bluuebunny/crossref_metadata_2025 huggingface dataset:
Polyunsaturated Fatty Acids (PUFAs): Sources, Digestion, Absorption, Application and Their Potential Adjunctive Effects on Visual Fatigue
Authors: Duan Hao , Song Wei , Zhao Jian , Yan Wenjie
Published: June 2023

When the eyes are exposed to the environment, they are easily affected by strong light stimulation and harmful substances. At the same time, prolonged use of the eyes or incorrect eye habits can cause visual fatigue, which mainly manifests as eye dryness, soreness, blurred vision, and various discomforts. The main reason for this is a decline in the function of the eye, especially the cornea and retina on the surface of the eye, which have the greatest impact on the normal function of the eye. Research has found that supplementation with appropriate foods or nutrients can effectively strengthen the eye against external and internal stimuli, thereby alleviating or avoiding visual fatigue. Among these, supplementation with polyunsaturated fatty acids has been found to be effective at protecting eye health and relieving visual fatigue. This article summarizes the sources of polyunsaturated fatty acids (including the main dietary sources and internal synthesis), the mechanisms of digestion and absorption of polyunsaturated fatty acids in the body and the safety of polyunsaturated fatty acid applications. It also reviews the mechanism of action of polyunsaturated fatty acids in aiding the relief of visual fatigue based on the mechanism of impaired function or structure of the ocular surface and fundus in the hope of providing some reference and insight into the development and application of polyunsaturated fatty acids in functional foods for the relief of visual fatigue.
Post-Recovery Relapse of Children Treated with a Simplified, Combined Nutrition Treatment Protocol in Mali: A Prospective Cohort Study
Authors: Kangas Suvi T. , Coulibaly Issa Niamanto , Tausanovitch Zachary , Ouologuem Bareye , Marron Bethany , Radin Elizabeth , Ritz Christian , Dembele Salimou , Ouédraogo Césaire T. , Bailey Jeanette
Published: June 2023

The present study aimed to determine the 6-month incidence of relapse and associated factors among children who recovered from acute malnutrition (AM) following mid-upper arm circumference (MUAC)-based simplified combined treatment using the ComPAS protocol. A prospective cohort of 420 children who had reached a MUAC ≥ 125 mm for two consecutive measures was monitored between December 2020 and October 2021. Children were seen at home fortnightly for 6 months. The overall 6-month cumulative incidence of relapse [95%CI] into MUAC < 125 mm and/or edema was 26.1% [21.7; 30.8] and 1.7% [0.6; 3.6] to MUAC < 115 mm and/or edema. Relapse was similar among children initially admitted to treatment with a MUAC < 115 mm and/or oedema and among those with a MUAC ≥ 115 mm but <125 mm. Relapse was predicted by lower anthropometry both at admission to and discharge from treatment, and a higher number of illness episodes per month of follow-up. Having a vaccination card, using an improved water source, having agriculture as the main source of income, and increases in caregiver workload during follow-up all protected from relapse. Children discharged as recovered from AM remain at risk of relapsing into AM. To achieve reduction in relapse, recovery criteria may need to be revised and post-discharge strategies tested.
An Exploratory Study on a New Method for Nutritional Status Assessment in Patients with Chronic Kidney Disease
Authors: Luo Yayong , Huang Hui , Wang Qian , Lin Wenwen , Duan Shuwei , Zhou Jianhui , Huang Jing , Zhang Weiguang , Zheng Ying , Tang Li , Cao Xueying , Yang Jian , Zhang Li , Wang Yong , Wu Jie , Cai Guangyan , Dong Zheyi , Chen Xiangmei
Published: June 2023

Malnutrition is a risk factor for disease progression and poor prognosis in chronic kidney disease (CKD). However, the complexity of nutritional status assessment limits its clinical application. This study explored a new method of nutritional assessment in CKD (stage 1–5) patients using the Subjective Global Assessment (SGA) as the gold standard and evaluated its applicability. The kappa test was used to analyze the consistency of the Renal Inpatient Nutrition Screening Tool (Renal iNUT) with SGA and protein-energy wasting. Logistic regression analysis was used to analyze the risk factors of CKD malnutrition and calculate the prediction probability of multiple indicators combined for the diagnosis of CKD malnutrition. The receiver operating characteristic curve of the prediction probability was drawn to evaluate its diagnostic efficiency. A total of 161 CKD patients were included in this study. The prevalence of malnutrition according to SGA was 19.9%. The results showed that Renal iNUT had a moderate consistency with SGA and a general consistency with protein-energy wasting. Age > 60 years (odds ratio, OR = 6.78), neutrophil–lymphocyte ratio > 2.62 (OR = 3.862), transferrin < 200 mg/dL (OR = 4.222), phase angle < 4.5° (OR = 7.478), and body fat percentage < 10% (OR = 19.119) were risk factors for malnutrition in patients with CKD. The area under the receiver operating characteristic curve of multiple indicators for the diagnosis of CKD malnutrition was 0.89 (95% confidence interval: 0.834–0.946, p < 0.001). This study demonstrated that Renal iNUT has good specificity as a new tool for the nutrition screening of CKD patients, but its sensitivity needs to be optimized. Advanced age, high neutrophil–lymphocyte ratio, low transferrin level, low phase angle, and low body fat percentage are risk factors for malnutrition in patients with CKD. The combination of the above indicators has high diagnostic efficiency in the diagnosis of CKD malnutrition, which may be an objective, simple, and reliable method to evaluate the nutritional status of patients with CKD.
Defining the Relationship of Gut Microbiota, Immunity, and Cognition in Early Life—A Narrative Review
Authors: Kartjito Melissa Stephanie , Yosia Mikhael , Wasito Erika , Soloan Garry , Agussalim Achmad Furqan , Basrowi Ray Wagiu
Published: June 2023

