A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various purposes.With that,there have been many discussions about com...A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various purposes.With that,there have been many discussions about commercializing HESS and improving it further.However,the design and sizing process can be overwhelming to comprehend with various sources to examine,and understanding optimal design methodologies is crucial to optimize a HESS design.With that,this review aims to collect and analyse a wide range of HESS studies to summarise recent studies.Two different collections of studies are studied,one was sourced by the main author for preliminary readings,and another was obtained via VOSViewer.The findings from the Web of Science platform were also examined for amore comprehensive understanding.Major findings include the People’sRepublic of China has been active in HESS research,as most works and active organizations originate from this country.HESS has been mainly researched to support power generation and balance load demands,with financial analysis being the common scope of analysis.MATLAB is a common tool used for HESS design,modelling,and optimization as it can handle complex calculations.Artificial neural network(ANN)has the potential to be used to model the HESS,but additional review is required as a formof future work.From a commercialization perspective,pressurized hydrogen tanks are ideal for hydrogen storage in a HESS,but other methods can be considered after additional research and development.From this review,it can be implied that modelling works will be the way forward for HESS research,but extensive collaborations and additional review are needed.Overall,this review summarized various takeaways that future research works on HESS can use.展开更多
In engineering practice,it is often necessary to determine functional relationships between dependent and independent variables.These relationships can be highly nonlinear,and classical regression approaches cannot al...In engineering practice,it is often necessary to determine functional relationships between dependent and independent variables.These relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable solutions.Nevertheless,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely explored.This study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic materials.The ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree Regression(DTR),and Gaussian Process Regression(GPR)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon steel.Although the GPR method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.展开更多
Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants h...Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.展开更多
Purpose–This research aims to investigate how the adhesion performance of GFRP composite components,commonly used in railway vehicles,is affected when bonded to cataphoresis coated steel substrate surfaces.Design/met...Purpose–This research aims to investigate how the adhesion performance of GFRP composite components,commonly used in railway vehicles,is affected when bonded to cataphoresis coated steel substrate surfaces.Design/methodology/approach–In this context,the aim was to determine the optimal adhesion parameters for bonding GFRP samples with natural and primed surfaces to steel samples with cataphoresis coatings.Then,single-lap joint samples with different bond thicknesses of 1 mm,2 mm and 3 mm were prepared.Finally,tensile tests were performed on the samples.Findings–The results showed that GFRP specimens with natural surfaces,characterised by the highest surface roughness,exhibited the lowest bond strength.But,the highest bonding performance was achieved in specimens where primed GFRP was bonded to cataphoresis coated steel,especially with a bond thickness of 1 mm,and achieving a yield strength of 20 MPa.This situation explains the characteristic difference between surface roughness and chemical coating,which are two essential pre-treatments in adhesive bonding.While surface roughness provides mechanical interlocking,excessive roughness can hinder the adhesive’s wetting ability,causing it to remain suspended on the surface as described in the Cassie–Baxter theorem.In contrast,it has been observed that,despite low surface roughness,chemical coatings enhance the bonding between primer paint and adhesive molecules,and–as stated in the Wenzel theorem–improve the surface wettability.Originality/value–As a preliminary preparation in the adhesive method,primer paint is applied to steel surfaces and GFRP material surfaces in classical industrial applications.In this research,the application of the catapheresis process to the steel substrate instead of primer paint and the bonding of primer-painted GFRP materials to this surface make a unique contribution to the research.展开更多
Purpose–This paper aims to offer a novel viewpoint for improving performance and reliability by developing and optimizing suspension components in a Y25 bogie through material optimization based on wheel–rail intera...Purpose–This paper aims to offer a novel viewpoint for improving performance and reliability by developing and optimizing suspension components in a Y25 bogie through material optimization based on wheel–rail interactions under variable load and track conditions.Design/methodology/approach–The suspension system,a critical component ensuring adaptation to road and load conditions in all vehicle types,is especially vital in heavy freight and passenger trains.In this context,the suspension set of the Y25 bogie–commonly used in T€urkiye and Europe–was modelled using CATIAV5,and stress analyses have been performed by way of ANSYS using the finite element analysis(FEA)method.E300-520-M cast steel was selected for the bogie frame,while two different spring steels,61SiCr7 and 51CrV4,were considered for the suspension springs.The modeled system was subjected to numerical analysis under loading conditions.The resulting stresses and displacements were compared with the mechanical properties of the selected materials to validate the design.Findings–The results demonstrate that the mechanical strength and deformation characteristics of the suspension components vary according to the applied external loads.The stress and displacement responses of the system were found to be within the allowable limits of the selected materials,confirming the structural integrity and reliability of the design.The suspension set is deemed suitable for the prescribed material and environmental conditions,suggesting potential for practical application in real-world rail systems.Originality/value–This research contributes to the design and optimization of bogie suspension systems using advanced CAD/CAE tools.It thinks that the material selection and numerical validation approach presented here can guide future designs in heavy load rail applications and potentially improve both safety and performance.展开更多
Purpose–This study examines the effect of increased surface energy on adhesion strength.Surface modifications were made using chemical coating methods such as primer paint(primer)and cataphoresis(KTL,Kathodische Tauc...Purpose–This study examines the effect of increased surface energy on adhesion strength.Surface modifications were made using chemical coating methods such as primer paint(primer)and cataphoresis(KTL,Kathodische Tauchlackierung).The wetting behaviour of adhesive on these surfaces and the resulting contact angles were analysed to evaluate bonding effectiveness.Design/methodology/approach–Primer paint was applied to glass fibre reinforced plastic(GFRP)materials and cataphoresis coating was applied to steel.Contact angles of the coated surfaces were measured and compared to those of the uncoated(natural)surfaces.Findings–Results showed that applying primer to GFRP and KTL to steel increased their surface energy compared to untreated surfaces.A decrease in contact angle correlated with improved wetting,suggesting enhanced adhesion potential.Originality/value–While the effects of surface coatings on adhesion have been studied,there is limited research specifically on the adhesion-enhancing potential of KTL coatings.Typically used for corrosion resistance,KTL is shown here to also improve adhesion.The novelty lies in experimentally demonstrating KTL’s dual role as both a protective and adhesion-enhancing layer.展开更多
