bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of the Rheological Properties and Chemical Structure of Asphalt under Multiple Aging Conditions of Heat, UV and Aqueous Solution
Authors: Zou Yingxue , Pang Ling , Xu Shi , Wu Shaopeng , Yuan Miao , Amirkhanian Serji , Xu Haiqin , Lv Yang , Gao Xiang
Published: August 2022

During the service period, asphalt materials are affected by various natural factors, including heat, ultraviolet light, oxygen and moisture, etc., resulting in the reduction of pavement performance, the increase of pavement distress and shortening of service life. This study aims to investigate the aging performance of asphalt under multiple aging conditions of heat, UV and aqueous solution. Thermal-oxygen aging, UV aging and hydrostatic erosion tests were carried out sequentially on asphalt. The rheological properties, chemical structure and element composition of asphalt were characterized before and after aging, and the effect mechanism of multiple conditions was discussed. The results show that the multiple conditions of heat and UV can increase the rutting resistance and weaken the cracking resistance of asphalt. However, the effect degree of UV decreases gradually with the deepening of aging degree. Additionally, the effect of water on the physicochemical properties is less than that of UV; however, water can increase the sensitivity of physicochemical properties to UV. In summary, this study explored the short-term cycling effect of heat, light and water on asphalt and provided an idea for simulation test of asphalt under multiple aging condition.
Utilizing Fish Skin of Ikan Belida (Notopterus lopis) as a Source of Collagen: Production and Rheology Properties
Authors: Heng Tzen T. , Tey Jing Y. , Soon Kean S. , Woo Kwan K.
Published: August 2022

Collagen hydrogels have been extensively applied in biomedical applications. However, their mechanical properties are insufficient for such applications. Our previous study showed improved mechanical properties when collagen was blended with alginate. The current study aims to analyze the physico-chemical properties of collagen-alginate (CA) films such as swelling, porosity, denaturation temperature (Td), and rheology properties. Collagen was prepared from discarded fish skin of Ikan Belida (Notopterus lopis) that was derived from fish ball manufacturing industries and cross-linked with alginate from brown seaweed (Sargasum polycystum) of a local species as a means to benefit the downstream production of marine industries. CA hydrogels were fabricated with ratios (v/v) of 1:1, 1:4, 3:7, 4:1, and 7:3 respectively. FTIR spectrums of CA film showed an Amide I shift of 1636.12 cm−1 to 1634.64 cm−1, indicating collagen-alginate interactions. SEM images of CA films show a porous structure that varied from pure collagen. DSC analysis shows Td was improved from 61.26 °C (collagen) to 83.11 °C (CA 3:7). CA 4:1 swelled nearly 800% after 48 h, correlated with the of hydrogels porosity. Most CA demonstrated visco-elastic solid characteristics with greater storage modulus (G′) than lost modulus (G″). Shear thinning and non-Newtonian behavior was observed in CA with 0.4% to 1.0% (w/v) CaCl2. CA hydrogels that were derived from discarded materials shows promising potential to serve as a wound dressing or ink for bio printing in the future.
Gene Correlation Network Analysis to Identify Biomarkers of Peri-Implantitis
Authors: Sun Binghuan , Zhang Wei , Song Xin , Wu Xin
Published: August 2022

Background and Objectives: The histopathological and clinical conditions for transforming peri-implant mucositis into peri-implantitis (PI) are not fully clarified. We aim to uncover molecular mechanisms and new potential biomarkers of PI. Materials and Methods: Raw GSE33774 and GSE57631 datasets were obtained from the Gene Expression Omnibus (GEO) database. The linear models for microarray data (LIMMA) package in R software completes differentially expressed genes (DEGs). We conducted a weighted gene co-expression network analysis (WGCNA) on the top 25% of altered genes and identified the key modules associated with the clinical features of PI. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the R software. We constructed a protein–protein interaction (PPI) network through the STRING database. After that we used Cytohubba plug-ins of Cytoscape to screen out the potential hub genes, which were subsequently verified via receiver operating characteristic (ROC) curves in another dataset, GSE178351, and revalidation of genes through the DisGeNET database. Results: We discovered 632 DEGs (570 upregulated genes and 62 downregulated genes). A total of eight modules were screened by WGCNA, among which the turquoise module was most correlated with PI. The Cytohubba plug-ins were used for filtering hub genes, which are highly linked with PI development, from the candidate genes in the protein–protein interaction (PPI) network. Conclusions: We found five key genes from PI using WGCNA. Among them, ICAM1, CXCL1, and JUN are worthy of further study of new target genes, providing the theoretical basis for further exploration of the occurrence and development mechanism of PI.
Effects of Chronic Bifidobacteria Administration in Adult Male Rats on Plasma Metabolites: A Preliminary Metabolomic Study
Authors: Biggio Francesca , Fattuoni Claudia , Mostallino Maria Cristina , Follesa Paolo
Published: August 2022

