bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Ampelometry: Morphometric Characterization of the Grape (Vitis spp.) Leaf
Authors: Bodor-Pesti Péter , Taranyi Dóra , Deák Tamás , Nyitrainé Sárdy Diána Ágnes , Varga Zsuzsanna
Published: January 2023

Grape (Vitis spp.) is one of the most important horticultural crops, cultivated worldwide on more than 7.3 million hectares for various purposes such as winemaking, fresh fruit consumption, rootstock, and ornamental plants. Based on the inter- and intraspecific morphological variability, several descriptor lists, manuals and ampelographic studies are available for identification. Among the organs, leaves have the most traits, while the young shoot, bunch and berry are also important in the characterization of the genotypes. Vitis species and cultivars are described by leaf morphological characterization developed in many ways for the identification of genotypes, to clarify synonymies and distinct clones or evaluate the diversity of wild Vitis taxa. Morphometric—also known as ampelometric—evaluation has an extensive background in the literature. However, for some reasons, only a part of the literature is cited, despite its significant scientific value. In this paper, we summarize the efforts of metric characterization of the grapevine leaf with the introduction of the scientific objectives and reviewing the studies showing the innovations in phenotyping during the past 120 years.
Dissection of Hyperspectral Reflectance to Estimate Photosynthetic Characteristics in Upland Cotton (Gossypium hirsutum L.) under Different Nitrogen Fertilizer Application Based on Machine Learning Algorithms
Authors: Han Peng , Zhai Yaping , Liu Wenhong , Lin Hairong , An Qiushuang , Zhang Qi , Ding Shugen , Zhang Dawei , Pan Zhenyuan , Nie Xinhui
Published: January 2023

Hyperspectral technology has enabled rapid and efficient nitrogen monitoring in crops. However, most approaches involve direct monitoring of nitrogen content or physiological and biochemical indicators directly related to nitrogen, which cannot reflect the overall plant nutritional status. Two important photosynthetic traits, the fraction of absorbed photosynthetically active radiation (FAPAR) and the net photosynthetic rate (Pn), were previously shown to respond positively to nitrogen changes. Here, Pn and FAPAR were used for correlation analysis with hyperspectral data to establish a relationship between nitrogen status and hyperspectral characteristics through photosynthetic traits. Using principal component and band autocorrelation analyses of the original spectral reflectance, two band positions (350–450 and 600–750 nm) sensitive to nitrogen changes were obtained. The performances of four machine learning algorithm models based on six forms of hyperspectral transformations showed that the light gradient boosting machine (LightGBM) model based on the hyperspectral first derivative could better invert the Pn of function–leaves in cotton, and the random forest (RF) model based on hyperspectral first derivative could better invert the FAPAR of the cotton canopy. These results provide advanced metrics for non–destructive tracking of cotton nitrogen status, which can be used to diagnose nitrogen nutrition and cotton growth status in large farms.
Progress and Prospects of the Molecular Basis of Soybean Cold Tolerance
Authors: Tsegaw Mesfin , Zegeye Workie Anley , Jiang Bingjun , Sun Shi , Yuan Shan , Han Tianfu , Wu Tingting
Published: January 2023

Cold stress is a major factor influencing the geographical distribution of soybean growth and causes immense losses in productivity. Understanding the molecular mechanisms that the soybean has undergone to survive cold temperatures will have immense value in improving soybean cold tolerance. This review focuses on the molecular mechanisms involved in soybean response to cold. We summarized the recent studies on soybean cold-tolerant quantitative trait loci (QTLs), transcription factors, associated cold-regulated (COR) genes, and the regulatory pathways in response to cold stress. Cold-tolerant QTLs were found to be overlapped with the genomic region of maturity loci of E1, E3, E4, pubescence color locus of T, stem growth habit gene locus of Dt1, and leaf shape locus of Ln, indicating that pleiotropic loci may control multiple traits, including cold tolerance. The C-repeat responsive element binding factors (CBFs) are evolutionarily conserved across species. The expression of most GmDREB1s was upregulated by cold stress and overexpression of GmDREB1B;1 in soybean protoplast, and transgenic Arabidopsis plants can increase the expression of genes with the DRE core motif in their promoter regions under cold stress. Other soybean cold-responsive regulators, such as GmMYBJ1, GmNEK1, GmZF1, GmbZIP, GmTCF1a, SCOF-1 and so on, enhance cold tolerance by regulating the expression of COR genes in transgenic Arabidopsis. CBF-dependent and CBF-independent pathways are cross-talking and work together to activate cold stress gene expression. Even though it requires further dissection for precise understanding, the function of soybean cold-responsive transcription factors and associated COR genes studied in Arabidopsis shed light on the molecular mechanism of cold responses in soybeans and other crops. Furthermore, the findings may also provide practical applications for breeding cold-tolerant soybean varieties in high-latitude and high-altitude regions.
Identification of miRNAs Involving Potato-Phytophthora infestans Interaction
Authors: Luo Ming , Sun Xinyuan , Xu Meng , Tian Zhendong
Published: January 2023

