bluuebunny/crossref_metadata_2025 huggingface dataset:
A Model-Free Control Scheme for Rehabilitation Robots: Integrating Real-Time Observations with a Deep Neural Network for Enhanced Control and Reliability
Authors: Alsubaie Hajid , Alotaibi Ahmed
Published: November 2023

Effective control of rehabilitation robots is of paramount importance and requires increased attention to achieve a fully reliable, automated system for practical applications. As the domain of robotic rehabilitation progresses rapidly, the imperative for precise and dependable control mechanisms grows. In this study, we present an innovative control scheme integrating state-of-the-art machine learning algorithms with traditional control techniques. Our approach offers enhanced adaptability to patient-specific needs while ensuring safety and effectiveness. We introduce a model-free feedback linearization control method underpinned by deep neural networks and online observation. While our controller is model-free, and system dynamics are learned during training phases, we employ an online observer to robustly estimate uncertainties that the systems may face in real-time, beyond their training. The proposed technique was tested through different simulations with varying initial conditions and step references, demonstrating the controller’s robustness and adaptability. These simulations, combined with Lyapunov’s stability verification, validate the efficacy of our proposed scheme in effectively controlling the system under diverse conditions.
A Parameterized Modeling Method for Magnetic Circuits of Adjustable Permanent Magnet Couplers
Authors: Wang Dazhi , Li Wenhui , Wang Jiaxing , Song Keling , Ni Yongliang , Li Yanming
Published: November 2023

The contactless transmission between the conductor rotor and the permanent magnet (PM) rotor of an adjustable permanent magnet coupler (APMC) provides the device with significant tolerance for alignment errors, making the performance estimation complicated and inaccurate. The first proposal of an edge coefficient in this paper helps to describe the edge effect with better accuracy. Accurate equivalent magnetic circuit (EMC) models of the APMC are established for each region. Models of magnetic flux, magnetic resistance, and eddy current density are established by defining the equivalent dimensional parameters of the eddy current circuit. Furthermore, the concept of magnetic inductance is proposed for the first time, parameterizing eddy currents that are difficult to describe with physical models and achieving the modeling of the dynamic eddy current circuit. The magnetic resistance is subdivided into two parts corresponding to the output and slip according to the power relationship. Furthermore, eddy current loss and dynamic torque models are further derived. The method proposed in this paper enables the APMC to be modeled and calculated in a completely new way. The correctness and accuracy of the model have been fully demonstrated using finite element simulation and an experimental prototype. In addition, the limitations of the proposed method and the reasons are fully discussed and investigated.
Modelling Infectious Disease Dynamics: A Robust Computational Approach for Stochastic SIRS with Partial Immunity and an Incidence Rate
Authors: Baazeem Amani S. , Nawaz Yasir , Arif Muhammad Shoaib , Abodayeh Kamaleldin , AlHamrani Mae Ahmed
Published: November 2023

For decades, understanding the dynamics of infectious diseases and halting their spread has been a major focus of mathematical modelling and epidemiology. The stochastic SIRS (susceptible–infectious–recovered–susceptible) reaction–diffusion model is a complicated but crucial computational scheme due to the combination of partial immunity and an incidence rate. Considering the randomness of individual interactions and the spread of illnesses via space, this model is a powerful instrument for studying the spread and evolution of infectious diseases in populations with different immunity levels. A stochastic explicit finite difference scheme is proposed for solving stochastic partial differential equations. The scheme is comprised of predictor–corrector stages. The stability and consistency in the mean square sense are also provided. The scheme is applied to diffusive epidemic models with incidence rates and partial immunity. The proposed scheme with space’s second-order central difference formula solves deterministic and stochastic models. The effect of transmission rate and coefficient of partial immunity on susceptible, infected, and recovered people are also deliberated. The deterministic model is also solved by the existing Euler and non-standard finite difference methods, and it is found that the proposed scheme forms better than the existing non-standard finite difference method. Providing insights into disease dynamics, control tactics, and the influence of immunity, the computational framework for the stochastic SIRS reaction–diffusion model with partial immunity and an incidence rate has broad applications in epidemiology. Public health and disease control ultimately benefit from its application to the study and management of infectious illnesses in various settings.
Therapeutic Potential of Marine-Derived Cyclic Peptides as Antiparasitic Agents
Authors: Ribeiro Ricardo , Costa Lia , Pinto Eugénia , Sousa Emília , Fernandes Carla
Published: November 2023

Parasitic diseases still compromise human health. Some of the currently available therapeutic drugs have limitations considering their adverse effects, questionable efficacy, and long treatment, which have encouraged drug resistance. There is an urgent need to find new, safe, effective, and affordable antiparasitic drugs. Marine-derived cyclic peptides have been increasingly screened as candidates for developing new drugs. Therefore, in this review, a systematic analysis of the scientific literature was performed and 25 marine-derived cyclic peptides with antiparasitic activity (1–25) were found. Antimalarial activity is the most reported (51%), followed by antileishmanial (27%) and antitrypanosomal (20%) activities. Some compounds showed promising antiparasitic activity at the nM scale, being active against various parasites. The mechanisms of action and targets for some of the compounds have been investigated, revealing different strategies against parasites.
Horizontal and Vertical Comparison of Microbial Community Structures in a Low Permeability Reservoir at the Local Scale
Authors: Zhi Zena , Bian Ziwei , Chen Yuan , Zhang Xiangchun , Wu Yifei , Wu Hanning
Published: November 2023