Recently, the immune system has been identified as one of the possible main bridges which connect the gut–brain axis. This review aims to examine available evidence on the microbiota–immunity–cognitive relationship and its possible effects on human health early in life. This review was assembled by compiling and analyzing various literature and publications that document the gut microbiota–immune system–cognition interaction and its implications in the pediatric population. This review shows that the gut microbiota is a pivotal component of gut physiology, with its development being influenced by a variety of factors and, in return, supports the development of overall health. Findings from current research focus on the complex relationship between the central nervous system, gut (along with gut microbiota), and immune cells, highlighting the importance of maintaining a balanced interaction among these systems for preserving homeostasis, and demonstrating the influence of gut microbes on neurogenesis, myelin formation, the potential for dysbiosis, and alterations in immune and cognitive functions. While limited, evidence shows how gut microbiota affects innate and adaptive immunity as well as cognition (through HPA axis, metabolites, vagal nerve, neurotransmitter, and myelination).
Towards Understanding Long COVID: SARS-CoV-2 Strikes the Host Cell Nucleus
Authors: Lafon-Hughes Laura
Published: June 2023

Despite what its name suggests, the effects of the COVID-19 pandemic causative agent “Severe Acute Respiratory Syndrome Coronavirus-2” (SARS-CoV-2) were not always confined, neither temporarily (being long-term rather than acute, referred to as Long COVID) nor spatially (affecting several body systems). Moreover, the in-depth study of this ss(+) RNA virus is defying the established scheme according to which it just had a lytic cycle taking place confined to cell membranes and the cytoplasm, leaving the nucleus basically “untouched”. Cumulative evidence shows that SARS-CoV-2 components disturb the transport of certain proteins through the nuclear pores. Some SARS-CoV-2 structural proteins such as Spike (S) and Nucleocapsid (N), most non-structural proteins (remarkably, Nsp1 and Nsp3), as well as some accessory proteins (ORF3d, ORF6, ORF9a) can reach the nucleoplasm either due to their nuclear localization signals (NLS) or taking a shuttle with other proteins. A percentage of SARS-CoV-2 RNA can also reach the nucleoplasm. Remarkably, controversy has recently been raised by proving that-at least under certain conditions-, SARS-CoV-2 sequences can be retrotranscribed and inserted as DNA in the host genome, giving rise to chimeric genes. In turn, the expression of viral-host chimeric proteins could potentially create neo-antigens, activate autoimmunity and promote a chronic pro-inflammatory state.
Bioinformatics Tools for the Analysis of Active Compounds Identified in Ranunculaceae Species
Authors: Mareş Cătălina , Udrea Ana-Maria , Şuţan Nicoleta Anca , Avram Speranţa
Published: June 2023

The chemical compounds from extracts of three Ranunculaceae species, Aconitum toxicum Rchb., Anemone nemorosa L. and Helleborus odorus Waldst. & Kit. ex Willd., respectively, were isolated using the HPLC purification technique and analyzed from a bioinformatics point of view. The classes of compounds identified based on the proportion in the rhizomes/leaves/flowers used for microwave-assisted extraction and ultrasound-assisted extraction were alkaloids and phenols. Here, the quantifying of pharmacokinetics, pharmacogenomics and pharmacodynamics helps us to identify the actual biologically active compounds. Our results showed that (i) pharmacokinetically, the compounds show good absorption at the intestinal level and high permeability at the level of the central nervous system for alkaloids; (ii) regarding pharmacogenomics, alkaloids can influence tumor sensitivity and the effectiveness of some treatments; (iii) and pharmacodynamically, the compounds of these Ranunculaceae species bind to carbonic anhydrase and aldose reductase. The results obtained showed a high affinity of the compounds in the binding solution at the level of carbonic anhydrases. Carbonic anhydrase inhibitors extracted from natural sources can represent the path to new drugs useful both in the treatment of glaucoma, but also of some renal, neurological and even neoplastic diseases. The identification of natural compounds with the role of inhibitors can have a role in different types of pathologies, both associated with studied and known receptors such as carbonic anhydrase and aldose reductase, as well as new pathologies not yet addressed.
Overview of Cardiac Arrhythmias and Treatment Strategies
Authors: Kingma John , Simard Chantale , Drolet Benoît
Published: June 2023