sRNAs (small RNAs) play an important role in regulation of plant immunity against a variety of pathogens. In this study, sRNA sequencing analysis was performed to identify miRNAs (microRNAs) during the interaction of potato and Phytophthora infestans. Totally, 171 potato miRNAs were identified, 43 of which were annotated in the miRNA database and 128 were assigned as novel miRNAs in this study. Those potato miRNAs may target 878 potato genes and half of them encode resistance proteins. Fifty-three potato miRNAs may target 194 P. infestans genes. Three potato miRNAs (novel 72, 133, and 140) were predicted to have targets only in the P. infestans genome. miRNAs transient expression and P. infestans inoculation assay showed that miR396, miR166, miR6149-5P, novel133, or novel140 promoted P. infestans colonization, while miR394 inhibited colonization on Nicotiana benthamiana leaves. An artificial miRNA target (amiRNA) degradation experiment demonstrated that miR394 could target both potato gene (PGSC0003DMG400034305) and P. infestans genes. miR396 targets the multicystatin gene (PGSC0003DMG400026899) and miR6149-5p could shear the galactose oxidase F-box protein gene CPR30 (PGSC0003DMG400021641). This study provides new information on the aspect of cross-kingdom immune regulation in potato-P. infestans interaction at the sRNAs regulation level.
Combined Effect of the Potassium Dose and Plant Biofertilization by Acinetobacter calcoaceticus on the Growth, Mineral Content, Nutritional Quality, Antioxidant Activity, and Metabolomic Features of Tomatillo Fruits (Physalis ixocarpa Brot.)
Authors: Ramírez-Cariño Heriberto F. , Ochoa-Velasco Carlos E. , Guerrero-Analco José A. , Monribot-Villanueva Juan L. , Calderón-García Concepción , González-Terreros Elizabeth , Escamirosa-Tinoco Cirenio , Morales Isidro , Valadez-Blanco Rogelio
Published: January 2023

An Acinetobacter calcoaceticus UTMR2 strain was evaluated in tomatillo plants (Physalis ixocarpa Brot.) using a factorial design with different potassium doses (100, 75, 50 and 0% of the recommended dose). In addition to the agronomic parameters, an analysis of the physicochemical, antioxidant, and metabolomic properties of the fruit was performed. The application of the inoculant affected several parameters of the plant (chlorophyll, weight, and contents of several mineral elements) as well as of the fruit (yield, maturity index, FRAP antioxidant capacity, and contents of protein, fiber, and fat). A multivariate analysis was performed by means of a PCA and a heatmap, indicating that the inoculant induced a strong modulating activity in tomatillo plants for the evaluated parameters, with a remarkable effect at low K doses (0 and 50%). The inoculated treatment at 75% of the K dose resulted in similar plant and fruit characteristics to the fully fertilized control. On the other hand, the biofertilized treatment with no K addition resulted in the highest values in the plant and fruit parameters. In addition, from the metabolomics analysis of the fruits at 75% of the K dose, the up-regulation of 4,4″-bis(N-feruloyl)serotonin, salvianolic acid K, and chlorogenic acid was observed, which may have a role in anti-senescence and resistance mechanisms. In conclusion, the rhizobacterial strain had a positive effect on plant growth, nutritional quality, bioactive compounds, and antioxidant activity of tomatillo fruits at reduced doses of K fertilizer, which gives support for its consideration as an effective biofertilizer strain.
Genomic Sequence of Canadian Chenopodium berlandieri: A North American Wild Relative of Quinoa
Authors: Samuels Mark E. , Lapointe Cassandra , Halwas Sara , Worley Anne C.
Published: January 2023

Chenopodium berlandieri (pitseed goosefoot) is a widespread native North American plant, which was cultivated and consumed by indigenous peoples prior to the arrival of European colonists. Chenopodium berlandieri is closely related to, and freely hybridizes with the domesticated South American food crop C. quinoa. As such it is a potential source of wild germplasm for breeding with C. quinoa, for improved quinoa production in North America. The C. berlandieri genome sequence could also be a useful source of information for improving quinoa adaptation. To this end, we first optimized barcode markers in two chloroplast genes, rbcL and matK. Together these markers can distinguish C. berlandieri from the morphologically similar Eurasian invasive C. album (lamb’s quarters). Second, we performed whole genome sequencing and preliminary assembly of a C. berlandieri accession collected in Manitoba, Canada. Our assembly, while fragmented, is consistent with the expected allotetraploid structure containing diploid Chenopodium sub-genomes A and B. The genome of our accession is highly homozygous, with only one variant site per 3–4000 bases in non-repetitive sequences. This is consistent with predominant self-fertilization. As previously reported for the genome of a partly domesticated Mexican accession of C. berlandieri, our genome assembly is similar to that of C. quinoa. Somewhat unexpectedly, the genome of our accession had almost as many variant sites when compared to the Mexican C. berlandieri, as compared to C. quinoa. Despite the overall similarity of our genome sequence to that of C. quinoa, there are differences in genes known to be involved in the domestication or genetics of other food crops. In one example, our genome assembly appears to lack one functional copy of the SOS1 (salt overly sensitive 1) gene. SOS1 is involved in soil salinity tolerance, and by extension may be relevant to the adaptation of C. berlandieri to the wet climate of the Canadian region where it was collected. Our genome assembly will be a useful tool for the improved cultivation of quinoa in North America.
Quali–Quantitative Fingerprinting of the Fruit Extract of Uapaca bojeri Bail. (Euphorbiaceae) and Its Antioxidant, Analgesic, Anti-Inflammatory, and Antihyperglycemic Effects: An Example of Biodiversity Conservation and Sustainable Use of Natural Resources in Madagascar
Authors: Rakotonirina Finiavana Mihary Valisoa , Donno Dario , Razafindrakoto Zoarilala Rinah , Tombozara Nantenaina , Rafanomezantsoa Roger Marie , Andrianjara Charles , Ramanitrahasimbola David , Beccaro Gabriele Loris
Published: January 2023

