bluuebunny/crossref_metadata_2025 huggingface dataset:
Highlighted Advances in Therapies for Difficult-To-Treat Brain Tumours Such as Glioblastoma
Authors: Cruz Nuno , Herculano-Carvalho Manuel , Roque Diogo , Faria Cláudia C. , Cascão Rita , Ferreira Hugo Alexandre , Reis Catarina Pinto , Matela Nuno
Published: March 2023

Glioblastoma multiforme (GBM) remains a challenging disease, as it is the most common and deadly brain tumour in adults and has no curative solution and an overall short survival time. This incurability and short survival time means that, despite its rarity (average incidence of 3.2 per 100,000 persons), there has been an increased effort to try to treat this disease. Standard of care in newly diagnosed glioblastoma is maximal tumour resection followed by initial concomitant radiotherapy and temozolomide (TMZ) and then further chemotherapy with TMZ. Imaging techniques are key not only to diagnose the extent of the affected tissue but also for surgery planning and even for intraoperative use. Eligible patients may combine TMZ with tumour treating fields (TTF) therapy, which delivers low-intensity and intermediate-frequency electric fields to arrest tumour growth. Nonetheless, the blood–brain barrier (BBB) and systemic side effects are obstacles to successful chemotherapy in GBM; thus, more targeted, custom therapies such as immunotherapy and nanotechnological drug delivery systems have been undergoing research with varying degrees of success. This review proposes an overview of the pathophysiology, possible treatments, and the most (not all) representative examples of the latest advancements.
Designing Formulation Strategies for Enhanced Stability of Therapeutic Peptides in Aqueous Solutions: A Review
Authors: Nugrahadi Primawan Putra , Hinrichs Wouter L. J. , Frijlink Henderik W. , Schöneich Christian , Avanti Christina
Published: March 2023

Over the past few decades, there has been a tremendous increase in the utilization of therapeutic peptides. Therapeutic peptides are usually administered via the parenteral route, requiring an aqueous formulation. Unfortunately, peptides are often unstable in aqueous solutions, affecting stability and bioactivity. Although a stable and dry formulation for reconstitution might be designed, from a pharmaco-economic and practical convenience point of view, a peptide formulation in an aqueous liquid form is preferred. Designing formulation strategies that optimize peptide stability may improve bioavailability and increase therapeutic efficacy. This literature review provides an overview of various degradation pathways and formulation strategies to stabilize therapeutic peptides in aqueous solutions. First, we introduce the major peptide stability issues in liquid formulations and the degradation mechanisms. Then, we present a variety of known strategies to inhibit or slow down peptide degradation. Overall, the most practical approaches to peptide stabilization are pH optimization and selecting the appropriate type of buffer. Other practical strategies to reduce peptide degradation rates in solution are the application of co-solvency, air exclusion, viscosity enhancement, PEGylation, and using polyol excipients.
Impact of Postharvest Putrescine Treatments on Phenolic Compounds, Antioxidant Capacity, Organic Acid Contents and Some Quality Characteristics of Fresh Fig Fruits during Cold Storage
Authors: Kucuker Emine , Aglar Erdal , Sakaldaş Mustafa , Şen Fatih , Gundogdu Muttalip
Published: March 2023

The storage and shelf life of the fig, which has a sensitive fruit structure, is short, and this results in excessive economic losses. In a study carried out to contribute to the solution of this problem, the effect of postharvest putrescine application at different doses (0, 0.5, 1.0, 2.0, and 4.0 mM) on fruit quality characteristics and biochemical content during cold storage in figs was determined. At the end of the cold storage, the decay rate and weight loss in the fruit were in the ranges of 1.0–1.6% and 1.0–5.0 %, respectively. The decay rate and weight loss were lower in putrescine-applied fruit during cold storage. Putrescine application had a positive effect on the changes in fruit flesh firmness values. The SSC rate of fruit varied between 14 and 20%, while significant differences in the SSC rate occurred depending on storage time and putrescine application dose. With putrescine application, the decrease in the acidity rate of the fig fruit during cold storage was smaller. At the end of the cold storage, the acidity rate was between 1.5–2.5% and 1.0–5.0. Putrescine treatments affected total antioxidant activity values and changes occurred in total antioxidant activity depending on the application dose. In the study, it was observed that the amount of phenolic acid in fig fruit decreased during storage and putrescine doses prevented this decrease. Putrescine treatment affected the changes in the quantity of organic acids during cold storage, and this effect varied depending on the type of organic acid and the length of the cold storage period. As a result, it was revealed that putrescine treatments can be used as an effective method to maintain postharvest fruit quality in figs.
Metabolic Profiling of Primary and Secondary Metabolites in Kohlrabi (Brassica oleracea var. gongylodes) Sprouts Exposed to Different Light-Emitting Diodes
Authors: Sathasivam Ramaraj , Park Sang Un , Kim Jae Kwang , Park Young Jin , Kim Min Cheol , Nguyen Bao Van , Lee Sook Young
Published: March 2023

