bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Study of Suppressing the Thermoacoustic Instabilities in a Rijke Tube Using Microsecond Discharge Plasma
Authors: Deng Jiangge , Li Ting , Wang Jinkui , Gao Chicheng
Published: December 2022

Thermoacoustic instabilities occur when heat release is coupled with pressure fluctuation, which may cause performance degradation of the combustor and serious structural damage. This study focued on an active control method using discharge plasma and showed experimentally that discharge plasma can make a difference in controlling the thermoacoustic instabilities in a Rijke tube. A vertically placed Rijke tube thermoacoustic system using induction heating tungsten mesh as a heat source was built. The results show that the high repetition rate discharge can effectively suppress the thermoacoustic oscillations in the Rijke tube and that they will not re-occur for some time. Additionally, their effectiveness depended more on average power than energy per pulse. Combining the collected pressure, schlieren data, and theoretical analysis, it can be suggested that the plasma discharge could heat the inlet airflow, which could influence the heat exchange and then could break thermo-acoustic coupling, and its high-frequency pressure perturbation might increase the dissipation of the energy of sound.
Investigation of Improvement Design on Aileron Surface Flow State of High Lift Configuration in BWB
Authors: Niu Xiaotian , Li Jie , Zhang Heng , Yang Zhao
Published: December 2022

The aileron is one of the most important tools for adjusting the roll attitude of the aircraft, but the surface flow state of the aileron is likely to be affected by high-lift devices. In this paper, by using computational fluid dynamics (CFD) simulations and wind tunnel tests, the Krueger flap effects on the surface flow state of ailerons in a typical blended wing body civil aircraft were investigated. In order to increase the lift, deflecting the Krueger flap makes the flow separation occur on the aileron surface of BWB civil aircraft. This way of the surface stall that the flow separation in the aileron zone first appears at the wing tip rather than at the wing root is unreasonable for civil aircraft. For the above problem, a sensitivity analysis of the design parameters of the Krueger flaps was carried out. The results indicate that the angle of the outboard Krueger flap mainly affects the flow separation of the ailerons. Its length affects the pitch moment tremendously, while its width slot affects the pitch moment slightly. Finally, the design principles of the BWB Krueger flap for the improvement aileron surface flow state were proposed, and the redesign of the BWB high lift configuration significantly improved the flow state of the aileron zone at a minimal cost of aerodynamic characteristics without losing the existing great aerodynamic performance.
Development of a Complex Mathematical and Hardware-in-the-Loop Simulation of the System for Controlling the Skew of Sections of Mechanization of the Wing
Authors: Chibizov Aleksandr , Podzharskaya Marina , Trofimov Alexey
Published: December 2022

In this paper, an innovative approach to the development of a skew control system is discussed to increase the speed and quality of the development of this system. To achieve this goal, we chose the Hardware-in-the-Loop simulation method, which involved creating a mathematical model to test a real control unit. This method reduced time and material costs at both the development and testing stages by enabling quick reconfiguration of the system and the changing parameters of the control model. As a result of this work, we developed a complex of mathematical and full-scale simulations, which included the SCS simulation scheme with distortion detection algorithms and SCS semi-random simulation stand.
Aeroservoelastic Stability Evaluation for Slender Vehicles Based on the Ground Frequency Response Test
Authors: Yu Changkun , Wu Zhigang , Yang Chao
Published: December 2022

With the increasing bandwidths of servo control systems and decreasing mode frequencies, aeroservoelastic (ASE) stability evaluation has become an essential part of flight vehicle design. However, the theoretical method is limited by the modeling errors of numerical models, and the dry wind tunnel method is limited by the complex design of force controllers. Given these limitations, a novel ASE stability evaluation method for slender vehicles based on the ground frequency response test (FRT) is proposed in this paper. FRTs are implemented for a slender vehicle to obtain the frequency response functions (FRFs) of the real structure and servo control systems. The low-order unsteady aerodynamic FRFs established in physical coordinates are calculated by the quasi-steady aerodynamic derivative method. An ASE open-loop FRF is established for stability evaluation via the Nyquist criterion. Comparison with the theoretical results shows that the proposed method is feasible and accurate for different positions of the inertial measurement unit, different control laws, and different Mach numbers. To deal with the unavoidable influence of hanging supports in the test, an FRF fitting and resynthesis method is used to remove the hanging modes and provide an accurate ASE open-loop FRF with free–free boundary conditions.
Assessment of Feed Efficiency and Its Relationship with Egg Quality in Two Purebred Chicken Lines and Their Reciprocal Crosses
Authors: Zhao Jinmeng , Yuan Jingwei , Wang Yuanmei , Ni Aixin , Sun Yanyan , Li Yunlei , Ma Hui , Wang Panlin , Shi Lei , Ge Pingzhuang , Bian Shixiong , Zong Yunhe , Chen Jilan
Published: December 2022