Antioxidants are important supplements for the human body for their roles in human life for the maintenance of homeostasis. Tapia fruits (Uapaca bojeri) are used by the riverain population of the Tapia forests in Madagascar as complementary foods. This study aims to quantify the main antioxidants in the U. bojeri fruits to verify their contribution to the enhancement of their anti-inflammatory and antihyperglycemic effects. Standard phytochemical screening was used for qualitative analysis, while spectrophotometric (TPC, TAC, and TFC) and chromatographic analyses (HPLC) were used to quantify several phytochemicals in U. bojeri fruits. The antioxidant activity was evaluated using DPPH and FRAP assays. The writhing test was used for the analgesic effects, the carrageenan-induced paw edema was used for the anti-inflammatory activity, and OGTT was used to test the anti-hyperglycemia property of the MEUB in mice. Several phytocompounds were detected and quantified in the fruits, including succinic acid (67.73%) as the main quantified compound. Fruits exerted a good antioxidant capacity and showed analgesic, anti-inflammatory, and antihyperglycemic activities in mice. Isolation of the bioactive compounds should be carried out to confirm these pharmacological properties and develop health-promoting food products or medicinal applications derived from this species.
Preparation of Heavy Metal Trapping Flocculant Polyacrylamide–Glutathione and Its Application for Cadmium Removal from Water
Authors: Ding Wenjie , Wang Yunyan , Zeng Weizhi , Xu Hui , Chen Bingxin
Published: January 2023

In this study, a heavy metal trapping gel with multiple ligand groups was prepared for the first time using response surface methodology. The gel was produced by condensing and grafting glutathione as a grafting monomer onto the main polyacrylamide chain, based on the Mannich reaction mechanism with formaldehyde. FTIR, SEM, TG-DSC, and zeta potentials were used to characterize the gel. The results demonstrated that the gel was morphologically folded and porous, with a net-like structure, which enhanced its net trapping and sweeping abilities, and that glutathione was used to provide sulfhydryl groups to boost the metal trapping ability of polyacrylamide. Coagulation experiments showed that the highest efficiency of the removal of Cd ions from water samples was achieved when the concentration of polyacrylamide–glutathione was 84.48 mgL−1, the concentration of Cd was 10.0 mgL−1, the initial turbidity was 10.40 NTU, and the initial pH was 9.0. Furthermore, the presence of two cations, Cu and Zn, had an inhibitory effect on the removal of Cd ions. In addition, analysis of the zeta potential revealed the flocculation of polyacrylamide–glutathione. The flocculation mechanism of glutathione is mainly chelation, adsorption bridging, and netting sweeping.
Nanocomposite Membranes for PEM-FCs: Effect of LDH Introduction on the Physic-Chemical Performance of Various Polymer Matrices
Authors: Rehman Muhammad Habib Ur , Lufrano Ernestino , Simari Cataldo
Published: January 2023

This is a comparative study to clarify the effect of the introduction of layered double hydroxide (LDH) into various polymer matrices. One perfluorosulfonic acid polymer, i.e., Nafion, and two polyaromatic polymers such as sulfonated polyether ether ketone (sPEEK) and sulfonated polysulfone (sPSU), were used for the preparation of nanocomposite membranes at 3 wt.% of LDH loading. Thereafter, the PEMs were characterized by X-ray diffraction (XRD) and dynamic mechanical analysis (DMA) for their microstructural and thermomechanical features, whereas water dynamics and proton conductivity were investigated by nuclear magnetic resonance (PFG and T1) and EIS spectroscopies, respectively. Depending on the hosting matrix, the LDHs can simply provide additional hydrophilic sites or act as physical crosslinkers. In the latter case, an impressive enhancement of both dimensional stability and electrochemical performance was observed. While pristine sPSU exhibited the lowest proton conductivity, the sPSU/LDH nanocomposite was able to compete with Nafion, yielding a conductivity of 122 mS cm−1 at 120 °C and 90% RH with an activation energy of only 8.7 kJ mol−1. The outcome must be ascribed to the mutual and beneficial interaction of the LDH nanoplatelets with the functional groups of sPSU, therefore the choice of the appropriate filler is pivotal for the preparation of highly-performing composites.
Accelerated Simple Preparation of Curcumin-Loaded Silk Fibroin/Hyaluronic Acid Hydrogels for Biomedical Applications
Authors: Chaala Mohamed , Sebba Fatima Zohra , Fuster Marta G. , Moulefera Imane , Montalbán Mercedes G. , Carissimi Guzmán , Víllora Gloria
Published: January 2023

