bluuebunny/crossref_metadata_2025 huggingface dataset:
Different Host Plants Distinctly Influence the Adaptability of Myzus persicae (Hemiptera: Aphididae)
Authors: Jiang Wenbin , Cheng Qian , Lu Changhao , Chen Wenlong , Zhao Degang , He Yingqin
Published: December 2022

Piercing–sucking insects are prominent phloem-feeding insect pests and understanding their feeding behavior and life characteristics plays a crucial role in studying insect host adaptability. The green peach aphid, Myzus persicae (Hemiptera: Aphididae), is one of the most prominent pests in tobacco-growing areas around the world. This study evaluated the adaptability of M. persicae to five host plants: tobacco, radish, Chinese cabbage, Brassica oleracea, and rape using the electropenetrography, age-stage, two-sex life table and population dynamics. The results demonstrated that the feeding behavior of M. persicae differed significantly according to the target hosts. M. persicae exhibited reduced pathway activities and increased phloem sap ingestion on radish, whereas the opposite was observed on Chinese cabbage. Additionally, the mechanical difficulties of M. persicae mouthparts in the probe pathway phase were significantly lower on tobacco and radish than on other host plants. Life table parameters indicated that for M. persicae reared on radish, preadult duration, longevity, and total preoviposition increased significantly and the fecundity was the highest. Furthermore, the net reproductive rate (R0) increased significantly. The population number of M. persicae on radish after 15 days was significantly higher than that on other hosts, except for tobacco. Although M. persicae can successfully survive on the five plants, our results demonstrated that radish is the optimal host. These results provide significant information for understanding the population dynamics of M. persicae and on different host crops integrated management strategy.
Does COVID-19 Affect Farmland Prices? How and Why?
Authors: Lee Brian , Cheng Po-Yuan , Sun Lih-Chyun , Hsieh Yi-Ting , Chang Hung-Hao
Published: December 2022

COVID-19 has profoundly impacted the global economy, particularly the agricultural sector. However, relatively little attention has been paid to the relationship between COVID-19 and the farmland market. A few descriptive studies have speculated about the impact of COVID-19 on farmland prices but presented no quantitative evidence. This study provides quantitative evidence on the causal effect of COVID-19 on farmland prices using the difference-in-differences method with population-based data on farmland transactions in Taiwan. While prior descriptive studies argued that increased farmland prices associated with COVID-19 were largely driven by macroeconomic conditions, we found that the onset of COVID-19 increased farmland prices by 5.1%, even after controlling for macroeconomic conditions and parcel-level farmland characteristics. Furthermore, we found that government payments are likely responsible for these increases in farmland prices. Financial assistance easing the economic burdens of the agricultural sector can also stabilize farmland prices.
Effects of Nursery Container Color and Spacing on Root Zone Temperatures of ‘Soft Touch’ Holly
Authors: McBrayer R. Hunter , Pickens Jeremy M. , Witcher Anthony L. , Wells Daniel E. , Sibley Jeff L.
Published: December 2022

Newly up-potted ‘Soft Touch’ Japanese hollies (Ilex crenata ‘Soft Touch’) were grown in Mobile, AL in 1.5 L containers to evaluate the effects of growth from black or white container colors and container spacing (jammed or spaced) in relation to root zone temperature. Two treatments, container color and container spacing, were evaluated and root ratings were reported. At termination, an interaction was observed in growth from 43 to 141 days after potting between container color and spacing. Both white container treatments and the black-jammed treatment experienced 36% and 21% more growth than black-spaced plants. Root ratings for white containers (jammed and spaced) were 42% greater than for black-spaced. Black-jammed root ratings were 25% greater than black-spaced. Black-spaced containers experienced the greatest number of time intervals over the critical temperature of 39 °C when compared to other treatments. Results suggest that ‘Soft Touch’ holly may be grown at final spacing when using white containers and have little impact from elevated root zone temperatures.
Progress in Studies of Climatic Suitability of Crop Quality and Resistance Mechanisms in the Context of Climate Warming
Authors: He Qijin , Zhou Guangsheng , Liu Jiahong
Published: December 2022

Crop quality is directly related to national food security and people’s living standards, and it is also key to the improvement of agricultural quality and efficiency. According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), climate change has already exerted a negative impact on crop quality. To address climate change scientifically, this paper reviews the latest progress in studies on the impact of climate change on crop quality, and points out limitations of existing studies: (1) Climate factors affecting crop quality are not yet clearly identified; (2) The climate change influencing mechanism and disaster-inducing critical meteorological conditions for crop quality are not clearly established; and (3) No climatic suitability model for crop quality has been constructed to reflect the synergy of multiple climate factors. To ensure food quality and security, and to adjust and optimize the industrial planning of grain crops, promote a high crop quality and yield, and address climate change scientifically, this paper argues that subsequent studies should discuss the following topics, focusing on the climatic suitability of crop quality and resistance mechanisms: (1) changing laws involving the climate sensitivity of crop quality in the context of climate change; (2) response mechanisms of crop quality to climate change; (3) crop quality monitoring and assessment modelling; (4) climatic suitability zoning of crop quality; (5) spatiotemporal evolution trends of crop quality and its responses; and (6) crop quality and its legal measures in the world.
Ophioglossum lusitanicum L.: New Records of Plant Community and 92/43/EEC Habitat in Italy
Authors: Perrino Enrico Vito , Tomaselli Valeria , Wagensommer Robert Philipp , Silletti Giuseppe Nicola , Esposito Assunta , Stinca Adriano
Published: December 2022

