factors affecting efficiency, and compare the efficiency in different periods and regions. Then, through the Tobit regression model, the four main factors affecting the efficiency of the logistics industry are analyzed. The results show that: (1) The highest value of low-carbon logistics efficiency of each province is 1.0000, and the lowest value is only 0.0944. The difference in logistics efficiency values among provinces is large, so there is great room for improvement and development potential. (2) From 2006 to 2020, the low-carbon logistics efficiency of the regions showed an overall upward trend, and the MI index values of each province reached or approached the DEA effective state. Among them, technological progress has a promoting effect, while scale and pure technical efficiency have hindered the efficiency growth. (3) Economic growth and industry structure have a positive effect, while energy consumption and government expenditure are negatively correlated with efficiency.
Multiobjective Optimization of Carbon Emission Reduction Responsibility Allocation in the Open-Pit Mine Production Process against the Background of Peak Carbon Dioxide Emissions
Authors: Wang Guoyu , Zhou Jinsheng
Published: August 2022

In the context of the “carbon peaking” policy for mining companies, this study was conducted to clarify the amount of carbon emission reduction required for each production process to achieve the carbon peaking target for mining companies. In this paper, after determining the fair interval of the carbon emission distribution, the fair deviation index was constructed, and a multiobjective carbon emission distribution model of the mine production process was established by combining the objectives of maximum stability and maximum efficiency with the constraint of output growth. The study found: (1) More carbon emission quotas should be allocated to the beneficiation link, while fewer carbon emission quotas should be allocated to the crushing link; (2) beneficiation, mining and transportation are all responsible for emission reduction, but crushing and blasting produced a carbon emission surplus and (3) after optimization, the carbon emission intensity in the beneficiation, mining and transportation processes was reduced. This paper argues that mining companies should increase their efforts to reduce emissions in beneficiation, mining and transportation. The study’s findings have important implications for achieving carbon emission reduction targets and refining carbon emission management in open pit mines in the context of carbon peaking.
Consumer Attitudes as Part of Lifestyle in the COVID-19 Emergency
Authors: Badora Aleksandra , Kud Krzysztof , Woźniak Marian
Published: August 2022

The pandemic brought significant changes to the functioning of society. This article examines the opinion of consumers in south-eastern Poland on lifestyle elements such as shopping preferences, physical activity, holiday preferences and others, against the background of the COVID-19 situation. The aim of this study was to identify the relationship between selected components included in the lifestyle of society in the context of the COVID-19 emergency situation. The research was conducted from 9 November 2020 to 17 January 2021. In order to identify the respondents’ attitudes and their perception of the issues discussed in this study, a questionnaire was created containing a number of theses formulations assessed by the respondents in terms of compliance with their beliefs. The evaluation was carried out using a seven-point bipolar Likert scale with a neutral value. The study was not probabilistic, therefore the inference applies only to the studied group. A total of 737 questionnaires meeting the research assumptions were collected. The form was used to identify ecological attitudes, shopping behavior, food preferences, physical activity and tourist preferences in the COVID-19 situation in which the research was conducted. Also identified were holiday destinations in 2019 and 2020, preferred diet type, and socio-demographic background: sex, age, place of residence and approximate per capita income. The research revealed that the purchasing behavior of the respondents was a predictor of their physical activity and tourist preferences. Studies have also shown that the food preferences of the respondents are an important part of their balanced lifestyle and depend on the sex of the person. The respondents preferred an active lifestyle as a form of pro-health activity when living in the situation of COVID-19. During the COVID-19 pandemic, respondents’ interest in domestic tourism also increased.
Investigating the Effects of Video-Based E-Word-of-Mouth on Consumers’ Purchase Intention: The Moderating Role of Involvement
Authors: Zhai Lingyun , Yin Pengzhen , Li Chenyang , Wang Jingjing , Yang Min
Published: August 2022

Short videos have been increasingly prevalent around the globe and have become an important channel for users to share product and service information and for marketers to attract potential customers. However, rarely have studies empirically examined the impact of product review videos posted on short video platforms on consumers’ purchase intention. Grounded in the elaboration likelihood model, this study proposes a research model to investigate how the product review video features (i.e., video information quality, product information visualization, video emotion polarity, and video publisher credibility) influence consumers’ purchase intention. Moreover, the moderating role of involvement (i.e., product involvement and video involvement) in the above-mentioned relationships have also been examined in this new research context. We empirically validate the research model with survey data. It is interesting to find that product information visualization and video publisher credibility are significantly and positively related to purchase intention. Video involvement negatively moderates the relationship between video publisher credibility and purchase intention. Furthermore, video emotion polarity negatively moderates the relationship between product information visualization and purchase intention. Both theoretical and practical implications are discussed.