The development of new biomaterials from natural fibres in the field of biomedicine have attracted great interest in recent years. One of the most studied fibres has been silk fibroin produced by the Bombyx mori worm, due to its excellent mechanical properties and its biodegradability and bioavailability. Among the different biomaterials that can be prepared from silk fibroin, hydrogels have attracted considerable attention due to their potential use in different fields, such as scaffolding, cell therapy and biomedical application. Hydrogels are essentially a three-dimensional network of flexible polymer chains that absorb considerable amounts of water and can be loaded with drugs and/or cells inside to be used in a wide variety of applications. Here we present a simple sonication process for the preparation of curcumin-hyaluronic acid-silk fibroin hydrogels. Different grades of hydrogels were prepared by controlling the relative amounts of their components. The hydrogels were physically and morphologically characterised by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and field emission scanning electron microscopy (FESEM) and their biological activity was tested in terms of cell viability in a fibroblast cell line.
A Star-Shaped Copolymer with Tetra-Hydroxy-Phenylporphyrin Core and Four PNIPAM-b-PMAGA Arms for Targeted Photodynamic Therapy
Authors: Liu Changling , Wang Yirong , Wang Siyu , Xu Pengcheng , Liu Renning , Han Dandan , Wei Yen
Published: January 2023

The novel thermosensitive star-shaped tetra-hydroxy-phenylporphyrin-cored (THPP) double hydrophilic poly(N-isopropylacrylamide)-b-poly(methylacrylamide glucose) block copolymers (THPP-(PNIPAM-b-PMAGA)4) were synthesized via the reversible addition-fragmentation chain transfer (RAFT) polymerization. Notably, the low critical solution temperatures (LCSTs) of THPP-(PNIPAM-b-PMAGA)4 were above normal body temperature (37 °C) which depended on the hydrophilic PMAGA contents of copolymers. When the temperature was higher than the LCST of the copolymer, the copolymer could be neutralized into micelles in aqueous and could be coated with antitumor drugs and released around tumor cells. The MTT study indicated that THPP-(PNIPAM-b-PMAGA)4 had a low toxicity to L929 and HeLa cells in the absence of light. However, THPP-(PNIPAM-b-PMAGA)4 showed a high toxicity with HeLa cells under light irradiation which could be used as a potential photosensitizer for photodynamic therapy (PDT). In addition, THPP-(PNIPAM-b-PMAGA)4 showed specific a recognition function with Concanavalin A (Con A) to achieve active targeted drug delivery. This work provides a new approach for the development of tumor targeting and chemotherapy/PDT.
Influence of Particle Size and Bulk Density on Sound Absorption Performance of Oil Palm Frond-Reinforced Composites Particleboard
Authors: Istana Budi , Batan I Made Londen , Sutikno  , Khem Samrith , Ubaidillah U , Yahya Iwan
Published: January 2023

The present study deals with the sound absorption performance of natural fibres from the oil palm frond (OPF), mainly considered agricultural waste. Therefore, this study aimed to investigate the sound absorption performance of OPF fibre-reinforced composite under normal incidence sound. The materials used were OPF particles and urea-formaldehyde was used as an adhesive. The particleboards were produced with three particle sizes and four target densities. The absorption coefficient of normal incidence sound (αn) was tested using an impedance tube. The effects of particle size and bulk density were also evaluated. The findings reveal thatαn exceeded 0.45 at 1000 Hz and could reach 0.95 above 3.3 kHz. This occurred when the bulk density of the OPF composite particleboards ranged between 0.3–0.4 g/cm3, and the particle size varied between medium to coarse. The results also indicated that the absorption frequency and the degree of αn significantly increased as the bulk density decreased. Therefore, OPF fibres can be used to create sound-absorbing composite particleboards.
Confinement-Induced Fractionation and Liquid–Liquid Phase Separation of Polymer Mixtures
Authors: Nikoubashman Arash , Yanagisawa Miho
Published: January 2023

The formation of (bio)molecular condensates via liquid–liquid phase separation in cells has received increasing attention, as these aggregates play important functional and regulatory roles within biological systems. However, the majority of studies focused on the behavior of pure systems in bulk solutions, thus neglecting confinement effects and the interplay between the numerous molecules present in cells. To better understand the physical mechanisms driving condensation in cellular environments, we perform molecular simulations of binary polymer mixtures in spherical droplets, considering both monodisperse and polydisperse molecular weight distributions for the longer polymer species. We find that confinement induces a spatial separation of the polymers by length, with the longer ones moving to the droplet center. This partitioning causes a distinct increase in the local polymer concentration near the droplet center, which is more pronounced in polydisperse systems. Consequently, the confined systems exhibit liquid–liquid phase separation at average polymer concentrations where bulk systems are still in the one-phase regime.
The Influence of Alkali Content on the Hydration of the Slag-Based Geopolymer: Relationships between Resistivity, Setting, and Strength Development
Authors: Fang Yuan , Zhuang Kunde , Zheng Dapeng , Guo Weitao
Published: January 2023

This study investigated the influence of alkali content on the early-age hydration process of slag-based geopolymer and the feasibility of non-destructive resistivity. Results showed that there existed a threshold of alkali content in adjusting the early-age hydration. Initially, increasing the alkali content tended to accelerate the dissolution period (detected by resistivity and heat release rate) and resulted in a denser microstructure (detected by TEM). When the alkali content surpassed 6 wt%, the increasing alkali content mitigated the structural development of a slag-based geopolymer, as it lowered the liquid water content and caused local precipitation, which trapped the early-age ions transmission and, therefore, the later-age mechanical development was inhibited. It was proven that the resistivity acted as a linkage among the reaction degree, workability, and strength development.
Facile Preparation of Cobalt Nanoparticles Encapsulated Nitrogen-Doped Carbon Sponge for Efficient Oxygen Reduction Reaction
Authors: Leng Ying , Jin Kai , Wang Tian , Sun Hui
Published: January 2023