Petroleum microorganisms play a crucial role in the application of microbial-enhanced oil recovery, and the community structures of petroleum microorganisms have been widely studied. Due to variations in reservoir geological conditions, reservoir microbial communities exhibit unique characteristics. However, previous studies have primarily focused on microbial community changes within a single well, a single block, and before and after water flooding, and thus, cross-horizon and cross-regional comparative studies of in situ microbial communities are lacking. In this study, the 16S rRNA full-length sequencing method was adopted to study bacterial communities in crude oil samples taken from two wells at the same depths (depths of 2425 m and 2412 m) but approximately 20 km apart in the Hujianshan oilfield, located in the Ordos Basin. At the same time, the results were combined with another layer of research data from another article (from a depth of 2140 m). The aim was to compare the differences in the microbial community structures between the oil wells on a horizontal scale and a vertical scale. The results revealed that there were minimal differences in the microbial community structures that were influenced by the horizontal distances within a small range (<20 km), while differences were observed at a larger spatial scale. However, the dominant bacteria (Proteobacteria and Bacteroidetes) in the different oilfields were similar. Vertical depth variations (>300 m) had significant impacts on the communities, and this was mainly controlled by temperature. The greater the depth, the higher formation temperature, leading to an increase in thermophilic and anaerobic bacteria within a community.
Changes in Diversity and Abundance of Ammonia-Oxidizing Archaea and Bacteria along a Glacier Retreating Chronosequence in the Tianshan Mountains, China
Authors: Wu Xiukun , Zhang Wei , Liu Guangxiu , Chen Tuo , Li Zhongqin
Published: November 2023

Glaciers retreating due to global warming create important new habitats, particularly suitable for studying ecosystem development where nitrogen is a limiting factor. Nitrogen availability mainly results from microbial decomposition and transformation processes, including nitrification. AOA and AOB perform the first and rate-limiting step of nitrification. Investigating the abundance and diversity of AOA and AOB is essential for understanding early ecosystem development. The dynamics of AOA and AOB community structure along a soil chronosequence in Tianshan No. 1 Glacier foreland were analyzed using qPCR and clone library methods. The results consistently showed low quantities of both AOA and AOB throughout the chronosequence. Initially, the copy numbers of AOB were higher than those of AOA, but they decreased in later stages. The AOB community was dominated by “Nitrosospira cluster ME”, while the AOA community was dominated by “the soil and sediment 1”. Both communities were potentially connected to supra- and subglacial microbial communities during early stages. Correlation analysis revealed a significant positive correlation between the ratios of AOA and AOB with soil ammonium and total nitrogen levels. These results suggest that variations in abundance and diversity of AOA and AOB along the chronosequences were influenced by ammonium availability during glacier retreat.
Preparation and Properties of UV-Curable Waterborne Polyurethane Acrylate/MXene Nanocomposite Films
Authors: Wang Ying , Zhang Shuai , Lin Yanli , Wang Qianyi , Zhang Ying , Sun Changmei , Qu Rongjun
Published: November 2023

In this study, waterborne polyurethane acrylate (WPUA)/MXene nanocomposite films with varying MXene loadings were fabricated using UV-curing technology, where MXene (Ti3C2Tx) was employed as a nanofiller. The microstructure and chemical structure of the WPUA/MXene nanocomposite films were examined by XRD and FTIR, respectively. The water contact angle testing demonstrated that the incorporation of MXene into the nanocomposite films led to an increase in their hydrophilic properties. The tensile strength, the elongation at break, and Young’s modulus of the WPUA/MXene nanocomposite coatings exhibited an initial increase followed by a decrease with increasing MXene loadings. Compared to the pure WPUA film, the tensile strength and elongation at break of nanocomposites with 0.077 wt% MXene loading reached their maximum values, which increased by 39.9% and 38.5%, respectively. Furthermore, the glass transition temperature and the thermal stability were both enhanced by MXene to some extent. This study introduces a novel method for utilizing MXene in UV-curable waterborne coatings.
Effects of Grain Boundary Misorientation Angle on the Mechanical Behavior of Al Bicrystals
Authors: Velilla-Díaz Wilmer , Zambrano Habib R.
Published: November 2023

This research article explores the effect of grain boundary (GB) misorientation on the mechanical behavior of aluminum (Al) bicrystals by means of molecular dynamics (MD) simulations. The effect of GB misorientation on the mechanical properties, fracture resistance, and crack propagation are evaluated under monotonic and cyclic load conditions. The J-integral and the crack tip opening displacement (CTOD) are assessed to establish the effect of the GB misorientation angle on the fracture resistance. The simulations reveal that the misorientation angle plays a significant role in the mechanical response of Al bicrystals. The results also evidence a gradual change in the mechanical behavior from brittle to ductile as the misorientation angle is increased.
Rapid Anti-tTG-IgA Screening Test for Early Diagnosis of Celiac Disease in Pediatric Populations
Authors: Mendia Irati , Segura Verónica , Ruiz-Carnicer Ángela , Coto Laura , Negrete María , Long Joshua C. D. , Reyes Joaquin , Amil Benito , Salamanca Ignacio , Comino Isabel , Cebolla Ángel , Sousa Carolina
Published: November 2023