Light-emitting diode (LED) technology is one of the most important light sources in the plant industry for enhancing growth and specific metabolites in plants. In this study, we analyzed the growth, primary and secondary metabolites of 10 days old kohlrabi (Brassica oleracea var. gongylodes) sprouts exposed to different LED light conditions. The results showed that the highest fresh weight was achieved under red LED light, whereas the highest shoot and root lengths were recorded below the blue LED light. Furthermore, high-performance liquid chromatography (HPLC) analysis revealed the presence of 13 phenylpropanoid compounds, 8 glucosinolates (GSLs), and 5 different carotenoids. The phenylpropanoid and GSL contents were highest under blue LED light. In contrast, the carotenoid content was found to be maximum beneath white LED light. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) of the 71 identified metabolites using HPLC and gas chromatography–time-of-flight mass spectrometry (GC-TOF-MS) showed a clear separation, indicating that different LEDs exhibited variation in the accumulation of primary and secondary metabolites. A heat map and hierarchical clustering analysis revealed that blue LED light accumulated the highest amount of primary and secondary metabolites. Overall, our results demonstrate that exposure of kohlrabi sprouts to blue LED light is the most suitable condition for the highest growth and is effective in increasing the phenylpropanoid and GSL content, whereas white light might be used to enhance carotenoid compounds in kohlrabi sprouts.
Differential and Cultivar-Dependent Antioxidant Response of Whole and Fresh-Cut Carrots of Different Root Colors to Postharvest UV-C Radiation
Authors: Valerga Lucia , González Roxana E. , Pérez María B. , Concellón Analía , Cavagnaro Pablo F.
Published: March 2023

Fresh-cut produce have become widely popular, increasing vegetable consumption in many parts of the word. However, they are more perishable than unprocessed fresh vegetables, requiring cold storage to preserve their quality and palatability. In addition to cold storage, UV radiation has been used experimentally to try to increase nutritional quality and postharvest shelf life, revealing increased antioxidant levels in some fruits and vegetables, including orange carrots. Carrot is one of the main whole and fresh-cut vegetables worldwide. In addition to orange carrots, other root color phenotypes (e.g., purple, yellow, red) are becoming increasingly popular in some markets. The effect of the UV radiation and cold storage has not been explored in these root phenotypes. This study investigated the effect of postharvest UV-C radiation in whole and fresh-cut (sliced and shredded) roots of two purple, one yellow, and one orange-rooted cultivar, with regard to changes in concentration of total phenolics (TP) and hydroxycinnamic acids (HA), chlorogenic acid (CGA), total and individual anthocyanins, antioxidant capacity (by DPPH and ABTS), and superficial color appearance, monitoring such changes during cold storage. Results revealed that the UV-C radiation, the fresh-cut processing, and the cold storage influenced the content of antioxidant compounds and activities to varying extents, depending on the carrot cultivar, the degree of processing, and the phytochemical compound analyzed. UV-C radiation increased antioxidant capacity up to 2.1, 3.8, 2.5-folds; TP up to 2.0, 2.2, and 2.1-folds; and CGA up to 3.2, 6.6, and 2.5-folds, relative to UV-C untreated controls, for orange, yellow, and purple carrots, respectively. Anthocyanin levels were not significantly modified by the UV-C in both purple carrots evaluated. A moderate increase in tissue browning was found in some fresh-cut processed UV-C treated samples of yellow and purple but not orange roots. These data suggest variable potential for increasing functional value by UV-C radiation in different carrot root colors.
Peptidome and Transcriptome Analysis of Plant Peptides Involved in Bipolaris maydis Infection of Maize
Authors: Sheng Pijie , Xu Minyan , Zheng Zhenzhen , Liu Xiaojing , Ma Wanlu , Ding Ting , Zhang Chenchen , Chen Meng , Zhang Mengting , Cheng Beijiu , Zhang Xin
Published: March 2023

Southern corn leaf blight (SCLB) caused by Bipolaris maydis threatens maize growth and yield worldwide. In this study, TMT-labeled comparative peptidomic analysis was established between infected and uninfected maize leaf samples using liquid-chromatography-coupled tandem mass spectrometry. The results were further compared and integrated with transcriptome data under the same experimental conditions. Plant peptidomic analysis identified 455 and 502 differentially expressed peptides (DEPs) in infected maize leaves on day 1 and day 5, respectively. A total of 262 common DEPs were identified in both cases. Bioinformatic analysis indicated that the precursor proteins of DEPs are associated with many pathways generated by SCLB-induced pathological changes. The expression profiles of plant peptides and genes in maize plants were considerably altered after B. maydis infection. These findings provide new insights into the molecular mechanisms of SCLB pathogenesis and offer a basis for the development of maize genotypes with SCLB resistance.
Transcriptomic Analysis Reveals Panicle Heterosis in an Elite Hybrid Rice ZZY10 and Its Parental Lines
Authors: Zhong Zhengzheng , Wu Yawen , Zhang Peng , Hu Guocheng , Fu Dong , Yu Guoping , Tong Hanhua
Published: March 2023