In this paper, integrating field surveys and literature data, an analysis of Ophioglossum lusitanicum plant communities and related 92/43/EEC habitats are reported for Italy. Two new syntaxa, Euphorbio exiguae-Ophioglossetum lusitanici ass. nova hoc loco and trifolietosum scabri subass. nova hoc loco of the Rumici bucephalophori-Ophioglossetum lusitanici were described in the Apulia and Campania regions.Both types of vegetation identified in Apulia, Campania, and Sicily regions represent two different aspects of the same priority habitat: “pseudo-steppe with grasses and annuals of the Thero-Brachypodietea” (habitat code 6220*). A phytosociological and ecological dataset of the literature and new field surveys highlighting the soil type as parameters affecting the vegetation cover of this small fernlike plant, with the Trachynion distachyae Rivas–Martínez, 1978 alliance on calcareous soils and Helianthemion guttati Br.-Bl. in Br.-Bl. et al., 1940 alliance on volcanic soils. Many species of other types of annual meadows have been identified within Ophioglossum communities due to the very small patches of land, where they have been found, and ecological conditions that facilitate this phenomenon of the transgression of other therophytes species.
Synergism of Neem and Karanja Oils against Colorado Potato Beetle Larvae in Field Conditions
Authors: Kovaříková Kateřina , Doležal Petr , Hausvater Ervín , Žabka Martin , Pavela Roman
Published: December 2022

The increasing scarcity of active substances approved for use in plant protection is reflected in the growing effort to find suitable plant protection alternatives. Products based on plant oils could provide a promising environmentally friendly solution. In previous research in laboratory conditions, the synergistic effect of neem and karanja oils on Leptinotarsa decemlineata (CPB) larvae was observed. The aim of this current study was to verify whether the synergistic effect would also be observed in field conditions. The active substances used included azadirachtin A (NeemAzal® T/S); in both a reduced dose of 10.6 g/ha and a normal dose of 26.5 g/ha (Neem1, Neem2), Pongamia pinnata oil (Rock Effect New–REN); in a reduced dose of 1987.6 g/ha, and a mixture of both reduced doses (MIX). The protective effect was expressed by a visual estimation of the damaged leaf area on the potato plant. The MIX variant was always among the least damaged variants throughout the experiments, while the control was always the most damaged variant. A synergistic effect was observed at site I in 2021 when the MIX variant was more than 10 times less damaged than the control; in other cases, it was around 3 times less damaged. Treatment with MIX provided a protective effect comparable to NeemAzal® T/S in the full dose. This mixture can therefore be used to expand the portfolio of suitable preparations against CPB larvae in potato production.
Adapting Tea Production to Climate Change under Rapid Economic Development in China from 1987 to 2017
Authors: Zhao Yuncheng , Xu Yinlong , Zhang Lei , Zhao Mingyue , Wang Chunyi
Published: December 2022

Tea (Camellia sinensis L.), as one of the most important cash crops in China, plays an important role in increasing farmers’ incomes and guaranteeing a high quality of life. Tea production has been greatly influenced by both climate change and economic development in China. However, without a scientific understanding of the interaction mechanism of climate change and the impetus from rapid economic development on tea production practices in China, it is difficult to take adaptive actions to meet the climate change challenges for the tea industry. In this paper, we firstly assessed the potential impacts of climate change on tea climate suitability by empirical formula calculation using meteorological data; then, the effects from the additional climatic stress due to warming on tea production were detected with the annual statistical tea yield record on a municipal level. The contribution of socioeconomic development to the tea industry was evaluated with the comparison of the movement of China’s national economy’s and tea industry’s gravity center during the period of 1987–2017. Finally, a conceptual adaptation framework was built to demonstrate the interaction mechanisms between climate change, tea production, and the economic development. The results showed that there was a negative impact of climate change on tea production in mainland China, with the percentage of high tea climate suitability (>0.9) areas dropping by 45% to 32%, while opportunities of enlarging the tea cultivating area emerged in the north tea production region where the tea climate suitability increased. We found that the tea planting area expanded northwards from 33° N in 1987 to 35° N in 2017 to take advantage of the favorable climatic resources due to warming, and tea planting decreased at an altitude of 100–400 m while increasing to higher altitude of 400–2000 m to avoid hot temperature damage and seek the optimum environment in high mountainous areas for tea production. In addition, the tea production moved westward along the longitude, decreasing obviously at 117–121° E while increasing significantly at 98–104° E and 107–110° E. Meanwhile, the tea production gravity center showed a westward movement consistent with the national economic gravity center moving trend, which means that tea industry development was driven by multiple socioeconomic factors and climatic forcings. A conceptual framework was built in this paper, aiming to show a robust adaptation mechanism for the tea system to maximize the benefits and minimize the damages from the altered climatic resources under rapid economic development in mainland China. The results in this study would help deepen the understanding of the adaptation process and practices for tea production in mainland China.
The Biomass Productivity of Maize, Hemp and Faba Bean Multi-Crops
Authors: Balandaitė Jovita , Romaneckas Kęstutis , Švereikaitė Austėja , Kimbirauskienė Rasa , Sinkevičienė Aušra , Romaneckas Andrius
Published: December 2022

