bluuebunny/crossref_metadata_2025 huggingface dataset:
The Inhibitory Effects and Cytotoxic Activities of the Stem Extract of Sarracenia purpurea against Melanoma Cells and the SsbA Protein
Authors: Liu Hong-Wen , Chiang Wei-Yu , Huang Yen-Hua , Huang Cheng-Yang
Published: November 2022

The Staphylococcus aureus SsbA protein (SaSsbA) is a single-stranded DNA-binding protein (SSB) that is categorically required for DNA replication and cell survival, and it is thus an attractive target for potential antipathogen chemotherapy. In this study, we prepared the stem extract of Sarracenia purpurea obtained from 100% acetone to investigate its inhibitory effect against SaSsbA. In addition, the cytotoxic effects of this extract on the survival, apoptosis, proliferation, and migration of B16F10 melanoma cells were also examined. Initially, myricetin, quercetin, kaempferol, dihydroquercetin, dihydrokaempferol, rutin, catechin, β-amyrin, oridonin, thioflavin T, primuline, and thioflavin S were used as possible inhibitors against SaSsbA. Of these compounds, dihydrokaempferol and oridonin were capable of inhibiting the ssDNA-binding activity of SaSsbA with respective IC50 values of 750 ± 62 and 2607 ± 242 μM. Given the poor inhibition abilities of dihydrokaempferol and oridonin, we screened the extracts of S. purpurea, Nepenthes miranda, and Plinia cauliflora for SaSsbA inhibitors. The stem extract of S. purpurea exhibited high anti-SaSsbA activity, with an IC50 value of 4.0 ± 0.3 μg/mL. The most abundant compounds in the stem extract of S. purpurea were identified using gas chromatography–mass spectrometry. The top five most abundant contents in this extract were driman-8,11-diol, deoxysericealactone, stigmast-5-en-3-ol, apocynin, and α-amyrin. Using the MOE-Dock tool, the binding modes of these compounds, as well as dihydrokaempferol and oridonin, to SaSsbA were elucidated, and their binding energies were also calculated. Based on the S scores, the binding capacity of these compounds was in the following order: deoxysericealactone > dihydrokaempferol > apocynin > driman-8,11-diol > stigmast-5-en-3-ol > oridonin > α-amyrin. Incubation of B16F10 cells with the stem extract of S. purpurea at a concentration of 100 μg/mL caused deaths at the rate of 76%, reduced migration by 95%, suppressed proliferation and colony formation by 99%, and induced apoptosis, which was observed in 96% of the B16F10 cells. Overall, the collective data in this study indicate the pharmacological potential of the stem extract of S. purpurea for further medical applications.
Ethnopharmacobotany and Diversity of Mediterranean Endemic Plants in Marmilla Subregion, Sardinia, Italy
Authors: Cocco Emma , Maccioni Delia , Sanjust Enrico , Falconieri Danilo , Farris Emmanuele , Maxia Andrea
Published: November 2022

Human populations in various regions across the world exploit the medicinal properties of plants to treat a wide variety of diseases. Areas with both high rates of endemic taxa and persisting traditional uses of the local botanical resources are key sites for the investigation of Traditional Botanical Knowledge (TBK). Commonly, in these areas, information regarding the medicinal properties of native plants has been transmitted orally from generation to generation, however, a rapid decline in this knowledge has been observed, which can be attributed to socio-economic changes in recent years. The Mediterranean basin is one such site, where human history is intimately entwined with nature. The unique geographical situation and unrivaled environmental heterogeneity of the area, have allowed both the development of diverse civilizations as well as providing the basis for the evolution of extraordinary biodiversity. The Mediterranean basin can therefore be considered a global hotspot of endemic vascular plants, and of traditional knowledge of medicinal and aromatic species. This study researches the historical subregion of Marmilla (central-southern Sardinia, Italy), which was chosen because of its specific cultural and demographic characteristics: i.e., prolonged isolation and extreme longevity of the inhabitants of the area. Semi-structured interviews were conducted with 145 people from the region, and 137 medicinal plants belonging to 62 families were identified, of which around 57,3% were taxa exclusive to the Mediterranean Basin. Findings showed that the most used parts of the plant were the leaves (49%), while as far as preparations are concerned, decoction (50%) was the most used to prepare medicinal formulations, making this the highest number of medico-botanical taxa reported in a study carried out in Sardinia using a similar methodology. In addition, this study contributes towards preventing the loss of TBK by documenting the medicinal traditions, passed down orally for centuries, in the words of the participants, shedding new light on the traditional knowledge of the inhabitants of the island. The findings lay the foundations for future applied studies in the fields of phytotherapy and phytochemical investigation.
Chrysosphaerella septentrionalis sp. nov. (Chrysophyceae, Chromulinales), a New Species from the Arctic Including the Description of Chrysosphaerellaceae, fam. nov.
Authors: Kapustin Dmitry , Kulikovskiy Maxim
Published: November 2022