Crossbreeding is normally applied to improve the economical traits of chickens. However, feed efficiency and its relationship with egg quality have rarely been explored in crossbreds. Herein, White Leghorn and Beijing You chickens were selected to generate purebreds (WW, YY) and reciprocal crossbreds (YW, WY), which were evaluated in terms of daily feed intake (DFI), feed conversion ratio (FCR), and residual feed intake (RFI) at 43 to 46 and 69 to 72 weeks of age, respectively. We found that WY was more efficient than YW in both laying periods. The correlation analysis showed that RFI was highly correlated with DFI (0.49 to 0.84) but unrelated to egg mass, and FCR was negatively correlated with egg mass (−0.77 to −0.43) in both purebreds and crossbreds. Moreover, RFI was not correlated with egg quality traits within each genetic group, except for the egg yolk ratio (0.27) in WW. FCR was negatively correlated with eggshell weight and thickness (−0.33 to −0.19) in WW and WY. Compared to FCR, selection for RFI could improve feed efficiency without significant changes in egg mass and quality in chickens. These findings provide new insights into the improvement of feed efficiency using rational parental lines in chicken crossbreeding.
Biostimulants Application on Olea europaea L. in Mediterranean Conditions Increase the Production and Bioactive Compounds of Drupes and Oil
Authors: Cirillo Aurora , De Luca Lucia , Graziani Giulia , Cepparulo Marco , El-Nakhel Christophe , Giordano Maria , Rouphael Youssef , Ritieni Alberto , Romano Raffaele , Di Vaio Claudio
Published: December 2022

Over the years, the use of biostimulants has become increasingly widespread due to their proven efficiency in improving plant productivity and quality of fruits and mitigating the effects related to environmental stress. The aim of the present study was to evaluate the effect of three biostimulants on oil yield, production of drupes per plant, and nutraceutical components of olive drupes and oil (total polyphenols, anthocyanins, and fatty acids %) for “Racioppella” cultivar trees growing in South Italy (May–October 2021). The biostimulants used were: a tropical plants extract (A) containing amino acids, vitamins, enzymes, phytochelatins, macro- and microelements, a glycine betaine-based product (B), and a Trichoderma spp.-based biostimulant (T). The three biostimulants were compared with a control thesis (C) treated only with water. T treatment increased the polyphenols content of olive drupes by 41.04% compared to C. A and B treatments increased polyphenols content by 21.87% on average compared to C. All three biostimulants showed positive effect by increasing the amount of polyphenols in olive oil compared to C:T showed an increase of 32.19%, B 7.76%, and A 19.78%. Biostimulant application proved useful in boosting fundamental parameters that determine better drupe and oil in terms of antioxidant capacity and nutraceutical potential, other than an increased production.
Determination of Nitrogen Application Ratio and Sowing Time for Improving the Future Yield of Double-Harvest Rice in Nanchang Based on the DSSAT-CERES-Rice Model
Authors: Lu Xianghui , Wang Han , Xiang Youzhen , Wang Qian , Su Tong , Gong Rongxin , Zhang Haina , Zhu Lvdan , Li Erhui , Abdelghany Ahmed Elsayed
Published: December 2022

Climate change is a very serious threat to the agricultural sector and potentially brings new problems to the sustainability of agricultural production systems. This paper aims to know how to improve crop yield by changing the nitrogen application ratio and sowing time under future climate change conditions based on the CERES-Rice model. The CERES-Rice model was calibrated and validated with a three-year field experiment (2018–2020), which was coupled with four N rates (50, 100, 150, and 200 kg/ha) and three different N ratios (B:T:S = 3:1:0; B:T:S = 5:3:2; B:T:S = 6:3:1). The results showed that the CERES-Rice model had better simulation effect on the phenophase (n-RMSE < 15%, d > 0.9 and R2 = 0.978) and yield (n-RMSE < 10%, d > 0.9 and R2 = 0.910) of double-harvest rice. The calibrated model was used to evaluate the growth period and yield of double-harvest rice under the RCP4.5 climate scenario and the results revealed that future yields of double-harvest rice in Nanchang are lower than those in experimental years, especially for early rice. Adjusting the nitrogen application ratio and sowing time can improve the yield of double-harvest rice to a certain extent, and the nitrogen application ratio of 5:3:2 has the best effect. In 2021–2035, the best yield of double-harvest rice can be obtained when the sowing date of early rice is about 15 days earlier and the sowing date of late rice is about 10 days earlier than the experiment year. From 2035 to 2050, the sowing date of early rice and late rice will be advanced by about 10 days, and the total yield of double-harvest rice will be higher. In 2050–2070, the total yield of double-harvest rice may reach the best when the sowing date is delayed by 10–15 days. Therefore, reasonably changing the sowing date of double-harvest rice and the nitrogen application regime of early rice can be used as a possible adaptive strategy to cope with the yield reduction in double-harvest rice in future climate scenarios.
Arbuscular Mycorrhiza Symbiosis as a Factor of Asteraceae Species Invasion
Authors: Sokornova Sonya , Malygin Daniil , Terentev Anton , Dolzhenko Viktor
Published: December 2022

Invasive weeds of the Asteraceae family are widespread in the world. Arbuscular mycorrhiza (AM) is one of the main factors contributing to the successful distribution of these species that is most clearly manifested in the subfamily Asteroideae. The benefits of plant-AMF symbiosis are most significant under unfavorable biotic and abiotic conditions. The specificity of the relationship between arbuscular mycorrhizal fungi (AMF) communities and plants and is determined at the presymbiotic stage. The AMF colonization level is higher in invasive species than in native ones, but AMF communities associated with Asteraceae invasive species are less diverse. AMF communities of Asteraceae invaders often include fewer common species (e.g., species belonging to Diversisporales). Invaders also reduce native AMF species richness in new areas. Arbuscular mycorrhizal fungi can form mycorrhizal networks that allow the redistribution of nutrients in plant communities. The most significant influence of AMF associated with invasive Asteraceae plants is seen in the formation of soil and rhizosphere microbiota, including the suppression of beneficial soil bacteria and fungi. This review could be useful in the development of practical recommendations for the use of AMF-based fertilizers.
Genome-Wide Association Study for Non-Photochemical Quenching Traits in Oryza sativa L.
Authors: Wei Youbo , Liu Sicheng , Xiong Dongliang , Xiong Zhuang , Zhang Zuolin , Wang Fei , Huang Jianliang
Published: December 2022