A large number of patients with celiac disease (CD) remain undiagnosed because they do not fulfill the criteria for entry into the conventional diagnostic workflow. This study evaluated the clinical utility of anti-tissue transglutaminase IgA antibody lateral flow immunoassays (anti-tTG-IgA LFIA) in the undiagnosed-CD-based pediatric population and the impact of a gluten-free diet (GFD) on screening-detected CD. A total of 576 volunteers were tested for anti-tTG-IgA. Gluten consumption habits, CD related symptoms, and risk factors for CD development were evaluated. Volunteers testing positive for anti-tTG-IgA were referred to the conventional CD diagnostic workflow, and the impact of the GFD on health-related quality of life (HR-QoL) was measured. Among them, 13 had a positive anti-tTG-IgA LFIA test result: 11 had confirmed CD (1.91%), one refused confirmatory tests, and another is undergoing diagnosis. Regarding the CD prevalence, no significant differences were observed among risk (1.89%) and symptomatic (2.65%) groups and the entire tested population (1.55%). Rapid anti-tTG-IgA LFIAs could be of clinical utility in primary care for the early identification of children with CD unidentified by the conventional diagnostic workflow. It could potentially reduce the costs of undiagnosed CD, avoiding unnecessary referrals to gastroenterologists, reducing diagnosis delays and long-term problems, and improving patients’ HR-QoL.
Total Sn-2 Palmitic Triacylglycerols and the Ratio of OPL to OPO in Human Milk Fat Substitute Modulated Bile Acid Metabolism and Intestinal Microbiota Composition in Rats
Authors: Zhu Lin , Fang Shuaizhen , Zhang Hong , Sun Xiangjun , Yang Puyu , Wan Jianchun , Zhang Yaqiong , Lu Weiying , Yu Liangli
Published: November 2023

In this study, the impact of sn-2 palmitic triacyclglycerols (TAGs) in combination with their ratio of two major TAGs (1-oleoyl-2-palmitoyl-3-linoleoylglycerol (OPL) to 1,3-dioleoyl-2-palmitoylglycerol (OPO)) in human milk fat substitute (HMFS) on bile acid (BA) metabolism and intestinal microbiota composition was investigated in newly-weaned Sprague–Dawley rats after four weeks of high-fat feeding. Compared to those of control group rats, HMFS-fed rats had significantly increased contents of six hepatic primary BAs (CDCA, αMCA, βMCA, TCDCA, TαMCA and TβMCA), four ileal primary BAs (UDCA, TCA, TCDCA and TUDCA) and three secondary BAs (DCA, LCA and ωMCA), especially for the HMFS with the highest sn-2 palmitic acid TAGs of 57.9% and OPL to OPO ratio of 1.4. Meanwhile, the inhibition of ileal FXR-FGF15 and activation of TGR5-GLP-1 signaling pathways in HMFS-fed rats were accompanied by the increased levels of enzymes involved in BA synthesis (CYP7A1, CYP27A1 and CYP7B1) in the liver and two key thermogenic proteins (PGC1α and UCP1) in perirenal adipose tissue, respectively. Moreover, increasing sn-2 palmitic TAGs and OPL to OPO ratio in HMFS also altered the microbiota composition both on the phylum and genus level in rats, predominantly microbes associated with bile-salt hydrolase activity, short-chain fatty acid production and reduced obesity risk, which suggested a beneficial effect on host microbial ecosystem. These observations provided important nutritional evidence for developing new HMFS products for infants.
Adherence to Anti-Malarial Treatment in Malaria Endemic Areas of Bangladesh
Authors: Hossain Mohammad Sharif , Matin Mohammad Abdul , Ferdous Nur-E Naznin , Hasan Anamul , Sazed Saiful Arefeen , Neogi Amit Kumer , Chakma Sumit , Islam Md. Atiqul , Khan Afsana Alamgir , Haque Md. Ekramul , Islam Shayla , Islam Md. Nazmul , Khan Wasif Ali , Islam Md. Akramul , Haque Rashidul , Alam Mohammad Shafiul
Published: November 2023

Ensuring adherence to antimalarial treatment is crucial for achieving a radical cure and elimination of malaria, especially in hard-to-reach areas. We conducted this study to assess the current scenario of drug adherence in four endemic sub-districts of Bangladesh. Among 110 enrolled participants, 70% were mono-infected with Plasmodium falciparum and the remaining 30% with P. vivax. The overall treatment adherence frequency was 92.7% (95% CI: 83.0–96.3%). A total of eight participants were found to be nonadherent to treatment and all of them were from Bandarban. Level of nonadherence was equally observed in two age groups: 11–17 and 18+ years. However, male participants (n = 6) were found to be more nonadherent than females (n = 2). Among 7.3% with nonadherence to treatment, a single participant with P. falciparum mono-infection refused to take medication and became nonadherent. Remaining participants stated that they were feeling well and going to work, thus leaving treatment course uncompleted. Although overall compliance with malaria medication seems good, a gradual increase in noncompliance to P. vivax malaria treatment suggests that the National Malaria Elimination Program must be enhanced and monitored to fulfil the projected malaria elimination goal before 2030 from Bangladesh.
The Concept of a Substance and Its Linguistic Embodiment
Authors: Laycock Henry
Published: November 2023