A new species, Chrysosphaerella septentrionalis, is described from a peat bog located on the bank of the Paz River (Pasvik Nature Reserve, Murmansk Region, Russia). Scale ultrastructure was studied using a scanning electron microscope. Morphologically, C. septentrionalis seems to closely resemble C. longispina. However, C. septentrionalis possesses subcircular scales in addition to the oval scales, and they are much smaller than in C. longispina. We suppose that C. septentrionalis is the first pseudocryptic species within the C. longispina complex. Additionally, we proposed an infrageneric classification of Chrysosphaerella based on the scale structure and divided the genus into three sections: Chrysosphaerella, Brevispinae sect. nov. and Septispinae sect. nov. The formal description of a new family Chrysosphaerellaceae fam. nov. is also provided.
Fungal Pathogens and Seed Storage in the Dry State
Authors: Martín Isaura , Gálvez Laura , Guasch Luis , Palmero Daniel
Published: November 2022

Seeds can harbor a wide range of microorganisms, especially fungi, which can cause different sanitary problems. Seed quality and seed longevity may be drastically reduced by fungi that invade seeds before or after harvest. Seed movement can be a pathway for the spread of diseases into new areas. Some seed-associated fungi can also produce mycotoxins that may cause serious negative effects on humans, animals and the seeds themselves. Seed storage is the most efficient and widely used method for conserving plant genetic resources. The seed storage conditions used in gene banks, low temperature and low seed moisture content, increase seed longevity and are usually favorable for the survival of seed-borne mycoflora. Early detection and identification of seed fungi are essential activities to conserve high-quality seeds and to prevent pathogen dissemination. This article provides an overview of the characteristics and detection methods of seed-borne fungi, with a special focus on their potential effects on gene bank seed conservation. The review includes the following aspects: types of seed-borne fungi, paths of infection and transmission, seed health methods, fungi longevity, risk of pathogen dissemination, the effect of fungi on seed longevity and procedures to reduce the harmful effects of fungi in gene banks.
Gamma Radiation Induced In-Vitro Mutagenesis and Isolation of Mutants for Early Flowering and Phytomorphological Variations in Dendrobium ‘Emma White’
Authors: Sherpa Rubina , Devadas Ramgopal , Bolbhat Sadashiv Narayan , Nikam Tukaram Dayaram , Penna Suprasanna
Published: November 2022

In vitro mutagenesis offers a feasible approach for developing new orchid cultivars through genetic manipulation. In the present study, protocorm-like bodies (PLBs) were exposed to gamma rays (10, 20, 40, 60, 80 Gy) to study in vitro growth responses and induction of mutants in Dendrobium ‘Emma White’. Both proliferation and regeneration of PLBs decreased progressively with increasing doses, except for a significantly enhanced growth response at 10 Gy. The optimal dose of gamma radiation for mutagenesis was found in the range 10 to 25 Gy based on the growth reduction curve. Analysis using a high-throughput cell analyzer revealed a significant reduction in nuclear DNA content at > 40 Gy doses. At 10 Gy treatment, the growth attributes, such as root length, plant height and leaf number, were significantly increased by 36%, 26% and 20%, respectively, compared to the control. This increase was significant over other tested doses as well. Testing of random amplified polymorphic DNA markers revealed the presence of detectable polymorphism among gamma mutant plantlets with a polymorphism information content value at 0.41. The gamma-ray-induced earliness in flower development was observed within 294 days post ex vitro growth of 10 Gy mutant compared to the control plants flowered after 959 days. Our results highlight the significance of gamma radiation in inducing enhanced growth, morphological variations and early floral initiation in Dendrobium, providing a basic framework for mutation breeding and improvement of orchids.
Exploiting Tomato Genotypes to Understand Heat Stress Tolerance
Authors: Fernández-Crespo Emma , Liu-Xu Luisa , Albert-Sidro Carlos , Scalschi Loredana , Llorens Eugenio , González-Hernández Ana Isabel , Crespo Oscar , Gonzalez-Bosch Carmen , Camañes Gemma , García-Agustín Pilar , Vicedo Begonya
Published: November 2022

Increased temperatures caused by climate change constitute a significant threat to agriculture and food security. The selection of improved crop varieties with greater tolerance to heat stress is crucial for the future of agriculture. To overcome this challenge, four traditional tomato varieties from the Mediterranean basin and two commercial genotypes were selected to characterize their responses at high temperatures. The screening of phenotypes under heat shock conditions allowed to classify the tomato genotypes as: heat-sensitive: TH-30, ADX2; intermediate: ISR-10 and Ailsa Craig; heat-tolerant: MM and MO-10. These results reveal the intra-genetical variation of heat stress responses, which can be exploited as promising sources of tolerance to climate change conditions. Two different thermotolerance strategies were observed. The MO-10 plants tolerance was based on the control of the leaf cooling mechanism and the rapid RBOHB activation and ABA signaling pathways. The variety MM displayed a different strategy based on the activation of HSP70 and 90, as well as accumulation of phenolic compounds correlated with early induction of PAL expression. The importance of secondary metabolism in the recovery phase has been also revealed. Understanding the molecular events allowing plants to overcome heat stress constitutes a promising approach for selecting climate resilient tomato varieties.
Variability and Nativeness in the Mediterranean Taxa: Divergence and Phylogeography of Genista etnensis (Fabaceae) Inferred from Nuclear and Plastid Data
Authors: De Castro Olga , Bacchetta Gianluigi , Brullo Salvatore , Del Guacchio Emanuele , Di Iorio Emanuela , Piazza Carole , Caputo Paolo
Published: November 2022