Manipulating the photoprotective mechanism has been demonstrated to be an effective way to enhance the photosynthetic productivity of crop plants. NPQ(T) is a chlorophyll fluorescence parameter for rapid estimation and imaging of non-photochemical quenching (NPQ) of excitons in the photoprotective mechanism. However, the variation and genetic basis of NPQ(T) are rarely reported in the Oryza sativa L. In this study, we collected 173 rice cultivars and investigated the NPQ(T) value. We found that the NPQ(T) has a wide variation, although it had not been under-selected in the different subspecies. A genome-wide association study (GWAS) utilizing 1,566,981 high-quality SNPs identified three significant associated signals on chromosomes 02, 05, and 07. Furthermore, one likely candidate gene Os02g0184100, underlying the associated signal on chromosome 02, was uncovered by identifying the expression pattern in flag leaves and testing the correlation between functional polymorphisms and phenotypic variation. The significant SNPs and candidate genes identified in this study provide us a comprehensive understanding of the genetic architecture of NPQ(T) and could be used for genetic improvement of rice photoprotection.
Rapid Nondestructive Detection of Chlorophyll Content in Muskmelon Leaves under Different Light Quality Treatments
Authors: Ma Ling , Zhang Yao , Zhang Yiyang , Wang Jing , Li Jianshe , Gao Yanming , Wang Xiaomin , Wu Longguo
Published: December 2022

In order to select the light quality suitable for plant growth, a quantitative detection model of chlorophyll content in muskmelon leaves was established to monitor plant growth quickly and accurately. In the paper, muskmelon “Boyang 91” was used as the experimental material, and six different light proportion treatments were set up. Through measuring plant height, stem diameter, number of leaves, nodes, and other growth indicators, in addition to leaf chlorophyll content, the response difference of muskmelon to different light qualities was explored in a plant factory. The hyperspectral imaging technology was used to establish the prediction model for the chlorophyll content of muskmelon. The original spectrum was preprocessed and optimized by five pretreatments, and then the characteristic wavelengths were extracted by six methods. Partial least squares regression (PLSR), least squares support vector machine (LSSVM), and convolutional neural network (CNN) were established for optimal feature wavelength. The results showed that the plant height and stem diameter of the T3 treatment were higher than those of other treatments, and their values were 14.48 (cm) and 5.02 (mm), respectively. The chlorophyll content of the T3 treatment was the highest, and its value was 40.16 (mg/g), which was higher than that of other treatments. Through comprehensive analysis, the T3 treatment (light ratio: 6R/1B/2W, light quantum flux: 360 μmol/(m2·s), photoperiod: 12 h) was optimal. Meanwhile, the average spectral reflectance data of 216 leaf samples were extracted, and the S-G preprocessing method was selected to preprocess the original spectral data (Rc = 0.860, RMSEC = 1.806; Rcv = 0.790, RMSECV = 2.161). By comparing and analyzing the correlation coefficients and root mean square errors of six feature wavelength extraction methods, it was concluded that the variable combination population analysis (VCPA) method had the best model effect for feature wavelength extraction (RP = 0.824, RMSEP = 1.973). Ten characteristic wavelengths ( 396, 409, 457, 518, 532, 565, 687, 691, 701, and 705 nm) extracted by the VCPA method were used to establish the chlorophyll content prediction model, and the chlorophyll content prediction model of S-G-VCPA-CNN had the best performance (Rc = 0.9151, RMSEC = 1.445; Rp = 0.811, RMSEP = 2.055). The results of this study provide data support and a theoretical basis for screening the light ratio of other crops, and also present technical support for online monitoring of crop growth in plant factories.
Changes in the Populations of Two Lymnaeidae and Their Infection by Fasciola hepatica and/or Calicophoron daubneyi over the Past 30 Years in Central France
Authors: Rondelaud Daniel , Vignoles Philippe , Dreyfuss Gilles
Published: December 2022

Field investigations were carried out during three periods (from 1976 to 1997, in 2013–2014, and in 2020–2021) on 39 cattle-raising farms on acidic soils to track changes in the populations of two Lymnaeidae (Galba truncatula and Omphiscola glabra) and their infection with Fasciola hepatica and/or Calicophoron daubneyi. Compared to the survey between 1976 and 1997 on these farms, there was a significant decrease in the number of the two lymnaeid populations and the size of the G. truncatula populations in both 2013–2014 and 2020–2021. This decline was significantly faster in the last nine years than it was before 2013. The area of habitats colonized by G. truncatula showed no significant variation over the years, while that of habitats with O. glabra significantly decreased in the period covered by the three surveys. The prevalence of F. hepatica infection in snails significantly decreased over the years, while C. daubneyi infection increased over time in both lymnaeid species. These changes are due to the use of triclabendazole to treat fasciolosis in ruminants since the 1990s, and are probably a consequence of the successive heatwaves that have occurred since 2018 in the region.
Informing Implementation: Perspectives from the Australian University Community Regarding an Animal Assisted Intervention
Authors: Cooke Emily , Henderson-Wilson Claire , Warner Elyse , LaMontagne Anthony D.
Published: December 2022

