Evaluation of the intracellular lipid-lowering effect of polyphenols extract from highland barley in HepG2 cells

Active ingredients from highland barley have received considerable attention as natural products for developing treatments and dietary supplements against obesity.In practical application,the research of food combinations is more significant than a specific food component.This study investigated the lipid-lowering effect of highland barley polyphenols via lipase assay in vitro and HepG2 cells induced by oleic acid(OA).Five indexes,triglyceride(TG),total cholesterol(T-CHO),low density lipoprotein-cholesterol(LDL-C),aspartate aminotransferase(AST),and alanine aminotransferase(ALT),were used to evaluate the lipidlowering effect of highland barley extract.We also preliminary studied the lipid-lowering mechanism by Realtime fluorescent quantitative polymerase chain reaction(q PCR).The results indicated that highland barley extract contains many components with lipid-lowering effects,such as hyperoside and scoparone.In vitro,the lipase assay showed an 18.4%lipase inhibition rate when the additive contents of highland barley extract were 100μg/m L.The intracellular lipid-lowering effect of highland barley extract was examined using 0.25 mmol/L OA-induced HepG2 cells.The results showed that intracellular TG,LDL-C,and T-CHO content decreased by 34.4%,51.2%,and 18.4%,respectively.ALT and AST decreased by 51.6%and 20.7%compared with the untreated hyperlipidemic HepG2 cells.q PCR results showed that highland barley polyphenols could up-regulation the expression of lipid metabolism-related genes such as PPARγand Fabp4.

Ginkgo biloba extract alleviates fatty liver hemorrhagic syndrome in laying hens via reshaping gut microbiota

Background Ginkgo biloba extract(GBE)is evidenced to be effective in the prevention and alleviation of metabolic disorders,including obesity,diabetes and fatty liver disease.However,the role of GBE in alleviating fatty liver hemorrhagic syndrome(FLHS)in laying hens and the underlying mechanisms remain to be elucidated.Here,we investigated the effects of GBE on relieving FLHS with an emphasis on the modulatory role of GBE in chicken gut microbiota.Results The results showed that GBE treatment ameliorated biochemical blood indicators in high-fat diet(HFD)-induced FLHS laying hen model by decreasing the levels of TG,TC,ALT and ALP.The lipid accumulation and pathological score of liver were also relieved after GBE treatment.Moreover,GBE treatment enhanced the antioxidant activity of liver and serum by increasing GSH,SOD,T-AOC,GSH-PX and reducing MDA,and downregulated the expression of genes related to lipid synthesis(FAS,LXRα,GPAT1,PPARγand Ch REBP1)and inflammatory cytokines(TNF-α,IL-6,TLR4 and NF-κB)in the liver.Microbial profiling analysis revealed that GBE treatment reshaped the HFD-perturbed gut microbiota,particularly elevated the abundance of Megasphaera in the cecum.Meanwhile,targeted metabolomic analysis of SCFAs revealed that GBE treatment significantly promoted the production of total SCFAs,acetate and propionate,which were positively correlated with the GBE-enriched gut microbiota.Finally,we confirmed that the GBE-altered gut microbiota was sufficient to alleviate FLHS by fecal microbiota transplantation(FMT).Conclusions We provided evidence that GBE alleviated FLHS in HFD-induced laying hens through reshaping the composition of gut microbiota.Our findings shed light on mechanism underlying the anti-FLHS efficacy of GBE and lay foundations for future use of GBE as additive to prevent and control FLHS in laying hen industry.

Automatic Extraction Method of 3D Feature Guidelines for Complex Cultural Relic Surfaces Based on Point Cloud

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduction is undoubtedly necessary for line drawings.However,most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex.Therefore,conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection.Based on the given criteria for assessing surface complexity,this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces.A 2D and 3D combined factor that measured the importance of points on describing surface features,vertex weight,was designed.Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions.The feasibility and stability were verified through experiments conducted on real cultural relic surface data.Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces.The extraction method and the obtained results will be useful for line graphic drawing,displaying and propaganda of cultural relics.