The facile preparation of non-noble metal nanoparticle loaded carbon nanomaterials is promising for efficient oxygen reduction reaction (ORR) electrocatalysis. Herein, a facile preparation strategy is proposed to prepare nitrogen-doped carbon sponge loaded with fine cobalt nanoparticles by the direct pyrolysis of the cobalt ions adsorbed polymeric precursor. The polymeric sponge precursor with continuous framework and high porosity is formed by the self-assembly of a poly(amic acid). Taking advantage of the negatively charged surface and porous structure, cobalt ions can be efficiently adsorbed into the polymeric sponge. After pyrolysis, fine cobalt nanoparticles covered by carbon layers are formed, while the sponge-like structure of the precursor is also well-preserved in order to give cobalt nanoparticles loaded nitrogen-doped carbon sponges (Co/CoO@NCS) with a high loading content of 44%. The Co/CoO@NCS exhibits promising catalytic activity toward ORR with a half-wave potential of 0.830 V and a limiting current density of 4.71 mA cm−2. Overall, we propose a facile polymer self-assembly strategy to encapsulate transition metal nanoparticles with high loading content on a nitrogen-doped carbon sponge for efficient ORR catalysis.
Quantitative Characterization of Shallow Marine Sediments in Tight Gas Fields of Middle Indus Basin: A Rational Approach of Multiple Rock Physics Diagnostic Models
Authors: Ali Muhammad , Ashraf Umar , Zhu Peimin , Ma Huolin , Jiang Ren , Lei Guo , Ullah Jar , Ali Jawad , Vo Thanh Hung , Anees Aqsa
Published: January 2023

For the successful discovery and development of tight sand gas reserves, it is necessary to locate sand with certain features. These features must largely include a significant accumulation of hydrocarbons, rock physics models, and mechanical properties. However, the effective representation of such reservoir properties using applicable parameters is challenging due to the complicated heterogeneous structural characteristics of hydrocarbon sand. Rock physics modeling of sandstone reservoirs from the Lower Goru Basin gas fields represents the link between reservoir parameters and seismic properties. Rock physics diagnostic models have been utilized to describe the reservoir sands of two wells inside this Middle Indus Basin, including contact cement, constant cement, and friable sand. The results showed that sorting the grain and coating cement on the grain’s surface both affected the cementation process. According to the models, the cementation levels in the reservoir sands of the two wells ranged from 2% to more than 6%. The rock physics models established in the study would improve the understanding of characteristics for the relatively high Vp/Vs unconsolidated reservoir sands under study. Integrating rock physics models would improve the prediction of reservoir properties from the elastic properties estimated from seismic data. The velocity–porosity and elastic moduli-porosity patterns for the reservoir zones of the two wells are distinct. To generate a rock physics template (RPT) for the Lower Goru sand from the Early Cretaceous period, an approach based on fluid replacement modeling has been chosen. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and the P-impedance template can detect cap shale, brine sand, and gas-saturated sand with varying water saturation and porosity from wells in the Rehmat and Miano gas fields, both of which have the same shallow marine depositional characteristics. Conventional neutron-density cross-plot analysis matches up quite well with this RPT’s expected detection of water and gas sands.
Towards a Knowledge Base to Support the Management of the Design Process of Formulated Products
Authors: Rivera-Gil Jose Luis , Serna-Rodas Juliana , Arrieta-Escobar Javier Andrés , Narváez-Rincón Paulo César , Boly Vincent , Falk Véronique
Published: January 2023

The design of new consumer chemical products is a complex task at different levels. In addition to the technical challenges of the formulation, design teams should also consider the requirements of the organization where the design is performed. The objective of this article is to present a knowledge base to support decision-making for the design of formulated products, considering the organizational dimension. For this, data were collected during ten semi-structured in-depth interviews with industrial experts who are also decisional actors in the design process. From the collected data, design recommendations were identified and analyzed. These recommendations are statements which can be used by organizations to evaluate, understand, improve, or create their own design methodologies considering their context and resources. Subsequently, the extracted recommendations were analyzed according to three types of criteria: the stages of the design process, the involved actors, and the organizational context. As a result, a knowledge base containing systematically organized recommendations that have led to the development of successful products is presented. Finally, the multiple uses of the knowledge base are shown with theoretical examples and the knowledge base is applied to analyze the design process of a real organization: in a small and medium-sized enterprise (SME) in the cosmetic sector.
Detection of Crustal Uplift Deformation in Response to Glacier Wastage in Southern Patagonia
Authors: Lenzano María Gabriela , Rivera Andrés , Durand Marcelo , Vacaflor Paulina , Carbonetti Micaela , Lannutti Esteban , Gende Mauricio , Lenzano Luis
Published: January 2023