Animal Assisted Interventions (AAIs) have become increasingly popular in the university setting; however, there is limited research exploring their potential on an Australian university campus and participants’ views prior to implementation. Therefore, this study aimed to explore university staff members’ and students’ interest in participating in an AAI and their perspectives on intervention characteristics. This was a mixed methods study, using an online survey and semi-structured interviews. The survey had 344 responses, and 45 interviews were conducted. A large majority of participants (86%) were interested in participating in an AAI. In the survey, participants indicated their preferred intervention characteristics for the location of the intervention, frequency of participating, and ways of hearing about the intervention. Participants also expressed concerns regarding therapy animal welfare. In interviews, participants discussed various considerations which may impact the intervention (such as the accessibility of the location, the impact of workload on participating, the effectiveness of promotion strategies, and factors that may assist therapy animal welfare, such as the therapy animals’ handlers). Gaining an insight into the university community’s views prior to implementation may ensure the intervention is feasible to implement and can be beneficial to both humans and therapy animals.
Plasma Amino Acid Concentration in Obese Horses with/without Insulin Dysregulation and Laminitis
Authors: Stoeckle Sabita Diana , Timmermann Detlef , Merle Roswitha , Gehlen Heidrun
Published: December 2022

Laminitic horses commonly suffer from an endocrine disease such as equine metabolic syndrome. Hyperinsulinemia is considered a key factor in the pathogenesis of laminitis. Since insulin also affects protein turnover in the body, the resting plasma amino acid concentrations of obese horses that were presented for a combined glucose insulin test (CGIT) were determined. In total, 25 obese horses and two lean horses with recurrent laminitis underwent a CGIT. Of these, five were not insulin dysregulated (obese), 14 were insulin dysregulated (ID), and eight were insulin-dysregulated and laminitic (IDL). Significant differences in the resting concentrations between obese and insulin dysregulated and laminitic (citrulline p = 0.038, obese: 73.001 ± 12.661 nmol/mL, IDL: 49.194 ± 15.486 nmol/mL; GABA p = 0.02, obese: 28.234 ± 3.885 nmol/mL, IDL: 16.697 ± 1.679 nmol/mL; methionine p = 0.018, obese: 28.691 ± 5.913 nmol/mL, IDL: 20.143 ± 3.09 nmol/mL) as well as between insulin dysregulated individuals with and without laminitis (GABA p < 0.001, ID: 28.169 ± 6.739 nmol/mL) regarding three amino acids were determined. This may be an interesting approach, especially for diagnostic testing and possibly also for the feed supplements of horses at risk of developing laminitis. However, further research, including a higher number of cases, is required.
Neurobiology of Maternal Behavior in Nonhuman Mammals: Acceptance, Recognition, Motivation, and Rejection
Authors: Coria-Avila Genaro A. , Herrera-Covarrubias Deissy , García Luis I. , Toledo Rebeca , Hernández María Elena , Paredes-Ramos Pedro , Corona-Morales Aleph A. , Manzo Jorge
Published: December 2022

Among the different species of mammals, the expression of maternal behavior varies considerably, although the end points of nurturance and protection are the same. Females may display passive or active responses of acceptance, recognition, rejection/fear, or motivation to care for the offspring. Each type of response may indicate different levels of neural activation. Different natural stimuli can trigger the expression of maternal and paternal behavior in both pregnant or virgin females and males, such as hormone priming during pregnancy, vagino-cervical stimulation during parturition, mating, exposure to pups, previous experience, or environmental enrichment. Herein, we discuss how the olfactory pathways and the interconnections of the medial preoptic area (mPOA) with structures such as nucleus accumbens, ventral tegmental area, amygdala, and bed nucleus of stria terminalis mediate maternal behavior. We also discuss how the triggering stimuli activate oxytocin, vasopressin, dopamine, galanin, and opioids in neurocircuitries that mediate acceptance, recognition, maternal motivation, and rejection/fear.
Dinactin: A New Antitumor Antibiotic with Cell Cycle Progression and Cancer Stemness Inhibiting Activities in Lung Cancer
Authors: Rawangkan Anchalee , Wongsirisin Pattama , Pook-In Grissana , Siriphap Achiraya , Yosboonruang Atchariya , Kiddee Anong , Chuerduangphui Jureeporn , Reukngam Nanthawan , Duangjai Acharaporn , Saokaew Surasak , Praphasawat Ratsada
Published: December 2022