Maintenance of normal cardiac rhythm requires coordinated activity of ion channels and transporters that allow well-ordered propagation of electrical impulses across the myocardium. Disruptions in this orderly process provoke cardiac arrhythmias that may be lethal in some patients. Risk of common acquired arrhythmias is increased markedly when structural heart disease caused by myocardial infarction (due to fibrotic scar formation) or left ventricular dysfunction is present. Genetic polymorphisms influence structure or excitability of the myocardial substrate, which increases vulnerability or risk of arrhythmias in patients. Similarly, genetic polymorphisms of drug-metabolizing enzymes give rise to distinct subgroups within the population that affect specific drug biotransformation reactions. Nonetheless, identification of triggers involved in initiation or maintenance of cardiac arrhythmias remains a major challenge. Herein, we provide an overview of knowledge regarding physiopathology of inherited and acquired cardiac arrhythmias along with a summary of treatments (pharmacologic or non-pharmacologic) used to limit their effect on morbidity and potential mortality. Improved understanding of molecular and cellular aspects of arrhythmogenesis and more epidemiologic studies (for a more accurate portrait of incidence and prevalence) are crucial for development of novel treatments and for management of cardiac arrhythmias and their consequences in patients, as their incidence is increasing worldwide.
Effect of Medication Therapy Management by Pharmaceutical Care on Blood Pressure and Cardiovascular Risk in Hypertension: A Systematic Review, Meta-Analysis, and Meta-Regression
Authors: de Souza Cazarim Maurilio , Cruz-Cazarim Estael Luzia Coelho , Boyd Kathleen , Wu Olivia , Nunes Altacílio Aparecido
Published: June 2023

Medication therapy management by pharmaceutical care (MTM-PC) has been shown to improve the effectiveness of antihypertensive treatments. The aim was to answer the question: what are the MTM-PC models and their impact on hypertensive patients’ outcomes? This is a systematic review with meta-analysis. The search strategies were run on 27 September 2022 in the following databases: PubMed, EMBASE, Scopus, LILACs, Central Cochrane Library, Web of Science; and International Pharmaceutical Abstracts. The quality and bias risk was assessed by the Downs and Black instrument. Forty-one studies met the eligibility criteria and were included, Kappa = 0.86; 95% CI, 0.66–1.0; (p < 0.001). Twenty-seven studies (65.9%) had MTM-PC models outlined by the clinical team, showing as characteristics the mean of 10.0 ± 10.7 months of follow-up of hypertensive patients, with 7.7 ± 4.9 consultations. Instruments to assess the quality of life measured the enhancement by 13.4 ± 10.7% (p = 0.047). The findings of the meta-analysis show a mean reduction of −7.71 (95% CI, −10.93 to −4.48) and −3.66 (95% CI, −5.51 to −1.80), (p < 0.001) in mmHg systolic and diastolic pressures, respectively. Cardiovascular relative risk (RR) over ten years was 0.561 (95% CI, 0.422 to 0.742) and RR = 0.570 (95% CI, 0.431 to 0.750), considering homogeneous studies, I² = 0%. This study shows the prevalence of MTM-PC models outlined by the clinical team, in which there are differences according to the models in reducing blood pressure and cardiovascular risk over ten years with the improvement in quality of life.
Hybrid Resonator 1319 nm Nd:YAG InnoSlab Laser
Authors: Zhang Shengzi , Chen Tanghan , Liu Xiaomeng , Zhang Hengli , Wang Jiang , Guo Heqing
Published: June 2023

The InnoSlab laser has the advantages of excellent thermal management and high overlapping efficiency. In this work, we report an InnoSlab laser with high efficiency at 1319 nm end-pumped 0.6at.% Nd:YAG by 808 nm. The hybrid stable–unstable resonator was adopted. For a cavity length of 17.9 mm and absorbed pumped power of 423.5 W, the output power of 81 W was obtained at T = 5%, exhibiting an optical conversion efficiency of 19.13% and a slope efficiency of 29.80%.
Synchronous Changes of GPP and Solar-Induced Chlorophyll Fluorescence in a Subtropical Evergreen Coniferous Forest
Authors: Wang Mingming , Zhang Leiming
Published: June 2023

Using in situ near-surface observations of solar-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) of a subtropical evergreen coniferous forest in southern China, this study analyzed the dynamics of SIF, GPP and their environmental responses, and explored the potential of SIF in characterizing the variation of GPP. The results showed that SIF and GPP have similar diurnal and seasonal variation and both reach the highest value in summer, indicating that the SIF can be applied to indicate the seasonal variation of GPP for the subtropical evergreen co-niferous. With the increase in temporal scale, the correlation between SIF and GPP becomes more linear. The diurnal variations of both SIF and GPP were characterized by photosynthetically active radiation (PAR), the seasonal variations of SIF and GPP were influenced by air temperature (Ta) and PAR. Probably due to the absent of drought stress during the study period, no significant correlation was detected between soil water content (SWC) and either SIF or GPP. With the in-crease in Ta, PAR or SWC, the linear correlation between the SIF and GPP gradually decreased, and when Ta or PAR was relatively higher, the correlation between SIF and GPP become weakly. Further research is still needed to illustrate the relationship between SIF and GPP under drought condition which occurred frequently in this region based on longer observation.
Plant-Produced Nanoparticles Based on Artificial Self-Assembling Peptide Bearing the Influenza M2e Epitope
Authors: Blokhina Elena A. , Mardanova Eugenia S. , Zykova Anna A. , Stepanova Liudmila A. , Shuklina Marina A. , Tsybalova Liudmila M. , Ravin Nikolai V.
Published: June 2023