My objective is a better comprehension of two theoretically fundamental concepts. One, the concept of a substance in an ordinary (non-Aristotelian) sense, ranging over such things as salt, carbon, copper, iron, water, and methane—kinds of stuff that now count as (chemical) elements and compounds. The other I will call the object-concept in the abstract sense of Russell, Wittgenstein, and Frege in their logico-semantical enquiries. The material object-concept constitutes the heart of our received logico/ontic system, still massively influenced by Aristotle after almost 2.5 millennia. On such an account, the fundamentality of material objects and their attributes are the metaphysical basis of the cosmos, as reflected in our received logic, Quine’s ‘canonical notation’—derived via the empiricism of Russell from Frege’s function-based Begriffschrifft, and consisting of concrete singular terms and variables, quantifiers and predicate-expressions. The inadequacy of Frege’s approach to understanding concepts is reflected in his initial question. Frege enquires of ‘what it is that we are calling an object’, remarking that he regards a regular definition as impossible: “we have here something too simple to admit of logical analysis”. The imagined ultimacy or simplicity of the idea of a single object (arithmetically, just a unit—one as opposed to two, three, four, etc.) as foundational to the calculus is just that—imagined. It is also guaranteed to block the comprehension of the substance-concept.
Cherenkov-Type Terahertz Generation by Long-Wavelength Ultrafast Laser Excitation of a GaP Crystal
Authors: Bodrov S. B. , Shugurov A. I. , Efimenko E. S. , Kurnikov M. A. , Ilyakov I. E. , Shishkin B. V. , Bakunov M. I.
Published: November 2023

We explore, both theoretically and experimentally, the potential of semiconductor materials for the Cherenkov scheme of terahertz generation on the example of GaP crystal pumped by femtosecond laser pulses of 1.54 μm wavelength. We use a convenient scheme with a focused-to-a-line laser beam which is introduced into the crystal by oblique incidence at the Brewster angle on the crystal front face and propagates in the crystal at the Cherenkov angle to its normal. A half of the generated Cherenkov wedge impinges normally the rear face of the crystal and generates an output terahertz beam with a plane wavefront. The whole generation process is simulated by FDTD method. In experiments, the laser pulses of 140 fs duration and 10 μJ energy were converted to wideband (~2.5 THz bandwidth) terahertz radiation with the efficiency of ~3 × 10−5, which exceeds the efficiency of the standard collinear scheme by at least an order of magnitude.
Effects of Inoculation with Stress-Tolerant Rhizobia on the Response of Alfalfa (Medicago sativa L.) to Combined Salinity and Cadmium Stress
Authors: Pacheco-Insausti M. Cecilia , Ponce Ivana Tamara , Quiñones Miguel A. , Pedranzani Hilda E. , Pueyo José J.
Published: November 2023

Agricultural soil salinization, which is often combined with heavy-metal contamination, is an ever-growing problem in the current era of global change. Legumes have a high potential for nitrogen fixation and are ideal crops for the reclamation of degraded soils. Alfalfa (Medicago sativa) is a valuable forage crop cultivated worldwide. Alfalfa plants fertilized with nitrogen or inoculated with a salt- and cadmium-tolerant Sinorhizobium meliloti strain were subjected to combined NaCl and CdCl2 stresses. Our results showed that inoculated plants presented higher aerial biomass than nitrogen-fertilized plants when they were exposed to salinity and cadmium together. To assess the mechanisms involved in the plant response to the combined stresses, superoxide dismutase and catalase antioxidant enzymatic activities were determined. Both increased upon stress; however, the increase in catalase activity was significantly less marked for inoculated plants, suggesting that other tolerance mechanisms might be active. Cd accumulation was lower in inoculated plants than in fertilized plants, which appears to imply that inoculation somehow prevented cadmium uptake by the plant roots. Expression analyses of several involved genes suggested that inoculation stimulated the biosynthesis of proline, phytochelatins, and homophytochelatins, together indicating that inoculated plants might be better suited to withstand combined salinity and cadmium stress effects.
Correction: Anglana et al. Dittrichia viscosa Selection Strategy Based on Stress Produces Stable Clonal Lines for Phytoremediation Applications. Plants 2023, 12, 2499
Authors: Anglana Chiara , Capaci Piergiorgio , Barozzi Fabrizio , Migoni Danilo , Rojas Makarena , Stigliano Egidio , Fanizzi Francesco Paolo , Di Sansebastiano Gian Pietro , Papadia Paride
Published: November 2023

In the original publication [...]
Chemical Composition in Juvenile and Mature Wood of Branch and Main Trunk of Leucaena leucocephala (Lam.) de Wit
Authors: Sivan Pramod , Rao Karumanchi S. , Rajput Kishore S.
Published: November 2023

Secondary growth is the most dynamic developmental aspect during the terrestrialization of plants. The development of secondary xylem tissue composed of thick-walled cells with characteristic changes in its structure and chemistry facilitates the growth and development of woody plants. In the present study, the chemical composition of the secondary xylem of juvenile and mature wood from the branch and main trunk of Leucaena leucocephala, has been investigated and the differences established. The biochemical analysis of different cell wall components in the mature wood of the main trunk revealed high holocellulose and α-cellulose and less lignin content in the juvenile wood while its syringyl/guaiacyl (S/G) ratio was less than for the mature wood. As compared to the branch xylem, concentration of cell wall polysaccharides and lignin content was higher in both juvenile and mature wood collected from the main trunk. Thioacidolysis and GC-MS analysis of wood lignin from juvenile and mature wood showed that an increased concentration in lignin content in mature wood is associated with a corresponding increase in S/G ratio. The structural information of the acetylated lignin was investigated by 1H NMR spectroscopy. Our results indicate that the mature wood from the main trunk is superior in pulp yielding and lignin degradability as compared to the juvenile wood of the branch and trunk.
Changes in the Metabolome and Nutritional Quality of Pulp from Three Types of Korla Fragrant Pears with Different Appearances as Revealed by Widely Targeted Metabolomics
Authors: Jiang Wei , Yan Pan , Zheng Qiangqing , Wang Zhendong , Chen Qiling , Wang Yi
Published: November 2023

