bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of the Ultrasound Operating Conditions for Extraction and Quantification of Fructooligosaccharides from Garlic (Allium sativum L.) via High-Performance Liquid Chromatography with Refractive Index Detector
Authors: Rahim Muhammad Abdul , Yasmin Adeela , Imran Muhammad , Nisa Mahr Un , Khalid Waseem , Esatbeyoglu Tuba , Korma Sameh A.
Published: September 2022

Dietary interventions have captured the attention of nutritionists due to their health-promoting aspects, in addition to medications. In this connection, supplementation of nutraceuticals is considered as a rational approach to alleviating various metabolic disorders. Among novel strategies, prebiotic-supplemented foods are an encouraging trend in addressing the issue. In the present investigation, prebiotic fructooligosaccharides (FOS) were extracted from garlic (Allium sativum L.) powder using ultrasound-assisted extraction (UAE). The response surface methodology (RSM) was used to optimize the independent sonication variables, i.e., extraction temperature (ET, 80, 90, and 100 °C), amplitude level (AL, 70, 80, and 90%) and sonication time (ST, 10, 15 and 20 min). The maximum FOS yield (6.23 ± 0.52%) was obtained at sonication conditions of ET (80 °C), AL (80%) and ST (10 min), while the minimum yield of FOS was obtained at high operating temperatures and time. The optimized FOS yield (7.19%) was obtained at ET (80 °C), AL (73%) and ST (15 min) after model validation. The influence of sonication parameters, i.e., ET, AL and ST, on FOS yield was evaluated by varying their coded levels from −1 to +1, respectively, for each independent variable. High-performance liquid chromatography with refractive index detector (HPLC-RID) detection and quantification indicated that sucrose was present in high amounts (2.06 ± 0.10 g/100 g) followed by fructose and glucose. Total FOS fractions which included nystose present in maximum concentration (526 ± 14.7 mg/100 g), followed by 1-kestose (428 ± 19.5 mg/100 g) and fructosylnystoses (195 ± 6.89 mg/100 g). Conclusively, garlic is a good source of potential prebiotics FOS and they can be extracted using optimized sonication parameters using ultrasound-assisted techniques with maximum yield percentage.
Antifungal Agents in Wood Protection—A Review
Authors: Woźniak Magdalena
Published: September 2022

The biodegradation of wood and wood products caused by fungi is recognized as one of the most significant problems worldwide. To extend the service life of wood products, wood is treated with preservatives, often with inorganic compounds or synthetic pesticides that have a negative impact on the environment. Therefore, the development of new, environmentally friendly wood preservatives is being carried out in research centers around the world. The search for natural, plant, or animal derivatives as well as obtaining synthetic compounds that will be safe for humans and do not pollute the environment, while at the same time present biological activity is crucial in terms of environmental protection. The review paper presents information in the literature on the substances and chemical compounds of natural origin (plant and animal derivatives) and synthetic compounds with a low environmental impact, showing antifungal properties, used in research on the ecological protection of wood. The review includes literature reports on the potential application of various antifungal agents including plant extracts, alkaloids, essential oils and their components, propolis extract, chitosan, ionic liquids, silicon compounds, and nanoparticles as well as their combinations.
Effects of Heat Treatment Duration on the Electrical Properties, Texture and Color of Polymerized Whey Protein
Authors: Bielska Paulina , Cais-Sokolińska Dorota , Dwiecki Krzysztof
Published: September 2022

In this research effects of heat treatment duration on the electrical properties (zeta potential and conductivity), texture and color of polymerized whey protein (PWP) were analyzed. Whey protein solutions were heated for 30 min to obtain single-heated polymerized whey protein (SPWP). After cooling to room temperature, the process was repeated to obtain double-heated polymerized whey protein (DPWP). The largest agglomeration was demonstrated after 10 min of single-heating (zeta potential recorded as −13.3 mV). Single-heating decreased conductivity by 68% and the next heating cycle by 54%. As the heating time increased, there was a significant increase in the firmness of the heated solutions. Zeta potential of the polymerized whey protein correlated with firmness, consistency, and index of viscosity, the latter of which was higher when the zeta potential (r = 0.544) and particle size (r = 0.567) increased. However, there was no correlation between zeta potential and color. This research has implications for future use of PWP in the dairy industry to improve the syneretic, textural, and sensory properties of dairy products.
Croargoids A–G, Eudesmane Sesquiterpenes from the Bark of Croton argyratus
Authors: Wu Min , Ji Kai-Long , Sun Peng , Lu Jian-Mei , Yue Jia-Rui , Cao Dong-Hua , Xiao Chun-Fen , Xu You-Kai
Published: September 2022

Seven new sesquiterpenes, named croargoid A–G (1–7), were isolated from the bark of Croton argyratus. Compounds 1–4 were the first examples of eudesmane sesquiterpene lactones containing C5-OH group. Compound 7 was a highly degraded eudesmane sesquiterpene possessing a rare eleven-carbon skeleton. Their structures with stereochemistry were mainly elucidated by NMR analyses in combination with MS and ECD data. Cytotoxicities and NO inhibitions of all isolates were evaluated and only compound 5 showed moderate NO inhibitory activity.
Sensitivity of Inner Spacer Thickness Variations for Sub-3-nm Node Silicon Nanosheet Field-Effect Transistors
Authors: Lee Sanguk , Jeong Jinsu , Yoon Jun-Sik , Lee Seunghwan , Lee Junjong , Lim Jaewan , Baek Rock-Hyun
Published: September 2022