Crop biomass is valuable not only from a nutritional and fodder point of view, but also from an energetic point of view. The main task is to increase biomass production while maintaining low nutrient and pesticide requirements and low ecological footprint. A stationary three-year field experiment was performed at the Experimental Station of Vytautas Magnus University, Lithuania, in 2020–2022. Single crops and mixtures of maize, hemp, and faba bean were investigated in terms of their biomass productivity. Results showed that as the crop diversification increases, the productivity of maize and hemp grown in the mixture decreases, while faba bean ensures high dried biomass productivity. During the three years of the experimentation, the highest total dried biomass was found in the ternary crop: on average, 1495.4 g m−2 per year. The highest dried biomass of the ternary crop was established in the first year of experimentation: 2081.1 g m−2. A decrease in biomass yields in the second and third years of the experiment was observed in all treatment plots. The results suggest that the low fertilization level (totally N 45, P 45, K 45 kg ha−1) in the experiment should be increased if multi-crop cultivations are to be regrown during vegetative seasons.
A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization
Authors: Di Yan , Gao Maofang , Feng Fukang , Li Qiang , Zhang Huijie
Published: December 2022

Early prediction of winter wheat yield at the regional scale is essential for food policy making and food security, especially in the context of population growth and climate change. Agricultural big data and artificial intelligence (AI) are key technologies for smart agriculture, bringing cost-effective solutions to the agricultural sector. Deep learning-based crop yield forecast has currently emerged as one of the key methods for guiding agricultural production. In this study, we proposed a Bayesian optimization-based long- and short-term memory model (BO-LSTM) to construct a multi-source data fusion-driven crop growth feature extraction algorithm for winter wheat yield prediction. The yield prediction performance of BO-LSTM, support vector machine (SVM), and least absolute shrinkage and selection operator (Lasso) was then compared with multi-source data as input variables. The results showed that effective deep learning hyperparameter optimization is made possible by Bayesian optimization. The BO-LSTM (RMSE = 177.84 kg/ha, R2 = 0.82) model had the highest accuracy of yield prediction with the input combination of “GPP + Climate + LAI + VIs”. BO-LSTM and SVM (RMSE = 185.7 kg/ha, R2 = 0.80) methods outperformed linear regression Lasso (RMSE = 214.5 kg/ha, R2 = 0.76) for winter wheat yield estimation. There were also differences between machine learning and deep learning, BO-LSTM outperformed SVM. indicating that the BO-LSTM model was more effective at capturing data correlations. In order to further verify the robustness of the BO-LSTM method, we explored the performance estimation performance of BO-LSTM in different regions. The results demonstrated that the BO-LSTM model could obtain higher estimation accuracy in regions with concentrated distribution of winter wheat cultivation and less influence of human factors. The approach used in this study can be expected to forecast crop yields, both in regions with a deficit of data and globally; it can also simply and effectively forecast winter wheat yields in a timely way utilizing publicly available multi-source data.
The Complete Mitogenome of Toxocara vitulorum: Novel In-Sights into the Phylogenetics in Toxocaridae
Authors: Xie Yue , Wang Lidan , Chen Yijun , Wang Zhao , Zhu Pengchen , Hu Zun , Han Xinfeng , Wang Zhisheng , Zhou Xuan , Zuo Zhicai
Published: December 2022

Toxocara vitulorum (Ascaridida: Nematoda) is one of the most common intestinal nematodes of cattle and buffalos and, therefore, represents a serious threat to their populations worldwide. Despite its significance in veterinary health the epidemiology, population genetics, and molecular ecology of this nematode remain poorly understood. The mitogenome can yield a foundation for studying these areas and assist in the surveillance and control of T. vitulorum. Herein, the first whole mitogenome of T. vitulorum was sequenced utilizing Illumina technology and characterized with bioinformatic pipeline analyses. The entire genome of T. vitulorum was 15,045 bp in length and contained 12 protein-coding genes (PCGs), 22 transfer RNAs (tRNAs), and two ribosomal RNAs (rRNAs). The gene arrangement (GA) of T. vitulorum was similar to those of other Toxocara species under GA3. The whole genome showed significant levels of AT and GC skew. Comparative mitogenomics including sequence identities, Ka/Ks, and sliding window analysis, indicated a purifying selection of 12 PCGs with cox1 and nad6 having the lowest and highest evolutionary rate, respectively. Whole amino acid sequence-based phylogenetic analysis supported a novel sister-species relationship of T. vitulorum with the congeneric species Toxocara canis, Toxocara cati, and Toxocara malaysiensis in the family Toxocaridae. Further, 12 (PCGs) single gene-based phylogenies suggested that nad4 and nad6 genes shared same topological trees with that of the whole genome, suggesting that these genes were suitable as novel genetic markers for phylogenetic and evolutionary studies of Ascaridida species. This complete mitogenome of T. vitulorum refined phylogenetic relationships in Toxocaridae and provided the resource of markers for population genetics, systematics, and epidemiology of this bovine nematode.
Life History of the Arctic Squid Gonatus fabricii (Cephalopoda: Oegopsida) Reconstructed by Analysis of Individual Ontogenetic Stable Isotopic Trajectories
Authors: Golikov Alexey V. , Ceia Filipe R. , Hoving Hendrik J. T. , Queirós José P. , Sabirov Rushan M. , Blicher Martin E. , Larionova Anna M. , Walkusz Wojciech , Zakharov Denis V. , Xavier José C.
Published: December 2022