Lung cancer, especially non-small cell lung cancer (NSCLC), is one of the most complex diseases, despite the existence of effective treatments such as chemotherapy and immunotherapy. Since cancer stem cells (CSCs) are responsible for chemo- and radio-resistance, metastasis, and cancer recurrence, finding new therapeutic targets for CSCs is critical. Dinactin is a natural secondary metabolite produced by microorganisms. Recently, dinactin has been revealed as a promising antitumor antibiotic via various mechanisms. However, the evidence relating to cell cycle progression regulation is constrained, and effects on cancer stemness have not been elucidated. Therefore, the aim of this study is to evaluate the new function of dinactin in anti-NSCLC proliferation, focusing on cell cycle progression and cancer stemness properties in Lu99 and A549 cells. Flow cytometry and immunoblotting analyses revealed that 0.1–1 µM of dinactin suppresses cell growth through induction of the G0/G1 phase associated with down-regulation of cyclins A, B, and D3, and cdk2 protein expression. The tumor-sphere forming capacity was used to assess the effect of dinactin on the cancer stemness potential in NSCLC cells. At a concentration of 1 nM, dinactin reduced both the number and size of the tumor-spheres. The quantitative RT-PCR analyses indicated that dinactin suppressed sphere formation by significantly reducing expression of CSC markers (i.e., ALDH1A1, Nanog, Oct4, and Sox2) in Lu99 cells. Consequently, dinactin could be a promising strategy for NSCLC therapy targeting CSCs.
Transcriptome and Metabolome Analysis of a Late-Senescent Vegetable Soybean during Seed Development Provides New Insights into Degradation of Chlorophyll
Authors: Wang Jian , Chen Guang , Li Xuetong , Fu Xujun , Li Sujuan , Tao Xiaoyuan , Chen Zhong-Hua , Xu Shengchun
Published: December 2022

(1) Background: Senescence represents the final stage of plant growth and development, which transfers nutrients to growing seeds and directly affects the yield and quality of crops. However, little is known about chlorophyll degradation in developing and maturing seeds, in contrast to leaf senescence; (2) Methods: RNA-Seq was used to analyze the differentially expressed genes of different late-senescent germplasms. A widely untargeted metabolic analysis was used to analyze differential metabolites. In addition, qRT-PCR was conducted to detect gene expression levels; (3) Results: Transcriptome analysis revealed that ZX12 seeds have a higher expression level of the chlorophyll synthesis genes in the early stage of maturity, compared with ZX4, and have a lower expression level of chlorophyll degradation genes in the late stage of maturity. Flavonoids were the primary differential metabolites, and ZX12 contains the unique and highest expression of three types of metabolites, including farrerol-7-O-glucoside, cyanidin-3-o-(6′-o-feruloyl) glucoside, and kaempferide-3-o-(6′-malonyl) glucoside. Among them, farrerol-7-O-glucoside and cyanidin-3-o-(6′-o-feruloyl) glucoside are flavonoid derivatives containing mono and dihydroxy-B-ring chemical structures, respectively; and (4) Conclusions: It is speculated that the two metabolites can slow down the degradation process of chlorophyll by scavenging oxygen-free radicals in the chloroplast.
Complex Interplay between Autophagy and Oxidative Stress in the Development of Endometriosis
Authors: D’Amico Ramona , Impellizzeri Daniela , Cordaro Marika , Siracusa Rosalba , Interdonato Livia , Marino Ylenia , Crupi Rosalia , Gugliandolo Enrico , Macrì Francesco , Di Paola Davide , Peritore Alessio Filippo , Fusco Roberta , Cuzzocrea Salvatore , Di Paola Rosanna
Published: December 2022

Endometriosis (Endo) is a chronic gynecological disease. This paper aimed to evaluate the modulation of autophagy, oxidative stress and apoptosis with Açai Berries in a rat model of endometriosis. Endometriosis was induced with an intraperitoneal injection of minced uterus tissue from a donor rat into a recipient one. The abdominal high-frequency ultrasound (hfUS) analysis was performed at 7 and 14 days from the endometriosis induction to evaluate the growth of the lesion during the experiment. Seven days from the induction, once the lesions were implanted, an Açai Berry was administered daily by gavage for the next seven days. At the end of the experiment, the hfUS analysis showed a reduced lesion diameter in animals given the Açai Berry. A macroscopical and histological analysis confirmed this result. From the molecular point of view, Western blot analyses were conducted to evaluate the autophagy induction. Samples collected from the Endo group showed impaired autophagy, while the Açai Berry administration inhibited PI3K and AKT and ERK1/2 phosphorylation and promoted autophagy by inactivating mTOR. Additionally, Açai Berry administration dephosphorylated ATG1, promoting the activity of the ATG1/ULK1 complex that recruited Ambra1/Beclin1 and Atg9 to promote autophagosome nucleation and LC3II expression. Açai Berry administration also restored mitophagy, which increased Parkin cytosolic expression. The Açai Berry increased the expression of NRF2 in the nucleus and the expression of its downstream antioxidant proteins as NQO-1 and HO-1, thereby restoring the oxidative imbalance. It also restored the impaired apoptotic pathway by reducing BCL-2 and increasing BAX expression. This result was also confirmed by the TUNEL assay. Overall, our results displayed that Açai Berry administration was able to modulate autophagy, oxidative stress and apoptosis during endometriosis.
Does the Type Matter? Verification of Different Tea Types’ Potential in the Synthesis of SeNPs
Authors: Sentkowska Aleksandra , Pyrzynska Krystyna
Published: December 2022