[Objective]Mental health is the essence of physical health,human beings pay more and more attention to the study of mental health recovery and after many studies,it is clear that the restorative environment has an imp...[Objective]Mental health is the essence of physical health,human beings pay more and more attention to the study of mental health recovery and after many studies,it is clear that the restorative environment has an important and positive significance for their mental recovery,and species as an important part of the environment since the natural environment has been used as an essential part of the research environment,based on the conditions of such a social reality,this paper analyzed the articles on species surveys in the last 30 years,used the data to reflect the importance of species survey,and the research hotspot of restorative environment.[Methods]The study analyzed the data in articles about species survey in CNKI database from 1994 to 2024 through Citespace visualization,and analyzed the data through the number of articles issued between years,keyword co-occurrence and other aspects,so as to give data support for the research of restorative environment.[Results]In the past 30 years,the number of articles published on species survey has increased year by year,and species survey is at the forefront of research hotspots.Clustering and timeline analysis results of insects,birds,diversity has become more important.[Conclusions]From the 621 articles,the following aspects could be concluded:(1)The importance of restorative environments research and the vast exchanges among scholars have been reflected and more research hotspots have been explored in this field;(2)For the research direction of restorative environments and this paper,the research hotspots were in line with the in-depth exploration of species diversity,which was not only in the field of species,but also in the field of health and the environment,and there were also investigations of the links;(3)The interdependence between species diversity and restorative environments was high,further research on restorative environments largely depended on the study of species surveys.展开更多
The paper deals with the FEM(Finite Element Method)simulation of rotary swaging of Dievar alloy produced by additive manufacturing technology Selective Laser Melting and conventional process.Swaging was performed at a...The paper deals with the FEM(Finite Element Method)simulation of rotary swaging of Dievar alloy produced by additive manufacturing technology Selective Laser Melting and conventional process.Swaging was performed at a temperature of 900℃.True flow stress-strain curves were determined for 600℃–900℃and used to construct a Hensel-Spittel model for FEM simulation.The process parameters,i.e.,stress,temperature,imposed strain,and force,were investigation during the rotary swaging process.Firstly,the stresses induced during rotary swaging and the resistance of the material to deformation were investigated.The amount and distribution of imposed strain in the cross-section can serve as a valuable indicator of the reduction in porosity and the texture evolution of the material.The simulation revealed the force required to swag the Dievar alloy.It also showed the evolution of temperature,which is important for phase transformation during solidification.Furthermore,microstructure evolutionwas observed before and then after rotary swaging.Dievar alloy is a critical material in the manufacture of dies for high-pressure die casting,forging tools,and other equipment subjected to high temperatures and mechanical loads.Understanding its viscoelastoplastic behavior under rotary swaging conditions is essential to optimize its performance in these demanding industrial applications.展开更多
In the effort to enhance cardiovascular diagnostics,deep learning-based heart sound classification presents a promising solution.This research introduces a novel preprocessing method:iterative k-means clustering combi...In the effort to enhance cardiovascular diagnostics,deep learning-based heart sound classification presents a promising solution.This research introduces a novel preprocessing method:iterative k-means clustering combined with silhouette score analysis,aimed at downsampling.This approach ensures optimal cluster formation and improves data quality for deep learning models.The process involves applying k-means clustering to the dataset,calculating the average silhouette score for each cluster,and selecting the clusterwith the highest score.We evaluated this method using 10-fold cross-validation across various transfer learningmodels fromdifferent families and architectures.The evaluation was conducted on four datasets:a binary dataset,an augmented binary dataset,amulticlass dataset,and an augmentedmulticlass dataset.All datasets were derived from the Heart Wave heart sounds dataset,a novelmulticlass dataset introduced by our research group.To increase dataset sizes and improve model training,data augmentation was performed using heartbeat cycle segmentation.Our findings highlight the significant impact of the proposed preprocessing approach on the HeartWave datasets.Across all datasets,model performance improved notably with the application of our method.In augmented multiclass classification,the MobileNetV2 model showed an average weighted F1-score improvement of 27.10%.In binary classification,ResNet50 demonstrated an average accuracy improvement of 8.70%,reaching 92.40%compared to its baseline performance.These results underscore the effectiveness of clustering with silhouette score analysis as a preprocessing step,significantly enhancing model accuracy and robustness.They also emphasize the critical role of preprocessing in addressing class imbalance and advancing precision medicine in cardiovascular diagnostics.展开更多
Plastometric experiments,supplemented with numerical simulations using the finite element method(FEM),can be advantageously used to characterize the deformation behavior of metallic materials.The accuracy of such simu...Plastometric experiments,supplemented with numerical simulations using the finite element method(FEM),can be advantageously used to characterize the deformation behavior of metallic materials.The accuracy of such simulations predicting deformation behaviors of materials is,however,primarily affected by the applied rheology law.The presented study focuses on the characterization of the deformation behavior of AISI 1045 type carbon steel,widely used e.g.,in automotive and power engineering,under extreme conditions(i.e.,high temperatures,strain rates).The study consists of two main parts:experimentally analyzing the flow stress development of the steel under different thermomechanical conditions via uniaxial hot compression tests and establishing the rheology law via numerical simulations implementing the experimentally acquired flow stress curves.The numerical simulations then not only serve to establish the rheology law but also to verify the reliability of the selected experimental process.The results of the numerical simulations showed that the established rheology law characterizes the behavior of the investigated steel with sufficient accuracy also at high temperatures and/or strain rates,and can,therefore,be used for practical purposes.Last but not least,supplementary microstructure analyses performed for the samples subjected to the highest deformation temperature provided a deeper insight into the effects of the applied(extreme)thermomechanical conditions on the behavior of the investigated steel.展开更多