Preferentially selective extraction of lithium from spent LiCoO_(2)cathodes by medium-temperature carbon reduction roasting

Lithium recovery from spent lithium-ion batteries(LIBs)have attracted extensive attention due to the skyrocketing price of lithium.The medium-temperature carbon reduction roasting was proposed to preferential selective extraction of lithium from spent Li-CoO_(2)(LCO)cathodes to overcome the incomplete recovery and loss of lithium during the recycling process.The LCO layered structure was destroyed and lithium was completely converted into water-soluble Li2CO_(3)under a suitable temperature to control the reduced state of the cobalt oxide.The Co metal agglomerates generated during medium-temperature carbon reduction roasting were broken by wet grinding and ultrasonic crushing to release the entrained lithium.The results showed that 99.10%of the whole lithium could be recovered as Li2CO_(3)with a purity of 99.55%.This work provided a new perspective on the preferentially selective extraction of lithium from spent lithium batteries.

Effects of conductive agent type on lithium extraction from salt lake brine with LiFePO_(4) electrodes

Electrochemical lithium extraction from salt lakes is an effective strategy for obtaining lithium at a low cost.Nevertheless,the elevated Mg:Li ratio and the presence of numerous coexisting ions in salt lake brines give rise to challenges,such as prolonged lithium extraction periods,diminished lithium extraction efficiency,and considerable environmental pollution.In this work,Li FePO4(LFP)served as the electrode material for electrochemical lithium extraction.The conductive network in the LFP electrode was optimized by adjusting the type of conductive agent.This approach resulted in high lithium extraction efficiency and extended cycle life.When the single conductive agent of acetylene black(AB)or multiwalled carbon nanotubes(MWCNTs)was replaced with the mixed conductive agent of AB/MWCNTs,the average diffusion coefficient of Li+in the electrode increased from 2.35×10^(-9)or 1.77×10^(-9)to 4.21×10^(-9)cm^(2)·s^(-1).At the current density of 20 mA·g^(-1),the average lithium extraction capacity per gram of LFP electrode increased from 30.36 mg with the single conductive agent(AB)to 35.62 mg with the mixed conductive agent(AB/MWCNTs).When the mixed conductive agent was used,the capacity retention of the electrode after 30 cycles reached 82.9%,which was considerably higher than the capacity retention of 65.8%obtained when the single AB was utilized.Meanwhile,the electrode with mixed conductive agent of AB/MWCNTs provided good cycling performance.When the conductive agent content decreased or the loading capacity increased,the electrode containing the mixed conductive agent continued to show excellent electrochemical performance.Furthermore,a self-designed,highly efficient,continuous lithium extraction device was constructed.The electrode utilizing the AB/MWCNT mixed conductive agent maintained excellent adsorption capacity and cycling performance in this device.This work provides a new perspective for the electrochemical extraction of lithium using LFP electrodes.

Effect of Rosmarinus officinalis and Origanum majorana extracts on stability of sunflower oil during storage and repeated heating

Both rosemary(Rosmarinus officinalis)and marjoram(Origanum majorana)are abundant in phenolic compounds,exhibiting exceptional antioxidant activity.This study aims to assess the impact of rosemary and marjoram extracts on the stability of sunflower oil during storage and repeated heating.Sunflower oil supplemented with herbal extracts or butylated hydroxytoluene(BHA)at a concentration of 200 ppm was stored for six months under light and dark conditions at room temperature.Peroxide value(PV),p-anisidine value(An-V),and total oxidation(TOTOX)value were measured to monitor lipid oxidation progression.A significant difference(P<0.05)was observed between light and dark storage for all studied samples regarding oxidation parameters.The ethanolic extract of rosemary exhibited higher antioxidant activity compared to BHA and other extracts.Furthermore,sunflower oil supplemented with the ethanolic extract of rosemary underwent weekly treatment at 100℃for 30 min over four consecutive weeks.Although all oxidation indicators increased during repeated heating,the addition of rosemary and marjoram extracts as well as BHA significantly reduced these indicators.These findings demonstrate that both rosemary extracts and marjoram extracts can serve as natural antioxidants in edible oils.

A Joint Entity Relation Extraction Model Based on Relation Semantic Template Automatically Constructed

The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of defining the semantic template of relation manually is particularly prominent in the extraction effect because it can obtain the deep semantic information of relation.However,this method has some problems,such as relying on expert experience and poor portability.Inspired by the rule-based entity relation extraction method,this paper proposes a joint entity relation extraction model based on a relation semantic template automatically constructed,which is abbreviated as RSTAC.This model refines the extraction rules of relation semantic templates from relation corpus through dependency parsing and realizes the automatic construction of relation semantic templates.Based on the relation semantic template,the process of relation classification and triplet extraction is constrained,and finally,the entity relation triplet is obtained.The experimental results on the three major Chinese datasets of DuIE,SanWen,and FinRE showthat the RSTAC model successfully obtains rich deep semantics of relation,improves the extraction effect of entity relation triples,and the F1 scores are increased by an average of 0.96% compared with classical joint extraction models such as CasRel,TPLinker,and RFBFN.