Probiotics are live microorganisms distributed in the gastrointestinal tract that confer health benefits to the host when administered in adequate amounts. Bifidobacteria have been widely tested as a therapeutic strategy in the prevention and treatment of a broad spectrum of gastrointestinal disorders as well as in the regulation of the “microbiota-gut-brain axis”. Metabolomic techniques can provide details in the study of molecular metabolic mechanisms involved in Bifidobacteria function through the analysis of metabolites that positively contribute to human health. This study was focused on the effects of the chronic assumption of a mixture of Bifidobacteria in adult male rats using a metabolomic approach. Plasma samples were collected at the end of treatment and analyzed with a gas chromatography-mass spectrometry (GC-MS) platform. Partial least square discriminant analysis (PLS-DA) was performed to compare the metabolic pattern in control and probiotic-treated rats. Our results show, in probiotic-treated animals, an increase in metabolites involved in the energetic cycle, such as glucose, erythrose, creatinine, taurine and glycolic acid, as well as 3-hydroxybutyric acid. This is an important metabolite of short-chain fatty acids (SCFA) with multitasking roles in energy circuit balance, and it has also been proposed to have a key role in the prevention and treatment of neurodegenerative diseases.
Efficient Storage of Methane in Hydrate Form Using Soybean Powder
Authors: Ganteda Rama Rao , Burla Sai Kiran , Boggu Jagan Mohan Reddy , Prasad Pinnelli S. R.
Published: August 2022

Natural gas is a promising future source for the increasing energy demand. It is partially clean energy with fewer environmental impacts, and it is necessary to develop technologies to cater to the supply chain. Due to their inherent structural properties, gas hydrates or clathrate hydrates are promising materials for capturing and storing methane gas. In the present study, the experimental investigations were performed to assess the utilization of soybean powder (SBP) as a promoting additive compared to sodium dodecyl sulfate (SDS) for methane hydrate formation. The methane hydrate formation temperature and pressure with SBP are 277.8 ± 3.2 K, 7050.9 ± 76.2 kPa, similar to SDS 277.2 ± 0.3 K, 7446.3 ± 5.7 kPa in the non-stirred system. The gas uptake capacity is about 94.2 ± 4.5 v/v and 92.4 ± 4.6 v/v with SBP and SDS, which is ~60% of the practical, achievable limit. The time for the 90% of hydrate conversion is ~4.6 times higher for SBP than SDS. The more prolonged kinetics is ascribed to the complex constituents in the SBP. In contrast to the SDS solution, no foam was produced in the sample of the SBP solution. The current studies demonstrate that SBP can be utilized to develop cleaner and more effective promoters for methane hydrate formation without foam creation.
Rapid Detection of Aspergillus flavus and Quantitative Determination of Aflatoxin B1 in Grain Crops Using a Portable Raman Spectrometer Combined with Colloidal Au Nanoparticles
Authors: Wang Huiqin , Liu Mengjia , Zhang Yumiao , Zhao Huimin , Lu Wenjing , Lin Taifeng , Zhang Ping , Zheng Dawei
Published: August 2022

Aspergillus flavus and Aflatoxins in grain crops give rise to a serious threat to food security and cause huge economic losses. In particular, aflatoxin B1 has been identified as a Class I carcinogen to humans by the International Agency for Research on Cancer (IARC). Compared with conventional methods, Surface-Enhanced Raman Scattering (SERS) has paved the way for the detection of Aspergillus flavus and Aflatoxins in grain crops as it is a rapid, nondestructive, and sensitive analytical method. In this work, the rapid detection of Aspergillus flavus and quantification of Aflatoxin B1 in grain crops were performed by using a portable Raman spectrometer combined with colloidal Au nanoparticles (AuNPs). With the increase of the concentration of Aspergillus flavus spore suspension in the range of 102–108 CFU/mL, the better the combination of Aspergillus flavus spores and AuNPs, the better the enhancement effect of AuNPs solution on the Aspergillus flavus. A series of different concentrations of aflatoxin B1 methanol solution combined with AuNPs were determined based on SERS and their spectra were similar to that of solid powder. Moreover, the characteristic peak increased gradually with the increase of concentration in the range of 0.0005–0.01 mg/L and the determination limit was 0.0005 mg/L, which was verified by HPLC in ppM concentration. This rapid detection method can greatly shorten the detection time from several hours or even tens of hours to a few minutes, which can help to take effective measures to avoid causing large economic losses.
A Usability Study on Widget Design for Selecting Boolean Operations
Authors: Lopes Diogo Chambel , Mendes Helena , Portal Ricardo , de Klerk Rui , Nogueira Isabel , Lopes Daniel Simões
Published: August 2022

Applying the correct set of Boolean operations is a fundamental task in constructive solid geometry (CSG), which is a staple in automated manufacturing systems. Although textual buttons and icons are the most common interfaces to apply such operations, these require an unnecessary cognitive load that hampers the solid modeling process. This study presents VennPad, a novel CSG widget that gathers all Boolean operations under the same user interface control element and is represented as a two-set Venn diagram. Contrary to conventional CSG widgets, VennPad supports a graphical interface that gives simultaneous access to several types of Boolean operations (intersection, union, difference, symmetric difference and split). A usability study was conducted to ascertain whether VennPad is a more natural interface compared to textual buttons and icon-based widgets for different solid modeling tasks. VennPad proved to be an effective interface to perform Boolean operations. Qualitative feedback places VennPad as the preferred interface, but efficiency results are operation dependent, thus, opening the way to new design iterations.
Direct Laser Writing of SERS Hollow Fibers
Authors: Li Jiajun , Mu Yunyun , Liu Miao , Zhang Xinping
Published: August 2022