A stepwise pretreatment process for coconut dregs(CD)has been investigated to enhance availability of hemicellulose.Recently,lignocellulose-rich agricultural waste such as CD has garnered substantial attention as a su...A stepwise pretreatment process for coconut dregs(CD)has been investigated to enhance availability of hemicellulose.Recently,lignocellulose-rich agricultural waste such as CD has garnered substantial attention as a sustainable raw material for producing value-added bio-products.To optimize the process variables within the stepwise pretreatment using Pulsed Electric Field(PEF)and Solid-State Fermentation(SSF),Response Surface Methodology(RSM)based on Central Composite Design(CCD)was employed.PEF,a non-thermal physical treatment,offers advantages such as low energy consumption and reduced processing times,while SSF utilizes Pleurotus ostreatus to promote biodegradation.A statistical model was constructed using a three-factor CCD that included five center points and axial points,with variables including PEF treatment duration(30,60,and 90 s),substrate particle size(20,40,and 60 mesh),and incubation time(10,20,and 30 days).Changes in lignocellulose composition were analyzed to evaluate their effects on the process.The optimal parameters identified were a particle size of 40 mesh,a PEF treatment duration of 61 s,and an incubation period of 12.5 days.Under these conditions,the process yielded an impressive increase in hemicellulose availability by 106.53%,a minimization of cellulose loss to 6.28%,and a successful delignification resulting in a 21.78%removal of lignin.展开更多
Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malwar...Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malware detection techniques need to be more efficient in detecting new and progressively sophisticated variants of malware.Therefore,the development of more advanced and accurate techniques is necessary for malware detection.This paper introduces a comprehensive Dual-Channel Attention Deep Bidirectional Long Short-Term Memory(DCADBiLSTM)model for malware detection and riskmitigation.The Dual Channel Attention(DCA)mechanism improves themodel’s capability to concentrate on the features that aremost appropriate in the input data,which reduces the false favourable rates.The Bidirectional Long,Short-Term Memory framework helps capture crucial interdependence from past and future circumstances,which is essential for enhancing the model’s understanding of malware behaviour.As soon as malware is detected,the risk mitigation phase is implemented,which evaluates the severity of each threat and helps mitigate threats earlier.The outcomes of the method demonstrate better accuracy of 98.96%,which outperforms traditional models.It indicates the method detects and mitigates several kinds of malware threats,thereby providing a proactive defence mechanism against the emerging challenges in cybersecurity.展开更多
The dynamic behavior of high-speed craft navigating through variable sea states plays a pivotal role in ensuring maritime safety.However,many existing simulation approaches rely on linear or overly simplified represen...The dynamic behavior of high-speed craft navigating through variable sea states plays a pivotal role in ensuring maritime safety.However,many existing simulation approaches rely on linear or overly simplified representations of the marine environment,thereby limiting the fidelity of motion predictions.This study explores the motion characteristics of a 4.5-t high-speed vessel by conducting fully coupled numerical simulations using the STAR-CCM+software.The analysis considers both calm and varying sea conditions,incorporating fluctuations in wave height,wavelength,and wind speed to reflect more realistic operating scenarios.Simulation results reveal that the vessel’s hydrodynamic response is highly sensitive to changes in sea state.As conditions deteriorate,the free surface becomes increasingly complex,with higher wave amplitudes and more pronounced interactions between the waves generated by the vessel and those imposed by the external environment.These effects lead to significant increases in roll,pitch,heave,and sway motions,thereby imposing greater demands on the vessel’s dynamic stability and operational safety.Furthermore,both hydrodynamic resistance and propulsive thrust exhibit notable dependence on sea state and vessel speed.Total resistance generally increases with rougher sea conditions,while thrust tends to rise with increasing forward speed.Under calm or mildly disturbed waters,a Froude number(Fr)of 0.5 appears to offer an optimal balance for initiating and controlling primary motions such as roll,pitch,heave,and sway.Conversely,in more challenging conditions-such as those represented by a Sea State 3-effective motion control is better achieved at a higher Froude number of approximately 1.0.展开更多
The prosthesis is an artificial device that can replace an organ of a human body member to restore a compromised function. It is necessary following the removal of a human organ, which can occur as a result of an illn...The prosthesis is an artificial device that can replace an organ of a human body member to restore a compromised function. It is necessary following the removal of a human organ, which can occur as a result of an illness, trauma or congenital malformation. The trans-tibia prosthesis, in particular, allows the amputee patient to recover the impaired function and regain autonomy, while facilitating their daily social integration. The trans-tibia prosthesis consists of a socket, a sleeve, connecting elements and a prosthetic foot. Each of these components plays a very important role. Among these components, the prosthetic foot usually called “SACH foot” is very often replaced due to cracking and therefore has a fairly short lifespan. At the Center for Equipment and Rehabilitation of Kabalaye (CERK), the SACH foot made using polyurethane and wood is imported and is given to patients with reduced mobility. The aim of this article is twofold, on the one hand, to make a social and pathological study of trans-tibia amputees in relation to the use of the SACH foot prosthesis, on the other hand, to compare this foot with a new prosthetic foot proposed and which is manufactured using extruded polystyrene. The result of prosthetic tests carried out on twenty-four amputees showed that the foot manufactured using extruded polystyrene is better in terms of resistance, bulk and adaptability to active amputees.展开更多
Polymeric materials,known for their lightweight and strength,are widely used today.However,their non-biodegradable nature poses significant environmental challenges.This research aimed to develop biodegradable films f...Polymeric materials,known for their lightweight and strength,are widely used today.However,their non-biodegradable nature poses significant environmental challenges.This research aimed to develop biodegradable films from fruits and vegetables,using alginate as a binding agent.Using a completely randomized design,seven experimental sets were prepared with carrots,Kimju guava,and Namwa banana peel fibers as the primary materials and alginate as the secondary material at three levels:1.2,1.8,and 2.4 by weight.The solution technique was employed to create the samples.Upon testing mechanical and physical properties,experimental set 3,consisting of 60%guava and 1.8%alginate,emerged as the optimal ratio.This combination exhibited favorable physical properties,including a thickness of 0.26±0.02 mm,meeting the standards for food packaging films.Additionally,the tensile strength was 0.50±0.01 N/m²,and the elongation at break was 55.60±0.44%.Regarding chemical properties,the moisture content of 5.64±0.03%fell within the acceptable range for dried food.Furthermore,a 30-day soil burial test revealed that the sample from experimental set 3 exhibited the highest degradation rate.In conclusion,these findings suggest that guava can be a promising raw material for producing biodegradable plastics suitable for packaging applications.展开更多