Cephalopods are important in Arctic marine ecosystems as predators and prey, but knowledge of their life cycles is poor. Consequently, they are under-represented in the Arctic ecosystems assessment models. One important parameter is the change in ecological role (habitat and diet) associated with individual ontogenies. Here, the life history of Gonatus fabricii, the most abundant Arctic cephalopod, is reconstructed by the analysis of individual ontogenetic trajectories of stable isotopes (δ13C and δ15N) in archival hard body structures. This approach allows the prediction of the exact mantle length (ML) and mass when the species changes its ecological role. Our results show that the life history of G. fabricii is divided into four stages, each having a distinct ecology: (1) epipelagic squid (ML < 20 mm), preying mostly on copepods; (2) epi- and occasionally mesopelagic squid (ML 20–50 mm), preying on larger crustaceans, fish, and cephalopods; (3) meso- and bathypelagic squid (ML > 50 mm), preying mainly on fish and cephalopods; and (4) non-feeding bathypelagic gelatinous females (ML > 200 mm). Existing Arctic ecosystem models do not reflect the different ecological roles of G. fabricii correctly, and the novel data provided here are a necessary baseline for Arctic ecosystem modelling and forecasting.
Nutritional Value of Climate-Resilient Forage Species Sustaining Peri-Urban Dairy Cow Production in the Coastal Grasslands of Benin (West Africa)
Authors: Koura Bossima Ivan , Vastolo Alessandro , Kiatti Dieu donné , Cutrignelli Monica Isabella , Houinato Marcel , Calabrò Serena
Published: December 2022

Along the coast of West Africa, grazing ruminants rely on perennial forage species remaining in uncultivated plots, roadsides, and marshlands during the dry season. To assess the quality of these forages, thirteen drought-tolerant plants were harvested at the mature stage, and the samples were evaluated for chemical composition, in vitro fermentation characteristics, and metabolizable energy (ME) content. They are ten drought-tolerant grasses, including: Andropogon virginicus, Brachiaria deflexa, Cenchorus biflorus, Dactyloctenium aegyptium, Eragrostis tremula, Leptochloa caerulescens, Loudetia aroundinacea, Paspalum notatum, Paspalum vaginatum, Pennisetum purpureum, two perennial herbs, Chamaecrista rotundifolia, Zornia latifolia, and one multipurpose tree, Elaeis guineensis. Legume species had the highest nutritional value (highest crude protein and ME, and lowest neutral detergent fiber) of the species studied. In terms of the in vitro data, the gas produced after 120 h of incubation ranged from 149 mL/g in E. tremula to 185 mL/g in Paspalum. Z. latifoliaa and had the fastest rate of fermentation, producing half of the total gas in 19.5 h, whereas E. tremula required 49.9 h (p < 0.01). The production of branched-chain fatty acids (isobutyrate and isovalerate) was greatest for E. guineensis and the lowest in both Paspalum species (p < 0.01). The study suggests the need for the protein supplementation of the animals to ensure maximum forage utilization and to satisfy the nutrient requirements of ruminant livestock.
The Prevalence of Trichinella spiralis in Domestic Pigs in China: A Systematic Review and Meta-Analysis
Authors: Bai Huifang , Tang Bin , Qiao Weidong , Wu Xiaoxia , Liu Mingyuan , Wang Xuelin
Published: December 2022

The meta-analysis was performed to assess the prevalence of T. spiralis in domestic pigs in China. The potential studies from seven databases (Pubmed, Web of science, Scopus, Google Scholar, CNKI, Wanfang, CBM) were searched. I2, Cochran’s Q statistic and the funnel plot and Egger’s test were used to assess heterogeneity and publication bias, respectively. In this study, a total of 179 articles were captured in the initially screened. Of these, we finally obtained 39 significant articles (including 43 studies involving in 551,097 pigs) for the final analysis. We calculated using a random-effects model, and we found the overall infection rate was 0.04 (95% CI 0.03–0.06). The highest prevalence region was Guangxi. The funnel plot and Egger’s test showed no publication bias in our meta-analysis. In addition, this high heterogeneity index was suggestive of potential variations which could be due to regions, quality scores, detection methods, publication years, or samplings. These results indicated that T. spiralis were still prevalent in some areas in China. This highlights the need for an increased focus on implementing affordable, appropriate control programs to reduce economic losses and T. spiralis infection in domestic pigs in China.
Redox Status, Estrogen and Progesterone Production by Swine Granulosa Cells Are Impaired by Triclosan
Authors: Basini Giuseppina , Grasselli Francesca , Quintavalla Fausto , Bussolati Simona , Andreoli Valentina , Carrillo Heredero Alicia Maria , Bertini Simone
Published: December 2022