We report the direct laser writing (DLW) of surface-enhanced Raman scattering (SERS) structures on the inner wall of a hollow fiber. Colloidal gold–silver alloy nanoparticles (Au–Ag ANPs) are firstly coated onto the inner wall of a hollow fiber. A green laser beam is focused through the outer surface of the hollow fiber to interact with colloidal Au–Ag ANPs so that they become melted and aggregated on the surface of the inner wall with strong adhesion. Such randomly distributed plasmonic nanostructures with high density and small gaps favor the SERS detection of low-concentration molecules in liquids flowing through the hollow fiber. Such a SERS device also supplies a three-dimensional microcavity for the interaction between excitation laser and the target molecules. The DLW system consists mainly of the flexible connection between the motor shaft and the hollow fiber, the program-controlled translation of the hollow fiber along its symmetric axis and rotation about the axis, as well as the mechanical design and the computer control system. This DLW technique enables high production, high stability, high reproducibility, high precision, and a high-flexibility fabrication of the hollow fiber SERS device. The resultant microcavity SERS scheme enables the high-sensitivity detection of R6G molecules in ethanol with a concentration of 10−7 mol/L.
Phosphate Metabolic Inhibition Contributes to Irradiation-Induced Myelosuppression through Dampening Hematopoietic Stem Cell Survival
Authors: Wu Yiding , Liao Weinian , Chen Jun , Liu Chaonan , Zhang Shuzhen , Yu Kuan , Wang Xinmiao , Chen Mo , Wang Song , Ran Xinze , Su Yongping , Cheng Tianmin , Wang Junping , Du Changhong
Published: August 2022

Myelosuppression is a common and intractable side effect of cancer therapies including radiotherapy and chemotherapy, while the underlying mechanism remains incompletely understood. Here, using a mouse model of radiotherapy-induced myelosuppression, we show that inorganic phosphate (Pi) metabolism is acutely inhibited in hematopoietic stem cells (HSCs) during irradiation-induced myelosuppression, and closely correlated with the severity and prognosis of myelosuppression. Mechanistically, the acute Pi metabolic inhibition in HSCs results from extrinsic Pi loss in the bone marrow niche and the intrinsic transcriptional suppression of soluble carrier family 20 member 1 (SLC20A1)-mediated Pi uptake by p53. Meanwhile, Pi metabolic inhibition blunts irradiation-induced Akt hyperactivation in HSCs, thereby weakening its ability to counteract p53-mediated Pi metabolic inhibition and the apoptosis of HSCs and consequently contributing to myelosuppression progression. Conversely, the modulation of the Pi metabolism in HSCs via a high Pi diet or renal Klotho deficiency protects against irradiation-induced myelosuppression. These findings reveal that Pi metabolism and HSC survival are causally linked by the Akt/p53–SLC20A1 axis during myelosuppression and provide valuable insights into the pathogenesis and management of myelosuppression.
The Menu Served in Canadian Penitentiaries: A Nutritional Analysis
Authors: Johnson Claire , Labbé Charlotte , Lachance Anne , LeBlanc Caroline P.
Published: August 2022

The food served in Canadian penitentiaries was scrutinized following food service reform where Correctional Service Canada (CSC) created a standardized menu to feed incarcerated male individuals. Food in prison is a complex issue because penitentiaries are responsible for providing adequate nutrition to the prison population, who are vulnerable to poor health outcomes but are often seen as undeserving. This study aimed to analyse the national menu served in Canadian penitentiaries, in order to compare them with Dietary Reference Intakes (DRIs) for male adults and the internal nutritional assessment reported by CSC. The goal was to verify if the menu served was adequate and to validate CSC’s nutritional assessment. The diet analysis software NutrificR was used to analyse the 4-week cycle menu. Both analyses were within range for DRIs for most nutrients. However, some nutrients were not within target. The sodium content (3404.2 mg) was higher than the Tolerable Upper Intake Levels (UL) of 2300 mg, the ω-6 (linolenic acid) content (10.8 g) was below the AI of 14 g, and the vitamin D content (16.2 μg) was below the target of 20 μg for individuals older than 70 years. When these outliers were analysed in-depth, the menu offering was consistent with the eating habits of non-incarcerated individuals. Based on this nutritional analysis and interpretation of the results in light of the complex nature of prison food, this study concludes that CSC meets its obligation to provide a nutritionally adequate menu offering to the general population during incarceration.
Associations of Dyslipidemia with Dietary Intakes, Body Weight Status and Sociodemographic Factors among Adults in the United Arab Emirates
Authors: Ali Habiba I. , Elmi Fadima , Stojanovska Lily , Ibrahim Naser , Cheikh Ismail Leila , Al Dhaheri Ayesha S.
Published: August 2022