The inner spacer thickness (TIS) variations in sub-3-nm, node 3-stacked, nanosheet field-effect transistors (NSFETs) were investigated using computer-aided design simulation technology. Inner spacer formation requires a high selectivity of SiGe to Si, which causes inevitable TIS variation (ΔTIS). The gate length (LG) depends on the TIS. Thus, the DC/AC performance is significantly affected by ΔTIS. Because the effects of ΔTIS on the performance depend on which inner spacer is varied, the sensitivities of the performance to the top, middle, and bottom (T, M, and B, respectively) ΔTIS should be studied separately. In addition, the source/drain (S/D) recess process variation that forms the parasitic bottom transistor (trpbt) should be considered with ΔTIS because the gate controllability over trpbt is significantly dependent on ΔTIS,B. If the S/D recess depth (TSD) variation cannot be completely eliminated, reducing ΔTIS,B is crucial for suppressing the effects of trpbt. It is noteworthy that reducing ΔTIS,B is the most important factor when the TSD variation occurs, whereas reducing ΔTIS,T and ΔTIS,M is crucial in the absence of TSD variation to minimize the DC performance variation. As the TIS increases, the gate capacitance (Cgg) decreases owing to the reduction in both parasitic and intrinsic capacitance, but the sensitivity of Cgg to each ΔTIS is almost the same. Therefore, the difference in performance sensitivity related to AC response is also strongly affected by the DC characteristics. In particular, since TSD of 5 nm increases the off-state current (Ioff) sensitivity to ΔTIS,B by a factor of 22.5 in NFETs, the ΔTIS,B below 1 nm is essential for further scaling and yield enhancement.
Synergetic Effect of Hybrid Conductive Additives for High-Capacity and Excellent Cyclability in Si Anodes
Authors: Yoo Byeong-Il , Kim Han-Min , Choi Min-Jae , Yoo Jung-Keun
Published: September 2022

Silicon is a promising anode material that can increase the theoretical capacity of lithium-ion batteries (LIBs). However, the volume expansion of silicon remains a challenge. In this study, we employed a novel combination of conductive additives to effectively suppress the volume expansion of Si during charging/discharging cycles. Rather than carbon black (CB), which is commonly used in SiO anodes, we introduced single-walled carbon nanotubes (SWCNTs) as a conductive additive. Owing to their high aspect ratio, CNTs enable effective connection of SiO particles, leading to stable electrochemical operation to prevent volume expansion. In addition, we explored a combination of CB and SWCNTs, with results showing a synergetic effect compared to a single-component of SWCNTs, as small-sized CB particles can enhance the interface contact between the conductive additive and SiO particles, whereas SWCNTs have limited contact points. With this hybrid conductive additive, we achieved a stable operation of full-cell LIBs for more than 200 cycles, with a retention rate of 91.1%, whereas conventional CB showed a 74.0% specific capacity retention rate.
Controlling CNT-Based Nanorotors via Hydroxyl Groups
Authors: Zhang Boyang , Li Rui , Peng Qing
Published: September 2022

Nanomotor systems have attracted extensive attention due to their applications in nanorobots and nanodevices. The control of their response is crucial but presents a great challenge. In this work, the rotating and braking processes of a carbon nanotube (CNT)-based rotor system have been studied using molecular dynamics simulation. The speed of response can be tuned by controlling the ratio of hydroxyl groups on the edges. The ratio of hydroxyl groups is positively correlated with the speed of response. The mechanism involved is that the strong hydrogen bonds formed between interfaces increase the interface interaction. Incremental increase in the hydroxyl group concentration causes more hydrogen bonds and thus strengthens the interconnection, resulting in the enhancement of the speed of response. The phonon density of states analysis reveals that the vibration of hydroxyl groups plays the key role in energy dissipation. Our results suggest a novel routine to remotely control the nanomotors by modulating the chemical environment, including tuning the hydroxyl groups concentration and pH chemistry.
Smart Modulators Based on Electric Field-Triggering of Surface Plasmon–Polariton for Active Plasmonics
Authors: Švanda Jan , Kalachyova Yevgeniya , Mareš David , Siegel Jakub , Slepička Petr , Kolská Zdeňka , Macháč Petr , Michna Štefan , Švorčík Václav , Lyutakov Oleksiy
Published: September 2022

Design and properties of a plasmonic modulator in situ tunable by electric field are presented. Our design comprises the creation of periodic surface pattern on the surface of an elastic polymer supported by a piezo–substrate by excimer laser irradiation and subsequent selective coverage by silver by tilted angle vacuum evaporation. The structure creation was confirmed by AFM and FIB-SEM techniques. An external electric field is used for fine control of the polymer pattern amplitude, which tends to decrease with increasing voltage. As a result, surface plasmon–polariton excitation is quenched, leading to the less pronounced structure of plasmon response. This quenching was checked using UV–Vis spectroscopy and SERS measurements, and confirmed by numerical simulation. All methods prove the proposed functionality of the structures enabling the creation smart plasmonic materials for a very broad range of advanced optical applications.
Deep Learning Models for Predicting Gas Adsorption Capacity of Nanomaterials
Authors: Guo Wenjing , Liu Jie , Dong Fan , Chen Ru , Das Jayanti , Ge Weigong , Xu Xiaoming , Hong Huixiao
Published: September 2022