Triclosan is a chlorinated biphenolic with a broad spectrum of antiseptic activities used in cosmetics and hygiene products. Continuous exposure can lead to absorption and bioaccumulation of this substance with harmful health effects. In fact, previous studies have shown that Triclosan acts as an endocrine-disrupting chemical on reproductive organs, with consequent negative effects on reproductive physiology. Therefore, to assess potential adverse impacts on fertility, we tested Triclosan on swine granulosa cells, a model of endocrine reproductive cells. We examined its effects on the main features of granulosa cell functions such as cell growth (BrdU incorporation and ATP production) and steroidogenesis (17-β estradiol and progesterone secretion). Moreover, since oxidant–antioxidant balance plays a pivotal role in follicular function, redox status markers (superoxide, hydrogen peroxide and nitric oxide production, enzymatic and non-enzymatic scavenging activity) were studied. Our results show that Triclosan significantly inhibits cell growth (p < 0.001), steroidogenesis (p < 0.001), superoxide and nitric oxide production (p < 0.001), while it increases (p < 0.05) enzymatic defense systems. Collectively, these data suggest a disruption of the main granulosa cell functions, i.e., proliferation and hormone production, as well as an imbalance in redox status. On these bases, we can speculate that Triclosan would impair granulosa cell functions, thus exerting negative effects on reproductive function. Further studies are needed to explore lower Triclosan concentrations and to unravel its mechanisms of action at gene level.
Pharmacokinetic of Cefiderocol in Critically Ill Patients Receiving Renal Replacement Therapy: A Case Series
Authors: Mornese Pinna Simone , Corcione Silvia , De Nicolò Amedeo , Montrucchio Giorgia , Scabini Silvia , Vita Davide , De Benedetto Ilaria , Lupia Tommaso , Mula Jacopo , Di Perri Giovanni , D’Avolio Antonio , De Rosa Francesco Giuseppe
Published: December 2022

Background: Cefiderocol is a novel parenteral siderophore cephalosporin, demonstrating enhanced activity against multidrug-resistant (MDR) Gram-negative bacteria and difficult-to-treat Acinetobacter baumannii (DTR-AB). Plasma-free trough concentration (fCtrough) over the minimum inhibitory concentration (MIC) was reported as the best pharmacokinetic parameter to describe the microbiological efficacy of cefiderocol. Materials and methods: We retrospectively described the pharmacokinetic and pharmacodynamic profile of three critically ill patients admitted to the intensive care unit, receiving cefiderocol under compassionate use to treat severe DTR-AB infections while undergoing continuous venovenous haemofiltration. Cefiderocol was administrated at a dosage of 2 g every 8 h infused over 3 h. Therapeutic drug monitoring (TDM) was assessed at the steady state. Cthrough was evaluated by assuming a plasma protein binding of 58.0%. The fCmin/MIC was calculated assuming a cefiderocol MIC equal to the PK-PD breakpoint of susceptibility ≤ 2. The association between the PK/PD parameters and microbiological outcome was assessed. Results: fCtrough/MIC were >12 in 2 patients and 2.9 in the 1 who rapidly recovered from renal failure. Microbiological cure occurred in 3/3 of patients. None of the 3 patients died within 30 days. Conclusions: A cefiderocol dosage of 2 g q8 h in critically ill patients with AKI undergoing CVVH may bring about a very high plasma concentration, corresponding to essentially 100% free time over the MIC for DTR-AB.
Preparation of an Antioxidant Assembly Based on a Copolymacrolactone Structure and Erythritol following an Eco-Friendly Strategy
Authors: Chiriac Aurica P. , Ghilan Alina , Serban Alexandru-Mihail , Macsim Ana-Maria , Bargan Alexandra , Doroftei Florica , Chiriac Vlad Mihai , Nita Loredana Elena , Rusu Alina Gabriela , Sandu Andreea-Isabela
Published: December 2022

The study presents the achievement of a new assembly with antioxidant behaviour based on a copolymacrolactone structure that encapsulates erythritol (Eryt). Poly(ethylene brassylate-co-squaric acid) (PEBSA) was synthesised in environmentally friendly conditions, respectively, through a process in suspension in water by opening the cycle of ethylene brassylate macrolactone, followed by condensation with squaric acid. The compound synthesised in suspension was characterised by comparison with the polymer obtained by polymerisation in solution. The investigations revealed that, with the exception of the molecular masses, the compounds generated by the two synthetic procedures present similar properties, including good thermal stability, with a Tpeak of 456 °C, and the capacity for network formation. In addition, the investigation by dynamic light scattering techniques evidenced a mean diameter for PEBSA particles of around 596 nm and a zeta potential of −25 mV, which attests to their stability. The bio-based copolymacrolactone was used as a matrix for erythritol encapsulation. The new PEBSA–Eryt compound presented an increased sorption/desorption process, compared with the PEBSA matrix, and a crystalline morphology confirmed by X-ray diffraction analysis. The bioactive compound was also characterised in terms of its biocompatibility and antioxidant behaviour.
Distributions of α- and δ-TOCopherol in Intact Olive and Soybean Oil-in-Water Emulsions at Various Acidities: A Test of the Sensitivity of the Pseudophase Kinetic Model
Authors: Fernández-Ventoso Lucía , Toba-Pérez Artai , Losada-Barreiro Sonia , Paiva-Martins Fátima , Bravo-Díaz Carlos
Published: December 2022