Heterosis is the phenomenon in which some hybrid traits are superior to those of their parents. Most studies have analyzed the heterosis of agronomic traits of crops; however, heterosis of the panicles can improve yield and is important for crop breeding. Therefore, a systematic study of panicle heterosis is needed, especially during the reproductive stage. RNA sequencing (RNA Seq) and transcriptome analysis are suitable for further study of heterosis. Using the Illumina Nova Seq platform, the transcriptome of ZhongZheYou 10 (ZZY10), an elite rice hybrid, the maintainer line ZhongZhe B (ZZB), and the restorer line Z7-10 were analyzed at the heading date in Hangzhou, 2022. 581 million high-quality short reads were obtained by sequencing and were aligned against the Nipponbare reference genome. A total of 9000 differential expression genes were found between the hybrids and their parents (DGHP). Of the DGHP, 60.71% were up-regulated and 39.29% were down-regulated in the hybrid. Comparative transcriptome analysis revealed that 5235 and 3765 DGHP were between ZZY10 and ZhongZhe B and between ZZY10 and Z7-10, respectively. This result is consistent with the transcriptome profile of ZZY10 and was similar to Z7-10. The expression patterns of DGHP mainly exhibited over-dominance, under-dominance, and additivity. Among the DGHP-involved GO terms, pathways such as photosynthesis, DNA integration, cell wall modification, thylakoid, and photosystem were significant. 21 DGHP, which were involved in photosynthesis, and 17 random DGHP were selected for qRT-PCR validation. The up-regulated PsbQ and down-regulated subunits of PSI and PSII and photosynthetic electron transport in the photosynthesis pathway were observed in our study. Extensive transcriptome data were obtained by RNA-Seq, providing a comprehensive overview of panicle transcriptomes at the heading stage in a heterotic hybrid.
Evaluation of Amino Acid Profiles of Rice Genotypes under Different Salt Stress Conditions
Authors: Farooq Muhammad , Jang Yoon-Hee , Kim Eun-Gyeong , Park Jae-Ryoung , Eom Gyu-Hyeon , Zhao Dan-Dan , Kim Kyung-Min
Published: March 2023

Amino acids are building blocks of proteins that are essential components of a wide range of metabolic pathways in plant species, including rice species. Previous studies only considered changes in the amino acid content of rice under NaCl stress. Here, we evaluated profiles of essential and non-essential amino acids in four rice genotype seedlings in the presence of three types of salts, namely NaCl, CaCl2, and MgCl2. Amino acid profiles in 14-day-old rice seedlings were determined. The total essential and non-essential amino acid contents in cultivar Cheongcheong were considerably increased upon NaCl and MgCl2 application, whereas total amino acids were increased upon NaCl, CaCl2, and MgCl2 application in the cultivar Nagdong. The total amino acid content was significantly lower in the salt-sensitive cultivar IR28 and salt-tolerant Pokkali under different salt stress conditions. Glycine was not detected in any of the rice genotypes. We observed that cultivars with the same origin respond similarly to each other under salinity stress conditions: cultivars Cheongcheong and Nagdong were found to show increased total amino acid content, whereas the content in foreign cultivars IR28 and Pokkali was found to decrease. Thus, our findings showed that the amino acid profile of each rice cultivar might depend on the origin, immune level, and genetic makeup of the respective cultivar.
Bilayer Films of Poly(lactic acid) and Cottonseed Protein for Packaging Applications
Authors: Biswas Atanu , Cheng Huai N. , Kuzniar Gary , He Zhongqi , Kim Sanghoon , Furtado Roselayne F. , Alves Carlucio R. , Sharma Brajendra K.
Published: March 2023

Poly(lactic acid) (PLA) is a common biobased film-former made from renewable biomass, such as polysaccharides from sugarcane, corn, or cassava. It has good physical properties but is relatively expensive when compared to the plastics used for food packaging. In this work, bilayer films were designed, incorporating a PLA layer and a layer of washed cottonseed meal (CSM), an inexpensive agro-based raw material from cotton manufacturing, where the main component is cottonseed protein. These bilayer films were made through the solvent casting method. The combined thickness of the PLA/CSM bilayer film was between 47 and 83 μm. The thickness of the PLA layer in this film was 10%, 30%, or 50% of the total bilayer film’s thickness. Mechanical properties of the films, opacity, water vapor permeation, and thermal properties were evaluated. Since PLA and CSM are both agro-based, sustainable, and biodegradable, the bilayer film may be used as an eco-friendlier food packaging material, which helps reduce the environmental problems of plastic waste and microplastics. Moreover, the utilization of cottonseed meal may add value to this cotton byproduct and provide a potential economic benefit to cotton farmers.
Characterization of Conductive 3D Printed Fingertips Manufactured by Fused Filament Fabrication
Authors: Kai Zhao , Jung Imjoo , Lee Sunhee
Published: March 2023

This study purposed to develop conductivity 3D printed (3DP) fingertips and confirm their potential for use in a pressure sensor. Index fingertips were 3D printed using thermoplastic polyurethane filament with three types of infill patterns (Zigzag (ZG), Triangles (TR), Honeycomb (HN)) and densities (20%, 50%, 80%). Hence, the 3DP index fingertip was dip-coated with 8 wt% graphene/waterborne polyurethane composite solution. The coated 3DP index fingertips were analyzed by appearance property, weight changes, compressive property, and electrical property. As results, the weight increased from 1.8 g to 2.9 g as infill density increased. By infill pattern, ZG was the largest, and the pick-up rate decreased from 18.9% for 20% infill density to 4.5% for 80% infill density. Compressive properties were confirmed. Compressive strength increased as infill density increased. In addition, the compressive strength after coating was improved more than 1000 times. Especially, TR had excellent compressive toughness as 13.9 J for 20%, 17.2 J for 50%, and 27.9 J for 80%. In the case of electrical properties, the current become excellent at 20% infill density. By infill patterns at 20% infill density, TR has 0.22 mA as the best conductivity. Therefore, we confirmed the conductivity of 3DP fingertips, and the infill pattern of TR at 20% was most suitable.
The Effect of Alkyl Terminal Chain Length of Schiff-Based Cyclotriphosphazene Derivatives towards Epoxy Resins on Flame Retardancy and Mechanical Properties
Authors: Waldin Nur Atika , Jamain Zuhair
Published: March 2023