Korla fragrant pear (Pyrus sinkiangensis Yü) fruits have a unique flavor and are rich in phenolic acids, flavonoids, amino acids, and other nutrients. At present, the molecular basis of the quality differences among Korla fragrant pear fruits with a convex calyx and rough skin (RS), calyx shedding (SD), and a convex calyx (CV) remains unknown. To analyze the main metabolic components of Korla fragrant pear fruits and compare the antioxidant activities of these three fruits with different qualities, we used nutrient composition analysis and ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC–MS/MS)-based widely targeted metabolomics approaches to analyze the changes in the quality characteristics of the pulp of these three Korla fragrant pear fruits with different appearances. The nutrient composition analysis showed that the fructose and glucose contents were not significantly different, and sucrose and vitamin C contents were significantly higher in SD fruits compared with CV and RS fruits. However, the levels of flavor substances such as titratable acids, total phenols, and total flavonoids were high in the pulp of RS fruits. The metabolomics results identified 1976 metabolites that were clustered into 12 categories, and phenolic acid and flavonoid metabolites were the most abundant. The differentially accumulated metabolites (DAMs) in the fruits with different appearances were screened by multivariate statistical methods, and a total of 595 DAMs were detected. The analysis identified 300 DAMs between the CV and SD fruits, 246 DAMs between the RS and CV fruits, and 405 DAMs between the RS and SD groups. SD fruits contained the most metabolites with a high relative content, especially phenolic acids, lipids, amino acids and derivatives, alkaloids, and organic acids. Compared with CV fruits, flavonoid metabolism was more active in RS fruits, which also had a higher content of flavonoids, whereas the fewest metabolites were found in CV fruits, which also displayed less flavonoid accumulation. KEGG pathway enrichment analysis revealed that the DAMs were mainly enriched in the metabolic pathways of flavone and flavonol biosynthesis, confirming that CV fruits have decreased flavone and flavonol biosynthesis and accumulate fewer flavonoids than RS fruits, which may explain the less bitter and astringent flavor of CV fruits. However, the flavonoid content in RS fruits was very high, which may be one of the reasons why RS fruits have a harder pulp and are less juicy, more slaggy, and less flavorful. Moreover, the analysis of the antioxidant activity showed that during fruit development and maturation, RS fruits had stronger antioxidant activity than SD and CV fruits. These results provide a theoretical basis for improving the fruit quality of Korla fragrant pears and the processing of pear pulp.
Can a Forest Tree Species Progeny Trial Serve as an Ex Situ Collection? A Case Study on Alnus glutinosa
Authors: Verbylaitė Rita , Aravanopoulos Filippos A. , Baliuckas Virgilijus , Juškauskaitė Aušra , Ballian Dalibor
Published: November 2023

Scientifically informed decisions for the long-term conservation of extant genetic diversity should combine in situ and ex situ conservation methods. The aim of the present study was to assess if a progeny plantation consisting of several open pollinated (OP) families and established for breeding purposes can also serve as an ex situ conservation plantation, using the case study of a Lithuanian progeny trial of Alnus glutinosa, a keystone species of riparian ecosystems that warrants priority conservation actions. We employed 17 nuclear microsatellite (Simple Sequence Repeat) markers and compared the genetic diversity and copy number of the captured alleles of 22 OP progeny families from this plantation, with 10 wild A. glutinosa populations, originating from the two provenance regions of the species in Lithuania. We conclude that the progeny plantation could be used as an ex situ plantation for the A. glutinosa populations from the first provenance region (represented by eight genetic conservation units (GCU)). Based on the present study’s results, we can expect that the A. glutinosa progeny plantation harbors enough genetic diversity of wild A. glutinosa populations from the first provenance region. This progeny plantation can serve as a robust ex situ collection containing local alleles present in at least one wild population with at least 0.05 frequency with 25 replications.
Effects of Low-Light Environments on the Growth and Physiological and Biochemical Parameters of Indocalamus and Seasonal Variations in Leaf Active Substance Contents
Authors: Yu Weiqian , Jiang Mingyan , Yue Qiling , Yang Yixiong , Luo Zhenghua , Lv Bingyang , He Rui , Feng Shihan , Yang Meng
Published: November 2023