Genista etnensis is a remarkable and well-known tree endemic to Sicily, Sardinia, and Corsica (Mediterranean Basin). Nevertheless, its morphological variability and its native status throughout its range need to be further investigated. In this study, we aim to clarify some aspects of this infraspecific variability by molecular means. Sequences of one nuclear and five plastid markers were analyzed under maximum parsimony by using TCS software. Plastid data were also time-calibrated under a Bayesian Inference framework. Plastid data revealed strong isolation between the populations from the Cyrno-Sardinian biogeographical province, which are also the most diverse and presumably the most archaic, and those from Sicily and Southern Italy (in this latter area, the species is naturalized). The calibration analysis indicates that the last common ancestor between G. etnensis and its sister group G. fasselata dates back to the middle Pliocene or slightly later, when sclerophyllous Mediterranean vegetation spread, whereas G. etnensis itself might have originated in the middle Pleistocene. The current, rather unusual distribution of G. etnensis could be explained by long-range seed dispersal from the western part of the range or by anthropogenic introduction into Sicily, with extinctions of transported haplotypes in the region of origin. Interestingly, the Vesuvius population, introduced from Sicily in recent times and locally naturalized, shows private genotypes, and was richer in both genotypes and haplotypes than the Sicilian ones.
An Alternative Source of Biopesticides and Improvement in Their Formulation—Recent Advances
Authors: Šunjka Dragana , Mechora Špela
Published: November 2022

Plant protection in contemporary agriculture requires intensive pesticide application. Their use has enabled the increase in yields, simplifying cultivation systems and crop protection strategies, through successful control of harmful organisms. However, it has led to the accumulation of pesticides in agricultural products and the environment, contaminating the ecosystem and causing adverse health effects. Therefore, finding new possibilities for plant protection and effective control of pests without consequences for humans and the environment is imperative for agricultural production. The most important alternatives to the use of chemical plant protection products are biopesticides. However, in order to increase their application and availability, it is necessary to improve efficacy and stability through new active substances and improved formulations. This paper represents an overview of the recent knowledge in the field of biopesticides and discusses the possibilities of the use of some new active substances and the improvement of formulations.
A Copy Paste and Semantic Segmentation-Based Approach for the Classification and Assessment of Significant Rice Diseases
Authors: Li Zhiyong , Chen Peng , Shuai Luyu , Wang Mantao , Zhang Liang , Wang Yuchao , Mu Jiong
Published: November 2022

The accurate segmentation of significant rice diseases and assessment of the degree of disease damage are the keys to their early diagnosis and intelligent monitoring and are the core of accurate pest control and information management. Deep learning applied to rice disease detection and segmentation can significantly improve the accuracy of disease detection and identification but requires a large number of training samples to determine the optimal parameters of the model. This study proposed a lightweight network based on copy paste and semantic segmentation for accurate disease region segmentation and severity assessment. First, a dataset for rice significant disease segmentation was selected and collated based on 3 open-source datasets, containing 450 sample images belonging to 3 categories of rice leaf bacterial blight, blast and brown spot. Then, to increase the diversity of samples, a data augmentation method, rice leaf disease copy paste (RLDCP), was proposed that expanded the collected disease samples with the concept of copy and paste. The new RSegformer model was then trained by replacing the new backbone network with the lightweight semantic segmentation network Segformer, combining the attention mechanism and changing the upsampling operator, so that the model could better balance local and global information, speed up the training process and reduce the degree of overfitting of the network. The results show that RLDCP could effectively improve the accuracy and generalisation performance of the semantic segmentation model compared with traditional data augmentation methods and could improve the MIoU of the semantic segmentation model by about 5% with a dataset only twice the size. RSegformer can achieve an 85.38% MIoU at a model size of 14.36 M. The method proposed in this paper can quickly, easily and accurately identify disease occurrence areas, their species and the degree of disease damage, providing a reference for timely and effective rice disease control.
Novel Polymeric Nanomaterial Based on Poly(Hydroxyethyl Methacrylate-Methacryloylamidophenylalanine) for Hypertension Treatment: Properties and Drug Release Characteristics
Authors: Bardakci Fevzi , Kusat Kevser , Adnan Mohd , Badraoui Riadh , Alam Mohammad , Alreshidi Mousa , Siddiqui Arif , Sachidanandan Manojkumar , Akgöl Sinan
Published: November 2022

In this study, a novel polymeric nanomaterial was synthesized and characterized, and it its potential usability in hypertension treatment was demonstrated. For these purposes, a poly(hydroxyethyl methacrylate-methacryloylamidophenylalanine)-based polymeric nanomaterial (p(HEMPA)) was synthesized using a mini-emulsion polymerization technique. The nanomaterials were characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and zeta size analysis. The synthesized p(HEMPA) nanomaterial had a diameter of about 113 nm. Amlodipine-binding studies were optimized by changing the reaction conditions. Under optimum conditions, amlodipine’s maximum adsorption value (Qmax) of the p(HEMPA) nanopolymer was found to be 145.8 mg/g. In vitro controlled drug release rates of amlodipine, bound to the nanopolymer at the optimum conditions, were studied with the dialysis method in a simulated gastrointestinal system with pH values of 1.2, 6.8 and 7.4. It was found that 99.5% of amlodipine loaded on the nanomaterial was released at pH 7.4 and 72 h. Even after 72 h, no difference was observed in the release of AML. It can be said that the synthesized nanomaterial is suitable for oral amlodipine release. In conclusion, the synthesized nanomaterial was studied for the first time in the literature as a drug delivery system for use in the treatment of hypertension. In addition, AML–p(HEMPA) nanomaterials may enable less frequent drug uptake, have higher bioavailability, and allow for prolonged release with minimal side effects.
Special Issue: Properties and Processing Process of Flour Products
Authors: Anyasi Tonna Ashim , Jideani Afam Israel Obiefuna
Published: November 2022