Metal–organic frameworks (MOFs), a class of porous nanomaterials, have been widely used in gas adsorption-based applications due to their high porosities and chemical tunability. To facilitate the discovery of high-performance MOFs for different applications, a variety of machine learning models have been developed to predict the gas adsorption capacities of MOFs. Most of the predictive models are developed using traditional machine learning algorithms. However, the continuously increasing sizes of MOF datasets and the complicated relationships between MOFs and their gas adsorption capacities make deep learning a suitable candidate to handle such big data with increased computational power and accuracy. In this study, we developed models for predicting gas adsorption capacities of MOFs using two deep learning algorithms, multilayer perceptron (MLP) and long short-term memory (LSTM) networks, with a hypothetical set of about 130,000 structures of MOFs with methane and carbon dioxide adsorption data at different pressures. The models were evaluated using 10 iterations of 10-fold cross validations and 100 holdout validations. The MLP and LSTM models performed similarly with high prediction accuracy. The models for predicting gas adsorption at a higher pressure outperformed the models for predicting gas adsorption at a lower pressure. The deep learning models are more accurate than the random forest models reported in the literature, especially for predicting gas adsorption capacities at low pressures. Our results demonstrated that deep learning algorithms have a great potential to generate models that can accurately predict the gas adsorption capacities of MOFs.
Biosynthesis of ZnONP Using Chamaecostus cuspidatus and Their Evolution of Anticancer Property in MCF-7 and A549 Cell Lines
Authors: Balaji Menaka Priya , Govindasamy Rajakumar , Alharbi Naiyf S. , Kadaikunnan Shine , Thiruvengadam Muthu , Baskar Venkidasamy , Devi Rajeswari Vijayarangan
Published: September 2022

The ZnO nanoparticle synthesis using the leaf part of Chamaecostus cuspidatus was characterized using UV–Vis spectrophotometry, IR, XRD, DLS, FESEM, EDX, TEM, AFM and XPS. The MTT assay was used to examine the cytotoxicity activity against lung epithelial and breast cell lines, and the IC50 value was determined. The presence of ZnO nanoparticles, which range in size from 200 to 800 nm, was confirmed by the absorption peak at 350 nm. The median particle size was 145.1 nm, and the ζ -the potential was −19.45 mV, showing that ZnONP is stable. Zinc, carbon, and oxygen contribute to the elemental composition of ZnONP, as determined by EDX analysis. MTT assay was used to investigate in vitro cytotoxicity in MCF-7 and A549 cell lines. The cytotoxicity activity IC50 value was determined to be 30 μg/mL for the A549 cell line and 37 μg/mL for the MCF-7 cell line.
First Record of Alternaria pogostemonis: A Novel Species Causing Leaf Spots in Pogostemon cablin
Authors: Luo Mei , Zhao Minping , Huang Yinghua , Liu Jiawei , Huang Qiurong , Shu Yongxin , Dong Zhangyong
Published: September 2022

Pogostemon cablin (Lamiaceae) is a component of traditional medicines in Southern China. The identification of P. cablin pathogens is essential for the production and development of this industry. During 2019–2020, a leaf spot on P. cablin was observed in Zhanjiang, Guangdong Province. The pathogen of the leaf spot was isolated and identified using morphological and phylogenetic methods. Phylogenetic analysis was performed using the internal transcribed spacer (ITS) region, glyceraldehyde-3-phosphate dehydrogenase (gapdh), RNA polymerase II (rpb2), translation extension factor 1-alpha (tef1), and Alternaria major allergen 1 (Alt-a1) genes. Based on phylogenetic and morphological studies, this was confirmed to be a novel species of Alternaria pogostemonis, with description and illustrations presented. The pathogenicity test of A. pogostemon was verified by Koch’s postulates as causing leaf spot disease. This is the first report of leaf spot disease in P. cablin caused by the Alternaria species. This study contributes to the knowledge of P. cablin leaf spot diseases.
Diversity of Rickettsiales in Rhipicephalus microplus Ticks Collected in Domestic Ruminants in Guizhou Province, China
Authors: Lu Miao , Meng Chao , Gao Xiang , Sun Yue , Zhang Jun , Tang Guangpeng , Li Yilin , Li Mengyao , Zhou Guangyi , Wang Wen , Li Kun
Published: September 2022

Rhipicephalus microplus ticks are vectors for multiple pathogens infecting animals and humans. Although the medical importance of R. microplus has been well-recognized and studied in most areas of China, the occurrence of tick-borne Rickettsiales has seldom been investigated in Guizhou Province, Southwest China. In this study, we collected 276 R. microplus ticks from cattle (209 ticks) and goats (67 ticks) in three locations of Guizhou Province. The Rickettsia, Anaplasma, and Ehrlichia were detected by targeting the 16S rRNA gene and were further characterized by amplifying the key genes. One Rickettsia (Ca. Rickettsia jingxinensis), three Ehrlichia (E. canis, E. minasensis, Ehrlichia sp.), and four Anaplasma (A. capra, A. ovis, A. marginale, Ca. Anaplasma boleense) species were detected, and their gltA and groEL genes were recovered. Candidatus Rickettsia jingxinensis, a spotted fever group of Rickettsia, was detected in a high proportion of the tested ticks (88.89%, 100%, and 100% in ticks from the three locations, respectively), suggesting the possibility that animals may be exposed to this type of Rickettsia. All the 16S, gltA, groEL, and ompA sequences of these strains are 100% identical to strains reported in Ngawa, Sichuan Province. E. minasensis, A. marginale, and Candidatus Anaplasma boleense are known to infect livestock such as cattle. The potential effects on local husbandry should be considered. Notably, E. canis, A. ovis, and A. capra have been reported to infect humans. The relatively high positive rates in Qianxinan (20.99%, 9.88%, and 4.94%, respectively) may indicate the potential risk to local populations. Furthermore, the genetic analysis indicated that the E. minasensis strains in this study may represent a variant or recombinant. Our results indicated the extensive diversity of Rickettsiales in R. microplus ticks from Guizhou Province. The possible occurrence of rickettsiosis, ehrlichiosis, and anaplasmosis in humans and domestic animals in this area should be further considered and investigated.
Evaluation of Nitrogen Fertilizer Fates and Related Environmental Risks for Main Cereals in China’s Croplands from 2004 to 2018
Authors: Song Daping , Jiang Rong , Fan Daijia , Zou Guoyuan , Du Lianfeng , Wei Dan , Guo Xuan , He Wentian
Published: September 2022