Research on dietary and other factors associated with dyslipidemia in the United Arab Emirates (UAE) is limited. This study assessed the association of diet, body weight and other risk factors of dyslipidemia by conducting a cross-sectional survey among adults residing in three emirates of the UAE. Validated quantitative food frequency questionnaire and the WHO STEPS Instrument were used to assess dietary intakes, body weight and dyslipidemia-related diagnosis. Composite Mediterranean Diet Score was used to assess adherence to the Mediterranean Diet (MD). Of the 610 participants, dyslipidemia was reported by 23.5% of the 319 participants who ever had blood cholesterol levels measured. Self-reported dyslipidemia was associated with increased age, higher BMI, diabetes, hypertension and cardiovascular disease. Most participants did not meet the recommendations for dietary fiber and calorie intake from saturated fats (61.3% and 81.2%, respectively). Participants with dyslipidemia reported a higher median daily intake of vegetables compared to those without dyslipidemia (p < 0.001), who also showed a significantly higher intake of refined grains and sugar-sweetened beverages (p = 0.008). Participants aged ≥50 years were more likely to have adhered to the MD compared to 18–30-year old participants (OR = 4.16; 95% CI 2.59–6.69). Non-Emiratis had higher odds of adherence to the MD compared to UAE nationals (OR = 1.46; 95%CI 1.04–2.06). Interventions targeting behavioral risk factors of dyslipidemia are warranted.
The Associations of Iron Related Biomarkers with Risk, Clinical Severity and Mortality in SARS-CoV-2 Patients: A Meta-Analysis
Authors: Zhou Shuya , Li Huihui , Li Shiru
Published: August 2022

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading rapidly around the world and has led to millions of infections and deaths. Growing evidence indicates that iron metabolism is associated with COVID-19 progression, and iron-related biomarkers have great potential for detecting these diseases. However, the results of previous studies are conflicting, and there is not consistent numerical magnitude relationship between those biomarkers and COVID-19. Thereby, we aimed to integrate the results of current studies and to further explore their relationships through a meta-analysis. We searched peer-reviewed literature in PubMed, Scopus and Web of Science up to 31 May 2022. A random effects model was used for pooling standard mean difference (SMD) and the calculation of the corresponding 95% confidence interval (CI). I2 was used to evaluate heterogeneity among studies. A total of 72 eligible articles were included in the meta-analysis. It was found that the ferritin levels of patients increased with the severity of the disease, whereas their serum iron levels and hemoglobin levels showed opposite trends. In addition, non-survivors had higher ferritin levels (SMD (95%CI): 1.121 (0.854, 1.388); Z = 8.22 p for Z < 0.001; I2 = 95.7%, p for I2 < 0.001), lower serum iron levels (SMD (95%CI): −0.483 (−0.597, −0.368), Z = 8.27, p for Z < 0.001; I2 = 0.9%, p for I2 =0.423) and significantly lower TIBC levels (SMD (95%CI): −0.612 (−0.900, −0.324), Z = 4.16, p for Z < 0.001; I2 = 71%, p for I2 = 0.016) than survivors. This meta-analysis demonstrates that ferritin, serum iron, hemoglobin and total iron banding capacity (TIBC) levels are strongly associated with the risk, severity and mortality of COVID-19, providing strong evidence for their potential in predicting disease occurrence and progression.
Evaluation of Next-Generation Sequencing Applied to Cryptosporidium parvum and Cryptosporidium hominis Epidemiological Study
Authors: Bailly Eloïse , Valot Stéphane , Vincent Anne , Duffourd Yannis , Grangier Nadège , Chevarin Martin , Costa Damien , Razakandrainibe Romy , Favennec Loïc , Basmaciyan Louise , Dalle Frédéric
Published: August 2022

Background. Nowadays, most of the C. parvum and C. hominis epidemiological studies are based on gp60 gene subtyping using the Sanger sequencing (SgS) method. Unfortunately, SgS presents the limitation of being unable to detect mixed infections. Next-Generation Sequencing (NGS) seems to be an interesting solution to overcome SgS limits. Thus, the aim of our study was to (i) evaluate the reliability of NGS as a molecular typing tool for cryptosporidiosis, (ii) investigate the genetic diversity of the parasite and the frequency of mixed infections, (iii) assess NGS usefulness in Cryptosporidium sp. outbreak investigations, and (iv) assess an interpretation threshold of sequencing data. Methods. 108 DNA extracts from positive samples were sequenced by NGS. Among them, two samples were used to validate the reliability of the subtyping obtained by NGS and its capacity to detect DNA mixtures. In parallel, 106 samples from French outbreaks were used to expose NGS to epidemic samples. Results. NGS proved suitable for Cryptosporidium sp. subtyping at the gp60 gene locus, bringing more genetic information compared to SgS, especially by working on many samples simultaneously and detecting more diversity. Conclusions. This study confirms the usefulness of NGS applied to C. hominis and C. parvum epidemiological studies, especially aimed at detecting minority variants.
Blind Restoration of Images Distorted by Atmospheric Turbulence Based on Deep Transfer Learning
Authors: Guo Yiming , Wu Xiaoqing , Qing Chun , Su Changdong , Yang Qike , Wang Zhiyuan
Published: August 2022