The development of flour from established native sources to alternative and sustainable sources is increasing as demands for flour products rise due to recent global conflicts [...]
Preparation and Application of Coal-Liquefaction-Residue-Based Carbon Material
Authors: Xu Liang , Lu Yizhe , Yalikun Nuerbiya , Shi Congchao , Wang Haoyang , Xu Yueyuan , Liu Jie
Published: November 2022

P-Nitrophenol (4-NP) is a high toxicity material and has harmful effects on the environment. Thus, the analysis of 4-NP is an important topic at present. In this work, the fabrication of a novel electrochemical sensor based on coal-liquefaction-residue (CLR)-derived porous carbon (PC) materials. CLR-based porous carbon material was prepared by the high-temperature carbonization method and the morphology and structure of the materials were characterized by scanning electron microscopy and other characterization methods. Subsequently, the electrochemical properties of the modified electrodes were studied by cyclic voltammetry (CV) and differential pulse voltammetry (DPV) measurements. The results showed that under optimal conditions, the sensor had a good electrochemical performance for environmental pollutant 4-NP. In particular, the linear range of the sensor was 10–200 μmol·L-1 and the detection limit was 1.169 μmol·L−1 on the basis of the signal-to-noise ratio S/N = 3. The electrode showed excellent stability, reproducibility and repetitiveness and the sensor also had good selectivity. In addition, the newly constructed sensor exhibited adsorption-controlled kinetics and the recovery rate of 4-NP in actual water samples could reach 90.06~95.17%, indicating that the sensor had good practical application prospects.
Cartilage Tissue in Forensic Science—State of the Art and Future Research Directions
Authors: Tomsia Marcin , Cieśla Julia , Pilch-Kowalczyk Joanna , Banaszek Przemysław , Chełmecka Elżbieta
Published: November 2022

Cartilage tissue performs many functions in the human body. The diseases and injuries affecting it are prevalent due to its slow regeneration rate. However, cartilage tissue is exceptionally important for its auspicious use in forensic medicine due to its slow postmortem degradation rate. The presented review summarizes the latest research on cartilage tissues and their current and potential applications in forensic science. It also describes the most important studies on using cartilage and its microscopic and macroscopic analyses to estimate the deceased age and determine postmortem interval (PMI) values and the crime weapon. Additionally, the review describes attempts to isolate DNA from cartilage tissue for individual identification. The review also mentions recent, less abundant studies on the cartilage in forensic toxicology and genetics. It points out further directions and prospects for research development on cartilage tissue and its promising use in forensic medicine
An Overlapping Presentation of Hypoglycemia and Catatonia—A Case Report and Literature Review
Authors: Mader Einat , Brikman Shay , Dori Guy , Sagi Or , Pinkhasov Aaron
Published: November 2022

Catatonia is a clinical syndrome characterized by a distinct constellation of psychomotor disturbances. It is known as a clinical manifestation of many medical and psychiatric conditions. Neuroglycopenia is a term that refers to a shortage of glucose in the brain resulting in the alteration of neuronal function. Catatonia has been observed in hypoglycemic states. We present a single case report of a 36-year-old male, with no known medical or psychiatric history, presenting with catatonia and hypoglycemia due to malnutrition. Catatonia and hypoglycemia may present similarly, and can present a challenge in differentiating the underlying etiology. It is unclear whether the hypoglycemia-catatonia overlap phenomenon is rare or rather underdiagnosed.
An Overall Perspective for the Study of Emerging Contaminants in Karst Aquifers
Authors: Campanale Claudia , Losacco Daniela , Triozzi Mariangela , Massarelli Carmine , Uricchio Vito Felice
Published: November 2022

Karst aquifers are essential drinking water sources, representing about 25% of the total available sources globally. Groundwater ecosystems consist of fissured carbonate rocks commonly covered with canopy collapse sinkholes. The open nature of karst aquifers makes them susceptible to rapidly transporting contaminants from the surface in dissolved and particulate forms. The principal aim of this review is to contribute to filling the gap in knowledge regarding major concerns affecting karst aquifers and understanding their vulnerabilities and dynamics. The principal groundwater pollutants of relevance are detailed in the present work, including well-known issues, such as the input of agriculture and its role in water quality. Emerging pollutants such as microplastics, still poorly studied in the groundwater systems, were also considered. Case studies for each typology of pollutant were highlighted, as their relative concerns for karst environments. Final considerations underlined an approach for studying karst environments more focused on understanding dynamics and links among different pollutants inputs and their drivers than on individual sources and impacts.
Research on Sediment Discharge Variations and Driving Factors in the Tarim River Basin
Authors: Ye Zhaoxia , Chen Yaning , Zhang Qifei , Liu Yongchang , Zhang Xueqi
Published: November 2022