During the last years, the formalism of the pseudophase kinetic model (PKM) has been successfully applied to determine the distributions of antioxidants and their effective interfacial concentrations, and to assess the relative importance of emulsion and antioxidant properties (oil and surfactant nature, temperature, acidity, chemical structure, hydrophilic-liphophilic balance (HLB), etc.) on their efficiency in intact lipid-based emulsions. The PKM permits separating the contributions of the medium and of the concentration to the overall rate of the reaction. In this paper, we report the results of a specifically designed experiment to further test the suitability of the PKM to evaluate the distributions of antioxidants among the various regions of intact lipid-based emulsions and provide insights into their chemical reactivity in multiphasic systems. For this purpose, we employed the antioxidants α- and δ-TOCopherol (α- and δ-TOC, respectively) and determined, at different acidities well below their pKa, the interfacial rate constants kI for the reaction between 16-ArN2+ and α- and δ-TOC, and the antioxidant distributions in intact emulsions prepared with olive and soybean oils. Results show that the effective interfacial concentration of δ-TOC is higher than that of α-TOC in 1:9 (v/v) soybean and 1:9 olive oil emulsions. The effective interfacial concentrations of tocopherols are much higher (15-96-fold) than the stoichiometric concentrations, as the effective interfacial concentrations of both δ-TOC and α-TOC in soybean oil emulsions are higher (2-fold) than those in olive oil emulsions. Overall, the results demonstrate that the PKM grants an effective separation of the medium and concentration effects, demonstrating that the PKM constitutes a powerful non-destructive tool to determine antioxidant concentrations in intact emulsions and to assess the effects of various factors affecting them.
Effect of Debittering with Different Solvents and Ultrasound on Carotenoids, Tocopherols, and Phenolics of Lupinus albus Seeds
Authors: Estivi Lorenzo , Fusi Davide , Brandolini Andrea , Hidalgo Alyssa
Published: December 2022

Lupin seeds represent a rich nutritional source of bioactive compounds, including antioxidant molecules such as carotenoids, tocopherols, and phenolics. However, before consumption, the lupin seeds must be debittered in order to remove their bitter and toxic alkaloids. This study analyzed the impact on the bioactive compounds of Lupinus albus seeds of a recent time- and water-saving debittering method, which employs alternative washing solutions (0.5% or 1% of either NaCl or citric acid), with or without the assistance of ultrasound. The results were compared with those of two control methods using water or a NaCl solution. The sonication, when it was significant, led to a large loss of bioactive compounds, which was most likely due to its extraction capability. The seeds that were debittered without ultrasound presented high concentrations of tocopherols (172.8–241.3 mg/kg DM), carotenoids (10.9–25.1 mg/kg DM), and soluble-free (106.9–361.1 mg/kg DM), soluble-conjugated (93.9–118.9 mg/kg DM), and insoluble-bound (59.2–156.7 mg/kg DM) phenolics. The soluble-free fraction showed the greatest loss after a prolonged treatment. Overall, debittering with citric acid or NaCl preserved the highest concentration of antioxidant compounds by shortening the treatment time, thus preventing extensive leaching.
Development and Application of Similar Materials for Foundation Pit Excavation Model Test of Metro Station
Authors: Zhang Zeyao , Gao Yang , Zheng Xinyu , Cao Jiarui , Chen Yong
Published: December 2022

Geomechanical model tests provide an intuitive and convenient method for observing physical phenomenon due to their easy implementation compared to in situ tests and prototype tests. The success of model tests depends heavily on the appropriate selection of model materials and proportions. Therefore, a new similar material is developed by utilizing the orthogonal experimental design method to conduct a series of proportioning tests. The new material is mixed with barite powder, iron ore powder, quartz sand, liquid paraffin, rosin, gypsum powder, and water. The physical and mechanical properties are studied through uniaxial compressive tests, Brazilian splitting tests, and direct shear tests. The influences of various raw material factors on the parameters of the similar material are systematically studied through range analysis. The results demonstrate that the mechanical parameters of similar materials have wide variation ranges; the adjustment range is 42.0–279.0 MPa for the elastic modulus, 0.37–5.37 MPa for the uniaxial compressive strength and 2.23–2.65 g/cm3 for the density. The new similar material has illustrated advantages in terms of performance stability, low price, and convenient production, which can simulate the similar relationship with different geomechanical model tests. The similar material is applied to a 3D geomechanical model test of the foundation pit excavation of Shenzhen metro station, which proves that the similar material can realistically reflect the change of earth pressure in the excavation process. With the deepening of excavation, the earth pressure curve shows significant fluctuations, and as the retaining structure is displaced, the parts with large earth pressure changes should be strengthened. The research methods and results can provide reference for further geological engineering research.
Grey Box Modeling of Gas Temperature for a High-Speed and High-Temperature Heat-Airflow Test System
Authors: Xue Yingfang , Cai Chaozhi , Xu Hui
Published: December 2022

Aiming at a problem that it is difficult for accurately obtaining the mathematical model of a gas temperature for a high-speed, high-temperature heat-airflow test system, a grey box modeling method combining first principle of modeling, recursive least squares identification with auxiliary variable and correlation analysis is proposed, and the precise mathematical model of gas temperature is established. Firstly, the preliminary mathematical model of gas temperature is obtained by using the first principle modeling method, and the dynamic behaviors of the system are analyzed; the prior knowledge of the system is obtained, and the parameters that need to be identified are pointed out. Secondly, the basic principles of recursive least square identification with auxiliary variables and correlation analysis are introduced, and the uncertain parameters of the gas temperature model are identified by using the introduced methods. Finally, the precise mathematical model of gas temperature is obtained by simulation and experimental research. The research results show that the mathematical model of gas temperature established by the grey box modeling method put forward in this article has satisfactory accuracy.
Landslide Susceptibility Modeling Using a Deep Random Neural Network
Authors: Huang Cheng , Li Fang , Wei Lei , Hu Xudong , Yang Yingdong
Published: December 2022