Despite advances in vaccine development, influenza remains a persistent global health threat and the search for a broad-spectrum recombinant vaccine against influenza continues. The extracellular domain of the transmembrane protein M2 (M2e) of the influenza A virus is highly conserved and can be used to develop a universal vaccine. M2e is a poor immunogen by itself, but it becomes highly immunogenic when linked to an appropriate carrier. Here, we report the transient expression of a recombinant protein comprising four tandem copies of M2e fused to an artificial self-assembling peptide (SAP) in plants. The hybrid protein was efficiently expressed in Nicotiana benthamiana using the self-replicating potato virus X-based vector pEff. The protein was purified using metal affinity chromatography under denaturing conditions. The hybrid protein was capable of self-assembly in vitro into spherical particles 15–30 nm in size. The subcutaneous immunization of mice with M2e-carrying nanoparticles induced high levels of M2e-specific IgG antibodies in serum and mucosal secretions. Immunization provided mice with protection against a lethal influenza A virus challenge. SAP-based nanoparticles displaying M2e peptides can be further used to develop a recombinant “universal” vaccine against influenza A produced in plants.
Integrative Taxonomy of Armeria Taxa (Plumbaginaceae) Endemic to Sardinia and Corsica
Authors: Tiburtini Manuel , Bacchetta Gianluigi , Sarigu Marco , Cambria Salvatore , Caputo Paolo , De Luca Daniele , Domina Gianniantonio , Turini Alessia , Peruzzi Lorenzo
Published: June 2023

Sardinia and Corsica are two Mediterranean islands where the genus Armeria is represented by 11 taxa, 10 out of which are endemic. An integrative approach, using molecular phylogeny, karyology, and seed and plant morphometry was used to resolve the complex taxonomy and systematics in this group. We found that several taxa are no longer supported by newly produced data. Accordingly, we describe a new taxonomic hypothesis that only considers five species: Armeria leucocephala and A. soleirolii, endemic to Corsica, and A. morisii, A. sardoa, and A. sulcitana, endemic to Sardinia.
Optimized End Functionality of Silane-Terminated Liquid Butadiene Rubber for Silica-Filled Rubber Compounds
Authors: Song Sanghoon , Choi Haeun , Jeong Junhwan , Kim Seongyoon , Kwon Myeonghee , Kim Minji , Kim Donghyuk , Jeon Heungbae , Paik Hyun-jong , Chung Sungwook , Kim Wonho
Published: June 2023

As the world is shifting from internal combustion engine vehicles to electric vehicles in response to environmental pollution, the tire industry has been conducting research on tire performance to meet the requirements of electric vehicles. In this experiment, functionalized liquid butadiene rubber (F-LqBR) with triethoxysilyl groups at both ends was introduced into a silica-filled rubber compound as a substitute for treated distillate aromatic extract (TDAE) oil, and comparative evaluation was conducted according to the number of triethoxysilyl groups. The results showed that F-LqBRs improved silica dispersion in the rubber matrix through the formation of chemical bonds between silanol groups and the base rubber, and reduced rolling resistance by limiting chain end mobility and improving filler–rubber interaction. However, when the number of triethoxysilyl groups in F-LqBR was increased from two to four, self-condensation increased, the reactivity of the silanol groups decreased, and the improvement of properties was reduced. As a result, the optimized end functionality of triethoxysilyl groups for F-LqBR in silica-filled rubber compound was two. The 2-Azo-LqBR with the optimized functionality showed an improvement of 10% in rolling resistance, 16% in snow traction, and 17% in abrasion resistance when 10 phr of TDAE oil was substituted.
Optimal Allocation Method for Energy Storage Capacity Considering Dynamic Time-of-Use Electricity Prices and On-Site Consumption of New Energy
Authors: Hu Wei , Zhang Xinyan , Zhu Lijuan , Li Zhenen
Published: June 2023

Configuring energy storage devices can effectively improve the on-site consumption rate of new energy such as wind power and photovoltaic, and alleviate the planning and construction pressure of external power grids on grid-connected operation of new energy. Therefore, a dual layer optimization configuration method for energy storage capacity with source load collaborative participation is proposed. The external model introduces a demand-side response strategy, determines the peak, flat, and valley periods of the time-of-use electricity price-based on the distribution characteristics of load and new energy output, and further aims to maximize the revenue of the wind and solar storage system. With the peak, flat, and valley electricity price as the decision variable, an outer optimization model is established. Based on the optimized electricity price, the user’s electricity consumption in each period is adjusted, and the results are transmitted to the inner optimization model. The internal model takes the configuration power and energy storage capacity in the wind and solar storage system as decision variables, establishes a multi-objective function that comprehensively considers the on-site consumption rate of new energy and the cost of energy storage configuration, and feeds back the optimization results of the inner layer to the outer layer optimization model. Use ISSA-MOPSO algorithm to solve the optimized configuration model. Finally, the rationality of the proposed model and algorithm in terms of on-site consumption rate and economy of new energy is verified through numerical examples.
The Use of Response Surface Methodology to Optimize Assisted Extraction of Bioactive Compounds from Cucurbita maxima Fruit By-Products
Authors: Mansour Rim Ben , Falleh Hanen , Hammami Majdi , Barros Lillian , Petropoulos Spyridon A. , Tarchoun Neji , Ksouri Riadh
Published: June 2023