Assessment of the nitrogen (N) inputs and outputs in croplands would help effectively manage the distribution of N to improve crop growth and environmental sustainability. To better understand the N flow of the main cereal systems in China, soil N balance, N use efficiency (NUE), N losses and the potential environmental impacts of maize, wheat and rice cropping systems were estimated at the regional and national scales from 2004 to 2018. Nationally, the soil N balance (N inputs—N outputs) of maize, wheat, single rice and double rice decreased by 28.8%,13.3%, 30.8% and 34.1% from 2004–2008 to 2014–2018, equivalent to an average of 33.3 to 23.7 kg N ha−1, 82.4 to 71.4 kg N ha−1, 93.6 to 64.8 kg N ha−1 and 51.8 to 34.1 kg N ha−1, respectively. The highest soil N balance were observed in Southeast (SE) region for maize and double rice, North central (NC) region for wheat single rice and Northwest region for wheat, whereas Northeast (NE) region had the lowest N balance for all crops. The NUE increased from 49.8%, 41.2%, 49.7% and 53.7% in 2004–2008 to 54.8%, 45.9%, 55.5% and 56.5% in 2014–2018 for maize, wheat, single rice and double rice, respectively. The fertilizer N losses (i.e., N2O emission, NO emission, N2 emission, NH3 volatilization, N leaching and N runoff) were estimated as 43.7%, 38.3%, 40.2% and 36.6% of the total N inputs for maize, wheat, single rice and double rice, respectively in 2014–2018. Additionally, the highest global warming potential and acidification effects were found in NE and NC regions for maize, NC region for wheat, the middle and lower reaches of Yangtze River for single rice and SE region for double rice, respectively. The highest risk of water contamination by N leaching and surface runoff was observed in NC region for all crops mainly due to high N fertilizer input. Furthermore, the dynamics of N balance for all crops were closely tied with grain yields, except for single rice, the N balance of which was mainly correlated with N fertilizer input. Our results could help researchers and policy makers effectively establish optimized fertilization strategies and adjust the regional allocation of grain cropping areas in response to environmental risks and climate change caused by food crop cultivation in China.
Green Synthesis of Silver Nanoparticles from Diospyros villosa Extracts and Evaluation of Antioxidant, Antimicrobial and Anti-Quorum Sensing Potential
Authors: Adu Oluwatosin Temilade , Mohamed Farzana , Naidoo Yougasphree , Adu Temitope Samson , Chenia Hafizah , Dewir Yaser Hassan , Rihan Hail
Published: September 2022

The biosynthesis of silver nanoparticles (AgNPs) from Diospyros villosa leaves and stem bark extracts is described. The stem bark AgNPs of D. villosa synthesized at 80 °C (S80) showed good scavenging activity with a lower IC50 value of 8.75 µg·mL−1 compared to ascorbic acid (9.58 µg·mL−1). The total phenol content of the S80 AgNPs was measured and found to be 10.22 ± 0.14 mg.g−1 gallic acid equivalence (GAE). Bacterial growth inhibition (% GI) and violacein inhibition (% VI) of 10.08% and 58.83%, respectively, was observed against C.subtsugae CV017 with leaf AgNPs synthesized at 80 °C (L80) at 80 μg·mL−1. Stem bark AgNPs synthesized at room temperature (SRT) also indicated % GI of 13.83% and % VI of 65.97% against C. subtsugae CV017 at 160 μg·mL−1. Leaf AgNPs of D. villosa synthesized at room temperature (LRT), showed % GI of 29.07% and % VI of 56.53%, respectively, against C. violaceum ATCC 12472 at 320 μg·mL−1. The L80 and SRT at 160 μg·mL−1 and LRT at 320 μg·mL−1 may be considered as potential QS inhibitors following their activity against C. subtsugae CV017 and C. violaceum ATCC 12472, respectively. Therefore, D. villosa represents a potential source of antioxidants as well as an anti-quorum sensing therapeutic candidate for the control of Gram-negative bacterial infections.
Garcinia cambogia Phenolics as Potent Anti-COVID-19 Agents: Phytochemical Profiling, Biological Activities, and Molecular Docking
Authors: Aati Hanan Y. , Ismail Ahmed , Rateb Mostafa E. , AboulMagd Asmaa M. , Hassan Hossam M. , Hetta Mona H.
Published: September 2022