Developing landslide susceptibility modeling is essential for detecting landslide-prone areas. Recently, deep learning theories and methods have been investigated in landslide modeling. However, their generalization is hindered because of the limited size of landslide data. In the present study, a novel deep learning-based landslide susceptibility assessment method named deep random neural network (DRNN) is proposed. In DRNN, a random mechanism is constructed to drop network layers and nodes randomly during landslide modeling. We take the Lushui area (Southwest China) as the case and select 12 landslide conditioning factors to perform landslide modeling. The performance evaluation results show that our method achieves desirable generalization performance (Kappa = 0.829) and outperforms other network models such as the convolution neural network (Kappa = 0.767), deep feedforward neural network (Kappa = 0.731), and Adaboost-based artificial neural network (Kappa = 0.732). Moreover, the robustness test shows the advantage of our DRNN, which is insensitive to variations in training data size. Our method yields an accuracy higher than 85% when the training data size stands at only 10%. The results demonstrate the effectiveness of the proposed landslide modeling method in enhancing generalization. The proposed DRNN produces accurate results in terms of delineating landslide-prone areas and shows promising applications.
Thermally and Air Stable Perovskite Solar Cells with a Hole Transporting PTAA/NiO Bilayer
Authors: Lee You-Sun , Kwon Sung-Nam , Na Seok-In , Kim Dohyung , Kim Sang-Woo
Published: December 2022

Organic/inorganic halide perovskite materials have attracted substantial attention in solar cells, and they have achieved significant improvements in recent years. In perovskite solar cells (PSCs), the engineering of interfacial properties between multilayers is an important determinant of performance and stability. Here, we designed a bilayer structure of hole transporting layer by inserting poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA), which can improve the interfacial properties between the perovskite and the nickel oxide (NiO) hole transport layer in p-i-n planar PSCs. We observed that the hole transporting PTAA/NiO bilayer leads to higher performance by optimizing the energy level and accelerating the extraction of charges from the interface. The power conversion efficiency of the PSC was improved from 17.29% to 19.05% when the PTAA/NiO bilayer was introduced instead of the NiO monolayer. Ultimately, we confirmed that this interface engineering provides thermal and air stability of PSCs.
Experimental Facility to Study the Threshold Characteristics of Laser Action at the p-s-Transition of Noble Gas Atom upon Excitation by 6Li(n,α)3H Nuclear Reaction Products
Authors: Batyrbekov Erlan , Khasenov Mendykhan , Gordienko Yuriy , Samarkhanov Kuanysh , Kenzhina Inesh E. , Kotlyar Andrey , Miller Alexandr , Tskhe Valentin , Bochkov Vadim
Published: December 2022

Almost all experimental studies of the characteristics of nuclear-excited plasma formed by excitation of gaseous media with nuclear reactions products are conducted at pulsed nuclear reactors that differ in the composition and design of the core, the duration, flux and fluence of the neutron pulse, the impulse repetition frequency, the volume and configuration of the irradiation space. This paper presents a description of the experimental (methodical and hardware) base of the National Nuclear Center of RK (Kurchatov) to conduct experiments on studying the threshold characteristics of laser action at the p-s-transition of noble gas atoms upon 6Li(n,α)3H nuclear reaction products excitation in conditions of a pulsed nuclear IGR reactor. To conduct in-pile reactor experiments, a special experimental facility was developed and constructed. The experimental facility functionally includes: in-pile experimental device, a gas–vacuum system, information and measurement system consisting of a system for registering and controlling the temperature of the device housing, and a system for registering optical radiation. The paper also briefly describes the methodology of in-pile reactor experiments on the pulsed nuclear reactor.
2D Winograd CNN Chip for COVID-19 and Pneumonia Detection
Authors: Fan Yu-Cheng , Lin Kun-Yao , Tsai Yen-Hsun
Published: December 2022

In this paper, a two-dimensional Winograd CNN (Convolutional Neural Network) chip for COVID-19 and pneumonia detection is proposed. In light of the COVID-19 pandemic, many studies have led to a dramatic increase in the effects of the virus on the lungs. Some studies have also pointed out that the clinical application of deep learning in the medical field is also increasing, and it is also pointed out that the radiation impact of CT exposure is more serious than that of X-ray films and that CT exposure is not suitable for viral pneumonia. This study will analyze the results of X-rays trained using CNN architecture and convolutional using Winograd. This research will also set up a popular model architecture to realize four kinds of grayscale image prediction to verify the actual prediction effect on this data. The experimental data is mainly composed of chest X-rays of four different types of grayscales as input material. Among them, the research method of this experiment is to design the basic CNN operation structure of the chip and apply the Winograd calculus method to the convolutional operation. Finally, according to the TSMC 0.18 μm process, the actual chip is produced, and each step is verified to ensure the correctness of the circuit. The experimental results prove that the accuracy of our proposed method reaches 87.87%, and the precision reaches 88.48%. This proves that our proposed method has an excellent recognition rate.
Deep Learning-Based Image Recognition of Agricultural Pests
Authors: Xu Weixiao , Sun Lin , Zhen Cheng , Liu Bo , Yang Zhengyi , Yang Wenke
Published: December 2022