The Southern Patagonian Icefield (SPI) is the largest continuous ice mass in the Southern Hemisphere outside Antarctica. It has been shrinking since the Little Ice Age (LIA) period, with increasing rates in recent years. An uplift of crustal deformation in response to this deglaciation process has been expected. The goal of this investigation is to analyze the crustal deformation caused by ice retreat using time-series data from continuous GPS stations (2015–2020) in the northern area of the SPI. For this purpose, we installed two continuous GPS stations on rocky nunataks of the SPI (the GRCS near Greve glacier and the GBCS close by Cerro Gorra Blanca). In addition, ice elevation changes (2000–2019) were analyzed by the co-registration of the SRTM digital elevation model and ICESat elevation data points. The results of the vertical components are positive (36.55 ± 2.58 mm a−1), with a maximum at GBCS, indicating the highest rate of crustal uplift ever continuously recorded in Patagonia; in addition, the mean horizontal velocities reached 11.7 mm a−1 with an azimuth of 43°. The negative ice elevation changes detected in the region have also accelerated in the recent two decades, with a median Δh (elevation change) of −3.36 ± 0.01 m a−1 in the ablation zone. The seasonality of the GPS signals was contrasted with the water levels of the main Patagonian lakes around the SPI, detecting a complex interplay between them. Hence, the study sheds light on the knowledge of the crustal uplift as evidence of the wastage experienced by the SPI glaciers.
A Transformer-Based Neural Network with Improved Pyramid Pooling Module for Change Detection in Ecological Redline Monitoring
Authors: Zou Yunjia , Shen Ting , Chen Zhengchao , Chen Pan , Yang Xuan , Zan Luyang
Published: January 2023

The ecological redline defines areas where industrialization and urbanization development should be prohibited. Its purpose is to establish the most stringent environmental protection system to meet the urgent needs of ecological function guarantee and environmental safety. Nowadays, deep learning methods have been widely used in change detection tasks based on remote sensing images, which can just be applied to the monitoring of the ecological redline. Considering the convolution-based neural networks’ lack of utilization of global information, we choose a transformer to devise a Siamese network for change detection. We also use a transformer to design a pyramid pooling module to help the network maintain more features. Moreover, we construct a self-supervised network based on a contrastive method to obtain a pre-trained model, especially for remote sensing images, aiming to achieve better results. As for study areas and data sources, we chose Hebei Province, where the environmental problem is quite nervous, and used its GF-1 satellite images to do our research. Through ablation experiments and contrast experiments, our method is proven to have significant advantages in terms of accuracy and efficiency. We also predict large-scale areas and calculate the intersection recall rate, which confirms that our method has practical values.
GloWS-Net: A Deep Learning Framework for Retrieving Global Sea Surface Wind Speed Using Spaceborne GNSS-R Data
Authors: Bu Jinwei , Yu Kegen , Zuo Xiaoqing , Ni Jun , Li Yongfa , Huang Weimin
Published: January 2023

Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) is a new remote sensing technology that uses GNSS signals reflected from the Earth’s surface to estimate geophysical parameters. Because of its unique advantages such as high temporal and spatial resolutions, low observation cost, wide coverage and all-weather operation, it has been widely used in land and ocean remote sensing fields. Ocean wind monitoring is the main objective of the recently launched Cyclone GNSS (CYGNSS). In previous studies, wind speed was usually retrieved using features extracted from delay-Doppler maps (DDMs) and empirical geophysical model functions (GMFs). However, it is a challenge to employ the GMF method if using multiple sea state parameters as model input. Therefore, in this article, we propose an improved deep learning network framework to retrieve global sea surface wind speed using spaceborne GNSS-R data, named GloWS-Net. GloWS-Net considers the fusion of auxiliary information including ocean swell significant wave height (SWH), sea surface rainfall and wave direction to build an end-to-end wind speed retrieval model. In order to verify the improvement of the proposed model, ERA5 and Cross-Calibrated Multi-Platform (CCMP) wind data were used as reference for extensive testing to evaluate the wind speed retrieval performance of the GloWS-Net model and previous models (i.e., GMF, fully connected network (FCN) and convolutional neural network (CNN)). The results show that, when using ERA5 winds as ground truth, the root mean square error (RMSE) of the proposed GloWS-Net model is 23.98% better than that of the MVE method. Although the GloWS-Net model and the FCN model have similar RMSE (1.92 m/s), the mean absolute percentage error (MAPE) of the former is improved by 16.56%; when using CCMP winds as ground truth, the RMSE of the proposed GloWS-Net model is 2.16 m/s, which is 20.27% better than the MVE method. Compared with the FCN model, the MAPE is improved by 17.75%. Meanwhile, the GloWS-Net outperforms the FCN, traditional CNN, modified CNN (MCNN) and CyGNSSnet models in global wind speed retrieval especially at high wind speeds.
Spatiotemporal Evolution and Influencing Mechanisms of Ecosystem Service Value in the Tarim River Basin, Northwest China
Authors: Zhang Shuai , Wang Yin , Wang Yang , Li Zhi , Hou Yifeng
Published: January 2023