This work aimed to optimize the extraction conditions of bioactive compounds obtained from three squash by-products (e.g., peel, endocarp, and seeds) using the response surface methodology (RSM). The selected independent variables were ethanol concentration, extraction time, and extraction temperature. Squash by-products’ bioactive molecules were extracted according to the matrix proposed by the experimental plan. Significant variability in total phenolic compound content (TPC) and antioxidant activity, depending on the extraction time, the solvent concentration, and the extraction temperature, was recorded for the tested by-products. The experimental results adequately fitted with second-order polynomial models and showed significant linear, quadratic, and interaction effects of the independent variables. Data analysis suggested that the optimal extraction conditions were 12.2% ethanol for 11.2 min at 55 °C for peels; 28.5% ethanol for 10.5 min at 37 °C for endocarp; and 20% ethanol for 10.5 min at 60 °C for seeds. The results obtained showed that the experimental and predicted values of TPC and antioxidant activities as an indicator of a successful extraction fit with each other, thus indicating the optimal extraction conditions. Under these conditions, the obtained extracts exhibited high, although variable, TPC with epicatechin and epigallocatechin as major compounds, as well significant antimicrobial potency, which reached 100% and 80% inhibition of the tested bacteria and fungi.
A Review on Impacting Parameters for Photocatalytic Degradation of Organic Effluents by Ferrites and Their Nanocomposites
Authors: Singh Gurpinder , Ubhi Manpreet Kaur , Jeet Kiran , Singla Chetan , Kaur Manpreet
Published: June 2023

Traditional wastewater treatment methods, such as reverse osmosis, adsorption, desalination, and others, are outweighed by the photocatalytic degradation of organic pollutants. Ferrites are prominent photocatalysts due to their tunable band gaps, surface areas, and magnetic properties, which render photodegradation economical. Ferrites and their nanocomposites have been reported as promising visible light active photocatalysts. The photocatalytic system is heavily reliant on a number of factors that influence the photodegradation of organic effluents. This review demonstrates various parameters such as substrate concentration, pH of solution, photocatalyst quantity, photocatalyst surface area, metal and non-metal ion doping, light intensity, irradiation time, quenchers, etc. affecting the photocatalytic degradation of organic effluents by ferrite nanoparticles and their nanocomposites in detail. The photodegradation efficiency of the ferrite nanoparticles alters with the change in the value of pH of the solution, which further depends upon the nature of the pollutant used. A dose of the substrate and the photocatalyst must be optimized so as to attain better photodegradation efficiency. Photocatalysts with different surface areas change the amount of active sites, which in turn affects the degradation of pollutant and render it a crucial factor. In addition, the mechanism of the action of photocatalysis is elaborated in this review. Future research perspectives for the advancement of ferrites and their nanocomposites are deliberated in order to improve their use as photocatalysts.
A Simulation and Empirical Study of Differential Test Functioning (DTF)
Authors: Yavuz Temel Güler
Published: June 2023

Detecting and understanding DTF is very important under various DIF conditions. In this study, the performance of DTF, DRF, SIBTEST, and CSIBTEST approaches in detecting DIF effects was investigated using a simulation study and a real dataset. It was observed that different DIF conditions (uniform, non-uniform), the proportion of DIF items in the test, the DIF size, and the DIF effect (balanced, unbalanced) affected the performance of the methods, and especially in the case of the non-uniform DIF condition, the power rates of sDTF, sDRF, and SIBTEST statistics were low. In addition, according to the DTF estimations with the balanced/unbalanced DIF effect condition, in some cases, the effect of DIF on the overall test could be negligible. However, it was clearly emphasized in this study that DTF analyses should accompany DIF studies since DTF analysis may change with different DIF and test conditions.
Improved Generalized IHS Based on Total Variation for Pansharpening
Authors: Zhang Xuefeng , Dai Xiaobing , Zhang Xuemin , Hu Yuchen , Kang Yingdong , Jin Guang
Published: June 2023

Pansharpening refers to the fusion of a panchromatic (PAN) and a multispectral (MS) image aimed at generating a high-quality outcome over the same area. This particular image fusion problem has been widely studied, but until recently, it has been challenging to balance the spatial and spectral fidelity in fused images. The spectral distortion is widespread in the component substitution-based approaches due to the variation in the intensity distribution of spatial components. We lightened the idea using the total variation optimization to improve upon a novel GIHS-TV framework for pansharpening. The framework drew the high spatial fidelity from the GIHS scheme and implemented it with a simpler variational expression. An improved L1-TV constraint to the new spatial–spectral information was introduced to the GIHS-TV framework, along with its fast implementation. The objective function was solved by the Iteratively Reweighted Norm (IRN) method. The experimental results on the “PAirMax” dataset clearly indicated that GIHS-TV could effectively reduce the spectral distortion in the process of component substitution. Our method has achieved excellent results in visual effects and evaluation metrics.
Impacts of Climate Change and Human Activities on Plant Species α-Diversity across the Tibetan Grasslands
Authors: Huang Shaolin , Fu Gang
Published: June 2023