Pectin is a natural polysaccharide with a complex structure consisting of linear and branched regions rich in galacturonic acid.The growing interest in orange peel pectin can be attributed to its abundant supply.Accor...Pectin is a natural polysaccharide with a complex structure consisting of linear and branched regions rich in galacturonic acid.The growing interest in orange peel pectin can be attributed to its abundant supply.According to statistics,about 10 million tons of orange peel waste are produced worldwide each year.Traditionally,the extraction and utilization of pectin have focused on its gelling,thickening,and stabilizing properties in food.However,as more and more research teams have found that pectin has good biocompatibility,biodegradability and easy chemical modification,its potential in drug delivery systems,tissue engineering,and wound healing is gradually being explored.This review focuses on orange peel pectin polysaccharides and discusses its traditional and modern extraction techniques,especially the advanced method of subcritical water extraction.This study also outlines the structural modifications of pectin such as methylation and acetylation,and introduces its antioxidant and anticancer biological activities and their emerging roles in the development of advanced biomaterials such as bone tissue engineering and fibre pad dressings.展开更多
Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps...Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.展开更多
Protein fibers derived from silk fibroin(SF)were chemically extracted and purified from cocoons.It was used as a reinforced fiber for hydrogel formation with collagen(Col)and hyaluronic acid(HA).Calcium chloride(8 wt....Protein fibers derived from silk fibroin(SF)were chemically extracted and purified from cocoons.It was used as a reinforced fiber for hydrogel formation with collagen(Col)and hyaluronic acid(HA).Calcium chloride(8 wt.%)was employed as a crosslinking reagent to synthesize the SF/Col/HA-based hydrogel composite.FTIR spec-troscopy confirmed the presence of N-H stretching due to the plane bending of amide II in theβ-sheet structure.XRD analysis confirmed the crystallinity of the SF/Col/HA-based hydrogel composite.Scanning electron mi-croscopy revealed three-dimensional porous structures with interconnected pores.These porous structures can serve as reservoirs for storing adsorbent media.The hydrogel composite was thermally stable at 250℃.The lowboiling bound solvent evaporation temperature,glass transition temperature,and degradation temperature were 102℃-105℃,298℃-300℃,and 524℃-545℃,respectively.The ranges of porosity and gel fraction were 60%-80%and 90%-95%,respectively.The hydrogel composite was rapidly swollen within 1 h,reaching a plateau afterward.The compressive strength was 4-6 MPa.As absorbent media,hydrogels can easily adhere to lead ions via electrostatic interactions.They can be used as reservoirs for the adsorption of heavy metals.展开更多
Targeted cancer therapy has emerged as a promising alternative to conventional chemotherapy,which is often plagued by poor selectivity,off-target effects,and drug resistance.Among the various targeting agents in devel...Targeted cancer therapy has emerged as a promising alternative to conventional chemotherapy,which is often plagued by poor selectivity,off-target effects,and drug resistance.Among the various targeting agents in development,peptides stand out for their unique advantages,including minimal immunogenicity,high tissue penetration,and ease of modification.Their small size,specificity,and flexibility allow them to target cancer cells while minimizing damage to healthy tissue selectively.Peptide-based therapies have shown great potential in enhancing the efficacy of drug delivery,improving tumor imaging,and reducing adverse effects.With cancer responsible for millions of deaths worldwide,the development of peptide-based therapeutics offers new hope in addressing the limitations of current treatments.As detailed studies on different aspects of targeting peptides are crucial for optimizing drug development,this review provides a comprehensive overview of the literature on tumor-targeting peptides,including their structure,sources,modes of action,and their application in cancer therapy—both as standalone agents and in fusion drugs.Additionally,various computational tools for peptide-based tumor-targeting drug design and validation are explored.The promising results from these studies highlight peptides as ideal candidates for targeted cancer therapies,offering valuable insights for researchers and accelerating the discovery of novel anti-tumor peptide base drug candidates.展开更多
Background:Liver injury often occurs but with limited drugs.Chaenomeles has a potent hepatoprotective effect,while the ability of Chaenomeles speciosa and Chaenomeles sinensis to treat liver injury in rats is unexplor...Background:Liver injury often occurs but with limited drugs.Chaenomeles has a potent hepatoprotective effect,while the ability of Chaenomeles speciosa and Chaenomeles sinensis to treat liver injury in rats is unexplored.Methods:The study involved 30 rats divided into five groups:negative control(NC),model control(MC),positive control(PC),Chaenomeles speciosa-delivered(ZP),and Chaenomeles sinensis-delivered(GP).Fecal samples from all groups were collected 24 h post-modeling for intestinal flora analysis.All rats were collected serum and liver tissues for biochemical and histopathological examinations,among other experiments.Chaenomeles would be effective in CCl4-induced liver injury in rats by analyzing the efficacy and mechanism and examining the differences between Chaenomeles speciosa and Chaenomeles sinensis through oxidative stress,inflammation,and apoptosis pathways.Then,we resolved the mechanism of action in the context of the intestinal flora.Results:The results showed that Chaenomeles intake improved the degree of CCl4-induced liver injury,decreased aspartate aminotransferase,alanine aminotransferase,and alkaline phosphatase levels,and increased total protein and total bilirubin levels.Noteworthy,the glutathione level in the GP group surpassed that a 1.5-fold increase compared to the PC group.Chaenomeles speciosa could exert its efficacy by regulating inflammatory and apoptotic pathways,while Chaenomeles speciosa did so through the oxidative stress pathway.In addition,Chaenomeles are both able to modulate intestinal flora and change the ratio of flora.Chaenomeles speciosa could regulate probiotics and prevent liver injury by altering the distribution and ratio of intestinal flora.Specifically,Lactobacillaceae in the ZP group exhibited 10-fold higher abundance than the other groups.Chaenomeles speciosa increased the abundance of probiotic Clostridiales butyricum in diseased rats,while Chaenomeles sinensis increased the abundance of pathogenic Escherichia Shigella.Conclusion:This study suggests that Chaenomeles may be hepatoprotective by oxidative stress,inflammation,and apoptosis pathways and modulating the composition and function of the intestinal flora.展开更多
文摘A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various purposes.With that,there have been many discussions about commercializing HESS and improving it further.However,the design and sizing process can be overwhelming to comprehend with various sources to examine,and understanding optimal design methodologies is crucial to optimize a HESS design.With that,this review aims to collect and analyse a wide range of HESS studies to summarise recent studies.Two different collections of studies are studied,one was sourced by the main author for preliminary readings,and another was obtained via VOSViewer.The findings from the Web of Science platform were also examined for amore comprehensive understanding.Major findings include the People’sRepublic of China has been active in HESS research,as most works and active organizations originate from this country.HESS has been mainly researched to support power generation and balance load demands,with financial analysis being the common scope of analysis.MATLAB is a common tool used for HESS design,modelling,and optimization as it can handle complex calculations.Artificial neural network(ANN)has the potential to be used to model the HESS,but additional review is required as a formof future work.From a commercialization perspective,pressurized hydrogen tanks are ideal for hydrogen storage in a HESS,but other methods can be considered after additional research and development.From this review,it can be implied that modelling works will be the way forward for HESS research,but extensive collaborations and additional review are needed.Overall,this review summarized various takeaways that future research works on HESS can use.