Sediment discharge is widely regarded as a critical indicator of soil and water loss. The Mann–Kendall (M-K) test was applied to analyze the trends of temperature, precipitation, annual runoff, annual sediment discharge (ASD), and snow cover area proportion (SCAP). Sensitivity coefficient and contribution rate were adopted to assess the sensitivity of ASD to driving factors, and the contribution of driving factors to ASD. The results showed: (1) ASD of the Kaidu River and the Aksu River originating from Tien Shan decreased at rates of 3.8503 × 107 kg per year (p < 0.01) and 47.198 × 107 kg per year, respectively, from 2001 to 2019. The ASD there was also found to be more sensitive to SCAP changes in autumn and winter, respectively. (2) ASD of the Yarkand River and the Yulong Kashgar River originating from the Karakoram Mountains increased at rates of 21.807 × 107 kg per year and 27.774 × 107 kg per year, respectively, during 2001–2019. The ASD there was determined to be more sensitive to annual runoff. (3) In terms of contribution rate, except for the Kaidu River, annual runoff of the other three rivers made the largest contribution. (4) In addition, the proportion of glacial-melt water, slope, glacierization and human activities are also possible factors affecting sediment discharge.
Performance Analysis of the Temperature and Humidity Profiles Retrieval for FY-3D/MWTHS in Arctic Regions
Authors: Zhang Lanjie , Tie Shengru , He Qiurui , Wang Wenyu
Published: November 2022

The special geographical location of the polar regions increases the difficulty of modeling surface emissivity, thus the physical retrieval algorithms of the temperature and humidity profiles for microwave radiometers mainly focus on the regions between 60°S and 60°N. In this paper, the deep neural networks (DNN) and long short-term memory (LSTM) models are first implemented to retrieve atmospheric temperature and humidity profiles in real time from FY-3D/MWHTS in Arctic regions and are compared with the physical retrieval algorithm. The hyperparameters of the machine learning models are determined using the grid search and 10-fold cross-validation. Results show that, compared with the physical retrieval algorithm, the retrieval accuracies of the atmospheric temperature and humidity profiles of the DNN and LSTM models in June 2021 are higher over sea ice, and the maximum retrieval accuracies are improved by about 3.5 K and 42%. Over land, the retrieval accuracies of the atmospheric temperature profiles for the DNN and LSTM models in June 2021 are improved by about 5 K. The retrieved humidity results for these two models are not compared with the physical retrieval algorithm, which fails for the humidity profile retrieval over land. In addition, the retrieval results of the DNN-based and LSTM-based models using the independent validation data in February, April, and September are also evaluated over different surface types. The RMSEs of the retrieved temperature profiles for the two models are within 4 K, except for the near-surface, and the humidity profiles are within 25%, except for in February. The temperature profiles in September and the humidity profiles in February are somewhat reduced compared to other months because of the highly variable emissivity properties in autumn and winter. Overall results show that the machine learning method can well-evaluate the retrieval capability of FY-3D/MWHTS of the atmospheric temperature and humidity profiles in Arctic regions.
Evaluation of Decision Fusions for Classifying Karst Wetland Vegetation Using One-Class and Multi-Class CNN Models with High-Resolution UAV Images
Authors: Li Yuyang , Deng Tengfang , Fu Bolin , Lao Zhinan , Yang Wenlan , He Hongchang , Fan Donglin , He Wen , Yao Yuefeng
Published: November 2022

Combining deep learning and UAV images to map wetland vegetation distribution has received increasing attention from researchers. However, it is difficult for one multi-classification convolutional neural network (CNN) model to meet the accuracy requirements for the overall classification of multi-object types. To resolve these issues, this paper combined three decision fusion methods (Majority Voting Fusion, Average Probability Fusion, and Optimal Selection Fusion) with four CNNs, including SegNet, PSPNet, DeepLabV3+, and RAUNet, to construct different fusion classification models (FCMs) for mapping wetland vegetations in Huixian Karst National Wetland Park, Guilin, south China. We further evaluated the effect of one-class and multi-class FCMs on wetland vegetation classification using ultra-high-resolution UAV images and compared the performance of one-class classification (OCC) and multi-class classification (MCC) models for karst wetland vegetation. The results highlight that (1) the use of additional multi-dimensional UAV datasets achieved better classification performance for karst wetland vegetation using CNN models. The OCC models produced better classification results than MCC models, and the accuracy (average of IoU) difference between the two model types was 3.24–10.97%. (2) The integration of DSM and texture features improved the performance of FCMs with an increase in accuracy (MIoU) from 0.67% to 8.23% when compared to RGB-based karst wetland vegetation classifications. (3) The PSPNet algorithm achieved the optimal pixel-based classification in the CNN-based FCMs, while the DeepLabV3+ algorithm produced the best attribute-based classification performance. (4) Three decision fusions all improved the identification ability for karst wetland vegetation compared to single CNN models, which achieved the highest IoUs of 81.93% and 98.42% for Eichhornia crassipes and Nelumbo nucifera, respectively. (5) One-class FCMs achieved higher classification accuracy for karst wetland vegetation than multi-class FCMs, and the highest improvement in the IoU for karst herbaceous plants reached 22.09%.
Predictive Modeling of Above-Ground Biomass in Brachiaria Pastures from Satellite and UAV Imagery Using Machine Learning Approaches
Authors: Alvarez-Mendoza Cesar I. , Guzman Diego , Casas Jorge , Bastidas Mike , Polanco Jan , Valencia-Ortiz Milton , Montenegro Frank , Arango Jacobo , Ishitani Manabu , Selvaraj Michael Gomez
Published: November 2022