Removing space-time varying blur and geometric distortions simultaneously from an image is a challenging task. Recent methods (including physical-based methods or learning-based methods) commonly default the turbulence-degraded operator as a fixed convolution operator. Obviously, the assumption does not hold in practice. According to the situation that the real turbulence distorted operator has double uncertainty in space and time dimensions, this paper reports a novel deep transfer learning (DTL) network framework to address this problem. Concretely, the training process of the proposed approach contains two stages. In the first stage, the GoPro Dataset was used to pre-train the Network D1 and freeze the bottom weight parameters of the model; in the second stage, a small amount of the Hot-Air Dataset was employed for finetuning the last two layers of the network. Furthermore, residual fast Fourier transform with convolution block (Res FFT-Conv Block) was introduced to integrate both low-frequency and high-frequency residual information. Subsequently, extensive experiments were carried out with multiple real-world degraded datasets by implementing the proposed method and four existing state-of-the-art methods. In contrast, the proposed method demonstrates a significant improvement over the four reported methods in terms of alleviating the blur and distortions, as well as improving the visual quality.
Improved Dimension-Reduced Structures of 3D-STAP on Nonstationary Clutter Suppression for Space-Based Early Warning Radar
Authors: Wang Zhihao , Chen Wei , Zhang Tianfu , Xing Mengdao , Wang Yongliang
Published: August 2022

By introducing degrees of freedom (DOFs) in elevation, the elevation-azimuth-Doppler three-dimensional space–time adaptive processing (3D-STAP) methods have better performance when suppressing the nonstationary clutter caused by the Earth’s rotation in space-based early warning radar (SBEWR). However, the 3D-STAP methods use much more auxiliary beams, leading to greater demands on the training samples and heavier computational burdens than the conventional STAP methods. To solve this problem, the ideas of sum–difference beams, generalized multiple beams and Doppler-domain localization are applied here, and three improved dimension-reduced structures of 3D-STAP are proposed in this article. After analyzing the characteristics and distribution of nonstationary clutter for SBEWR, we find that the demands for auxiliary beams are different in elevation, azimuth and Doppler dimension. In addition, the suggestion to choose the number of auxiliary beams in each dimension is given. Simulation experiments are conducted to verify the analysis and evaluate the performance of the proposed methods. The simulation results show that the proposed 3D-STAP methods have better performance and lower computational burdens than typical 3D-STAP methods.
An Empirical Study of Fully Black-Box and Universal Adversarial Attack for SAR Target Recognition
Authors: Peng Bowen , Peng Bo , Yong Shaowei , Liu Li
Published: August 2022

It has been demonstrated that deep neural network (DNN)-based synthetic aperture radar (SAR) automatic target recognition (ATR) techniques are extremely susceptible to adversarial intrusions, that is, malicious SAR images including deliberately generated perturbations that are imperceptible to the human eye but can deflect DNN inference. Attack algorithms in previous studies are based on direct access to a ATR model such as gradients or training data to generate adversarial examples for a target SAR image, which is against the non-cooperative nature of ATR applications. In this article, we establish a fully black-box universal attack (FBUA) framework to craft one single universal adversarial perturbation (UAP) against a wide range of DNN architectures as well as a large fraction of target images. It is of both high practical relevance for an attacker and a risk for ATR systems that the UAP can be designed by an FBUA in advance and without any access to the victim DNN. The proposed FBUA can be decomposed to three main phases: (1) SAR images simulation, (2) substitute model training, and (3) UAP generation. Comprehensive evaluations on the MSTAR and SARSIM datasets demonstrate the efficacy of the FBUA, i.e., can achieve an average fooling ratio of 64.6% on eight cutting-edge DNNs (when the magnitude of the UAP is set to 16/255). Furthermore, we empirically find that the black-box UAP mainly functions by activating spurious features which can effectively couple with clean features to force the ATR models to concentrate on several categories and exhibit a class-wise vulnerability. The proposed FBUA aligns with the non-cooperative nature and reveals the access-free adversarial vulnerability of DNN-based SAR ATR techniques, providing a foundation for future defense against black-box threats.
Analysis of Annual Deformation Characteristics of Xilongchi Dam Using Historical GPS Observations
Authors: Xi Ruijie , Liang Yuhan , Chen Qusen , Jiang Weiping , Chen Yan , Liu Simin
Published: August 2022

Global Positioning System (GPS) has been confirmed to be a feasible tool to measure displacement of civil engineering structures. In this paper, we report on an analysis of annual deformations of a pumped-storage power station dam using historical GPS observations. Data spanning more than nine years are resolved using the GAMIT (GPS at MIT) software, and a GPS time-series method is employed to extract linear trends and annual cycle signals. It is evident that the monument located on the main dam has a linear trend, with rates of 1.0 mm/yr and 1.8 mm/yr in east and up directions, respectively. Annual cycles with amplitudes larger than 0.5 mm are shown in coordinate components at all monitoring stations. However, the annual amplitude can be 30–84% lower when a monitoring station whose monument materials and height are similar to other monitoring stations is chosen as the reference station. This suggests that differential thermal expansion of monuments could be 30% to 80% and even higher in baseline time series. A spurious offset style annual signal with 5 mm amplitude that is highly correlated with annual temperature variance is observed in the east–west direction of the monitoring station located at the east side of the reservoir. This suggests that upper ground layer movement correlated with temperature could be responsible for these annual cycles. Meanwhile, no periodic correlations are observed between the water level data and the baseline time series.
Hyperspectral Reflectance and Machine Learning Approaches for the Detection of Drought and Root–Knot Nematode Infestation in Cotton
Authors: Ramamoorthy Purushothaman , Samiappan Sathishkumar , Wubben Martin J. , Brooks John P. , Shrestha Amrit , Panda Rajendra Mohan , Reddy K. Raja , Bheemanahalli Raju
Published: August 2022