基金supported by the SP2024/089 Project by the Faculty of Materials Science and Technology,VˇSB-Technical University of Ostrava.
文摘In engineering practice,it is often necessary to determine functional relationships between dependent and independent variables.These relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable solutions.Nevertheless,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely explored.This study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic materials.The ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree Regression(DTR),and Gaussian Process Regression(GPR)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon steel.Although the GPR method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.
基金supported by the key project at the central government level:The ability establishment of sustainable use for valuable Chinese medicine resources(Grant number 2060302)the National Natural Science Foundation of China(Grant number 82373982,82173929).
文摘Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.
文摘Purpose–This research aims to investigate how the adhesion performance of GFRP composite components,commonly used in railway vehicles,is affected when bonded to cataphoresis coated steel substrate surfaces.Design/methodology/approach–In this context,the aim was to determine the optimal adhesion parameters for bonding GFRP samples with natural and primed surfaces to steel samples with cataphoresis coatings.Then,single-lap joint samples with different bond thicknesses of 1 mm,2 mm and 3 mm were prepared.Finally,tensile tests were performed on the samples.Findings–The results showed that GFRP specimens with natural surfaces,characterised by the highest surface roughness,exhibited the lowest bond strength.But,the highest bonding performance was achieved in specimens where primed GFRP was bonded to cataphoresis coated steel,especially with a bond thickness of 1 mm,and achieving a yield strength of 20 MPa.This situation explains the characteristic difference between surface roughness and chemical coating,which are two essential pre-treatments in adhesive bonding.While surface roughness provides mechanical interlocking,excessive roughness can hinder the adhesive’s wetting ability,causing it to remain suspended on the surface as described in the Cassie–Baxter theorem.In contrast,it has been observed that,despite low surface roughness,chemical coatings enhance the bonding between primer paint and adhesive molecules,and–as stated in the Wenzel theorem–improve the surface wettability.Originality/value–As a preliminary preparation in the adhesive method,primer paint is applied to steel surfaces and GFRP material surfaces in classical industrial applications.In this research,the application of the catapheresis process to the steel substrate instead of primer paint and the bonding of primer-painted GFRP materials to this surface make a unique contribution to the research.
文摘Purpose–This paper aims to offer a novel viewpoint for improving performance and reliability by developing and optimizing suspension components in a Y25 bogie through material optimization based on wheel–rail interactions under variable load and track conditions.Design/methodology/approach–The suspension system,a critical component ensuring adaptation to road and load conditions in all vehicle types,is especially vital in heavy freight and passenger trains.In this context,the suspension set of the Y25 bogie–commonly used in T€urkiye and Europe–was modelled using CATIAV5,and stress analyses have been performed by way of ANSYS using the finite element analysis(FEA)method.E300-520-M cast steel was selected for the bogie frame,while two different spring steels,61SiCr7 and 51CrV4,were considered for the suspension springs.The modeled system was subjected to numerical analysis under loading conditions.The resulting stresses and displacements were compared with the mechanical properties of the selected materials to validate the design.Findings–The results demonstrate that the mechanical strength and deformation characteristics of the suspension components vary according to the applied external loads.The stress and displacement responses of the system were found to be within the allowable limits of the selected materials,confirming the structural integrity and reliability of the design.The suspension set is deemed suitable for the prescribed material and environmental conditions,suggesting potential for practical application in real-world rail systems.Originality/value–This research contributes to the design and optimization of bogie suspension systems using advanced CAD/CAE tools.It thinks that the material selection and numerical validation approach presented here can guide future designs in heavy load rail applications and potentially improve both safety and performance.
基金supported by the Sakarya University of Applied Sciences-Scientific Research Projects Coordination in the scope of master’s thesis Project under project number 285–2025.
文摘Purpose–This study examines the effect of increased surface energy on adhesion strength.Surface modifications were made using chemical coating methods such as primer paint(primer)and cataphoresis(KTL,Kathodische Tauchlackierung).The wetting behaviour of adhesive on these surfaces and the resulting contact angles were analysed to evaluate bonding effectiveness.Design/methodology/approach–Primer paint was applied to glass fibre reinforced plastic(GFRP)materials and cataphoresis coating was applied to steel.Contact angles of the coated surfaces were measured and compared to those of the uncoated(natural)surfaces.Findings–Results showed that applying primer to GFRP and KTL to steel increased their surface energy compared to untreated surfaces.A decrease in contact angle correlated with improved wetting,suggesting enhanced adhesion potential.Originality/value–While the effects of surface coatings on adhesion have been studied,there is limited research specifically on the adhesion-enhancing potential of KTL coatings.Typically used for corrosion resistance,KTL is shown here to also improve adhesion.The novelty lies in experimentally demonstrating KTL’s dual role as both a protective and adhesion-enhancing layer.