Grassland pastures are crucial for the global food supply through their milk and meat production; hence, forage species monitoring is essential for cattle feed. Therefore, knowledge of pasture above-ground canopy features help understand the crop status. This paper finds how to construct machine learning models to predict above-ground canopy features in Brachiaria pasture from ground truth data (GTD) and remote sensing at larger (satellite data on the cloud) and smaller (unmanned aerial vehicles (UAV)) scales. First, we used above-ground biomass (AGB) data obtained from Brachiaria to evaluate the relationship between vegetation indices (VIs) with the dry matter (DM). Next, the performance of machine learning algorithms was used for predicting AGB based on VIs obtained from ground truth and satellite and UAV imagery. When comparing more than twenty-five machine learning models using an Auto Machine Learning Python API, the results show that the best algorithms were the Huber with R2 = 0.60, Linear with R2 = 0.54, and Extra Trees with R2 = 0.45 to large scales using satellite. On the other hand, short-scale best regressions are K Neighbors with an R2 of 0.76, Extra Trees with an R2 of 0.75, and Bayesian Ridge with an R2 of 0.70, demonstrating a high potential to predict AGB and DM. This study is the first prediction model approach that assesses the rotational grazing system and pasture above-ground canopy features to predict the quality and quantity of cattle feed to support pasture management in Colombia.
Theory and Experiment Analysis on the Influence of Floods on a GNSS Pseudo-Range Multipath and CNR Signal Based on Two Cases Study in China
Authors: Su Mingkun , Chang Xin , Zheng Fu , Shang Junna , Qiao Lei , Teng Xuyang , Sun Minhong
Published: November 2022

The surrounding environment of a GNSS observation station is changed during a flood, and this results in a more serious multipath than in a normal environment. Considering that the multipath error is largely related to the pseudo-range multipath and CNR (Carrier-to-noise ratio) of the GNSS signal, the influence of floods on a pseudo-range multipath and CNR is analyzed in theory and through experiment. To ensure the accuracy of the analysis results, the ground track repeat period of GPS, GLONASS, and BDS satellites is investigated from the perspective of theory and skyplots. Two real cases study collected in Zhengzhou and Xinxiang, China, in 2021, are used to demonstrate the influence of floods on a pseudo-range multipath and CNR in detail. Experimental results show that the pseudo-range multipath of a GPS satellite performs more seriously during a flood. The maximum RMS increase rate is approximately 17.85%, and the average of all other satellites with a whole arc is approximately 6.55%. In addition, the CNR of three GNSS systems performs a decrease during a flood. For GPS and GLONASS satellites, the decrease performs more seriously at a high elevation angle than that at a low elevation angle. The maximum decrease is approximately 5 dB-Hz for the GPS satellite and approximately 7 dB-Hz for the GLONASS satellite. In terms of the BDS system, the CNR of all three orbital type satellites decreases during a flood. The average decrease is approximately 2 dB-Hz for BDS MEO and GEO satellites, and about 1 dB-Hz for the BDS IGSO satellite.
Development of a Lightweight Single-Band Bathymetric LiDAR
Authors: Zhou Guoqing , Zhou Xiang , Li Weihao , Zhao Dawei , Song Bo , Xu Chao , Zhang Haotian , Liu Zhexian , Xu Jiasheng , Lin Gangchao , Deng Ronghua , Hu Haocheng , Tan Yizhi , Lin Jinchun , Yang Jiazhi , Nong Xueqin , Li Chenyang , Zhao Yiqiang , Wang Cheng , Zhang Lieping , Zou Liping
Published: November 2022

Traditional bathymetry LiDAR (light detection and ranging) onboard manned and/or unmanned airborne systems cannot operate in the context of narrow rivers in urban areas with high buildings and in mountainous areas with high peaks. Therefore, this study presents a prototype of a lightweight bathymetry LiDAR onboard an unmanned shipborne vehicle (called “GQ-Cor 19”). The GQ-Cor 19 system primarily includes an emitting optical module, a receiving optical module, control module, detection module, high-speed A/D sampling module, and data processing system. Considering that the “GQ-Cor 19” is extremely close to the water surface, various new technical challenges are encountered, such as significant laser scattering energy from the surface of the water, which saturates signals received by the photomultiplier tube detector. Therefore, this study presents various new technical solutions, including (1) an improved Bresenham algorithm, (2) a small and lightweight receiving optical system with a split-field method, and (3) a data acquisition module with a high-speech A/D collector. Following a series of different experimental verifications, the results demonstrate that the new generation of single-band LiDAR onboard an unmanned shipborne vehicle can swiftly measure the underwater depth, and the maximum measurement depth is more than 25 m. The measurement accuracy is better than 30 cm and the weight is less than 12 kg.
Lidar- and V2X-Based Cooperative Localization Technique for Autonomous Driving in a GNSS-Denied Environment
Authors: Kang Min-Su , Ahn Jae-Hoon , Im Ji-Ung , Won Jong-Hoon
Published: November 2022