Selenium nanoparticles (SeNPs) are gaining popularity due to their potential biomedical applications. This work describes their green synthesis using various types of tea. Black, green, red and white tea infusions were tested for the content of polyphenolic compounds and antioxidant properties and then used in the synthesis of SeNPs. In each of the syntheses, nanoparticles with dimensions ranging from 3.9 to 12.5 nm, differing in shape and properties, were obtained. All of them were characterized by a very high ability to neutralize hydroxyl radicals, which was about three-times higher than for the tea infusions from which they were obtained. The main inconvenience in obtaining SeNPs was the difficulties with their purification, which should be a further stage in the described research.
Green Extraction of Polyphenols from Waste Bentonite to Produce Functional Antioxidant Excipients for Cosmetic and Pharmaceutical Purposes: A Waste-to-Market Approach
Authors: Di Prima Giulia , Belfiore Elena , Migliore Martina , Scarpaci Amalia Giulia , Angellotti Giuseppe , Restivo Ignazio , Allegra Mario , Arizza Vincenzo , De Caro Viviana
Published: December 2022

In an ever-growing perspective of circular economy, the development of conscious, sustainable and environmental-friendly strategies to recycle the waste products is the key point. The scope of this work was to validate the waste bentonite from the grape processing industries as a precious matrix to extract polyphenols by applying a waste-to-market approach aimed at producing novel functional excipients. The waste bentonite was recovered after the fining process and opportunely pre-treated. Subsequently, both the freeze dried and the so-called “wet” bentonites were subjected to maceration. PEG200 and Propylene Glycol were selected as solvents due to their ability to dissolve polyphenols and their wide use in the cosmetic/pharmaceutical field. The extracts were evaluated in terms of yield, density, pH after water-dilution, total phenolic (Folin–Ciocalteu) and protein (Bradford) contents, antioxidant power (DPPH), amount of some representative polyphenols (HPLC-DAD), cytocompatibility and stability. Both solvents validated the bentonite as a valuable source of polyphenols and led to colored fluids characterized by an acidic pH after water-dilution. The best extract was obtained from the wet bentonite with PEG200 and highlighted the highest phenolic content and consequently the strongest antioxidant activity. Additionally, it displayed proliferative properties and resulted almost stable over time. Hence, it might be directly used as polyphenols-enriched functional novel raw material for cosmetic and pharmaceutics purposes.
Malware Classification Using Convolutional Fuzzy Neural Networks Based on Feature Fusion and the Taguchi Method
Authors: Lin Cheng-Jian , Huang Min-Su , Lee Chin-Ling
Published: December 2022

The applications of computer networks are increasingly extensive, and networks can be remotely controlled and monitored. Cyber hackers can exploit vulnerabilities and steal crucial data or conduct remote surveillance through malicious programs. The frequency of malware attacks is increasing, and malicious programs are constantly being updated. Therefore, more effective malware detection techniques are being developed. In this paper, a convolutional fuzzy neural network (CFNN) based on feature fusion and the Taguchi method is proposed for malware image classification; this network is referred to as FT-CFNN. Four fusion methods are proposed for the FT-CFNN, namely global max pooling fusion, global average pooling fusion, channel global max pooling fusion, and channel global average pooling fusion. Data are fed into this network architecture and then passed through two convolutional layers and two max pooling layers. The feature fusion layer is used to reduce the feature size and integrate the network information. Finally, a fuzzy neural network is used for classification. In addition, the Taguchi method is used to determine optimal parameter combinations to improve classification accuracy. This study used the Malimg dataset to evaluate the accuracy of the proposed classification method. The accuracy values exhibited by the proposed FT-CFNN, proposed CFNN, and original LeNet model in malware family classification were 98.61%, 98.13%, and 96.68%, respectively.
Reducing False Negatives in Ransomware Detection: A Critical Evaluation of Machine Learning Algorithms
Authors: Bold Robert , Al-Khateeb Haider , Ersotelos Nikolaos
Published: December 2022

Technological achievement and cybercriminal methodology are two parallel growing paths; protocols such as Tor and i2p (designed to offer confidentiality and anonymity) are being utilised to run ransomware companies operating under a Ransomware as a Service (RaaS) model. RaaS enables criminals with a limited technical ability to launch ransomware attacks. Several recent high-profile cases, such as the Colonial Pipeline attack and JBS Foods, involved forcing companies to pay enormous amounts of ransom money, indicating the difficulty for organisations of recovering from these attacks using traditional means, such as restoring backup systems. Hence, this is the benefit of intelligent early ransomware detection and eradication. This study offers a critical review of the literature on how we can use state-of-the-art machine learning (ML) models to detect ransomware. However, the results uncovered a tendency of previous works to report precision while overlooking the importance of other values in the confusion matrices, such as false negatives. Therefore, we also contribute a critical evaluation of ML models using a dataset of 730 malware and 735 benign samples to evaluate their suitability to mitigate ransomware at different stages of a detection system architecture and what that means in terms of cost. For example, the results have shown that an Artificial Neural Network (ANN) model will be the most suitable as it achieves the highest precision of 98.65%, a Youden’s index of 0.94, and a net benefit of 76.27%, however, the Random Forest model (lower precision of 92.73%) offered the benefit of having the lowest false-negative rate (0.00%). The risk of a false negative in this type of system is comparable to the unpredictable but typically large cost of ransomware infection, in comparison with the more predictable cost of the resources needed to filter false positives.
Improving ECG Classification Performance by Using an Optimized One-Dimensional Residual Network Model
Authors: Zang Junbin , Wang Juliang , Zhang Zhidong , Zheng Yongqiu , Xue Chenyang
Published: December 2022