Plant species α-diversity is closely correlated with ecosystem structures and functions. However, whether climate change and human activities will reduce plant species α-diversity remains controversial. In this study, potential (i.e., potential species richness: SRp, Shannonp, Simpsonp and Pieloup) and actual plant species α-diversity (i.e., actual species richness: SRa, Shannona, Simpsona and Pieloua) during 2000–2020 were quantified based on random forests in grasslands on the Tibetan Plateau. Overall, climate change had positive influences on potential plant species α-diversity across all the grassland systems. However, more than one-third areas showed decreasing trends for potential plant species α-diversity. Climate change increased the SRp at rates of 0.0060 and 0.0025 yr−1 in alpine steppes and alpine meadows, respectively. Temperature change predominated the variations of Shannonp and Simpsonp, and radiation change predominated the variations of SRp and Pieloup. Geography position, local temperature, precipitation and radiation conditions regulated the impacts of climate change on potential species α-diversity. On average, human activities caused 1% plant species loss but elevated the Shannon, Simpson and Pielou by 26%, 4% and 5%, respectively. There were 46.51%, 81.08%, 61.26% and 61.10% areas showing positive effects of human activities on plant species richness, Shannon, Simpson and Pielou, respectively. There were less than 48% areas showing increasing trends of human activities’ impacts on plant species α-diversity. Human activities increased plant species richness by 2% in alpine meadows but decreased plant species richness by 1% in alpine steppes. Accordingly, both the impacts of climate change and human activities on plant species α-diversity were not always negative and varied with space and grassland types. The study warned that both climate change and human activities may not cause as much species loss as expected. This study also cautioned that the impacts of radiation change on plant species α-diversity should be at least put on the same level as the impacts of climate warming and precipitation change on plant α-diversity.
Developing Spatial and Temporal Continuous Fractional Vegetation Cover Based on Landsat and Sentinel-2 Data with a Deep Learning Approach
Authors: Wang Zihao , Song Dan-Xia , He Tao , Lu Jun , Wang Caiqun , Zhong Dantong
Published: June 2023

Fractional vegetation cover (FVC) has a significant role in indicating changes in ecosystems and is useful for simulating growth processes and modeling land surfaces. The fine-resolution FVC products represent detailed vegetation cover information within fine grids. However, the long revisit cycle of satellites with fine-resolution sensors and cloud contamination has resulted in poor spatial and temporal continuity. In this study, we propose to derive a spatially and temporally continuous FVC dataset by comparing multiple methods, including the data-fusion method (STARFM), curve-fitting reconstruction (S-G filtering), and deep learning prediction (Bi-LSTM). By combining Landsat and Sentinel-2 data, the integrated FVC was used to construct the initial input of fine-resolution FVC with gaps. The results showed that the FVC of gaps were estimated and time-series FVC was reconstructed. The Bi-LSTM method was the most effective and achieved the highest accuracy (R2 = 0.857), followed by the data-fusion method (R2 = 0.709) and curve-fitting method (R2 = 0.705), and the optimal time step was 3. The inclusion of relevant variables in the Bi-LSTM model, including LAI, albedo, and FAPAR derived from coarse-resolution products, further reduced the RMSE from 5.022 to 2.797. By applying the optimized Bi-LSTM model to Hubei Province, a time series 30 m FVC dataset was generated, characterized by a spatial and temporal continuity. In terms of the major vegetation types in Hubei (e.g., evergreen and deciduous forests, grass, and cropland), the seasonal trends as well as the spatial details were captured by the reconstructed 30 m FVC. It was concluded that the proposed method was applicable to reconstruct the time-series FVC over a large spatial scale, and the produced fine-resolution dataset can support the data needed by many Earth system science studies.
A Support Vector Machine-Based Approach for Bolt Loosening Monitoring in Industrial Customized Vehicles
Authors: Carone Simone , Pappalettera Giovanni , Casavola Caterina , De Carolis Simone , Soria Leonardo
Published: June 2023

Machine learning techniques have progressively emerged as important and reliable tools that, when combined with machine condition monitoring, can diagnose faults with even superior performance than other condition-based monitoring approaches. Furthermore, statistical or model-based approaches are often not applicable in industrial environments with a high degree of customization of equipment and machines. Structures such as bolted joints are a key part of the industry; therefore, monitoring their health is critical to maintaining structural integrity. Despite this, there has been little research on the detection of bolt loosening in rotating joints. In this study, vibration-based detection of bolt loosening in a rotating joint of a custom sewer cleaning vehicle transmission was performed using support vector machines (SVM). Different failures were analyzed for various vehicle operating conditions. Several classifiers were trained to evaluate the influence of the number and location of accelerometers used and to determine the best approach between specific models for each operating condition or a single model for all cases. The results showed that using a single SVM model with data from four accelerometers mounted both upstream and downstream of the bolted joint resulted in more reliable fault detection, with an overall accuracy of 92.4%.
A Low-Carbon and Economic Dispatch Strategy for a Multi-Microgrid Based on a Meteorological Classification to Handle the Uncertainty of Wind Power
Authors: Liu Yang , Li Xueling , Liu Yamei
Published: June 2023