Pests and diseases are an inevitable problem in agricultural production, causing substantial economic losses yearly. The application of convolutional neural networks to the intelligent recognition of crop pest images has become increasingly popular due to advances in deep learning methods and the rise of large-scale datasets. However, the diversity and complexity of pest samples, the size of sample images, and the number of examples all directly affect the performance of convolutional neural networks. Therefore, we designed a new target-detection framework based on Cascade RCNN (Regions with CNN features), aiming to solve the problems of large image size, many pest types, and small and unbalanced numbers of samples in pest sample datasets. Specifically, this study performed data enhancement on the original samples to solve the problem of a small and unbalanced number of examples in the dataset and developed a sliding window cropping method, which could increase the perceptual field to learn sample features more accurately and in more detail without changing the original image size. Secondly, combining the attention mechanism with the FPN (Feature Pyramid Networks) layer enabled the model to learn sample features that were more important for the current task from both channel and space aspects. Compared with the current popular target-detection frameworks, the average precision value of our model (mAP@0.5) was 84.16%, the value of (mAP@0.5:0.95) was 65.23%, the precision was 67.79%, and the F1 score was 82.34%. The experiments showed that our model solved the problem of convolutional neural networks being challenging to use because of the wide variety of pest types, the large size of sample images, and the difficulty of identifying tiny pests.
Anomaly Detection Method in Railway Using Signal Processing and Deep Learning
Authors: Shim Jaeseok , Koo Jeongseo , Park Yongwoon , Kim Jaehoon
Published: December 2022

In this paper, anomaly detection of wheel flats based on signal processing and deep learning techniques is analyzed. Wheel flats mostly affect running stability and ride comfort. Currently, domestic railway companies visually inspect wheel flats one by one with their eyes after railway vehicles enter the railway depots for maintenance. Therefore, CBM (Condition-Based Maintenance) is required for wheel flats resolution. Anomaly detection for wheel flat signals of railway vehicles using Order analysis and STFT (Short Time Fourier Transform) is studied in this paper. In the case of railway vehicles, it is not easy to obtain actual failure data through running vehicles in a university laboratory due to safety and cost issues. Therefore, vibration-induced acceleration was obtained using a multibody dynamics simulation software, SIMPACK. This method is also proved in the other paper by rig tests. In addition, since the noise signal was not included in the simulated vibration, the noise signal obtained from the Seoul Metro Subway Line 7 vehicle was overlapped with the simulated one. Finally, to improve the performance of both detection rate and real-time of characteristics based on existing LeNet-5 architectures, spectrogram images transformed from time domain data were proceeded with the LeNet deep learning model modified with the pooling method and activation function. As a result, it is validated that the method using the spectrogram with a deep learning approach yields higher accuracy than the time domain data.
Casein Hydrolysate and Casein–Iron Chelate as Natural Bioactive Compounds for Yoghurt Fortification
Authors: Mandecka Anna , Dąbrowska Anna , Bobak Łukasz , Szołtysik Marek
Published: December 2022

The aim of the study was to apply the bioactive components casein hydrolysate and casein–iron chelate to yoghurt and to analyze their influence on product parameters. Casein was hydrolyzed with the non-commercial protease obtained from Yarrowia lipolytica yeast and subjected to chelating process with Fe2+ ions. Both preparations were introduced to yoghurt production as additives for elevation of dry matter by 2%. The control yoghurt was produced with the addition of skim milk powder. In the prepared experimental yoghurts, the content of dry matter [DM], protein, fat, as well as iron contents were determined. The conducted studies showed that in all analyzed yogurts, DM content was at a similar level, while the protein content was significantly (p < 0.05) higher in the variant containing 2% casein–iron chelate. In yoghurts with the casein–iron chelate as a bioactive compound, the iron concentration was about 61.5–123 times higher than in yoghurt with the addition of skim milk powder. It was shown that during storage the addition of casein–iron chelate positively influenced the number of analyzed microbe groups.
An Approach to Improve the Resolution of DLP 3D Printing by Parallel Mechanism
Authors: Huang Junjie , Zhang Bowen , Xiao Junfeng , Zhang Qinlei
Published: December 2022

For 3D printing based on Digital Light Processing (DLP) technology, the tradeoff of size and resolution remains challenging due to the limitations of the existing techniques. Therefore, we propose an approach to improve the feature resolution without sacrificing the part size. It is achieved by changing the projection distance and then adjusting the projection resolution and format, which is different from the previous printing principle of fixed resolution. To achieve this process, the tripteron 3-Degree-of-Freedom (3-DoF) parallel mechanism is innovatively applied to the DLP 3D printing structure, which simplifies the control process. Since the projection is fixed on the motion platform, the projection distance changes as the platform moves in space. Then the PLC-based program is developed according to the motion process, which successfully runs on the established prototype. Finally, the experiments are designed through the orthogonal method to optimize the molding process parameters. The effectiveness of the approach is verified by the feature forming comparison experiment. The results show that it can reduce the size of features by about 1.3 times through adjusting the projection resolution under the same size parts. Our method provides a new way for solving the contradiction, but more research needs to be done.