Indocalamus, characterized by its expansive leaves, low height, strong reproductive capacity, and abundant bioactive compounds, has extensive utility in the realms of food processing, the manufacturing of packaging materials, and the advancement of novel pharmaceuticals. Two light environments, CK (100% full light) and ST (50% full light), were established to explore the effects of low-light environments on the reproductive ability, morphological characteristics, photosynthetic properties, and leaf active substances of 14 Indocalamus species. The findings revealed that in comparison to the CK treatment, for 14 species of Indocalamus under the ST treatment, (1) the diameter, single leaf area, and leaf area index increased by 8.27%, 8.14%, and 17.88%, respectively; (2) the net photosynthetic rate decreased by 15.14%, and the total chlorophyll contents increased by 20.25%; and (3) the total flavonoid contents increased by 18.28% in autumn, the total polyphenol contents increased by 48.96% in spring, and the total polysaccharide contents increased by 31.44% and 30.81% in summer and winter, respectively. In summary, Indocalamus are adapted to survive in low-light environments; the growth and physiological indices differ significantly between the two light environments, and the low-light environment can effectively promote the growth and development of the leaves. Furthermore, the leaves are rich in flavonoids, polyphenols, polysaccharides, and active substances, which are affected by the light intensity and the season to varying degrees, and autumn and winter are the best times for harvesting the leaves. The leaves of I. hunanensis and I. lacunosus are richest in flavonoids and polyphenols, while the leaves of I. kunmingensis cv. fuminer are richest in polysaccharides. The main findings of this study demonstrate that Indocalamus has strong shade tolerance and tremendous leaf value, laying the foundation for broadening the application of their leaves and for their industrial development in understory composite planting systems.
Special Issue on “Green Manufacturing and Sustainable Supply Chain Management”
Authors: Sun Bilian , Jiang Zhigang , Wang Yan , Cai Wei
Published: November 2023

Manufacturing plays a vital role in the global economy, as it drives economic growth and development [...]
Defect Detection in Food Using Multispectral and High-Definition Imaging Combined with a Newly Developed Deep Learning Model
Authors: Deng Dongping , Liu Zhijiang , Lv Pin , Sheng Min , Zhang Huihua , Yang Ruilong , Shi Tiezhu
Published: November 2023

The automatic detection of defects (cortical fibers) in pickled mustard tubers (Chinese Zhacai) remains a challenge. Moreover, few papers have discussed detection based on the segmentation of the physical characteristics of this food. In this study, we designate cortical fibers in pickled mustard as the target class, while considering the background and the edible portion of pickled mustard as other classes. We attempt to realize an automatic defect-detection system to accurately and rapidly detect cortical fibers in pickled mustard based on multiple images combined with a UNet4+ segmentation model. A multispectral sensor (MS) covering nine wavebands with a resolution of 870 × 750 pixels and an imaging speed over two frames per second and a high-definition (HD), 4096 × 3000 pixel resolution imaging system were applied to obtain MS and HD images of 200 pickled mustard tuber samples. An improved imaging fusion method was applied to fuse the MS with HD images. After image fusion and other preprocessing methods, each image contained a target; 150 images were randomly selected as the training data and 50 images as the test data. Furthermore, a segmentation model called UNet4+ was developed to detect the cortical fibers in the pickled mustard tubers. Finally, the UNet4+ model was tested on three types of datasets (MS, HD, and fusion images), and the detection results were compared based on Recall, Precision, and Dice values. Our study indicates that the model can successfully detect cortical fibers within about a 30 ± 3 ms timeframe for each type of image. Among the three types of images, the fusion images achieved the highest mean average Dice value of 73.91% for the cortical fibers. At the same time, we compared the UNet4+ model with the UNet++ and UNet3+ models using the same fusion data; the results show that our model achieved better prediction performance for the Dice values, i.e., 9.72% and 27.41% higher than those of the UNet++ and UNet3+ models, respectively.
A Preliminary Numerical Study on the Performance of Cyclone Separators in Supercritical CO2 Solar Power Plants
Authors: Li Anjun , Zhu Ziang , Liu Peikun , Li Xiaoyu
Published: November 2023

A combined approach of computational fluid dynamics, the discrete phase model, and the wall erosion model was used to numerically investigate the hydrodynamics, separation efficiency, and erosion rate in cyclone separators for s-CO2 solar power plants. Moreover, the results were compared with those for air and CO2 as carrier phases. The experimental data from the literature were used to validate the numerical model, and it was observed that the simulated gas velocities and wall erosion rate accurately aligned with the experimental measurements. The numerical results reveal that s-CO2 had the largest tangential velocity compared to the other two media; its area-weighted axial velocity of upward flow was the lowest in the middle part of the cyclone body, and varied considerably in the bottom region of the conical section. The particles were all collected at the bottom surface of air and CO2, but the separation efficiency of s-CO2 was 81.51%, due to the poor distribution of the vortex and short circuit. Finally, the erosion rate distribution and averaged surface erosion rate were also analyzed for the three carrier phases.
Training Tricks for Steel Microstructure Segmentation with Deep Learning
Authors: Ma Xudong , Yu Yunhe
Published: November 2023

Data augmentation and other training techniques have improved the performance of deep learning segmentation methods for steel materials. However, these methods often depend on the dataset and do not provide general principles for segmenting different microstructural morphologies. In this work, we collected 64 granular carbide images (2048 × 1536 pixels) and 26 blocky ferrite images (2560 × 1756 pixels). We used five carbide images and two ferrite images and derived from them the test set to investigate the influence of frequently used training techniques on model segmentation accuracy. We propose a novel method for quickly building models that achieve the highest segmentation accuracy for a given dataset through combining multiple training techniques that enhance the segmentation quality. This method leads to a 1–2.5% increase in mIoU values. We applied the optimal models to the quantization of carbides. The results show that the optimal models achieve the smallest errors of 5.39 nm for the mean radius and 29 for the total number of carbides on the test set. The segmentation results are also more reasonable than those of traditional segmentation methods.
Flow Potential Analysis-Based Gas Channeling Control for Enhanced Artificial Gas Cap Drive in Fractured-Vuggy Reservoirs
Authors: Ye Jinxi , Hu Rongrong , Xin Xiankang , Lu Hao , Yu Gaoming
Published: November 2023