COVID-19 is a disease caused by the coronavirus SARS-CoV-2 and became a pandemic in a critically short time. Phenolic secondary metabolites attracted much attention from the pharmaceutical industries for their easily accessible natural sources and proven antiviral activity. In our mission, a metabolomics study of the Garcinia cambogia Roxb. fruit rind was performed using LC-HRESIMS to investigate its chemical profile, especially the polar aspects, followed by a detailed phytochemical analysis, which led to the isolation of eight known compounds. Using spectrometric techniques, the isolated compounds were identified as quercetin, amentoflavone, vitexin, rutin, naringin, catechin, p-coumaric, and gallic acids. The antiviral activities of the isolated compounds were investigated using two assays; the 3CL-Mpro enzyme showed that naringin had a potent effect with IC50 16.62 μg/mL, followed by catechin and gallic acid (IC50 26.2, 30.35 μg/mL, respectively), while the direct antiviral inhibition effect of naringin confirmed the potency with an EC50 of 0.0169 μM. To show the molecular interaction, in situ molecular docking was carried out using a COVID-19 protease enzyme. Both biological effects and docking studies showed the hydrophobic interactions with Gln 189 or Glu 166, per the predicated binding pose of the isolated naringin.
The Anticancer Potential of Plant-Derived Nutraceuticals via the Modulation of Gene Expression
Authors: Vrânceanu Maria , Galimberti Damiano , Banc Roxana , Dragoş Ovidiu , Cozma-Petruţ Anamaria , Hegheş Simona-Codruţa , Voştinaru Oliviu , Cuciureanu Magdalena , Stroia Carmina Mariana , Miere Doina , Filip Lorena
Published: September 2022

Current studies show that approximately one-third of all cancer-related deaths are linked to diet and several cancer forms are preventable with balanced nutrition, due to dietary compounds being able to reverse epigenetic abnormalities. An appropriate diet in cancer patients can lead to changes in gene expression and enhance the efficacy of therapy. It has been demonstrated that nutraceuticals can act as powerful antioxidants at the cellular level as well as anticarcinogenic agents. This review is focused on the best studies on worldwide-available plant-derived nutraceuticals: curcumin, resveratrol, sulforaphane, indole-3-carbinol, quercetin, astaxanthin, epigallocatechin-3-gallate, and lycopene. These compounds have an enhanced effect on epigenetic changes such as histone modification via HDAC (histone deacetylase), HAT (histone acetyltransferase) inhibition, DNMT (DNA methyltransferase) inhibition, and non-coding RNA expression. All of these nutraceuticals are reported to positively modulate the epigenome, reducing cancer incidence. Furthermore, the current review addresses the issue of the low bioavailability of nutraceuticals and how to overcome the drawbacks related to their oral administration. Understanding the mechanisms by which nutraceuticals influence gene expression will allow their incorporation into an “epigenetic diet” that could be further capitalized on in the therapy of cancer.
Control of Grain Shape and Size in Rice by Two Functional Alleles of OsPUB3 in Varied Genetic Background
Authors: Li Zhu-Hao , Wang Shi-Lin , Zhu Yu-Jun , Fan Ye-Yang , Huang De-Run , Zhu Ai-Ke , Zhuang Jie-Yun , Liang Yan , Zhang Zhen-Hua
Published: September 2022

Grain shape and size are key determinants of grain appearance quality and yield in rice. In our previous study, a grain shape QTL, qGS1-35.2, was fine-mapped using near-isogenic lines (NILs) derived from a cross between Zhenshan 97 (ZS97) and Milyang 46 (MY46). One annotated gene, OsPUB3, was found to be the most likely candidate gene. Here, knockout and overexpression experiments were performed to investigate the effects of OsPUB3 on grain shape and size. Four traits were tested, including grain length, grain width, grain weight, and the ratio of grain length to width. Knockout of OsPUB3 in NILZS97, NILMY46, and another rice cultivar carrying the OsPUB3MY46 allele all caused decreases in grain width and weight and increases in the ratio of grain length to width. Results also showed that the magnitude of the mutational effects varied depending on the target allele and the genetic background. Moreover, it was found that NILZS97 and NILMY46 carried different functional alleles of OsPUB3, causing differences in grain shape rather than grain weight. In the overexpression experiment, significant differences between transgenic-positive and transgenic-negative plants were detected in all four traits. These results indicate that OsPUB3 regulates grain shape and size through a complex mechanism and is a good target for deciphering the regulatory network of grain shape. This gene could be used to improve grain appearance quality through molecular breeding as well.
Phenology and Floral Biology of Diospyros sericea A. DC. (Ebenaceae): Inconstant Males May Be behind an Enigma of Dioecy
Authors: Ramaldes Bárbara , Santos Renata , Rech André Rodrigo , Soares Michellia
Published: September 2022

Diospyros sericea is a tree/shrub species considered dioecious and broadly distributed in Brazil. Despite its importance for niche composition in a range of ecosystems, there is little knowledge about this species, and so far no study has analyzed its sexual system. We aimed to investigate dioecy expression in D. sericea through sexual dimorphisms in its phenology and floral biology. We analyzed the phenological events over a year and studied floral biology traits (morphology, flower development, floral resource, floral attractants supply, viability of pollen, and stigma receptivity) in both male and female plants. D. sericea presents typical features of dioecious plants like well-established primary and secondary dimorphisms that contribute to its reproductive success. However, we also identified fruit development in what should be structurally male individuals. We suggest that the evolutionary pathway leading to the observed phenomenon may be the existence of subdioecious populations with “inconstant males”. Although our data prevented us from making further assumptions about the origin of this trait, the study contributes to future analyses towards unraveling the enigma of dioecy not only in D. sericea but in other Diospyros species.
Inhibitory Effects of Grewia tomentosa Juss. on IgE-Mediated Allergic Reaction and DNCB-Induced Atopic Dermatitis
Authors: Lee Hwa Pyoung , Choi Wooram , Kwon Ki Woong , You Long , Rahmawati Laily , Luong Van Dung , Kim Wonhee , Lee Byoung-Hee , Lee Sarah , Kim Ji Hye , Cho Jae Youl
Published: September 2022