Upland cotton encounters biotic and abiotic stresses during the growing season, which significantly affects the genetic potential of stress tolerance and productivity. The root-knot nematode (RKN) (Meloidogyne incognita) is a soilborne roundworm affecting cotton production. The occurrence of abiotic stress (drought stress, DS) can alter the plant–disease (RKN) interactions by enhancing host plant sensitivity. Experiments were conducted for two years under greenhouse conditions to investigate the effect of RKN and DS and their combination using nematode-resistant (Rk-Rn-1) and nematode susceptible (M8) cotton genotypes. These genotypes were subjected to four treatments: control (100% irrigation with no nematodes), RKN (100% irrigation with nematodes), DS (50% irrigation with no nematodes), and DS + RKN (50% irrigation with nematodes). We measured treatments-induced changes in cotton (i) leaf reflectance between 350 and 2500 nm; and (ii) physiology and biomass-related traits for diagnosing plant health under combined biotic and abiotic stresses. We used a maximum likelihood classification model of hyperspectral data with different dimensionality reduction techniques to learn RKN and DS stressors on two cotton genotypes. The results indicate (i) the RKN stress can be detected at an early stage of 10 days after infestation; (ii) RKN, DS, and DS + RKN can be detected with an accuracy of over 98% using bands from 350–1000 nm and 350–2500 nm. The genotypes ‘Rk-Rn-1’and ‘M8’ showed differential responses to DS, RKN, and DS + RKN. With a few exceptions, all three stressors reduced the pigments, physiology, and biomass traits and the magnitude of reduction was higher in ‘M8’ than ‘Rk-Rn-1’. Observed impact of stressors on plant growth followed DS + RKN > DS > RKN. Similarly, leaf reflectance properties exhibited a significant difference between individual stress treatments indicating that the hyperspectral sensor data can be used to discriminate RKN-infected plants from drought-stressed plants. Thus, our study reveals that hyperspectral and physiological changes in response to RKN and DS could help diagnose plant health before visual symptoms.
A Study of the Change in Surface Parameters during the Last Four Decades in the MuUs Desert Based on Remote Sensing Data
Authors: Li Mengyao , Zhong Shouyi , Luo Youming , Liu Qiang , Li Xiuhong
Published: August 2022

As an important part of the Earth’s environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way.
ZY-1 02D Hyperspectral Imagery Super-Resolution via Endmember Matrix Constraint Unmixing
Authors: Zhang Xintong , Zhang Aiwu , Portelli Raechel , Zhang Xizhen , Guan Hongliang
Published: August 2022

This paper proposes an endmember matrix constraint unmixing method for ZY-1 02D hyperspectral imagery (HSI) super-resolution reconstruction (SRR) to overcome the low resolution of ZY-1 02D HSI. The proposed method combines spectral unmixing and adds novel smoothing constraints to traditional non-negative matrix factorization to improve details and preserve the spectral information of traditional SRR methods. The full utilization of the endmember spectral matrix and endmember abundance matrix of HSI and multispectral imagery (MSI) reconstructs the high spatial resolution and high spectral fidelity HSI. Furthermore, given the ZY-1 02D HSI infrared bands are seriously corrupted by noise, the influence of denoising on the SRR accuracy is also discussed. Experiments show that the proposed method restores spatial details and spectral information and is robust for noise, preserving more spectral information. Therefore, the proposed method is a ZY-1 02D HSI SRR method with high spatial resolution and high spectral fidelity, which improves the spatial resolution while simultaneously solving spectral mixing and provides the possibility for the data further expansion.
The Use of Sentinel-3 Altimetry Data to Assess Wind Speed from the Weather Research and Forecasting (WRF) Model: Application over the Gulf of Cadiz
Authors: Mulero-Martinez Roberto , Román-Cascón Carlos , Mañanes Rafael , Izquierdo Alfredo , Bruno Miguel , Gómez-Enri Jesús
Published: August 2022

This work presents the quality performance and the capabilities of altimetry derived wind speed (WS) retrievals from the altimeters on-board Copernicus satellites Sentinel-3A/B (S3A/B) for the spatial assessment of WS outputs from the weather research and forecasting (WRF) model over the complex area of the Gulf of Cádiz (GoC), Spain. In order to assess the applicability of the altimetry data for this purpose, comparisons between three different WS data sources over the area were evaluated: in situ measurements, S3A/B 20 Hz altimetry data, and WRF model outputs. Sentinel-3A/B WS data were compared against two different moored buoys to guarantee the quality of the data over the GoC, resulting in satisfying scores (average results: RMSE = 1.21 m/s, r = 0.93 for S3A and RMSE = 1.36 m/s, r = 0.89 for S3B). Second, the WRF model was validated with in situ data from four different stations to ensure the correct performance over the area. Finally, the spatial variability of the WS derived from the WRF model was compared with the along-track altimetry-derived WS. The analysis was carried out under different wind synoptic conditions. Qualitative and quantitative results (average RMSE < 1.0 m/s) show agreement between both data sets under low/high wind regimes, proving that the spatial coverage of satellite altimetry enables the spatial assessment of high-resolution numerical weather prediction models in complex water-covered zones.
Extraction of Liana Stems Using Geometric Features from Terrestrial Laser Scanning Point Clouds
Authors: Han Tao , Sánchez-Azofeifa Gerardo Arturo
Published: August 2022