Fractured-vuggy reservoirs are known for containing substantial amounts of oil in high positions of reservoir, even after natural energy development and water injection development. However, due to their poor physical properties and fracture distribution, gas channeling becomes a common occurrence when injecting large amounts of gas, which hinders the formation of an effective gas cap, resulting in reduced oil displacement efficiency. This phenomenon results in a lengthy period of effective gas cap formation and reduces the oil displacement efficiency of an artificial gas cap. In this paper, according to the actual geological characteristics, logging data, and production data, the mechanism model and the numerical model of Oilfield A are established. The variation law of flow potential difference before and after gas injection channeling is studied by simulation, and the control method of artificial gas cap gas channeling in fractured-vuggy reservoir is put forward. The results show that the production gas–oil ratio method is the most convenient and practical in the oil field, and the flow potential difference can effectively predict the occurrence of gas channeling. It likely occurs when the ratio of flow potential difference between injection and production wells is less than 0.972. Gas channeling can be controlled effectively by altering the energy of position and pressure, as well as body measures including injection–production well pattern adjustment, injection–production parameter optimization. This technology provides a new approach for controlling gas channeling through gas cap drive in fractured-vuggy reservoirs. After the implementation of this technology, the effect is obvious, and can effectively improve the efficiency of gas top oil displacement and save costs. This gas channeling control technology is of great significance for the development of fractured-vuggy reservoirs.
On Risk Management of Mortality and Longevity Capital Requirement: A Predictive Simulation Approach
Authors: Yang Shuai , Zhou Kenneth Q.
Published: November 2023

In the insurance industry, life insurers are required by regulators to meet capital requirements to avoid insolvency caused by, for example, sudden mortality changes due to the COVID-19 pandemic. To prevent any large movements in this required capital, insurance companies are motivated to establish hedging strategies to mitigate the inherent risk exposures they face. Nonetheless, devising and implementing risk mitigation solutions to risk managing capital requirement is frequently impeded by the computational complexities stemming from the extensive simulations required. In this paper, we delve into a simulation quandary concerning the management of solvency capital risk associated with mortality and longevity. More specifically, we introduce a thin-plate regression spline method as a surrogate alternative to the standard nested simulation approach. Using this efficient simulation method, we further investigate hedging strategies that utilize mortality-linked securities coupled with stochastic mortality dynamics. Our simulation results provide a numerical justification to the market-making of mortality-linked securities in the context of mortality and longevity capital risk management.
Optimizing the Retrieval of Wheat Crop Traits from UAV-Borne Hyperspectral Image with Radiative Transfer Modelling Using Gaussian Process Regression
Authors: Sahoo Rabi N. , Gakhar Shalini , Rejith Rajan G. , Verrelst Jochem , Ranjan Rajeev , Kondraju Tarun , Meena Mahesh C. , Mukherjee Joydeep , Daas Anchal , Kumar Sudhir , Kumar Mahesh , Dhandapani Raju , Chinnusamy Viswanathan
Published: November 2023

The advent of high-spatial-resolution hyperspectral imagery from unmanned aerial vehicles (UAVs) made a breakthrough in the detailed retrieval of crop traits for precision crop-growth monitoring systems. Here, a hybrid approach of radiative transfer modelling combined with a machine learning (ML) algorithm is proposed for the retrieval of the leaf area index (LAI) and canopy chlorophyll content (CCC) of wheat cropland at the experimental farms of ICAR-Indian Agricultural Research Institute (IARI), New Delhi, India. A hyperspectral image captured from a UAV platform with spatial resolution of 4 cm and 269 spectral bands ranging from 400 to 1000 nm was processed for the retrieval of the LAI and CCC of wheat cropland. The radiative transfer model PROSAIL was used for simulating spectral data, and eight machine learning algorithms were evaluated for hybrid model development. The ML Gaussian process regression (GPR) algorithm was selected for the retrieval of crop traits due to its superior accuracy and lower associated uncertainty. Simulated spectra were sampled for training GPR models for LAI and CCC retrieval using dimensionality reduction and active learning techniques. LAI and CCC biophysical maps were generated from pre-processed hyperspectral data using trained GPR models and validated against in situ measurements, yielding R2 values of 0.889 and 0.656, suggesting high retrieval accuracy. The normalised root mean square error (NRMSE) values reported for LAI and CCC retrieval are 8.579% and 14.842%, respectively. The study concludes with the development of optimized GPR models tailored for UAV-borne hyperspectral data for the near-real-time retrieval of wheat traits. This workflow can be upscaled to farmers’ fields, facilitating efficient crop monitoring and management.
Optimizing Image Compression Ratio for Generating Highly Accurate Local Digital Terrain Models: Experimental Study for Martian Moons eXploration Mission
Authors: Shimizu Yuta , Miyamoto Hideaki , Kameda Shingo
Published: November 2023