Grewia tomentosa Juss. is a deciduous shrub that mainly grows in Asia. Despite studies of other Grewia species for treatment of various diseases, Grewia tomentosa Juss. has not been studied as a medicinal herb. This study evaluates the anti-allergic and anti-topic dermatitis activity of Grewia tomentosa Juss. ethanol extract (Gt-EE). The results show that Gt-EE suppressed IgE–antigen-induced β-hexosaminidase release. The mRNA expression of IL-1β, IL-4, IL-5, IL-6, IL-13, TNF-α, MCP-1, and TSLP, which are involved in allergic responses, was inhibited by Gt-EE in IgE-stimulated RBL-2H3 cells. In addition, the phosphorylation of Syk, PLCγ1, PKCδ, PI3K, AKT, NF-κB p65, NF-κB p50, p38, JNK, and ERK1/2 was decreased by Gt-EE in these cells. Gt-EE also showed anti-inflammatory effects in in vivo mouse models. In passive cutaneous anaphylaxis (PCA), a commonly used mouse model, Gt-EE decreased the allergic response, infiltration of mast cells, and mRNA level of IL-4. Furthermore, Gt-EE ameliorated symptoms of DNCB-induced atopic dermatitis (AD). In DNCB-induced AD, Gt-EE suppressed the increase in mast cells, serum IgE level, expression of allergic mediators (IL-1β, IL-4, IL-5, IL-6, TNF-α), and phosphorylation of proteins (IκBα, NF-κB p65, NF-κB p50, p38, JNK, and ERK1/2) implicated in allergic reactions
Emerging Food Packaging Applications of Cellulose Nanocomposites: A Review
Authors: Li Jingwen , Zhang Feifan , Zhong Yaqi , Zhao Yadong , Gao Pingping , Tian Fang , Zhang Xianhui , Zhou Rusen , Cullen Patrick
Published: September 2022

Cellulose is the most abundant biopolymer on Earth, which is synthesized by plants, bacteria, and animals, with source-dependent properties. Cellulose containing β-1,4-linked D-glucoses further assembles into hierarchical structures in microfibrils, which can be processed to nanocellulose with length or width in the nanoscale after a variety of pretreatments including enzymatic hydrolysis, TEMPO-oxidation, and carboxymethylation. Nanocellulose can be mainly categorized into cellulose nanocrystal (CNC) produced by acid hydrolysis, cellulose nanofibrils (CNF) prepared by refining, homogenization, microfluidization, sonification, ball milling, and the aqueous counter collision (ACC) method, and bacterial cellulose (BC) biosynthesized by the Acetobacter species. Due to nontoxicity, good biodegradability and biocompatibility, high aspect ratio, low thermal expansion coefficient, excellent mechanical strength, and unique optical properties, nanocellulose is utilized to develop various cellulose nanocomposites through solution casting, Layer-by-Layer (LBL) assembly, extrusion, coating, gel-forming, spray drying, electrostatic spinning, adsorption, nanoemulsion, and other techniques, and has been widely used as food packaging material with excellent barrier and mechanical properties, antibacterial activity, and stimuli-responsive performance to improve the food quality and shelf life. Under the driving force of the increasing green food packaging market, nanocellulose production has gradually developed from lab-scale to pilot- or even industrial-scale, mainly in Europe, Africa, and Asia, though developing cost-effective preparation techniques and precisely tuning the physicochemical properties are key to the commercialization. We expect this review to summarise the recent literature in the nanocellulose-based food packaging field and provide the readers with the state-of-the-art of this research area.
Prediction Models for Railway Track Geometry Degradation Using Machine Learning Methods: A Review
Authors: Liao Yingying , Han Lei , Wang Haoyu , Zhang Hougui
Published: September 2022

Keeping railway tracks in good operational condition is one of the most important tasks for railway owners. As a result, railway companies have to conduct track inspections periodically, which is costly and time-consuming. Due to the rapid development in computer science, many prediction models using machine learning methods have been developed. It is possible to discover the degradation pattern and develop accurate prediction models. The paper reviews the existing prediction methods for railway track degradation, including traditional methods and prediction methods based on machine learning methods, including probabilistic methods, Artificial Neural Network (ANN), Support Vector Machine (SVM), and Grey Model (GM). The advantages, shortage, and applicability of methods are discussed, and recommendations for further research are provided.
Estimation of Humidity Variation and Electric Resistivity in Hardened Concrete by Means of a Stainless Steel Voltammetric Sensor
Authors: Martínez Ibernón Ana , Lliso Ferrando Josep , Gasch Isabel , Valcuende Manuel
Published: September 2022