The Tarim River Basin (TRB) is situated in the hinterland of northwest China, which is an extremely arid and fragile ecological zone. In recent years, the region’s ecological civilization construction has been facing huge challenges that are exacerbated by climate change and human activities. In order to verify the current ecological status of TRB, this paper explores the spatial and temporal variation in ecosystem service value (ESV) and the impact mechanism based on LUCC data from 2000 to 2020, using the adjusted unit area value equivalent method, the elasticity index method and the geo-probe analysis method. The results show that: (1) the ESV of the TRB has fluctuated since 2000, increasing by CNY 14.02 billion, especially in the Hotan River region. Among the individual ecosystem services, the increase in regulatory services is the largest, rising to CNY 8.842 billion. The growth of ESV mostly occurred in the mountains and oases. (2) The rise in ESV is mainly due to the conversion of barren land to water and grassland; ESV loss is mainly affected by the conversion of water to cropland and barren land and grassland to cropland and barren land. (3) Human activity impact or intensity (HAI) is the key driving factor for the spatial stratified heterogeneity of ESV, followed by elevation (DEM). In the interaction analysis, HAI∩DEM interaction is the primary reason for ESV’s spatial differentiation. The study’s findings show that the combined effects of human activities, DEM, and hydrothermal conditions underlie the spatial stratified heterogeneity of ESV in the TRB. This conclusion provides a scientific basis for future ecological civilization construction planning.
Real-Time Scan-to-Map Matching Localization System Based on Lightweight Pre-Built Occupancy High-Definition Map
Authors: Wen Jingren , Tang Jian , Liu Hui , Qian Chuang , Fan Xiaoyun
Published: January 2023

High-precision and robust localization in GNSS-denied areas is crucial for autonomous vehicles and robots. Most state-of-the-art localization methods are based on simultaneous localization and mapping (SLAM) with a camera or light detection and ranging (LiDAR). However, SLAM will suffer from drift during long-term running without loop closure or prior constraints. Lightweight, high-precision environmental maps have gradually become an indispensable part of future autonomous driving. In order to solve the problem of real-time global localization for autonomous vehicles and robots, we propose a precise and robust LiDAR localization system based on a pre-built, occupied high-definition (HD) map called the Extended QuadTree (EQT) map. It makes use of a planar quadtree for block division and a Z-sequence index structure within the block cells. Then, a four-level occupancy probability cell value model is adopted. It will save about eight times the storage space compared with Google Cartographer, and the EQT map can be extended to store other information. For efficient scan-to-map matching with our specialized EQT map, the Bursa linearized model is used in the Gauss–Newton iteration of our algorithm, which makes the calculation of partial derivatives fast. All the above improvements lead to optimal storage and efficient querying for real-time scan-to-map matching localization. Field tests in an industrial park and road environment prove that positioning accuracy of about 6–13 cm and attitude accuracy of about 0.15° were achieved using a VLP-16 LiDAR. They also show that the method proposed in this paper is significantly better than the NDT method. For the long and narrow environment of an underground mine tunnel, high-resolution maps are also helpful for accurate and robust localization.
Water Area Variation and River–Lake Interactions in the Poyang Lake from 1977–2021
Authors: Tian Biqing , Gao Peng , Mu Xingmin , Zhao Guangju
Published: January 2023

Lakes are an important part of the Earth’s surface. Poyang Lake is China’s largest freshwater lake with complex hydrological relationships and unique rhythmic changes. There is no systematic understanding of the relationship between lake watershed area and river–lake connectivity. In this study, using remote sensing imagery, hydrological data, meteorological data, and land use surveys, we investigated changes in the Poyang Lake water area from 1977–2021. In addition, we examined the relationship between the lake water area and potential impact factors and analyzed the influence of river–lake interactions on the lake water area. The results showed that the water area of Poyang Lake decreased during the study period. River runoff and sediment load changes in the Poyang Lake basin are the main factors affecting the lake water area. Additionally, the Three Gorges Dam water impoundment situated in the upper reaches of the Yangtze River weakened and eliminated the block and reverse flow of the Yangtze River into the Poyang Lake, causing the water area to decrease toward the end of the flood season in 2005 and in the dry season in 2003. Changes in the lakebed elevation caused by sedimentation and anthropogenic activities have also accelerated the shrinkage of the water area. Overall, the results of this study indicate that variations in the river–lake interactions are the primary cause of the significant changes observed in the Poyang Lake water area in the last five decades.
Multi-Objective Message Routing in Electric and Flying Vehicles Using a Genetics Algorithm
Authors: Alolaiwy Muhammad , Zohdy Mohamed
Published: January 2023

With progressive technological advancements, the time for electric vehicles (EVs) and unmanned aerial vehicles (UAVs) has finally arrived for the masses. However, intelligent transportation systems need to develop appropriate protocols that enable swift predictive communication among these battery-powered devices. In this paper, we highlight the challenges in message routing in a unified paradigm of electric and flying vehicles (EnFVs). We innovate over the existing routing scheme by considering multi-objective EnFVs message routing using a novel modified genetics algorithm. The proposed scheme identifies all possible solutions, outlines the Pareto-front, and considers the optimal solution for the best route. Moreover, the reliability, data rate, and residual energy of vehicles are considered to achieve high communication gains. An exhaustive evaluation of the proposed and three existing schemes using a New York City real geographical trace shows that the proposed scheme outperforms existing solutions and achieves a 90%+ packet delivery ratio, longer connectivity time, shortest average hop distance, and efficient energy consumption.
Transfer Learning on Small Datasets for Improved Fall Detection
Authors: Maray Nader , Ngu Anne Hee , Ni Jianyuan , Debnath Minakshi , Wang Lu
Published: January 2023