Antimicrobial Activities of Extracts of Macrosphyra longistyla against Gram-Positive Oral Biofilm-Formers from School Children in Southwestern Nigeria and Toxicity Studies Using Brine Shrimps

The world will benefit from more effective antimicrobial agents against oral conditions arising from the actions of biofilm forming bacteria. Also, information is lacking on the oral biofilm-forming bacterial diversity in Southwestern Nigeria. In this study, we isolate and characterize oral biofilm producing bacteria in the oral cavities of schoolchildren in Southwestern Nigeria. We also investigate the antimicrobial properties of Macrosphyra longistyla extracts against the biofilm-formers and the toxicity of potent extracts. Samples were obtained from 109 schoolchildren aged 4 - 14 years from Lagos, Oyo and Osun States. Agar well diffusion technique was used in the antimicrobial susceptibility testing. Toxicity testing was done using brine shrimps (Artemia salina). Biofilm-formers in this study are Klebsiella sp., Streptococcus sp., Staphylococcus sp., and Micrococcus sp. Ethanol leaf extracts had the highest activity against all biofilm-producing bacteria. Ethanol stem bark extract, which elicited activity against Klebsiella only, was found to be less toxic than the ethanol leaf extract. Staphylococcus showed >10 mm susceptibility to the ethanol and aqueous extracts of Macrosphyra longistyla. Streptococcus and Micrococcus were susceptible to the antimicrobial actions of the ethanolic leaf extracts. Although the ethanol extracts of the leaves had lower minimum inhibitory concentrations than the ethanol extracts of the stem bark, toxicity studies showed ethanol extracts of the stem-bark to be more toxic than the ethanol extracts of the leaves. In conclusion, ethanolic extracts of Macrosphyra longistyla show potential as sources of antimicrobials against gram-positive, oral biofilm-forming bacteria.

Environmental,economic and exergy analysis of separation of ternary azeotrope by variable pressure extractive distillation based on multi-objective optimization

In this work,the ternary azeotrope of tert-butyl alcohol/ethyl acetate/water is separated by extractive distillation(ED)to recover the available constituents and protect the environment.Based on the conductor like shielding model and relative volatility method,ethylene glycol was selected as the extractant in the separation process.In addition,in view of the characteristic that the relative volatility between components changes with pressure,the multi-objective optimization method based on nondominated sorting genetic algorithm II optimizes the pressure and the amount of solvent cooperatively to avoid falling into the optimal local solution.Based on the optimal process parameters,the proposed heat-integrated process can reduce the gas emissions by 29.30%.The heat-integrated ED,further coupled with the pervaporation process,can reduce gas emission by 42.36%and has the highest exergy efficiency of 47.56%.In addition,based on the heat-integrated process,the proposed two heat pump assisted heat-integrated ED processes show good economic and environmental performance.The double heat pump assisted heat-integrated ED can reduce the total annual cost by 28.78%and the gas emissions by 55.83%compared with the basis process,which has a good application prospect.This work provides a feasible approach for the separation of ternary azeotropes.

Management of Strawberry Grey Mold Disease Using Biocontrol Agents and Plant Extracts

Strawberry (Fragaria × ananassa Duch.) is a significant global soft fruit crop, prized for its nutrient content and pleasant flavor. However, diseases, particularly grey mold caused by Botrytis cinerea Pers. Fr. poses major constraints to strawberry production and productivity. Grey mold severely impacts fruit quality and quantity, diminishing market value. This study evaluated five B. cinerea isolates from various locations in the Ri-Bhoi district of Meghalaya. All isolates were pathogenic, with isolate SGM 2 identified as highly virulent. Host range studies showed the pathogen-producing symptoms in the fava bean pods, marigold, gerbera, and chrysanthemum flowers and in the fava bean, gerbera, and lettuce leaves. In vitro tests revealed that neem extract (15% w/v) achieved the highest mycelial growth inhibition at 76.66%, while black turmeric extract (5% w/v) had the lowest inhibition at 9.62%. Dual culture methods with bio-control agents indicated that Bacillus subtilis recorded the highest mean inhibition at 77.03%, while Pseudomonas fluorescens had the lowest at 20.36% against the two virulent isolates. Pot evaluations demonstrated that B. subtilis resulted in the lowest percent disease index at 20.59%, followed by neem extract at 23.31%, with the highest disease index in the control group at 42.51%. Additionally, B. subtilis significantly improved plant growth, yielding an average of 0.32 kg compared to 0.14 kg in the control. The promising results of B. subtilis and neem leaf extract from this study suggest their potential for eco-friendly managing grey mold in strawberries under field conditions.