Reinforced concrete structures’ (RCSs) ageing and early deterioration are some of the main challenges faced by the building sector today, and steel bar corrosion is one of the main problems. In this phenomenon, water and concrete’s electric resistivity play a fundamental role. Therefore, developing sensor systems capable of estimating any variations in these parameters in real time and remotely would represent considerable progress in sustainably maintaining RCSs. Many types of sensors capable of estimating humidity variation and electrical resistivity in concrete currently exist, but the variability of these sensors’ sensitivity can be extreme depending on several factors; for example, temperature or presence of ions and their incorporation into smart monitoring systems, which is difficult. As an alternative to today’s sensors, this study centered on developing two estimation models by means of the response of a novel voltammetric stainless steel (SS) sensor. The estimation models were one of humidity variation and another of concrete’s electric resistivity. These models were calibrated, fitted and validated. In the validation, both these models explained a percentage of variance over 80%.
Digital Twin-Driven Rear Axle Assembly Torque Prediction and Online Control
Authors: Liu Lilan , Xu Zifeng , Gao Chaojia , Zhang Tingting , Gao Zenggui
Published: September 2022

During the assembly process of the rear axle, the assembly quality and assembly efficiency decrease due to the accumulation errors of rear axle assembly torque. To deal with the problem, we proposed a rear axle assembly torque online control method based on digital twin. First, the gray wolf-based optimization variational modal decomposition and long short-term memory network (GWO-VMD-LSTM) algorithm was raised to predict the assembly torque of the rear axle, which solves the shortcomings of unpredictable non-stationarity and nonlinear assembly torque, and the prediction accuracy reaches 99.49% according to the experimental results. Next, the evaluation indexes of support vector machine (SVM), recurrent neural network (RNN), LSTM, and SVM, RNN, and LSTM based on gray wolf optimized variational modal decomposition (GWO-VMD) were compared, and the performance of the GWO-VMD-LSTM is the best. For the purpose of solving the insufficient information interaction capability problem of the assembly line, we developed a digital twin system for the rear axle assembly line to realize the visualization and monitoring of the assembly process. Finally, the assembly torque prediction model is coupled with the digital twin system to realize real-time prediction and online control of assembly torque, and the experimental testing manifests that the response time of the system is about 1 s. Consequently, the digital twin-based rear axle assembly torque prediction and online control method can significantly improve the assembly quality and assembly efficiency, which is of great significance to promote the construction of intelligent production line.
A Needs Learning Algorithm Applied to Stable Gait Generation of Quadruped Robot
Authors: Zhang Hanzhong , Yin Jibin , Wang Haoyang
Published: September 2022

Based on Maslow’s hierarchy of needs theory, we have proposed a novel machine learning algorithm that combines factors of the environment and its own needs to make decisions for different states of an agent. This means it can be applied to the gait generation of a quadruped robot, which needs to make demand decisions. To evaluate the design, we created an experimental task in order to compare the needs learning algorithm with a reinforcement learning algorithm, which was also derived from psychological motivation theory. It was found that the needs learning algorithm outperformed the reinforcement learning in tasks that involved making decisions between different levels of needs. Finally, we applied the needs learning algorithm to the problem of stable gait generation of quadruped robot, and it had achieved good results in simulation and real robot.
Laser Remote Sensing of Lake Kinneret by Compact Fluorescence LiDAR
Authors: Pershin Sergey M. , Katsnelson Boris G. , Grishin Mikhail Ya. , Lednev Vasily N. , Zavozin Vladimir A. , Ostrovsky Ilia
Published: September 2022

Harmful algal blooms in freshwater reservoirs became a steady phenomenon in recent decades, so instruments for monitoring water quality in real time are of high importance. Modern satellite remote sensing is a powerful technique for mapping large areas but cannot provide depth-resolved data on algal concentrations. As an alternative to satellite techniques, laser remote sensing is a perspective technique for depth-resolved studies of fresh or seawater. Recent progress in lasers and electronics makes it possible to construct compact and lightweight LiDARs (Light Detection and Ranging) that can be installed on small boats or drones. LiDAR sensing is an established technique; however, it is more common in studies of seas rather than freshwater reservoirs. In this study, we present an experimental verification of a compact LiDAR as an instrument for the shipborne depth profiling of chlorophyll concentration across the freshwater Lake Kinneret (Israel). Chlorophyll depth profiles of 3 m with a 1.5 m resolution were measured in situ, under sunlight conditions. A good correlation (R2 = 0.89) has been established between LiDAR signals and commercial algae profiler data. A non-monotonic algae depth distribution was observed along the boat route during daytime (Tiberias city–Jordan River mouth–Tiberias city). The impact of high algal concentration on water temperature laser remote sensing has been studied in detail to estimate the LiDAR capability of in situ simultaneous measurements of temperature and chlorophyll concentration.
Estimating Time of Coordinate Measurements Based on the Adopted Measurement Strategy
Authors: Magdziak Marek
Published: September 2022

This article concerns coordinate metrology and contact coordinate measurements which are conducted using a coordinate measuring machine. The paper presents the results of experimental investigations, based on which a model to calculate the time needed to conduct coordinate measurements to determine the flatness deviation of a selected surface of a machined product was developed. The time taken and the accuracy of the coordinate measurements influence the effectiveness of coordinate measurements of geometrical quantities of products and the productivity of the entire manufacturing process. Therefore, when planning a strategy for the coordinate measurement process, apart from considering the measurement uncertainty, the duration of individual measurement tasks should also be taken into account. A coordinate measurement time model was developed by use of response surface methodology (RSM). Experimental research was carried out using an ACCURA II coordinate measuring machine equipped with a VAST XXT measuring probe and cooperating with Calypso inspection software. The coordinate measurement time model which was developed was implemented in the selected metrology software of the coordinate measuring machine. The purpose of the implementation was to enable application of the mathematical model created into industrial practice.
Design and Characterisation of an Optical Fibre Dosimeter Based on Silica Optical Fibre and Scintillation Crystal
Authors: Jelinek Michal , Cip Ondrej , Lazar Josef , Mikel Bretislav
Published: September 2022