Recent technological advances have significantly increased the data volume obtained from deep space exploration missions, making the downlink rate a primary limiting factor. Particularly, JAXA’s Martian Moons eXploration (MMX) mission encounters this problem when identifying safe and scientifically valuable landing sites on Phobos using high-resolution images. A strategic approach in which we effectively reduce image data volumes without compromising essential scientific information is thus required. In this work, we investigate the influence of image data compression, especially as it concerns the accuracy of generating the local Digital Terrain Models (DTMs) that will be used to determine MMX’s landing sites. We obtain simulated images of Phobos that are compressed using the algorithm with integer/float-point discrete wavelet transform (DWT) defined by the Consultative Committee for Space Data Systems (CCSDS), which are candidate algorithms for the MMX mission. Accordingly, we show that, if the compression ratio is 70% or lower, the effect of image compression remains constrained, and local DTMs can be generated within altitude errors of 40 cm on the surface of Phobos, which is ideal for selecting safe landing spots. We conclude that the compression ratio can be increased as high as 70%, and such compression enables us to facilitate critical phases in the MMX mission even with the limited downlink rate.
Spatial and Spectral Translation of Landsat 8 to Sentinel-2 Using Conditional Generative Adversarial Networks
Authors: Mukherjee Rohit , Liu Desheng
Published: November 2023

Satellite sensors like Landsat 8 OLI (L8) and Sentinel-2 MSI (S2) provide valuable multispectral Earth observations that differ in spatial resolution and spectral bands, limiting synergistic use. L8 has a 30 m resolution and a lower revisit frequency, while S2 offers up to a 10 m resolution and more spectral bands, such as red edge bands. Translating observations from L8 to S2 can increase data availability by combining their images to leverage the unique strengths of each product. In this study, a conditional generative adversarial network (CGAN) is developed to perform sensor-specific domain translation focused on green, near-infrared (NIR), and red edge bands. The models were trained on the pairs of co-located L8-S2 imagery from multiple locations. The CGAN aims to downscale 30 m L8 bands to 10 m S2-like green and 20 m S2-like NIR and red edge bands. Two translation methodologies are employed—direct single-step translation from L8 to S2 and indirect multistep translation. The direct approach involves predicting the S2-like bands in a single step from L8 bands. The multistep approach uses two steps—the initial model predicts the corresponding S2-like band that is available in L8, and then the final model predicts the unavailable S2-like red edge bands from the S2-like band predicted in the first step. Quantitative evaluation reveals that both approaches result in lower spectral distortion and higher spatial correlation compared to native L8 bands. Qualitative analysis supports the superior fidelity and robustness achieved through multistep translation. By translating L8 bands to higher spatial and spectral S2-like imagery, this work increases data availability for improved earth monitoring. The results validate CGANs for cross-sensor domain adaptation and provide a reusable computational framework for satellite image translation.
Assessment of Machine Learning Models for Remote Sensing of Water Quality in Lakes Cajititlán and Zapotlán, Jalisco—Mexico
Authors: Villota-González Freddy Hernán , Sulbarán-Rangel Belkis , Zurita-Martínez Florentina , Gurubel-Tun Kelly Joel , Zúñiga-Grajeda Virgilio
Published: November 2023

Remote sensing has emerged as a promising tool for monitoring water quality (WQ) in aquatic ecosystems. This study evaluates the effectiveness of remote sensing in assessing WQ parameters in Cajititlán and Zapotlán lakes in the state of Jalisco, Mexico. Over time, these lakes have witnessed a significant decline in WQ, necessitating the adoption of advanced monitoring techniques. In this research, satellite-based remote sensing data were combined with ground-based measurements from the National Water Quality Monitoring Network of Mexico (RNMCA). These data sources were harnessed to train and evaluate the performance of six distinct categories of machine learning (ML) algorithms aimed at estimating WQ parameters with active spectral signals, including chlorophyll-a (Chl-a), turbidity, and total suspended solids (TSS). Various limitations were encountered during the study, primarily due to atmospheric conditions and cloud cover. These challenges affected both the quality and quantity of the data. However, these limitations were overcome through rigorous data preprocessing, the application of ML techniques designed for data-scarce scenarios, and extensive hyperparameter tuning. The superlearner algorithm (SLA), which leverages a combination of individual algorithms, and the multilayer perceptron (MLP), capable of handling complex and non-linear problems, outperformed others in terms of predictive accuracy. Notably, in Lake Cajititlán, these models provided the most accurate predictions for turbidity (r2 = 0.82, RMSE = 9.93 NTU, MAE = 7.69 NTU), Chl-a (r2 = 0.60, RMSE = 48.06 mg/m3, MAE = 37.98 mg/m3), and TSS (r2 = 0.68, RMSE = 13.42 mg/L, MAE = 10.36 mg/L) when using radiometric data from Landsat-8. In Lake Zapotlán, better predictive performance was observed for turbidity (r2 = 0.75, RMSE = 2.05 NTU, MAE = 1.10 NTU) and Chl-a (r2 = 0.71, RMSE = 6.16 mg/m3, MAE = 4.97 mg/m3) with Landsat-8 radiometric data, while TSS (r2 = 0.72, RMSE = 2.71 mg/L, MAE = 2.12 mg/L) improved when Sentinel-2 data were employed. While r2 values indicate that the models do not exhibit a perfect fit, those approaching unity suggest that the predictor variables offer valuable insights into the corresponding responses. Moreover, the model’s robustness could be enhanced by increasing the quantity and quality of input variables. Consequently, remote sensing emerges as a valuable tool to support the objectives of WQ monitoring systems.