Phytochemical Analysis and Antioxidant Activity of Aqueous and Hydroethanolic Extracts from Three Anticancerous Fabaceae of Northern Cameroon Pharmacopoeia

Background: Cancer continues to pose a significant threat to our society, representing one of the most pressing health concerns worldwide. This study aimed to evaluate the chemical composition and the antioxidant activity of aqueous and hydroethanolic extracts from Acacia nilotica (An), Bauhinia reticulate (Br), and Tamarindus indica (Ti) of Fabaceae family, traditionally used in Northern Cameroon for cancer treatment. Methods: The phytochemical screening of the three plants was conducted using conventional colorimetric methods, followed by the measurement of total phenol content, flavonoids, and tannins. The antiradical and antioxidant activities of both plant extracts were assessed through FRAP, ABTS, and DPPH methods. A principal components analysis was employed to correlate the quantities of the evaluated secondary metabolites with the activities. Results: Both types of extracts from the three plants contain alkaloids, saponins, flavonoids, phenolic compounds, tannins, glycosides, terpenoids, coumarins, anthocyanins, and anthraquinones. The aqueous extracts of Br and An are significantly richer (p Conclusion: The three Fabaceae plants from northern Cameroon, prepared in different solvents, can be utilized for their antiradical properties in cancer treatment.

Assessing the Efficacy of Lemongrass (Cymbopogon citratus) and Sambong (Blumea balsamifera) Extracts in Combating Black Pod Disease: Sustainable Solutions for Controlling Phytophthora megakarya in Cameroon’s Cocoa Plantations

The use of plant extracts as antifungal agents is gaining increasing attention, particularly for the control of black pod disease in cocoa. Despite extensive research, current strategies haven’t been entirely effective. This study evaluated the effectiveness of Cymbopogon citratus and Blumea balsamifora leaf extracts, both individually and in combination, against Phytophthora megakarya. We assessed the efficacy of the most promising combination (75% B. balsamifera, 25% C. citratus) after storage at room temperature for up to 9 days. Agar microdilution and in vivo bioassays were conducted to determine antifungal susceptibility and effectiveness. Blumea extract exhibited the highest overall inhibitory activity, with the lowest minimum inhibitory concentration (117 µl mL−1) while C. citratus had a narrower range of MIC (146 to 233 µl mL−1). The combination of C. citratus and B. balsamifera demonstrated a synergistic effect against P. megakarya, achieving growth inhibition on V8 media (92.72 ± 4.20% to 100%) and on artificially infected detached pod cortex (92.24 ± 4.53% to 98.75 ± 1.25%), which was not significantly different from the positive control (Ridomil). Furthermore, this combination maintained its effectiveness for up to 9 days at room temperature. These findings suggest that combining plant extracts can enhance their antifungal properties.

Highly selective extraction of aromatics from aliphatics by using metal chloride-based ionic liquids

The separation of aromatics from aliphatics is essential for achieving maximum exploitation of oil resources in the petrochemical industry.In this study,a series of metal chloride-based ionic liquids were prepared and their performances in the separation of 1,2,3,4-tetrahydronaphthalene(tetralin)/dodecane and tetralin/decalin systems were studied.Among these ionic liquids,1-ethyl-3-methylimidazolium tetrachloroferrate([EMIM][FeCl_(4)])with the highest selectivity was used as the extractant.Density functional theory calculations showed that[EMIM][FeCl_(4)]interacted more strongly with tetralin than with dodecane and decalin.Energy decomposition analysis of[EMIM][FeCl_(4)]-tetralin indicated that electrostatics and dispersion played essential roles,and induction cannot be neglected.The van der Waals forces was a main effect in[EMIM][FeCl_(4)]-tetralin by independent gradient model analysis.The tetralin distribution coefficient and selectivity were 0.8 and 110,respectively,with 10%(mol)tetralin in the initial tetralin/dodecane system,and 0.67 and 19.5,respectively,with 10%(mol)tetralin in the initial tetralin/decalin system.The selectivity increased with decreasing alkyl chain length of the extractant.The influence of the extraction temperature,extractant dosage,and initial concentrations of the system components on the separation performance were studied.Recycling experiments showed that the regenerated[EMIM][FeCl_(4)]could be used repeatedly.