In a modern power system, reducing carbon emissions has become a significant goal in mitigating the impact of global warming. Therefore, renewable energy sources, particularly wind-power generation, have been extensively implemented in the system. Despite the advantages of wind power, its uncertainty and randomness lead to critical security, stability, and economic issues in the power system. Recently, multi-microgrid systems (MMGSs) have been considered as a suitable wind-power deployment candidate. Although wind power can be efficiently utilized by MMGSs, uncertainty and randomness still have a significant impact on the dispatching and operation of the system. Therefore, to address the wind power uncertainty issue and achieve an optimal dispatching strategy for MMGSs, this paper presents an adjustable robust optimization (ARO) model based on meteorological clustering. Firstly, the maximum relevance minimum redundancy (MRMR) method and the CURE clustering algorithm are employed for meteorological classification in order to better identify wind patterns. Secondly, a conditional generative adversarial network (CGAN) is adopted to enrich the wind-power datasets with different meteorological patterns, resulting in the construction of ambiguity sets. Thirdly, the uncertainty sets that are finally employed by the ARO framework to establish a two-stage cooperative dispatching model for MMGS can be derived from the ambiguity sets. Additionally, stepped carbon trading is introduced to control the carbon emissions of MMGSs. Finally, the alternative direction method of multipliers (ADMM) and the column and constraint generation (C&CG) algorithm are adopted to achieve a decentralized solution for the dispatching model of MMGSs. Case studies indicate that the presented model has a great performance in improving the wind-power description accuracy, increasing cost efficiency, and reducing system carbon emissions. However, the case studies also report that the approach consumes a relative long running time. Therefore, in future research, the solution algorithm will be further improved for the purpose of raising the efficiency of the solution.
A Holistic 4D Approach to Optimize Intrinsic and Extrinsic Factors Contributing to Variability in Microarray Biosensing in Glycomics
Authors: Kundalia Paras H. , Pažitná Lucia , Kianičková Kristína , Jáné Eduard , Lorencová Lenka , Katrlík Jaroslav
Published: June 2023

Protein–carbohydrate interactions happen to be a crucial facet of biology, discharging a myriad of functions. Microarrays have become a premier choice to discern the selectivity, sensitivity and breadth of these interactions in a high-throughput manner. The precise recognition of target glycan ligands among the plethora of others is central for any glycan-targeting probe being tested by microarray analyses. Ever since the introduction of the microarray as an elemental tool for high-throughput glycoprofiling, numerous distinct array platforms possessing different customizations and assemblies have been developed. Accompanying these customizations are various factors ushering variances across array platforms. In this primer, we investigate the influence of various extrinsic factors, namely printing parameters, incubation procedures, analyses and array storage conditions on the protein–carbohydrate interactions and evaluate these factors for the optimal performance of microarray glycomics analysis. We hereby propose a 4D approach (Design–Dispense–Detect–Deduce) to minimize the effect of these extrinsic factors on glycomics microarray analyses and thereby streamline cross-platform analyses and comparisons. This work will aid in optimizing microarray analyses for glycomics, minimize cross-platform disparities and bolster the further development of this technology.
Shoulder Range of Motion Measurement Using Inertial Measurement Unit—Validation with a Robot Arm
Authors: Białecka Martyna , Gruszczyński Kacper , Cisowski Paweł , Kaszyński Jakub , Baka Cezary , Lubiatowski Przemysław
Published: June 2023

The invention of inertial measurement units allowed the construction of sensors suitable for human motion tracking that are more affordable than expensive optical motion capture systems, but there are a few factors influencing their accuracy, such as the calibration methods and the fusion algorithms used to translate sensor readings into angles. The main purpose of this study was to test the accuracy of a single RSQ Motion sensor in comparison to a highly precise industrial robot. The secondary objectives were to test how the type of sensor calibration affects its accuracy and whether the time and magnitude of the tested angle have an impact on the sensor’s accuracy. We performed sensor tests for nine repetitions of nine static angles made by the robot arm in eleven series. The chosen robot movements mimicked shoulder movements in a range of motion test (flexion, abduction, and rotation). The RSQ Motion sensor appeared to be very accurate, with a root-mean-square error below 0.15°. Furthermore, we found a moderate-to-strong correlation between the sensor error and the magnitude of the measured angle but only for the sensor calibrated with the gyroscope and accelerometer readings. Although the high accuracy of the RSQ Motion sensors was demonstrated in this paper, they require further study on human subjects and comparisons to the other devices known as the gold standards in orthopedics.
Can Metabolomic Approaches Become a Tool for Improving Early Plant Disease Detection and Diagnosis with Modern Remote Sensing Methods? A Review
Authors: Terentev Anton , Dolzhenko Viktor
Published: June 2023