A series of Schiff-based cyclotriphosphazenes with different alkyl chain length terminal ends, 4a (dodecyl) and 4b (tetradecyl), were synthesized and the structures were characterized using Fourier-transform infrared spectroscopy (FT-IR), and 1H, 13C, and 31P nuclear magnetic resonance (NMR) and carbon, hydrogen, and nitrogen (CHN) elemental analysis. The flame-retardant and mechanical properties of the epoxy resin (EP) matrix were examined. The limiting oxygen index (LOI) of 4a (26.55%) and 4b (26.71%) revealed a good increment compared to pure EP (22.75%). The LOI results corresponded to their thermal behavior studied using thermogravimetric analysis (TGA) and the char residue analyzed under field emission scanning electron microscopy (FESEM). The mechanical properties of EP showed a positive impact on tensile strength with a trend of EP < 4a < 4b. The tensile strength went from 8.06 N/mm2 (pure EP) to 14.36 and 20.37 N/mm2, indicating that the additives were compatible with epoxy resin.
Identification of a Thermostable Levansucrase from Pseudomonas orientalis That Allows Unique Product Specificity at Different Temperatures
Authors: Guang Cuie , Zhang Xiaoqi , Ni Dawei , Zhang Wenli , Xu Wei , Mu Wanmeng
Published: March 2023

The biological production of levan by levansucrase (LS, EC 2.4.1.10) has aroused great interest in the past few years. Previously, we identified a thermostable levansucrase from Celerinatantimonas diazotrophica (Cedi-LS). A novel thermostable LS from Pseudomonas orientalis (Psor-LS) was successfully screened using the Cedi-LS template. The Psor-LS showed maximum activity at 65 °C, much higher than the other LSs. However, these two thermostable LSs showed significantly different product specificity. When the temperature was decreased from 65 to 35 °C, Cedi-LS tended to produce high-molecular-weight (HMW) levan. By contrast, Psor-LS prefers to generate fructooligosaccharides (FOSs, DP ≤ 16) rather than HMW levan under the same conditions. Notably, at 65 °C, Psor-LS would produce HMW levan with an average Mw of 1.4 × 106 Da, indicating that a high temperature might favor the accumulation of HMW levan. In summary, this study allows a thermostable LS suitable for HMW levan and levan-type FOSs production simultaneously.
Elastic Modulus of a Carbonized Layer on Polyurethane Treated by Ion-Plasma
Authors: Chudinov Vyacheslav S. , Shardakov Igor N. , Ivanov Yaroslav N. , Morozov Ilya A. , Belyaev Anton Y.
Published: March 2023

Nanocoatings formed by various plasma and chemical methods on the surface of polymeric materials have unique properties. However, the applicability of polymeric materials with nanocoatings under specific temperature and mechanical conditions depends on the physical and mechanical properties of the coating. The determination of Young’s modulus is a task of paramount importance since it is widely used in calculations of the stress–strain state of structural elements and structures in general. Small thicknesses of nanocoatings limit the choice of methods for determining the modulus of elasticity. In this paper, we propose a method for determining the Young’s modulus for a carbonized layer formed on a polyurethane substrate. For its implementation, the results of uniaxial tensile tests were used. This approach made it possible to obtain patterns of change in the Young’s modulus of the carbonized layer depending on the intensity of ion-plasma treatment. These regularities were compared with regularities of changes in the molecular structure of the surface layer caused by plasma treatment of different intensity. The comparison was made on the basis of correlation analysis. Changes in the molecular structure of the coating were determined from the results of infrared Fourier spectroscopy (FTIR) and spectral ellipsometry.
Experimental Investigation of the Flow Conditions in Spiral Jet Mills via Particle Image Velocimetry—Influence of Product Outlet Diameter and Gas Flow Rate
Authors: Radeke Lisa Marie , Jongebloed Niklas , Ulbricht Mathias , Schultz Heyko Jürgen
Published: March 2023

Spiral jet mills used for fine and colloid grinding have an enormously high energy consumption resulting in a great potential for optimization. In order to increase their efficiency, it is essential to precisely understand the flow conditions within the grinding chamber and the influencing parameters. In this work, the experimental method of particle image velocimetry is applied, which is optimized to the extent that the velocity fields of the grinding gas flow can be determined in the entire mill cross-section. Additionally, the influence of the product outlet diameter and the grinding gas flow rate on the flow profiles are investigated. With decreasing outlet diameter, significantly higher velocities are obtained in the inner mill region resulting in higher classifying efficiencies. At the same time, as the outlet diameter declines, an overpressure builds up in the mill, causing a deceleration of the entire flow in the outer region, preventing the complete formation of the nozzle jets and leading to worse comminution efficiencies. Therefore, there is an optimum between the competing comminution and classifying processes regarding the effect of the product outlet diameter. In contrast, increasing the gas flow rate can consistently achieve a gain in velocity, improving both comminution and classifying efficiency.
A Novel Hybrid Model of CNN-SA-NGU for Silver Closing Price Prediction
Authors: Wang Haiyao , Dai Bolin , Li Xiaolei , Yu Naiwen , Wang Jingyang
Published: March 2023