Influence of extraction voltage on electron and ion behavior characteristics

The characteristics of the extracted ion current have a significant impact on the design and testing of ion source performance.In this paper,a 2D in space and 3D in velocity space particle in cell(2D3V PIC)method is utilized to simulate plasma motion and ion extraction characteristics under various initial plasma velocity distributions and extraction voltages in a Cartesian coordinate system.The plasma density is of the order of 10^(15)m^(-3)-10^(16)m^(-3)and the extraction voltage is of the order of 100 V-1000 V.The study investigates the impact of various extraction voltages on the velocity and density distributions of electrons and positive ions,and analyzes the influence of different initial plasma velocity distributions on the extraction current.The simulation results reveal that the main reason for the variation of extraction current is the spacecharge force formed by the relative aggregation of positive and negative net charges.This lays the foundation for a deeper understanding of extraction beam characteristics.

Feature extraction and learning approaches for cancellable biometrics:A survey

Biometric recognition is a widely used technology for user authentication.In the application of this technology,biometric security and recognition accuracy are two important issues that should be considered.In terms of biometric security,cancellable biometrics is an effective technique for protecting biometric data.Regarding recognition accuracy,feature representation plays a significant role in the performance and reliability of cancellable biometric systems.How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community,especially from researchers of cancellable biometrics.Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance,while the privacy of biometric data is protected.This survey informs the progress,trend and challenges of feature extraction and learning for cancellable biometrics,thus shedding light on the latest developments and future research of this area.

Chemical profiling of bioactive compounds in the methanolic extract of wild leaf and callus of Vitex negundo using gas chromatographymass spectrometry

BACKGROUND The investigation of plant-based therapeutic agents in medicinal plants has revealed their presence in the extracts and provides the vision to formulate novel techniques for drug therapy.Vitex negundo(V.negundo),a perennial herb belonging to the Varbanaceae family,is extensively used in conventional medication.AIM To determine the existence of therapeutic components in leaf and callus extracts from wild V.negundo plants using gas chromatography-mass spectrometry(GCMS).METHODS In this study,we conducted GC-MS on wild plant leaf extracts and correlated the presence of constituents with those in callus extracts.Various growth regulators such as 6-benzylaminopurine(BAP),2,4-dichlorophenoxyacetic acid(2,4-D),α-naphthylacetic acid(NAA),and di-phenylurea(DPU)were added to plant leaves and in-vitro callus and grown on MS medium.RESULTS The results clearly indicated that the addition of BAP(2.0 mg/L),2,4-D(0.2 mg/mL),DPU(2.0 mg/L)and 2,4-D(0.2 mg/mL)in MS medium resulted in rapid callus development.The plant profile of Vitex extracts by GC-MS analysis showed that 24,10,and 14 bioactive constituents were detected in the methanolic extract of leaf,green callus and the methanolic extract of white loose callus,respectively.CONCLUSION Octadecadienoic acid,hexadecanoic acid and methyl ester were the major constituents in the leaf and callus methanolic extract.Octadecadienoic acid was the most common constituent in all samples.The maximum concentration of octadecadienoic acid in leaves,green callus and white loose callus was 21.93%,47.79%and 40.38%,respectively.These findings demonstrate that the concentration of octadecadienoic acid doubles in-vitro compared to in-vivo.In addition to octadecadienoic acid;butyric acid,benzene,1-methoxy-4-(1-propenyl),dospan,tridecanedialdehyde,methylcyclohexenylbutanol,chlorpyrifos,n-secondary terpene diester,anflunine and other important active compounds were also detected.All these components were only available in callus formed in-vitro.This study showed that the callus contained additional botanical characteristics compared with wild plants.Due to the presence of numerous bioactive compounds,the medical use of Vitex for various diseases has been accepted and the plant is considered an important source of therapeutics for research and development.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Insight into the experiment and extraction mechanism for separating carbazole from anthracene oil with quaternary ammonium-based deep eutectic solvents