Autonomous vehicles are equipped with multiple heterogeneous sensors and drive while processing data from each sensor in real time. Among the sensors, the global navigation satellite system (GNSS) is essential to the localization of the vehicle itself. However, if a GNSS-denied situation occurs while driving, the accident risk may be high due to the degradation of the vehicle positioning performance. This paper presents a cooperative positioning technique based on the lidar sensor and vehicle-to-everything (V2X) communication. The ego-vehicle continuously tracks surrounding vehicles and objects, and localizes itself using tracking information from the surroundings, especially in GNSS-denied situations. We present the effectiveness of the cooperative positioning technique by constructing a GNSS-denied case during autonomous driving. A numerical simulation using a driving simulator is included in the paper to evaluate and verify the proposed method in various scenarios.
Characterizing Spatiotemporal Patterns of Snowfall in the Kaidu River Basin from 2000–2020 Using MODIS Observations
Authors: Wang Jiangeng , Zhu Linglong , Zhang Yonghong , Huang Wei , Song Kaida , Tian Feng
Published: November 2022

Characterizing spatiotemporal patterns of snowfall is essential for understanding cryosphere responses to warming climate stress. The changes in snowfall and topographic controls in mountain regions still need to be clarified. This study proposes a general parsimonious methodology to obtain the frequency of snowfall in mountainous areas. The methodology employed is easily transferable to any other mountain region. Utilizing daily MODIS observations from June 2000 to May 2020 and the snowfall event detection algorithm, we monitored the frequency of snowfall in a long time series in the Kaidu river basin. The results are as follows: (1) The method for detecting the frequency of snowfall has high accuracy. The annual detected results agreed with surface observations, with an R2 of 0.65 and RMSE of 3.39. (2) The frequency of snowfall events increased monotonically with elevation. The influence of slope angle on snowfall gradually decreased with increasing elevation. (3) The frequency of snowfall events in the Kaidu river basin was dominated by an increasing trend. The trends showed a pronounced topographic dependence. This study reveals the distribution characteristics and changing snowfall trends in mountain regions. The results provide a reference for snowfall research in mountainous areas.
Spatio-Temporal Calibration of Multiple Kinect Cameras Using 3D Human Pose
Authors: Eichler Nadav , Hel-Or Hagit , Shimshoni Ilan
Published: November 2022

RGB and depth cameras are extensively used for the 3D tracking of human pose and motion. Typically, these cameras calculate a set of 3D points representing the human body as a skeletal structure. The tracking capabilities of a single camera are often affected by noise and inaccuracies due to occluded body parts. Multiple-camera setups offer a solution to maximize coverage of the captured human body and to minimize occlusions. According to best practices, fusing information across multiple cameras typically requires spatio-temporal calibration. First, the cameras must synchronize their internal clocks. This is typically performed by physically connecting the cameras to each other using an external device or cable. Second, the pose of each camera relative to the other cameras must be calculated (Extrinsic Calibration). The state-of-the-art methods use specialized calibration session and devices such as a checkerboard to perform calibration. In this paper, we introduce an approach to the spatio-temporal calibration of multiple cameras which is designed to run on-the-fly without specialized devices or equipment requiring only the motion of the human body in the scene. As an example, the system is implemented and evaluated using Microsoft Azure Kinect. The study shows that the accuracy and robustness of this approach is on par with the state-of-the-art practices.
Development of Three-Axis Fibre-Optic Seismograph for Direct and Autonomous Monitoring of Rotational Events with Perspective of Historical Review
Authors: Kurzych Anna T. , Jaroszewicz Leszek R. , Kowalski Jerzy K.
Published: November 2022

The paper presents historical perspective of fibre-optic seismographs designed and constructed at the Institute of Applied Physics at Military University of Technology, Poland based on the so-called minimum configuration of fibre-optic gyroscope. The briefly presented history, which originated in the 1998 by the system named GS-13P, laid solid foundations for the construction of a three-axis fibre-optic seismograph. The presented system meets all technical requirements of rotational seismology in terms of measurement parameters (measuring range from 10−8 rad/s to several rad/s and frequency from 0.01 Hz to 100 Hz) and utility features (mobility, autonomy, power independence, environmental stability). The presented device provides universal application both for research in engineering applications (high buildings, chimneys, wind towers) as well as in seismological research.
Bottom-Gated ZnO TFT Pressure Sensor with 1D Nanorods
Authors: Kim Ki-Nam , Ko Woon-San , Byun Jun-Ho , Lee Do-Yeon , Jeong Jun-Kyo , Lee Hi-Deok , Lee Ga-Won
Published: November 2022