In nuclear power plants, particle accelerators, and other nuclear facilities, measuring the level of ionising gamma radiation is critical for the safety and management of the operation and the environment’s protection. However, in many cases, it is impossible to monitor ionising radiation directly at the required location continuously. This is typically either due to the lack of space to accommodate the entire dosimeter or in environments with high ionising radiation activity, electromagnetic radiation, and temperature, which significantly shorten electronics’ lifetime. To allow for radiation measurement in such scenarios, we designed a fibre optic dosimeter that introduces an optical fibre link to deliver the scintillation radiation between the ionising radiation sensor and the detectors. The sensors can thus be placed in space-constrained and electronically hostile locations. We used silica optical fibres that withstand high radiation doses, high temperatures, and electromagnetic interference. We use a single photon counter and a photomultiplier to detect the transmitted scintillation radiation. We have shown that selected optical fibres, combined with different scintillation materials, are suitable for measuring gamma radiation levels in hundreds of kBq. We present the architecture of the dosimeter and its experimental characterisation with several combinations of optical fibres, detectors, and scintillation crystals.
Potential Benefit of Structural Health Monitoring System on Civil Jet Aircraft
Authors: Cusati Vincenzo , Corcione Salvatore , Memmolo Vittorio
Published: September 2022

Structural health monitoring represents an interesting enabling technology towards increasing aviation safety and reducing operating costs by unlocking novel maintenance approaches and procedures. However, the benefits of such a technology are limited to maintenance costs reductions by cutting or even eliminating some maintenance scheduled checks. The key limitation to move a step further in exploiting structural health monitoring technology is represented by the regulation imposed in sizing aircraft composite structures. A safety margin of 2.0 is usually applied to estimate the ultimate loading that composite structures must withstand. This limitation is imposed since physical nondestructive inspection of composite structures is really challenging or even impossible in some cases. However, a structural health monitoring system represents a viable way for a real time check for the health status of a composite structure. Thus, the introduction of structural health monitoring should help into reducing the stringent safety margin imposed by aviation regulation for a safe design of composite structures. By assuming a safety margin reduction from 2.0 to 1.75 thanks to the installation of permanently attached sensors for structural health diagnostics, this paper assesses the potential fuel savings and direct operating costs through a multidisciplinary analysis on a A220-like aircraft. According to the foreseen level of technology, addressed through the number of sensors per square meter, a DOC saving from 2% up to 5% is achievable preserving, at the same time, all the key aircraft performance.
A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators
Authors: Loredo Antonio , Maya Mauro , González Alejandro , Cardenas Antonio , Gonzalez-Galvan Emilio , Piovesan Davide
Published: September 2022

It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a robot’s kinematics and the target’s trajectory. Tracking precision heavily relies on kinematics to infer the trajectory. Control implementation in parallel robots is especially difficult due to their complex kinematics. Vision-based controllers are robust to uncertainties of a robot’s kinematic model since they can correct end-point trajectories as error estimates become available. Robustness is guaranteed by taking the vision sensor’s model into account when designing the control law. All camera space manipulation (CSM) models in the literature are position-based, where the mapping between the end effector position in the Cartesian space and sensor space is established. Such models are not appropriate for tracking moving targets because the relationship between the target and the end effector is a fixed point. The present work builds upon the literature by presenting a novel CSM velocity-based control that establishes a relationship between a movable trajectory and the end effector position. Its efficacy is shown on a Delta-type parallel robot. Three types of experiments were performed: (a) static tracking (average error of 1.09 mm); (b) constant speed linear trajectory tracking—speeds of 7, 9.5, and 12 cm/s—(tracking errors of 8.89, 11.76, and 18.65 mm, respectively); (c) freehand trajectory tracking (max tracking errors of 11.79 mm during motion and max static positioning errors of 1.44 mm once the object stopped). The resulting control cycle time was 48 ms. The results obtained show a reduction in the tracking errors for this robot with respect to previously published control strategies.
Latency-Aware Task Scheduling for IoT Applications Based on Artificial Intelligence with Partitioning in Small-Scale Fog Computing Environments
Authors: Lim JongBeom
Published: September 2022

The Internet of Things applications have become popular because of their lightweight nature and usefulness, which require low latency and response time. Hence, Internet of Things applications are deployed with the fog management layer (software) in closely located edge servers (hardware) as per the requirements. Due to their lightweight properties, Internet of Things applications do not consume many computing resources. Therefore, it is common that a small-scale data center can accommodate thousands of Internet of Things applications. However, in small-scale fog computing environments, task scheduling of applications is limited to offering low latency and response times. In this paper, we propose a latency-aware task scheduling method for Internet of Things applications based on artificial intelligence in small-scale fog computing environments. The core concept of the proposed task scheduling is to use artificial neural networks with partitioning capabilities. With the partitioning technique for artificial neural networks, multiple edge servers are able to learn and calculate hyperparameters in parallel, which reduces scheduling times and service level objectives. Performance evaluation with state-of-the-art studies shows the effectiveness and efficiency of the proposed task scheduling in small-scale fog computing environments while introducing negligible energy consumption.