Cardiovascular disease and its consequences on human health have never stopped and even show a trend of appearing in increasingly younger generations. The establishment of an excellent deep learning algorithm model to assist physicians in identifying and the early screening of ECG abnormalities can effectively improve the accuracy of diagnosis. Therefore, in this study, the deep residual network model is adapted for feature extraction and classification of ECG signals by pooling embedded into layers and double channel connection. At the same time, the wavelet adaptive threshold denoising algorithm is used to complete the high signal-to-noise filtering of ECG signals. Then, the alternate pooling residual network (APRN) is compared with the convolutional neural network (CNN), CNN with one residual unit (CNN-R), and the deep residual network (ResNet-18) using ECG datasets from the American MIT-BIH arrhythmia and ST segment abnormality database, European ST-T database, and sudden cardiac death ambulatory ECG database. The results are as follows: The average classification accuracy of the APRN on the four datasets is 97.89%, while the accuracies on CNN, CNN-R, and ResNet-18 are 97.17%, 97.53%, and 97.73%, respectively. In addition, compared with ResNet-18, the classification accuracy of our APRN on each class of data improves by 16.44% in total.
Adaptive Active Positioning of Camellia oleifera Fruit Picking Points: Classical Image Processing and YOLOv7 Fusion Algorithm
Authors: Zhou Yunhe , Tang Yunchao , Zou Xiangjun , Wu Mingliang , Tang Wei , Meng Fan , Zhang Yunqi , Kang Hanwen
Published: December 2022

Camellia oleifera fruits are randomly distributed in an orchard, and the fruits are easily blocked or covered by leaves. In addition, the colors of leaves and fruits are alike, and flowers and fruits grow at the same time, presenting many ambiguities. The large shock force will cause flowers to fall and affect the yield. As a result, accurate positioning becomes a difficult problem for robot picking. Therefore, studying target recognition and localization of Camellia oleifera fruits in complex environments has many difficulties. In this paper, a fusion method of deep learning based on visual perception and image processing is proposed to adaptively and actively locate fruit recognition and picking points for Camellia oleifera fruits. First, to adapt to the target classification and recognition of complex scenes in the field, the parameters of the You Only Live Once v7 (YOLOv7) model were optimized and selected to achieve Camellia oleifera fruits’ detection and determine the center point of the fruit recognition frame. Then, image processing and a geometric algorithm are used to process the image, segment, and determine the morphology of the fruit, extract the centroid of the outline of Camellia oleifera fruit, and then analyze the position deviation of its centroid point and the center point in the YOLO recognition frame. The frontlighting, backlight, partial occlusion, and other test conditions for the perceptual recognition processing were validated with several experiments. The results demonstrate that the precision of YOLOv7 is close to that of YOLOv5s, and the mean average precision of YOLOv7 is higher than that of YOLOv5s. For some occluded Camellia oleifera fruits, the YOLOv7 algorithm is better than the YOLOv5s algorithm, which improves the detection accuracy of Camellia oleifera fruits. The contour of Camellia oleifera fruits can be extracted entirely via image processing. The average position deviation between the centroid point of the image extraction and the center point of the YOLO recognition frame is 2.86 pixels; thus, the center point of the YOLO recognition frame is approximately considered to be consistent with the centroid point of the image extraction.
Diagnosis Method for Mechanical Faults Based on Rotation Synchroextracting Chirplet Transform
Authors: Hu Zhifeng , Li Zhinong , Ge Liying , Mao Qinghua , Zhang Xuhui
Published: December 2022

The problems of the synchroextracting transform method being unable to handle FM signals and being prone to time–frequency feature discontinuity in a strong noise environment are addressed by the construction of a novel rotation synchroextracting chirplet transform under the framework of the synchroextracting transform. The method retains the advantage of the generalized linear chirplet transform that can fit the time–frequency characteristics of the original signal and retains the high precision time–frequency analysis ability of the synchroextracting transform. The simulation results show that the proposed method is obviously superior to the generalized chirplet transform and synchroextracting transform method. The method can obtain the time–frequency energy located at the time–frequency ridges of FM-AM signals and multicomponent signals with crossed-frequency components, and has high time–frequency analysis ability and anti-interference ability. Finally, the proposed method is applied to diagnose mechanical faults. The experimental results further verify the effectiveness of the proposed method, which can effectively extract the characteristic freque.ncy of fault signal.
A Novel Methodology to Assess Seismic Resilience (SR) of Interconnected Infrastructures
Authors: Forcellini Davide
Published: December 2022

Modern and smart cities are significantly vulnerable to natural hazard, and their functionality is based on resilient infrastructure systems. In particular, seismic resilience may be considered the ability to deliver services during and after hazard events. Therefore, it is fundamental to identify the most critical components within a system, especially when multiple infrastructure systems are interdependent. The paper aims to propose a novel methodology that consider interconnected infrastructures to assess seismic resilience that may be defined as a function that depends on time, and the different components are considered the functional dimensions. The proposed methodology may be applied for several typologies of infrastructures, specifically looking at the seismic resilience analyses related to transportation systems. A case study has been considered in order to apply the proposed formulation and to demonstrate the importance of considering interdependency in the assessment of the seismic resilience. Many stakeholders (infrastructure owners, public administrations, decision makers) may be interested in applying the methodology that could be used to study several applications.
A Microscopic Traffic Flow Model Characterization for Weather Conditions
Authors: Ali Faryal , Khan Zawar Hussain , Khattak Khurram Shehzad , Gulliver Thomas Aaron
Published: December 2022