In this study, a bottom-gated ZnO thin film transistor (TFT) pressure sensor with nanorods (NRs) is suggested. The NRs are formed on a planar channel of the TFT by hydrothermal synthesis for the mediators of pressure amplification. The fabricated devices show enhanced sensitivity by 16~20 times better than that of the thin film structure because NRs have a small pressure transmission area and causes more strain in the underlayered piezoelectric channel material. When making a sensor with a three-terminal structure, the leakage current in stand-by mode and optimal conductance state for pressure sensor is expected to be controlled by the gate voltage. A scanning electron microscope (SEM) was used to identify the nanorods grown by hydrothermal synthesis. X-ray diffraction (XRD) was used to compare ZnO crystallinity according to device structure and process conditions. To investigate the effect of NRs, channel mobility is also extracted experimentally and the lateral flow of current density is analyzed with simulation (COMSOL) showing that when the piezopotential due to polarization is formed vertically in the channel, the effective mobility is degraded.
IoT Enabled Intelligent Stick for Visually Impaired People for Obstacle Recognition
Authors: Farooq Muhammad Siddique , Shafi Imran , Khan Harris , Díez Isabel De La Torre , Breñosa Jose , Espinosa Julio César Martínez , Ashraf Imran
Published: November 2022

This paper presents the design, development, and testing of an IoT-enabled smart stick for visually impaired people to navigate the outside environment with the ability to detect and warn about obstacles. The proposed design employs ultrasonic sensors for obstacle detection, a water sensor for sensing the puddles and wet surfaces in the user’s path, and a high-definition video camera integrated with object recognition. Furthermore, the user is signaled about various hindrances and objects using voice feedback through earphones after accurately detecting and identifying objects. The proposed smart stick has two modes; one uses ultrasonic sensors for detection and feedback through vibration motors to inform about the direction of the obstacle, and the second mode is the detection and recognition of obstacles and providing voice feedback. The proposed system allows for switching between the two modes depending on the environment and personal preference. Moreover, the latitude/longitude values of the user are captured and uploaded to the IoT platform for effective tracking via global positioning system (GPS)/global system for mobile communication (GSM) modules, which enable the live location of the user/stick to be monitored on the IoT dashboard. A panic button is also provided for emergency assistance by generating a request signal in the form of an SMS containing a Google maps link generated with latitude and longitude coordinates and sent through an IoT-enabled environment. The smart stick has been designed to be lightweight, waterproof, size adjustable, and has long battery life. The overall design ensures energy efficiency, portability, stability, ease of access, and robust features.
Detection of Salmonella Typhimurium with Gold Nanoparticles Using Quartz Crystal Microbalance Biosensor
Authors: Min Hyun Jung , Mina Hansel A. , Deering Amanda J. , Robinson J. Paul , Bae Euiwon
Published: November 2022

Demonstration of the Salmonella Typhimurium detection system was shown utilizing a quartz crystal microbalance (QCM) biosensor and signal enhancement by gold nanoparticles. In this study, a benchtop system of a QCM biosensor was utilized for the detection of Salmonella Typhimurium. It was designed with a peristaltic pump system to achieve immobilization of antibodies, detection of Salmonella, and the addition of gold nanoparticles to the sensor. As a series of biochemical solutions were introduced to the surface, the proposed system was able to track the changes in the resonant frequency which were proportional to the variations of mass on the sensor. For antibody immobilization, polyclonal antibodies were immobilized via self-assembled monolayers to detect Salmonella O-antigen. Subsequently, Salmonella Typhimurium was detected by antibodies and the average frequency before and after detecting Salmonella was compared. The highest frequency shifts were −26.91 Hz for 109 CFU/mL while the smallest frequency shift was −3.65 Hz corresponding to 103 CFU/mL. For the specificity tests, non-Salmonella samples such as E. coli, Listeria, and Staphylococcus resulted in low cross-reactivity. For signal amplification, biotinylated antibodies reacted to Salmonella followed by streptavidin—100 nm AuNPs through biotin-avidin interaction. The frequency shifts of 103 CFU/mL showed −28.04 Hz, and consequently improved the limit of detection.
Passive Exoskeleton with Gait-Based Knee Joint Support for Individuals with Cerebral Palsy
Authors: Kennard Maxwell , Kadone Hideki , Shimizu Yukiyo , Suzuki Kenji
Published: November 2022

Cerebral palsy is a neurological disorder with a variety of symptoms that can affect muscle coordination and movement. Crouch gait is one such symptom that is defined as excessive knee flexion accompanied by a crouched posture. This paper introduces a passive exoskeleton to support the knee joint during stance of individuals with cerebral palsy that are affected by crouch gait. The exoskeleton utilizes a hydraulic disc brake mechanism that is actuated only by the body weight and gait of the wearer to provide a braking torque at the knee joint. This passive, gait-based control method aims to offer a compact, lightweight, and simple alternative to existing exoskeletons. Preliminary experiments were conducted to verify the mechanics, safety, and braking capabilities of the device with healthy participants. A pilot study with an individual with cerebral palsy was then conducted. The individual with cerebral palsy showed a reduction in hip joint angle when using the device (18.8∘ and 21.7∘ for left and right sides, respectively). The muscle co-activation index was also reduced from 0.48 to 0.24 on the right side and from 0.17 to 0.017 on the left side. However, changes such as activation timing and device training need to be improved to better support the user.