Falls in the elderly are associated with significant morbidity and mortality. While numerous fall detection devices incorporating AI and machine learning algorithms have been developed, no known smartwatch-based system has been used successfully in real-time to detect falls for elderly persons. We have developed and deployed a SmartFall system on a commodity-based smartwatch which has been trialled by nine elderly participants. The system, while being usable and welcomed by the participants in our trials, has two serious limitations. The first limitation is the inability to collect a large amount of personalized data for training. When the fall detection model, which is trained with insufficient data, is used in the real world, it generates a large amount of false positives. The second limitation is the model drift problem. This means an accurate model trained using data collected with a specific device performs sub-par when used in another device. Therefore, building one model for each type of device/watch is not a scalable approach for developing smartwatch-based fall detection system. To tackle those issues, we first collected three datasets including accelerometer data for fall detection problem from different devices: the Microsoft watch (MSBAND), the Huawei watch, and the meta-sensor device. After that, a transfer learning strategy was applied to first explore the use of transfer learning to overcome the small dataset training problem for fall detection. We also demonstrated the use of transfer learning to generalize the model across the heterogeneous devices. Our preliminary experiments demonstrate the effectiveness of transfer learning for improving fall detection, achieving an F1 score higher by over 10% on average, an AUC higher by over 0.15 on average, and a smaller false positive prediction rate than the non-transfer learning approach across various datasets collected using different devices with different hardware specifications.
Advanced Feature Extraction Methods from Images of Drillings in Melamine Faced Chipboard for Automatic Diagnosis of Drill Wear
Authors: Antoniuk Izabella , Kurek Jarosław , Krupa Artur , Wieczorek Grzegorz , Bukowski Michał , Kruk Michał , Jegorowa Albina
Published: January 2023

In this paper, a novel approach to evaluation of feature extraction methodologies is presented. In the case of machine learning algorithms, extracting and using the most efficient features is one of the key problems that can significantly influence overall performance. It is especially the case with parameter-heavy problems, such as tool condition monitoring. In the presented case, images of drilled holes are considered, where state of the edge and the overall size of imperfections have high influence on product quality. Finding and using a set of features that accurately describes the differences between the edge that is acceptable or too damaged is not always straightforward. The presented approach focuses on detailed evaluation of various feature extraction approaches. Each chosen method produced a set of features, which was then used to train a selected set of classifiers. Five initial feature sets were obtained, and additional ones were derived from them. Different voting methods were used for ensemble approaches. In total, 38 versions of the classifiers were created and evaluated. Best accuracy was obtained by the ensemble approach based on Weighted Voting methodology. A significant difference was shown between different feature extraction methods, with a total difference of 11.14% between the worst and best feature set, as well as a further 0.2% improvement achieved by using the best voting approach.
Rolling Bearing Performance Degradation Assessment with Adaptive Sensitive Feature Selection and Multi-Strategy Optimized SVDD
Authors: Feng Zhengjiang , Wang Zhihai , Liu Xiaoqin , Li Jiahui
Published: January 2023

In light of the problems of a single vibration feature containing limited information on the degradation of rolling bearings, the redundant information in high-dimensional feature sets inaccurately reflecting the reliability of rolling bearings in service, and assessments of the degradation performance being disturbed by outliers and false fluctuations in the signal, this study proposes a method of assessing rolling bearings’ performance in terms of degradation using adaptive sensitive feature selection and multi-strategy optimized support vector data description (SVDD). First, a high-dimensional feature set of vibration signals from rolling bearings was extracted. Second, a method combining the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and K-medoids was used to comprehensively evaluate the features with multiple evaluation indicators and to adaptively select better degradation features to construct the sensitive feature set. Next, multi-strategy optimization of the SVDD model was carried out by introducing the autocorrelation kernel regression (AAKR) and a multi-kernel function to improve the ability of the evaluation model to overcome outliers and false fluctuations. Through validation, it could be seen that the method in this study uses samples of rolling bearings in the healthy early stage to establish the evaluation model, which can adaptively determine the starting point of the bearing’s degradation. The stability and accuracy of the model were effectively improved.
A Novel Screen-Printed Textile Interface for High-Density Electromyography Recording
Authors: Murciego Luis Pelaez , Komolafe Abiodun , Peřinka Nikola , Nunes-Matos Helga , Junker Katja , Díez Ander García , Lanceros-Méndez Senentxu , Torah Russel , Spaich Erika G. , Dosen Strahinja
Published: January 2023

Recording electrical muscle activity using a dense matrix of detection points (high-density electromyography, EMG) is of interest in a range of different applications, from human-machine interfacing to rehabilitation and clinical assessment. The wider application of high-density EMG is, however, limited as the clinical interfaces are not convenient for practical use (e.g., require conductive gel/cream). In the present study, we describe a novel dry electrode (TEX) in which the matrix of sensing pads is screen printed on textile and then coated with a soft polymer to ensure good skin-electrode contact. To benchmark the novel solution, an identical electrode was produced using state-of-the-art technology (polyethylene terephthalate with hydrogel, PET) and a process that ensured a high-quality sample. The two electrodes were then compared in terms of signal quality as well as functional application. The tests showed that the signals collected using PET and TEX were characterised by similar spectra, magnitude, spatial distribution and signal-to-noise ratio. The electrodes were used by seven healthy subjects and an amputee participant to recognise seven hand gestures, leading to similar performance during offline analysis and online control. The comprehensive assessment, therefore, demonstrated that the proposed textile interface is an attractive solution for practical applications.