Silver is an important industrial raw material, and the price of silver has always been a concern of the financial industry. Silver price data belong to time series data and have high volatility, irregularity, nonlinearity, and long-term correlation. Predicting the silver price for economic development is of great practical significance. However, the traditional time series prediction models have shortcomings, such as poor nonlinear fitting ability and low prediction accuracy. Therefore, this paper presents a novel hybrid model of CNN-SA-NGU for silver closing price prediction, which includes conventional neural networks (CNNs), the self-attention mechanism (SA), and the new gated unit (NGU). A CNN extracts the feature of input data. The SA mechanism captures the correlation between different eigenvalues, thus forming new eigenvectors to make weight distribution more reasonable. The NGU is a new deep-learning gated unit proposed in this paper, which is formed by a forgetting gate and an input gate. The NGU’s input data include the cell state of the previous time, the hidden state of the previous time, and the input data of the current time. The NGU learns the previous time’s experience to process the current time’s input data and adds a Tri module behind the input gate to alleviate the gradient disappearance and gradient explosion problems. The NGU optimizes the structure of traditional gates and reduces the computation. To prove the prediction accuracy of the CNN-SA-NGU, this model is compared with the thirteen other time series forecasting models for silver price prediction. Through comparative experiments, the mean absolute error (MAE) value of the CNN-SA-NGU model is 87.898771, the explained variance score (EVS) value is 0.970745, the r-squared (R2) value is 0.970169, and the training time is 332.777 s. The performance of CNN-SA-NGU is better than other models.
Intersections, Assimilations, and Conflicts in Eighteenth-Century Palermo: The Church of the Forty Martyrs and Saint Ranieri of the Pisan Nation
Authors: Viola Valeria
Published: March 2023

Due to its strategic position in the Mediterranean Sea, Sicily was a place of multiple cultural contaminations and commercial exchanges throughout the early modern era. Trade, piracy, and even slavery implemented continuous contacts between populations from opposing shores, regardless of their different religious beliefs. Yet, the island was also intended as a Christian bulwark against the Islamic world and its institutions fostered anti-Muslim prejudices. To date, this discrepancy has been little investigated, but the responsibilities of art in fueling discriminatory attitudes have been explored even less. Drawing on Francisco Bethencourt’s idea that racism is motivated by political projects, this paper illustrates the complicity of art in reinforcing prejudices for political interests. To do so, it explores the 1725 frescoes by the Flemish painter Guglielmo Borremans (1670–1744) in the church of the Forty Martyrs and Saint Ranieri of the Pisan Nation, in Palermo. In the face of persistent multiculturalism in the daily life of the population, these frescoes affirmed the supremacy of Pisa as a victorious guardian of Christianity in the Mediterranean. In this way, they celebrated the urban nobility of Pisan descent, while disguising the problematic identity of its enemy.
Christian Women and the Development of Nascent Feminist Consciousness in Nineteenth-Century China
Authors: Stasson Anneke H.
Published: March 2023

In 2010, Padma Anagol argued that the first modern feminists in India were Christian women, women such as Laxmibai Tilak and Pandita Ramabai. Using Anagol’s definition of feminism as “a theory and practice which presented a challenge to the subordination of women in society and attempted to redress the balance of power between the sexes,” this article shows how feminist consciousness was cultivated in Christian schools, churches, hospitals, and organizations in late-nineteenth-century China. Kwok Pui Lan pointed out in 1992 that Christians were the first women in China to band together to fight women’s oppression; however, like so many of the claims made about women in global Christianity, this one has not yet been fully appreciated by historians and missiologists. I show how mission schools gave girls access to new models of personhood and womanhood. Likewise, Christian scriptures, churches, and voluntary societies such as the WCTU and YWCA provided space to reflect on gender identity and activism. Through all these avenues, a modest version of Christian feminism was cultivated in China decades before the secular women’s movement began in 1900.
CHFNet: Curvature Half-Level Fusion Network for Single-Frame Infrared Small Target Detection
Authors: Zhang Mingjin , Li Bate , Wang Tianyu , Bai Haichen , Yue Ke , Li Yunsong
Published: March 2023

Single-frame infrared small target detection (IRSTD) aims to extract targets from background clutter and distinguish them from noise. In recent years, semantic segmentation deep learning methods such as CNNs have made many breakthroughs in the field of IRSTD. However, there are limitations to this method; for example, the targets tend to be too dim, and heavy background clutter exists. To further improve the accuracy of IRSTD, we propose a novel curvature half-level fusion network (CHFNet) for IRSTD. First, we developed a half-level fusion (HLF) block as a new cross-layer feature fusion module. With the HLF block, the network excavates the half-level features between two levels of features, thus ensuring that each feature of the levels has minimal distortion. Given that even dim targets have certain curvature features, we calculated the weighted mean curvature of the image to obtain the attention of the boundary, then fused it with the features of each level to detect the edges of targets. In comparison, the prediction results of the proposed CHFNet on the NUAA-SIRST dataset were more complete and better preserved edge targets.
A Cross Stage Partial Network with Strengthen Matching Detector for Remote Sensing Object Detection
Authors: Ren Shougang , Fang Zhiruo , Gu Xingjian
Published: March 2023