The various areas of ultra-sensitive remote sensing research equipment development have provided new ways for assessing crop states. However, even the most promising areas of research, such as hyperspectral remote sensing or Raman spectrometry, have not yet led to stable results. In this review, the main methods for early plant disease detection are discussed. The best proven existing techniques for data acquisition are described. It is discussed how they can be applied to new areas of knowledge. The role of metabolomic approaches in the application of modern methods for early plant disease detection and diagnosis is reviewed. A further direction for experimental methodological development is indicated. The ways to increase the efficiency of modern early plant disease detection remote sensing methods through metabolomic data usage are shown. This article provides an overview of modern sensors and technologies for assessing the biochemical state of crops as well as the ways to apply them in synergy with existing data acquisition and analysis technologies for early plant disease detection.
Models for Organising the Education of Ukrainian Children Who Have Fled the War in Lithuanian Municipalities: Psychological, Material, and Linguistic Support
Authors: Jakavonytė-Staškuvienė Daiva
Published: June 2023

This article presents the situation of the education of Ukrainian refugee children in Lithuania. It analyses the political and practical actions taken by the Lithuanian state when, after the outbreak of the war in Ukraine, schools unexpectedly received a large number of children from Ukraine who had not come of their own free will, having fled the war. This article presents how Lithuanian municipalities have acted and the decisions taken to strengthen the psychological microclimate and devise a suitable model of language education. The aim of this study was to describe the experience of different regions of Lithuania in integrating Ukrainian war refugee children into educational institutions in terms of psychological, material, and linguistic support. Semi-structured group interviews (n = 12) were carried out with municipal education department staff, the staff of pedagogical qualification centres, and school managers (n = 206) who have worked on the integration of war refugee children in their municipality. The interviews were analysed using thematic content analysis. The results were divided into the following groups: (1) psychological needs of the children, (2) physical needs of the children, (3) the chosen model of Lithuanian language education, and (4) support measures for the integration of the children. The study shows that the quick but timely decisions taken in Lithuania to recruit teachers from Ukraine have helped to resolve the traumatic situations regarding the integration of children.
Spatiotemporal Evolution of Coordinated Development between Economic Resilience and Green Finance under the Background of Sustainable Development
Authors: Zhang Jin , Zhang Shuiping , Huang Xin , Zhang Zhiwei , Jin Chengtuo
Published: June 2023

The coupling and coordination between green finance (GF) and economic resilience (ER) are the foundation of sustainable economic development. This paper uses the panel data of 30 provinces (autonomous regions and municipalities) in mainland China from 2011 to 2021 to calculate the comprehensive development level of the two systems by the entropy weight method. At the same time, we analyze the spatiotemporal evolution characteristics of the coupling coordination degree of the two systems by using the coupling coordination degree model, kernel density curve, spatial autocorrelation model, and Markov transition matrix. The results show that (1) the development level of ER increased steadily while that of GF fluctuated. The coupling coordination degree of the two systems shows an increasing trend. (2) The coupling coordination level of the two systems presents a spatial gradient pattern of “East > Middle > West”. (3) The level of coupling coordination has an obvious spatial correlation. (4) The coupling coordination level in our country remains stable in the future, and there is a possibility of transition to a higher level. The research of this paper provides valuable enlightenment for implementing a sustainable development strategy in China.
From Staple Food to Scarce Resource: The Population Status of an Endangered Striped Catfish Pangasianodon hypothalamus in the Mekong River, Cambodia
Authors: Soem Sothearith , Hogan Zeb S. , Chan Bunyeth , Chhuoy Samol , Uy Sophorn , Pin Kakada , Touch Bunthang , Chandra Sudeep , Ngor Peng Bun
Published: June 2023

Striped catfish Pangasianodon hypopthalmus (Sauvage, 1878) is a flagship catfish species of the Mekong River region, a commercially valuable food fish that is important in freshwater fisheries, and a popular aquaculture species in many Asian countries. The species was assessed as “Endangered” by the International Union for Conservation of Nature (IUCN) due to range contraction and declining abundance, though the status of the species’ wild population in Cambodia, a critical habitat for the species, is not well understood. Here, we assess the population status of the striped catfish in Cambodia using multiple sources, including time-series catch data and length frequency distribution data from a commercial fishery (stationary trawl bagnet or dai) operated in the Tonle Sap River from 1998/99 to 2017/18 and larval drift data monitored in the Mekong River in Phnom Penh from 2004 to 2018. We found that there was a significant decline (R2 = 0.54, p = 0.0002) in the catch (metric tonnes) of the striped catfish from the commercial dai fishery over the last two decades. Similarly, length-based indicator analysis indicates that striped catfish mean length and abundance have both declined over the study period, raising concerns about the sustainability of river catfish fisheries. Moreover, long-term larval drift monitoring in Mekong River shows that there was a marginally significant decline in the quantity of striped catfish larvae/juvenile drifting downstream to the lower floodplain over the last decade. Changes in flood index (extent and duration of flood) in the Tonle Sap floodplain affected by the Mekong’s flow are likely key factors driving the decline of the wild populations of the striped catfish. Both larval fish abundance and floodplain fish harvests have a significant positive relationship with Mekong flow and flood extent. Indiscriminate fishing exacerbates pressures on striped catfish stocks. Therefore, actions such as maintaining natural seasonal flows (flood timing, extent, and duration) to the Tonle Sap floodplain and protecting migratory fish stocks from overharvest and habitat fragmentation are essential to the persistence of stocks of striped catfish and other large-bodied migratory fishes that utilize both the Cambodian Mekong and Tonle Sap floodplains.