基金Sponsored by The 2024 Inter-university Cooperation Project for Innovation and Entrepreneurship Training of College Students in Beijing Universities(202498025)National Natural Science Foundation of China(NSFC)(52278045).
文摘[Objective]Mental health is the essence of physical health,human beings pay more and more attention to the study of mental health recovery and after many studies,it is clear that the restorative environment has an important and positive significance for their mental recovery,and species as an important part of the environment since the natural environment has been used as an essential part of the research environment,based on the conditions of such a social reality,this paper analyzed the articles on species surveys in the last 30 years,used the data to reflect the importance of species survey,and the research hotspot of restorative environment.[Methods]The study analyzed the data in articles about species survey in CNKI database from 1994 to 2024 through Citespace visualization,and analyzed the data through the number of articles issued between years,keyword co-occurrence and other aspects,so as to give data support for the research of restorative environment.[Results]In the past 30 years,the number of articles published on species survey has increased year by year,and species survey is at the forefront of research hotspots.Clustering and timeline analysis results of insects,birds,diversity has become more important.[Conclusions]From the 621 articles,the following aspects could be concluded:(1)The importance of restorative environments research and the vast exchanges among scholars have been reflected and more research hotspots have been explored in this field;(2)For the research direction of restorative environments and this paper,the research hotspots were in line with the in-depth exploration of species diversity,which was not only in the field of species,but also in the field of health and the environment,and there were also investigations of the links;(3)The interdependence between species diversity and restorative environments was high,further research on restorative environments largely depended on the study of species surveys.
基金funded by the project SP2024/089 of the Specific Research of the VŠB-Technical University of Ostrava and realized within the framework of the Johannes Amos Comenius Program,Materials and Technologies for Sustainable Development-MATUR,No.CZ.02.01.01/00/22_008/0004631Brno University of Technology project No.FSI-S-23-8231“Investigation of Dynamic Deformation Behavior ofMetallicMaterials Prepared via Alternative Production Methods”.
文摘The paper deals with the FEM(Finite Element Method)simulation of rotary swaging of Dievar alloy produced by additive manufacturing technology Selective Laser Melting and conventional process.Swaging was performed at a temperature of 900℃.True flow stress-strain curves were determined for 600℃–900℃and used to construct a Hensel-Spittel model for FEM simulation.The process parameters,i.e.,stress,temperature,imposed strain,and force,were investigation during the rotary swaging process.Firstly,the stresses induced during rotary swaging and the resistance of the material to deformation were investigated.The amount and distribution of imposed strain in the cross-section can serve as a valuable indicator of the reduction in porosity and the texture evolution of the material.The simulation revealed the force required to swag the Dievar alloy.It also showed the evolution of temperature,which is important for phase transformation during solidification.Furthermore,microstructure evolutionwas observed before and then after rotary swaging.Dievar alloy is a critical material in the manufacture of dies for high-pressure die casting,forging tools,and other equipment subjected to high temperatures and mechanical loads.Understanding its viscoelastoplastic behavior under rotary swaging conditions is essential to optimize its performance in these demanding industrial applications.
基金supported by the Deanship of Scientific Research(DSR),King Abdulaziz University,Jeddah,under grant No.IPP:533-611-2025DSR technical and financial support.
文摘In the effort to enhance cardiovascular diagnostics,deep learning-based heart sound classification presents a promising solution.This research introduces a novel preprocessing method:iterative k-means clustering combined with silhouette score analysis,aimed at downsampling.This approach ensures optimal cluster formation and improves data quality for deep learning models.The process involves applying k-means clustering to the dataset,calculating the average silhouette score for each cluster,and selecting the clusterwith the highest score.We evaluated this method using 10-fold cross-validation across various transfer learningmodels fromdifferent families and architectures.The evaluation was conducted on four datasets:a binary dataset,an augmented binary dataset,amulticlass dataset,and an augmentedmulticlass dataset.All datasets were derived from the Heart Wave heart sounds dataset,a novelmulticlass dataset introduced by our research group.To increase dataset sizes and improve model training,data augmentation was performed using heartbeat cycle segmentation.Our findings highlight the significant impact of the proposed preprocessing approach on the HeartWave datasets.Across all datasets,model performance improved notably with the application of our method.In augmented multiclass classification,the MobileNetV2 model showed an average weighted F1-score improvement of 27.10%.In binary classification,ResNet50 demonstrated an average accuracy improvement of 8.70%,reaching 92.40%compared to its baseline performance.These results underscore the effectiveness of clustering with silhouette score analysis as a preprocessing step,significantly enhancing model accuracy and robustness.They also emphasize the critical role of preprocessing in addressing class imbalance and advancing precision medicine in cardiovascular diagnostics.
文摘Plastometric experiments,supplemented with numerical simulations using the finite element method(FEM),can be advantageously used to characterize the deformation behavior of metallic materials.The accuracy of such simulations predicting deformation behaviors of materials is,however,primarily affected by the applied rheology law.The presented study focuses on the characterization of the deformation behavior of AISI 1045 type carbon steel,widely used e.g.,in automotive and power engineering,under extreme conditions(i.e.,high temperatures,strain rates).The study consists of two main parts:experimentally analyzing the flow stress development of the steel under different thermomechanical conditions via uniaxial hot compression tests and establishing the rheology law via numerical simulations implementing the experimentally acquired flow stress curves.The numerical simulations then not only serve to establish the rheology law but also to verify the reliability of the selected experimental process.The results of the numerical simulations showed that the established rheology law characterizes the behavior of the investigated steel with sufficient accuracy also at high temperatures and/or strain rates,and can,therefore,be used for practical purposes.Last but not least,supplementary microstructure analyses performed for the samples subjected to the highest deformation temperature provided a deeper insight into the effects of the applied(extreme)thermomechanical conditions on the behavior of the investigated steel.
基金funded by BIMA from Ministry of Education,Culture,Research and Technology,grant number 045/E5/PG.02.00.PL/2024,with derivative contracts 00309.54/UN10.A0501/BT.01.03.2/2024.