Lianas are self-supporting systems that are increasing their dominance in tropical forests due to climate change. As lianas increase tree mortality and reduce tree growth, one key challenge in ecological remote sensing is the separation of a liana and its host tree using remote sensing techniques. This separation can provide essential insights into how tropical forests respond, from the point of view of ecosystem structure to climate and environmental change. Here, we propose a new machine learning method, derived from Random Forest (RF) and eXtreme Gradient Boosting (XGBoosting) algorithms, to separate lianas and trees using Terrestrial Laser Scanning (TLS) point clouds. We test our method on five tropical dry forest trees with different levels of liana infestation. First, we use a multiple radius search method to define the optimal radius of six geometric features. Second, we compare the performance of RF and XGBoosting algorithms on the classification of lianas and trees. Finally, we evaluate our model against independent data collected by other projects. Our results show that the XGBoosting algorithm achieves an overall accuracy of 0.88 (recall of 0.66), and the RF algorithm has an accuracy of 0.85 (recall of 0.56). Our results also show that the optimal radius method is as accurate as the multiple radius method, with F1 scores of 0.49 and 0.48, respectively. The RF algorithm shows the highest recall of 0.88 on the independent data. Our method provides a new flexible approach to extracting lianas from 3D point clouds, facilitating TLS to support new studies aimed to evaluate the impact of lianas on tree and forest structures using point clouds.
A Truck-Borne System Based on Cold Atom Gravimeter for Measuring the Absolute Gravity in the Field
Authors: Wang Helin , Wang Kainan , Xu Yunpeng , Tang Yituo , Wu Bin , Cheng Bing , Wu Leyuan , Zhou Yin , Weng Kanxing , Zhu Dong , Chen Peijun , Zhang Kaijun , Lin Qiang
Published: August 2022

The cold atom gravimeter (CAG) has proven to be a powerful quantum sensor for the high-precision measurement of gravity field, which can work stably for a long time in the laboratory. However, most CAGs cannot operate in the field due to their complex structure, large volume and poor environmental adaptability. In this paper, a home-made, miniaturized CAG is developed and a truck-borne system based on it is integrated to measure the absolute gravity in the field. The measurement performance of this system is evaluated by applying it to measurements of the gravity field around the Xianlin reservoir in Hangzhou City of China. The internal and external coincidence accuracies of this measurement system were demonstrated to be 35.4 μGal and 76.7 μGal, respectively. Furthermore, the theoretical values of the measured eight points are calculated by using a forward modeling of a local high-resolution digital elevation model, and the calculated values are found to be in good agreement with the measured values. The results of this paper show that this home-made, truck-borne CAG system is reliable, and it is expected to improve the efficiency of gravity surveying in the field.
OFDM Network Optimization Using a QPSK Based on a Wind-Driven Genetic Algorithm
Authors: Sun Yanxia , Shambare Chikomborero , Imoru OdunAyo
Published: August 2022

Quadrature phase shift keying (QPSK) is a digital modulation technique that transmits data at a constant frequency whilst varying the phases of the carrier signal. QPSK is one of the fundamental modulation schemes for orthogonal frequency division multiplexing systems (OFDM). It is a stable modulation technique with good spectral efficiency. However, during transmission, the carrier signal can undergo numerous phase changes. This creates phase ambiguity problems at the receiver end. This results in inter-symbol interference (ISI) and a high bit error rate (BER). In this paper, the wind-driven optimization was incorporated into the genetic algorithm (GA) as its population selection function. This hybrid algorithm was used to determine the phase assignments for the QPSK. The developed QPSK was implemented on an OFDM network and the message signal was recovered at more than 92% accuracy in a noisy Rayleigh fading channel and 100% accuracy in a noiseless channel. The enhancements greatly mitigated phase ambiguity and bit errors.
Device-Free Multi-Location Human Activity Recognition Using Deep Complex Network
Authors: Ding Xue , Hu Chunlei , Xie Weiliang , Zhong Yi , Yang Jianfei , Jiang Ting
Published: August 2022

Wi-Fi-based human activity recognition has attracted broad attention for its advantages, which include being device-free, privacy-protected, unaffected by light, etc. Owing to the development of artificial intelligence techniques, existing methods have made great improvements in sensing accuracy. However, the performance of multi-location recognition is still a challenging issue. According to the principle of wireless sensing, wireless signals that characterize activity are also seriously affected by location variations. Existing solutions depend on adequate data samples at different locations, which are labor-intensive. To solve the above concerns, we present an amplitude- and phase-enhanced deep complex network (AP-DCN)-based multi-location human activity recognition method, which can fully utilize the amplitude and phase information simultaneously so as to mine more abundant information from limited data samples. Furthermore, considering the unbalanced sample number at different locations, we propose a perception method based on the deep complex network-transfer learning (DCN-TL) structure, which effectively realizes knowledge sharing among various locations. To fully evaluate the performance of the proposed method, comprehensive experiments have been carried out with a dataset collected in an office environment with 24 locations and five activities. The experimental results illustrate that the approaches can achieve 96.85% and 94.02% recognition accuracy, respectively.
Low Profile Monopole Meander Line Antenna for WLAN Applications
Authors: Ibrahim Husam Hamid , Singh Mandeep Jit , Al-Bawri Samir Salem , Ibrahim Sura Khalil , Islam Mohammad Tariqul , Soliman Mohamed S. , Islam Md Shabiul
Published: August 2022