Carbazole is an irreplaceable basic organic chemical raw material and intermediate in industry.The separation of carbazole from anthracene oil by environmental benign solvents is important but still a challenge in chemical engineering.Deep eutectic solvents (DESs) as a sustainable green separation solvent have been proposed for the separation of carbazole from model anthracene oil.In this research,three quaternary ammonium-based DESs were prepared using ethylene glycol (EG) as hydrogen bond donor and tetrabutylammonium chloride (TBAC),tetrabutylammonium bromide or choline chloride as hydrogen bond acceptors.To explore their extraction performance of carbazole,the conductor-like screening model for real solvents (COSMO-RS) model was used to predict the activity coefficient at infinite dilution (γ^(∞)) of carbazole in DESs,and the result indicated TBAC:EG (1:2) had the stronger extraction ability for carbazole due to the higher capacity at infinite dilution (C^(∞)) value.Then,the separation performance of these three DESs was evaluated by experiments,and the experimental results were in good agreement with the COSMO-RS prediction results.The TBAC:EG (1:2) was determined as the most promising solvent.Additionally,the extraction conditions of TBAC:EG (1:2) were optimized,and the extraction efficiency,distribution coefficient and selectivity of carbazole could reach up to 85.74%,30.18 and 66.10%,respectively.Moreover,the TBAC:EG (1:2) could be recycled by using environmentally friendly water as antisolvent.In addition,the separation performance of TBAC:EG (1:2) was also evaluated by real crude anthracene,the carbazole was obtained with purity and yield of 85.32%,60.27%,respectively.Lastly,the extraction mechanism was elucidated byσ-profiles and interaction energy analysis.Theoretical calculation results showed that the main driving force for the extraction process was the hydrogen bonding ((N–H...Cl) and van der Waals interactions (C–H...O and C–H...π),which corresponding to the blue and green isosurfaces in IGMH analysis.This work presented a novel method for separating carbazole from crude anthracene oil,and will provide an important reference for the separation of other high value-added products from coal tar.

Feature extraction for machine learning-based intrusion detection in IoT networks

A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have occurred,which led to an active research area for improving NIDS technologies.In an analysis of related works,it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction(FR)and Machine Learning(ML)techniques on NIDS datasets.However,these datasets are different in feature sets,attack types,and network design.Therefore,this paper aims to discover whether these techniques can be generalised across various datasets.Six ML models are utilised:a Deep Feed Forward(DFF),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),Decision Tree(DT),Logistic Regression(LR),and Naive Bayes(NB).The accuracy of three Feature Extraction(FE)algorithms is detected;Principal Component Analysis(PCA),Auto-encoder(AE),and Linear Discriminant Analysis(LDA),are evaluated using three benchmark datasets:UNSW-NB15,ToN-IoT and CSE-CIC-IDS2018.Although PCA and AE algorithms have been widely used,the determination of their optimal number of extracted dimensions has been overlooked.The results indicate that no clear FE method or ML model can achieve the best scores for all datasets.The optimal number of extracted dimensions has been identified for each dataset,and LDA degrades the performance of the ML models on two datasets.The variance is used to analyse the extracted dimensions of LDA and PCA.Finally,this paper concludes that the choice of datasets significantly alters the performance of the applied techniques.We believe that a universal(benchmark)feature set is needed to facilitate further advancement and progress of research in this field.

Extraction,chemical components,bioactive functions and adulteration identification of walnut oils:A review

Walnut oil is a functional wood oil known to researchers that may potentially be a large source of Chinese edible oils.There are various extraction methods for walnut oil,including traditional(pressing,solvent-and enzymeassisted extraction)and novel methods(microwave,ultrasound,supercritical CO_(2),subcritical and other extraction technologies).Walnut oil is rich in nutrients,including phytosterols,tocopherols,polyphenols,squalene and minerals.It provides many health benefits,such as antioxidant,antitumor,anti-inflammatory,antidiabetic and lipid metabolism-related functions.In addition,the authentication of walnut oil has received much research attention.The present review provides detailed research on walnut oil extraction,composition,health benefits and adulteration identification methods.The path toward further walnut oil improvement in the context of the market value of walnut oil is also discussed.