文摘A stepwise pretreatment process for coconut dregs(CD)has been investigated to enhance availability of hemicellulose.Recently,lignocellulose-rich agricultural waste such as CD has garnered substantial attention as a sustainable raw material for producing value-added bio-products.To optimize the process variables within the stepwise pretreatment using Pulsed Electric Field(PEF)and Solid-State Fermentation(SSF),Response Surface Methodology(RSM)based on Central Composite Design(CCD)was employed.PEF,a non-thermal physical treatment,offers advantages such as low energy consumption and reduced processing times,while SSF utilizes Pleurotus ostreatus to promote biodegradation.A statistical model was constructed using a three-factor CCD that included five center points and axial points,with variables including PEF treatment duration(30,60,and 90 s),substrate particle size(20,40,and 60 mesh),and incubation time(10,20,and 30 days).Changes in lignocellulose composition were analyzed to evaluate their effects on the process.The optimal parameters identified were a particle size of 40 mesh,a PEF treatment duration of 61 s,and an incubation period of 12.5 days.Under these conditions,the process yielded an impressive increase in hemicellulose availability by 106.53%,a minimization of cellulose loss to 6.28%,and a successful delignification resulting in a 21.78%removal of lignin.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant No.(IPP:421-611-2025).
文摘Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malware detection techniques need to be more efficient in detecting new and progressively sophisticated variants of malware.Therefore,the development of more advanced and accurate techniques is necessary for malware detection.This paper introduces a comprehensive Dual-Channel Attention Deep Bidirectional Long Short-Term Memory(DCADBiLSTM)model for malware detection and riskmitigation.The Dual Channel Attention(DCA)mechanism improves themodel’s capability to concentrate on the features that aremost appropriate in the input data,which reduces the false favourable rates.The Bidirectional Long,Short-Term Memory framework helps capture crucial interdependence from past and future circumstances,which is essential for enhancing the model’s understanding of malware behaviour.As soon as malware is detected,the risk mitigation phase is implemented,which evaluates the severity of each threat and helps mitigate threats earlier.The outcomes of the method demonstrate better accuracy of 98.96%,which outperforms traditional models.It indicates the method detects and mitigates several kinds of malware threats,thereby providing a proactive defence mechanism against the emerging challenges in cybersecurity.
基金funded by the National College Students Innovation and Entrepreneurship Training Program(202411646031)the Zhejiang Xinmiao Talents Program(2024R405A052)the SRIP Research Program of Ningbo University(2025SRIP1707).
文摘The dynamic behavior of high-speed craft navigating through variable sea states plays a pivotal role in ensuring maritime safety.However,many existing simulation approaches rely on linear or overly simplified representations of the marine environment,thereby limiting the fidelity of motion predictions.This study explores the motion characteristics of a 4.5-t high-speed vessel by conducting fully coupled numerical simulations using the STAR-CCM+software.The analysis considers both calm and varying sea conditions,incorporating fluctuations in wave height,wavelength,and wind speed to reflect more realistic operating scenarios.Simulation results reveal that the vessel’s hydrodynamic response is highly sensitive to changes in sea state.As conditions deteriorate,the free surface becomes increasingly complex,with higher wave amplitudes and more pronounced interactions between the waves generated by the vessel and those imposed by the external environment.These effects lead to significant increases in roll,pitch,heave,and sway motions,thereby imposing greater demands on the vessel’s dynamic stability and operational safety.Furthermore,both hydrodynamic resistance and propulsive thrust exhibit notable dependence on sea state and vessel speed.Total resistance generally increases with rougher sea conditions,while thrust tends to rise with increasing forward speed.Under calm or mildly disturbed waters,a Froude number(Fr)of 0.5 appears to offer an optimal balance for initiating and controlling primary motions such as roll,pitch,heave,and sway.Conversely,in more challenging conditions-such as those represented by a Sea State 3-effective motion control is better achieved at a higher Froude number of approximately 1.0.
文摘The prosthesis is an artificial device that can replace an organ of a human body member to restore a compromised function. It is necessary following the removal of a human organ, which can occur as a result of an illness, trauma or congenital malformation. The trans-tibia prosthesis, in particular, allows the amputee patient to recover the impaired function and regain autonomy, while facilitating their daily social integration. The trans-tibia prosthesis consists of a socket, a sleeve, connecting elements and a prosthetic foot. Each of these components plays a very important role. Among these components, the prosthetic foot usually called “SACH foot” is very often replaced due to cracking and therefore has a fairly short lifespan. At the Center for Equipment and Rehabilitation of Kabalaye (CERK), the SACH foot made using polyurethane and wood is imported and is given to patients with reduced mobility. The aim of this article is twofold, on the one hand, to make a social and pathological study of trans-tibia amputees in relation to the use of the SACH foot prosthesis, on the other hand, to compare this foot with a new prosthetic foot proposed and which is manufactured using extruded polystyrene. The result of prosthetic tests carried out on twenty-four amputees showed that the foot manufactured using extruded polystyrene is better in terms of resistance, bulk and adaptability to active amputees.
基金funding from the Environmental Science Program for Academic Excellence and Community Research for Fiscal Year 2024,a financial resource of the Environmental Science and Technology Program,Faculty of Science,Buriram Rajabhat University.Additionally,Buriram Rajabhat University provided a publication budget.
文摘Polymeric materials,known for their lightweight and strength,are widely used today.However,their non-biodegradable nature poses significant environmental challenges.This research aimed to develop biodegradable films from fruits and vegetables,using alginate as a binding agent.Using a completely randomized design,seven experimental sets were prepared with carrots,Kimju guava,and Namwa banana peel fibers as the primary materials and alginate as the secondary material at three levels:1.2,1.8,and 2.4 by weight.The solution technique was employed to create the samples.Upon testing mechanical and physical properties,experimental set 3,consisting of 60%guava and 1.8%alginate,emerged as the optimal ratio.This combination exhibited favorable physical properties,including a thickness of 0.26±0.02 mm,meeting the standards for food packaging films.Additionally,the tensile strength was 0.50±0.01 N/m²,and the elongation at break was 55.60±0.44%.Regarding chemical properties,the moisture content of 5.64±0.03%fell within the acceptable range for dried food.Furthermore,a 30-day soil burial test revealed that the sample from experimental set 3 exhibited the highest degradation rate.In conclusion,these findings suggest that guava can be a promising raw material for producing biodegradable plastics suitable for packaging applications.