An antenna assumes a significant role in expanding the levels of communication to meet the demands of contemporary technologically based industry and private data services. In this paper, a printed compact meander line patch antenna array for wireless local-area network (WLAN) applications in the frequency span of 2.3685–2.4643 GHz is presented. The impedance matching of the antenna is generated by applying a partial rectangular-shaped ground plane backside of the meander line antenna. The proposed antenna evolved on the Rogers RT5880 substrate with a dielectric permittivity of 2.2, and the height of the substrate was 1.575 mm to accomplish the lowest possible return loss. The proposed antenna was developed to achieve particular outcomes, for example, voltage standing wave ratio (VSWR) 1.32, reflection coefficient 20 dB with a bandwidth of 94.2 MHz, a gain of 2.8 dBi, and an efficacy measurement of 97%. This antenna is appropriate for WLAN applications that utilize a 2.4 GHz resonance frequency. The overall dimensions of the antenna are 15 mm × 90.86 mm.
Highly Sensitive Electrochemical Detection of Azithromycin with Graphene-Modified Electrode
Authors: Pogăcean Florina , Varodi Codruţa , Măgeruşan Lidia , Stefan-van Staden Raluca-Ioana , Pruneanu Stela
Published: August 2022

An electrochemical cell containing two graphite rods was filled with the appropriate electrolyte (0.2 M ammonia + 0.2 M ammonium sulphate) and connected to the exfoliation system to synthesize graphene (EGr). A bias of 7 V was applied between the anode and cathode for 3 h. After synthesis, the morphology and structure of the sample was characterized by SEM, XRD, and FTIR techniques. The material was deposited onto the surface of a glassy carbon (GC) electrode (EGr/GC) and employed for the electrochemical detection of azithromycin (AZT). The DPV signals recorded in pH 5 acetate containing 6 × 10−5 M AZT revealed significant differences between the GC and EGr/GC electrodes. For EGr/GC, the oxidation peak was higher and appeared at lower potential (+1.12 V) compared with that of bare GC (+1.35 V). The linear range for AZT obtained with the EGr/GC electrode was very wide, 10−8–10−5 M, the sensitivity was 0.68 A/M, and the detection limit was 3.03 × 10−9 M. It is important to mention that the sensitivity of EGr/GC was three times higher than that of bare GC (0.23 A/M), proving the advantages of using graphene-modified electrodes in the electrochemical detection of AZT.
Adaptive Null Widening Beamforming Algorithm in Spatially Correlated Color Noise
Authors: Xiao Shijing , Li Bin , Wang Qing
Published: August 2022

Under the background of spatially correlated color noise, the incidence angle of a jamming signal in a high-speed moving platform rapidly changes, which leads to the degradation of the anti-interference performance and the waveform distortion of the adaptive beamformer. In this paper, a projection-constrained null broadening beamforming algorithm based on the Toeplitz matrix structure is proposed. The algorithm first extracts the subspace of the covariance matrix of the steering vector of the pre-determined extended angle interval and constructs the constraint matrix and the projection transformation matrix. The received signal covariance matrix with a Toeplitz structure is then constructed using the correlation number between each array element and the pre-set reference array element. Finally, the constructed covariance matrix is transformed through projection, and the weight of each array element is constrained by the constraint matrix. The theoretical optimal solution of adaptive wide null beamforming in spatially correlated color noise is obtained. The simulation results show that, compared with the existing robust adaptive beamforming algorithms, the proposed algorithm can efficiently improve the distortion of adaptive anti-jamming beams, and can achieve null broadening in the jamming direction under the condition of spatially correlated color noise, which improves the output signal to the interference-plus-noise ratio (SINR) of the adaptive beamformer.
Microfluidic-Assisted Human Cancer Cells Culturing Platform for Space Biology Applications
Authors: Krakos (Podwin) Agnieszka , Jarosz Joanna , Śniadek Patrycja , Psurski Mateusz , Graja Adrianna , Białas Marcin , Oliszewska Ewa , Wietrzyk Joanna , Walczak Rafał , Dziuban Jan
Published: August 2022

In the paper, the lab-on-chip platform applicable for the long-term cultivation of human cancer cells, as a solution meeting the demands of the CubeSat biological missions, is presented. For the first time, the selected cancer cell lines—UM-UC-3 and RT 112 were cultured on-chip for up to 50 days. The investigation was carried out in stationary conditions (without medium microflow) in ambient temperature and utilizing the microflow perfusion system in the incubation chamber assuring typical cultivation atmosphere (37 °C). All the experiments were performed to imitate the conditions that are provided before the biological mission starts (waiting for the rocket launch) and when the actual experiment is initialized on a CubeSat board in space microgravity. The results of the tests showed appropriate performance of the lab-on-chip platform, especially in the context of material and technological biocompatibility. Cultured cells were characterized by adequate morphology—high attachment rate and visible signs of proliferation in each of the experimental stage. These results are a good basis for further tests of the lab-on-chip platform in both terrestrial and space conditions. At the end of the manuscript, the authors provide some considerations regarding a potential 3-Unit CubeSat biological mission launched with Virgin Orbit company. The lab-on-chip platform was modelled to fit a 2-Unit autonomous laboratory payload.