Remote sensing object detection is a difficult task because it often requires real-time feedback through numerous objects in complex environments. In object detection, Feature Pyramids Networks (FPN) have been widely used for better representations based on a multi-scale problem. However, the multiple level features cause detectors’ structures to be complex and makes redundant calculations that slow down the detector. This paper uses a single-layer feature to make the detection lightweight and accurate without relying on Feature Pyramid Structures. We proposed a method called the Cross Stage Partial Strengthen Matching Detector (StrMCsDet). The StrMCsDet generates a single-level feature map architecture in the backbone with a cross stage partial network. To provide an alternative way of replacing the traditional feature pyramid, a multi-scale encoder was designed to compensate the receptive field limitation. Additionally, a stronger matching strategy was proposed to make sure that various scale anchors may be equally matched. The StrMCsDet is different from the conventional full pyramid structure and fully exploits the feature map which deals with a multi-scale encoder. Methods achieved both comparable precision and speed for practical applications. Experiments conducted on the DIOR dataset and the NWPU-VHR-10 dataset achieved 65.6 and 73.5 mAP on 1080 Ti, respectively, which can match the performance of state-of-the-art works. Moreover, StrMCsDet requires less computation and achieved 38.5 FPS on the DIOR dataset.
Accounting for Turbulence-Induced Canopy Heat Transfer in the Simulation of Sensible Heat Flux in SEBS Model
Authors: Njuki Sammy M. , Mannaerts Chris M. , Su Zhongbo
Published: March 2023

Surface turbulent heat fluxes are crucial for monitoring drought, heat waves, urban heat islands, agricultural water management, and other hydrological applications. Energy Balance Models (EBMs) are widely used to simulate surface heat fluxes from a combination of remote sensing-derived variables and meteorological data. Single-source EBMs, in particular, are preferred in mapping surface turbulent heat fluxes due to their relative simplicity. However, most single-source EBMs suffer from uncertainties inherent to the parameter kB−1, which is used to account for differences in the source of heat and the sink of momentum when representing aerodynamic resistance in single-source EBMs. For instance, the parameterization of kB−1 in the commonly used single-source Surface Energy Balance System (SEBS) model uses a constant value of the foliage heat transfer coefficient (Ct), in the parameterization of the vegetation component of kB−1 (kBv−1). Thus, SEBS ignores the effect of turbulence on canopy heat transfer. As a result, SEBS has been found to greatly underestimate sensible heat flux in tall forest canopies, where turbulence is a key contributor to canopy heat transfer. This study presents a revised parameterization of kBv−1 for the SEBS model. A physically based formulation of Ct, which considers the effect of turbulence on Ct, is used in deriving the revised parameterization. Simulation results across 15 eddy covariance (EC) flux tower sites show that the revised parameterization significantly reduces the underestimation of sensible heat flux compared to the original parameterization under tall forest canopies. The revised parameterization is relatively simple and does not require additional information on canopy structure compared to some more complex parameterizations proposed in the literature. As such, the revised parameterization is suitable for mapping surface turbulent heat fluxes, especially under tall forest canopies.
Hyperspectral Video Tracker Based on Spectral Deviation Reduction and a Double Siamese Network
Authors: Zhang Zhe , Hu Bin , Wang Mengyuan , Arun Pattathal V. , Zhao Dong , Zhu Xuguang , Hu Jianling , Li Huan , Zhou Huixin , Qian Kun
Published: March 2023

The advent of hyperspectral cameras has popularized the study of hyperspectral video trackers. Although hyperspectral images can better distinguish the targets compared to their RGB counterparts, the occlusion and rotation of the target affect the effectiveness of the target. For instance, occlusion obscures the target, reducing the tracking accuracy and even causing tracking failure. In this regard, this paper proposes a novel hyperspectral video tracker where the double Siamese network (D-Siam) forms the basis of the framework. Moreover, AlexNet serves as the backbone of D-Siam. The current study also adopts a novel spectral–deviation-based dimensionality reduction approach on the learned features to match the input requirements of the AlexNet. It should be noted that the proposed dimensionality reduction method increases the distinction between the target and background. The two response maps, namely the initial response map and the adjacent response map, obtained using the D-Siam network, were fused using an adaptive weight estimation strategy. Finally, a confidence judgment module is proposed to regulate the update for the whole framework. A comparative analysis of the proposed approach with state-of-the-art trackers and an extensive ablation study were conducted on a publicly available benchmark hyperspectral dataset. The results show that the proposed tracker outperforms the existing state-of-the-art approaches against most of the challenges.
MCBAM-GAN: The Gan Spatiotemporal Fusion Model Based on Multiscale and CBAM for Remote Sensing Images
Authors: Liu Hui , Yang Guangqi , Deng Fengliang , Qian Yurong , Fan Yingying
Published: March 2023