Road surfaces are affected by rain, snow, and ice, which influence traffic flow. In this paper, a microscopic traffic flow model based on weather conditions is proposed. This model characterizes traffic based on the weather severity index. The Intelligent Driver (ID) model characterizes traffic behavior based on a constant acceleration exponent resulting in similar traffic behavior regardless of the conditions, which is unrealistic. The ID and proposed models are evaluated over a circular road of length 800 m. The results obtained indicate that the proposed model characterizes the velocity and density better than the ID model. Further, variations in the traffic flow with the proposed model are smaller during adverse weather, as expected. It is also shown that traffic is stable with the proposed model, even during adverse weather.
Development of FEM Calculation Methods to Analyse Subcooled Boiling Heat Transfer in Minichannels Based on Experimental Results
Authors: Piasecka Magdalena , Maciejewska Beata , Łabędzki Paweł
Published: December 2022

Even though two-phase heat transfer of refrigerants in minichannel heat sinks has been studied extensively, there is still a demand for improvements in overall thermal performance of miniature heat transfer exchangers. Experimental investigation and sophisticated heat transfer calculations with respect to heat transfer devices are still needed. In this work, a time-dependent experimental study of subcooled boiling was carried out for FC-72 flow in a heat sink, comprising of five asymmetrically heated minichannels. The heater surface temperature was continuously monitored by an infrared camera. The boiling heat transfer characteristics were investigated and the effect of the mass flow rate on the heat transfer coefficient was studied. In order to solve the heat transfer problem related to time-dependent flow boiling, two numerical methods, based on the FEM were applied, and based on the Trefftz functions (FEMT) and using the ADINA program. The results achieved with these two calculation methods were explored with an emphasis on the impact of the mass flow rate (range from 5 to 55 kg/h) on the resulting heat transfer coefficient. It was found that, with increasing mass flow, the heat transfer coefficient increased. Good agreement was found between the heat transfer coefficients, determined according to two numerical methods and the simple 1D calculation method.
Effect of Lyophilization Process on Nutritional Value of Meat By-Products
Authors: Juknienė Ignė , Zaborskienė Gintarė , Jankauskienė Agnė , Kabašinskienė Aistė , Zakarienė Gintarė , Bliznikas Saulius
Published: December 2022

The meat industry generates large amounts of by-products, and their mass represents approximately one-third of the live weight of animals. Most by-products are disposed of and not used for processing, although they meet hygiene requirements and are suitable for human consumption or for the processing of food supplements. The aim of this study was to investigate the effect of lyophilization on the nutritional value and retention of functional ingredients in ovine and porcine by-products: liver, kidneys, hearts, and lungs. For this purpose, meat by-products of the third category were selected in X and Y slaughterhouses and divided into two parts: one part was freeze-dried at −80 °C for 72 h, and the other part was left raw. Fatty acid composition was determined by gas chromatography–mass spectrometry (GC-MS), and amino acid analysis was performed by AccQ Tag technology (Waters Corp., Milford, MA, USA) and HPLC. Our study shows that the lyophilization process did not significantly affect protein and fat content. The largest decrease in the amount of proteins was determined in samples of ovine kidneys, at 0.8%, while the difference in protein in ovine liver samples before and after lyophilization was 0.38%. The composition of essential amino acids did not change after lyophilization, except a decrease in Leu and Thr in porcine samples and Leu, Thr, and Met in ovine samples (p < 0.05). The lyophilization process did not significantly affect the polyunsaturated fatty acid content, including the amounts of omega 3 and omega 6 fatty acids. The optimal ratio of omega 6 and 3 fatty acids was determined in samples of lyophilized ovine livers (2.65), and the largest ratio was found in samples of lyophilized porcine hearts (16.67). The study results show that, after lyophilization, meat by-products of the third category (according to Regulation (EC) No. 1069/2009, Categorization, Article 10), especially ovine liver, can be used as a source of amino acids and polyunsaturated fatty acids for functional food processing. The process of lyophilization is also appropriate for preserving meat by-products without losing the nutritional value and beneficial components.
Product Innovation Design Process Model Based on Functional Genes Extraction and Construction
Authors: Wang Hongxiang , Zhang Peng , Zhang Zhimin , Zhang Yuchen , Wang Yaru
Published: December 2022

The product innovation design is an innovation-intensive process that requires abundant knowledge and design experience, even across industries and disciplines, as a resource for problem solving. Therefore, designers need to have a good command of more design knowledge in this process. However, due to varied expressions of design knowledge (function, principle, structure) in different fields lead to the difficulty in representation of design knowledge, which makes designers unable to innovate by directly using design knowledge. Therefore, to solve the problem above, this paper, analogous to biological gene, proposes a product innovation process model based on functional gene extraction and construction. The proposed process model normalizes design knowledge through functional genes and help designers acquire design knowledge in different fields, which further promotes the product innovation design. The process model consists of four following steps. First, Obtain the overall function of product based on user needs and decompose it. Second, Build the functional gene model based on digital twin ones to expand the breadth of design knowledge and facilitate the retrieval. Third, Screen similar functional gene by the functional similarity algorithm. Finally, Obtain the design scheme through recombination, transcription, and translation of the functional gene. The feasibility of the research method is verified by using a shared bicycle parking device as an example.