文摘Pectin is a natural polysaccharide with a complex structure consisting of linear and branched regions rich in galacturonic acid.The growing interest in orange peel pectin can be attributed to its abundant supply.According to statistics,about 10 million tons of orange peel waste are produced worldwide each year.Traditionally,the extraction and utilization of pectin have focused on its gelling,thickening,and stabilizing properties in food.However,as more and more research teams have found that pectin has good biocompatibility,biodegradability and easy chemical modification,its potential in drug delivery systems,tissue engineering,and wound healing is gradually being explored.This review focuses on orange peel pectin polysaccharides and discusses its traditional and modern extraction techniques,especially the advanced method of subcritical water extraction.This study also outlines the structural modifications of pectin such as methylation and acetylation,and introduces its antioxidant and anticancer biological activities and their emerging roles in the development of advanced biomaterials such as bone tissue engineering and fibre pad dressings.
文摘Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.
基金supported by a Matching Fund between Tham-masat University Research Fund and the National Taipei University of Technology(Taipei Tech),contract no MF 1/2567National Taipei University of Technology-Thammasat University Joint Research Program(NTUT-TU Joint Research Program NTUT-TU-113-03).
文摘Protein fibers derived from silk fibroin(SF)were chemically extracted and purified from cocoons.It was used as a reinforced fiber for hydrogel formation with collagen(Col)and hyaluronic acid(HA).Calcium chloride(8 wt.%)was employed as a crosslinking reagent to synthesize the SF/Col/HA-based hydrogel composite.FTIR spec-troscopy confirmed the presence of N-H stretching due to the plane bending of amide II in theβ-sheet structure.XRD analysis confirmed the crystallinity of the SF/Col/HA-based hydrogel composite.Scanning electron mi-croscopy revealed three-dimensional porous structures with interconnected pores.These porous structures can serve as reservoirs for storing adsorbent media.The hydrogel composite was thermally stable at 250℃.The lowboiling bound solvent evaporation temperature,glass transition temperature,and degradation temperature were 102℃-105℃,298℃-300℃,and 524℃-545℃,respectively.The ranges of porosity and gel fraction were 60%-80%and 90%-95%,respectively.The hydrogel composite was rapidly swollen within 1 h,reaching a plateau afterward.The compressive strength was 4-6 MPa.As absorbent media,hydrogels can easily adhere to lead ions via electrostatic interactions.They can be used as reservoirs for the adsorption of heavy metals.
文摘Targeted cancer therapy has emerged as a promising alternative to conventional chemotherapy,which is often plagued by poor selectivity,off-target effects,and drug resistance.Among the various targeting agents in development,peptides stand out for their unique advantages,including minimal immunogenicity,high tissue penetration,and ease of modification.Their small size,specificity,and flexibility allow them to target cancer cells while minimizing damage to healthy tissue selectively.Peptide-based therapies have shown great potential in enhancing the efficacy of drug delivery,improving tumor imaging,and reducing adverse effects.With cancer responsible for millions of deaths worldwide,the development of peptide-based therapeutics offers new hope in addressing the limitations of current treatments.As detailed studies on different aspects of targeting peptides are crucial for optimizing drug development,this review provides a comprehensive overview of the literature on tumor-targeting peptides,including their structure,sources,modes of action,and their application in cancer therapy—both as standalone agents and in fusion drugs.Additionally,various computational tools for peptide-based tumor-targeting drug design and validation are explored.The promising results from these studies highlight peptides as ideal candidates for targeted cancer therapies,offering valuable insights for researchers and accelerating the discovery of novel anti-tumor peptide base drug candidates.
基金supported by the Key Project at the Central Government Level(No.2060302),the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(No.ZYYCXTD-D-202005),and the National Natural Science Foundation of China(No.8187295682173929).
文摘Background:Liver injury often occurs but with limited drugs.Chaenomeles has a potent hepatoprotective effect,while the ability of Chaenomeles speciosa and Chaenomeles sinensis to treat liver injury in rats is unexplored.Methods:The study involved 30 rats divided into five groups:negative control(NC),model control(MC),positive control(PC),Chaenomeles speciosa-delivered(ZP),and Chaenomeles sinensis-delivered(GP).Fecal samples from all groups were collected 24 h post-modeling for intestinal flora analysis.All rats were collected serum and liver tissues for biochemical and histopathological examinations,among other experiments.Chaenomeles would be effective in CCl4-induced liver injury in rats by analyzing the efficacy and mechanism and examining the differences between Chaenomeles speciosa and Chaenomeles sinensis through oxidative stress,inflammation,and apoptosis pathways.Then,we resolved the mechanism of action in the context of the intestinal flora.Results:The results showed that Chaenomeles intake improved the degree of CCl4-induced liver injury,decreased aspartate aminotransferase,alanine aminotransferase,and alkaline phosphatase levels,and increased total protein and total bilirubin levels.Noteworthy,the glutathione level in the GP group surpassed that a 1.5-fold increase compared to the PC group.Chaenomeles speciosa could exert its efficacy by regulating inflammatory and apoptotic pathways,while Chaenomeles speciosa did so through the oxidative stress pathway.In addition,Chaenomeles are both able to modulate intestinal flora and change the ratio of flora.Chaenomeles speciosa could regulate probiotics and prevent liver injury by altering the distribution and ratio of intestinal flora.Specifically,Lactobacillaceae in the ZP group exhibited 10-fold higher abundance than the other groups.Chaenomeles speciosa increased the abundance of probiotic Clostridiales butyricum in diseased rats,while Chaenomeles sinensis increased the abundance of pathogenic Escherichia Shigella.Conclusion:This study suggests that Chaenomeles may be hepatoprotective by oxidative stress,inflammation,and apoptosis pathways and modulating the composition and function of the intestinal flora.