Due to the limitations of current technology and budget, as well as the influence of various factors, obtaining remote sensing images with high-temporal and high-spatial (HTHS) resolution simultaneously is a major challenge. In this paper, we propose the GAN spatiotemporal fusion model Based on multiscale and convolutional block attention module (CBAM) for remote sensing images (MCBAM-GAN) to produce high-quality HTHS fusion images. The model is divided into three stages: multi-level feature extraction, multi-feature fusion, and multi-scale reconstruction. First of all, we use the U-NET structure in the generator to deal with the significant differences in image resolution while avoiding the reduction in resolution due to the limitation of GPU memory. Second, a flexible CBAM module is added to adaptively re-scale the spatial and channel features without increasing the computational cost, to enhance the salient areas and extract more detailed features. Considering that features of different scales play an essential role in the fusion, the idea of multiscale is added to extract features of different scales in different scenes and finally use them in the multi loss reconstruction stage. Finally, to check the validity of MCBAM-GAN model, we test it on LGC and CIA datasets and compare it with the classical algorithm for spatiotemporal fusion. The results show that the model performs well in this paper.
Determination of Magnetic Structures in Magnetic Microwires with Longitudinally Distributed Magnetic Anisotropy
Authors: Chizhik Alexander , Corte-Leon Paula , Zhukova Valentina , Gonzalez Julian , Gawronski Przemyslaw , Blanco Juan Mari , Zhukov Arcady
Published: March 2023

We studied the magnetic properties of a glass-covered amorphous microwire that was stress-annealed at temperatures distributed along the microwire length. The Sixtus-Tonks, Kerr effect microscopy and magnetic impedance techniques have been applied. There was a transformation of the magnetic structure across the zones subjected to annealing at different temperatures. The annealing temperature distribution induces the graded magnetic anisotropy in the studied sample. The variety of the surface domain structures depending on the longitudinal location has been discovered. Spiral, circular, curved, elliptic and longitudinal domain structures coexist and replace each other in the process of magnetization reversal. The analysis of the obtained results was carried out based on the calculations of the magnetic structure, assuming the distribution of internal stresses.
Two-Stage Framework for Faster Semantic Segmentation
Authors: Cruz Ricardo , Silva Diana Teixeira e , Gonçalves Tiago , Carneiro Diogo , Cardoso Jaime S.
Published: March 2023

Semantic segmentation consists of classifying each pixel according to a set of classes. Conventional models spend as much effort classifying easy-to-segment pixels as they do classifying hard-to-segment pixels. This is inefficient, especially when deploying to situations with computational constraints. In this work, we propose a framework wherein the model first produces a rough segmentation of the image, and then patches of the image estimated as hard to segment are refined. The framework is evaluated in four datasets (autonomous driving and biomedical), across four state-of-the-art architectures. Our method accelerates inference time by four, with additional gains for training time, at the cost of some output quality.
Introduction to Door Opening Type Classification Based on Human Demonstration
Authors: Šimundić Valentin , Džijan Matej , Pejić Petra , Cupec Robert
Published: March 2023

Opening doors and drawers will be an important ability for future service robots used in domestic and industrial environments. However, in recent years, the methods for opening doors and drawers have become more diverse and difficult for robots to determine and manipulate. We can divide doors into three distinct handling types: regular handles, hidden handles, and push mechanisms. While extensive research has been done on the detection and handling of regular handles, the other types of handling have not been explored as much. In this paper, we set out to classify the types of cabinet door handling types. To this end, we collect and label a dataset consisting of RGB-D images of cabinets in their natural environment. As part of the dataset, we provide images of humans demonstrating the handling of these doors. We detect the poses of human hands and then train a classifier to determine the type of cabinet door handling. With this research, we hope to provide a starting point for exploring the different types of cabinet door openings in real-world environments.
Cyclist Orientation Estimation Using LiDAR Data
Authors: Chang Hyoungwon , Gu Yanlei , Goncharenko Igor , Hsu Li-Ta , Premachandra Chinthaka
Published: March 2023

It is crucial for an autonomous vehicle to predict cyclist behavior before decision-making. When a cyclist is on real traffic roads, his or her body orientation indicates the current moving directions, and his or her head orientation indicates his or her intention for checking the road situation before making next movement. Therefore, estimating the orientation of cyclist’s body and head is an important factor of cyclist behavior prediction for autonomous driving. This research proposes to estimate cyclist orientation including both body and head orientation using deep neural network with the data from Light Detection and Ranging (LiDAR) sensor. In this research, two different methods are proposed for cyclist orientation estimation. The first method uses 2D images to represent the reflectivity, ambient and range information collected by LiDAR sensor. At the same time, the second method uses 3D point cloud data to represent the information collected from LiDAR sensor. The two proposed methods adopt a model ResNet50, which is a 50-layer convolutional neural network, for orientation classification. Hence, the performances of two methods are compared to achieve the most effective usage of LiDAR sensor data in cyclist orientation estimation. This research developed a cyclist dataset, which includes multiple cyclists with different body and head orientations. The experimental results showed that a model that uses 3D point cloud data has better performance for cyclist orientation estimation compared to the model that uses 2D images. Moreover, in the 3D point cloud data-based method, using reflectivity information has a more accurate estimation result than using ambient information.
Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
Authors: Jakopec Ivan , Marendić Ante , Grgac Igor
Published: March 2023

One of the most commonly used surveying techniques for landslide monitoring is a photogrammetric survey using an Unmanned Aerial System (UAS), where landslide displacements can be determined by comparing dense point clouds, digital terrain models, and digital orthomosaic maps resulting from different measurement epochs. A new data processing method for calculating landslide displacements based on UAS photogrammetric survey data is presented in this paper, whose main advantage is the fact that it does not require the production of the above-mentioned products, enabling faster and simpler displacement determination. The proposed method is based on matching features between the images from two different UAS photogrammetric surveys and calculating the displacements based only on the comparison of two reconstructed sparse point clouds. The accuracy of the method was analyzed on a test field with simulated displacements and on an active landslide in Croatia. Moreover, the results were compared with the results obtained with a commonly used method based on comparing manually tracked features on orthomosaics from different epochs. Analysis of the test field results using the presented method show the ability to determine displacements with a centimeter level accuracy in ideal conditions even with a flight height of 120 m, and on the Kostanjek landslide with a sub-decimeter level accuracy.
Research on Underdetermined DOA Estimation Method with Unknown Number of Sources Based on Improved CNN
Authors: Zhao Fangzheng , Hu Guoping , Zhou Hao , Guo Shuhan
Published: March 2023

This paper proposes a joint estimation method for source number and DOA based on an improved convolutional neural network for unknown source number and undetermined DOA estimation. By analyzing the signal model, the paper designs a convolutional neural network model based on the existence of a mapping relationship between the covariance matrix and both the source number and DOA estimation. The model, which discards the pooling layer to avoid data loss and introduces the dropout method to improve generalization, takes the signal covariance matrix as input and the two branches of source number estimation and DOA estimation as outputs, and achieves the unfixed number of DOA estimation by filling in invalid values. Simulation experiments and analysis of the results show that the algorithm can effectively achieve the joint estimation of source number and DOA. Under the conditions of high SNR and a large snapshot number, both the proposed algorithm and the traditional algorithm have high estimation accuracy, while under the conditions of low SNR and a small snapshot, the algorithm is better than the traditional algorithm, and under the underdetermined conditions, where the traditional algorithm often fails, the algorithm can still achieve the joint estimation.
Revealing Local Temporal Profile of Laser Pulses of Intensity above 1014 W/cm2
Authors: Lu Qi , Zhang Xiang , Couairon Arnaud , Liu Yi
Published: March 2023

We demonstrated a method for in situ temporal characterization of an intense femtosecond laser pulse around its focus where the laser intensity exceeds 1014 W/cm2. Our method is based on the second harmonic generation (SHG) by a relatively weak femtosecond probe pulse and the intense femtosecond pulses under analysis in the gas plasma. With the increase in the gas pressure, it was found that the incident pulse evolves from a Gaussian profile to a more complicated structure featured by multiple peaks in the temporal domain. Numerical simulations of filamentation propagation support the experimental observations of temporal evolution. This simple method can be applied to many situations involving femtosecond laser–gas interaction, when the temporal profile of the femtosecond pump laser pulse with an intensity above 1014 W/cm2 cannot be measured in traditional ways.
Denoising Generalization Performance of Channel Estimation in Multipath Time-Varying OFDM Systems
Authors: Li Yinying , Bian Xin , Li Mingqi
Published: March 2023

Although Orthogonal Frequency Division Multiplexing (OFDM) technology is still the key transmission waveform technology in 5G, traditional channel estimation algorithms are no longer sufficient for the high-speed multipath time-varying channels faced by both existing 5G and future 6G. In addition, the existing Deep Learning (DL) based OFDM channel estimators are only applicable to Signal-to-Noise Ratios (SNRs) in a small range, and the estimation performance of the existing algorithms is greatly limited when the channel model or the mobile speed at the receiver does not match. To solve this problem, this paper proposes a novel network model NDR-Net that can be used for channel estimation under unknown noise levels. NDR-Net consists of a Noise Level Estimate subnet (NLE), a Denoising Convolutional Neural Network subnet (DnCNN), and a Residual Learning cascade. Firstly, a rough channel estimation matrix value is obtained using the conventional channel estimation algorithm. Then it is modeled as an image and input to the NLE subnet for noise level estimation to obtain the noise interval. Then it is input to the DnCNN subnet together with the initial noisy channel image for noise reduction to obtain the pure noisy image. Finally, the residual learning is added to obtain the noiseless channel image. The simulation results show that NDR-Net can obtain better estimation results than traditional channel estimation, and it can be well adapted when the SNR, channel model, and movement speed do not match, which indicates its superior engineering practicability.
High-Sensitivity 2D MoS2/1D MWCNT Hybrid Dimensional Heterostructure Photodetector
Authors: Fu Nanxin , Zhang Jiazhen , He Yuan , Lv Xuyang , Guo Shuguang , Wang Xingjun , Zhao Bin , Chen Gang , Wang Lin
Published: March 2023

A photodetector based on a hybrid dimensional heterostructure of laterally aligned multiwall carbon nanotubes (MWCNTs) and multilayered MoS2 was prepared using the micro-nano fixed-point transfer technique. Thanks to the high mobility of carbon nanotubes and the efficient interband absorption of MoS2, broadband detection from visible to near-infrared (520–1060 nm) was achieved. The test results demonstrate that the MWCNT-MoS2 heterostructure-based photodetector device exhibits an exceptional responsivity, detectivity, and external quantum efficiency. Specifically, the device demonstrated a responsivity of 3.67 × 103 A/W (λ = 520 nm, Vds = 1 V) and 718 A/W (λ = 1060 nm, Vds = 1 V). Moreover, the detectivity (D*) of the device was found to be 1.2 × 1010 Jones (λ = 520 nm) and 1.5 × 109 Jones (λ = 1060 nm), respectively. The device also demonstrated external quantum efficiency (EQE) values of approximately 8.77 × 105% (λ = 520 nm) and 8.41 × 104% (λ = 1060 nm). This work achieves visible and infrared detection based on mixed-dimensional heterostructures and provides a new option for optoelectronic devices based on low-dimensional materials.