Nanotechnology has revolutionized drug delivery,particularly through nanoformulations of phytoconstituents,enhancing their therapeutic potential.Despite their broad bioactivities,plant-based compounds often suffer fro...Nanotechnology has revolutionized drug delivery,particularly through nanoformulations of phytoconstituents,enhancing their therapeutic potential.Despite their broad bioactivities,plant-based compounds often suffer from poor bioavailability and stability.Nanoformulations address these limitations by improving solubility,targeted delivery,and controlled release.This approach opens new possibilities for treating chronic diseases like cancer,diabetes,and neurodegenerative disorders.This review aims to examine recent advancements in nanotechnology-based formulation strategies designed to enhance the delivery,stability,and therapeutic efficacy of phytochemicals and also discusses regulatory issues,safety concerns,scalability,and cost-effectiveness.Emphasis was placed on nanoformulation techniques employed for key phytoconstituents such as curcumin,resveratrol,epigallocatechin gallate,and quercetin.The most commonly employed nanocarriers included polymeric nanoparticles,solid lipid nanoparticles,and liposomes.These formulations significantly improved the solubility,stability,and controlled release profiles of phytochemicals.In vitro and in vivo studies demonstrated enhanced anti-inflammatory,anticancer,and antioxidant activities.Moreover,surface-modified and targeted nanoparticles showed promise in increasing site-specific targeting and enhancing bioavailability of the encapsulated compounds.Nanoformulations present a promising strategy for overcoming the pharmacokinetic limitations of phytochemicals.Despite encouraging preclinical results,further studies are needed to address issues related to long-term safety,clinical efficacy,and regulatory approval for successful clinical translation.展开更多
This paper presents Dual Adaptive Neural Topology(Dual ANT),a distributed dual-network metaadaptive framework that enhances ant-colony-based multi-agent coordination with online introspection,adaptive parameter contro...This paper presents Dual Adaptive Neural Topology(Dual ANT),a distributed dual-network metaadaptive framework that enhances ant-colony-based multi-agent coordination with online introspection,adaptive parameter control,and privacy-preserving interactions.This approach improves standard Ant Colony Optimization(ACO)with two lightweight neural components:a forward network that estimates swarm efficiency in real time and an inverse network that converts these descriptors into parameter adaptations.To preserve the privacy of individual trajectories in shared pheromone maps,we introduce a locally differentially private pheromone update mechanism that adds calibrated noise to each agent’s pheromone deposit while preserving the efficacy of the global pheromone signal.The resulting systemenables agents to dynamically and autonomously adapt their coordination strategies under challenging and dynamic conditions,including varying obstacle layouts,uncertain target locations,and time-varying disturbances.Extensive simulations of large grid-based search tasks demonstrated that Dual ANT achieved faster convergence,higher robustness,and improved scalability compared to advanced baselines such asMulti-StrategyACO and Hierarchical ACO.The meta-adaptive feedback loop compensates for the performance degradation caused by privacy noise and prevents premature stagnation by triggering Levy flight exploration only when necessary.展开更多
Poly-and perfluoroalkyl substances(PFAS),including perfluorooctanoic acid(PFOA)and perfluorooctane sul-fonate(PFOS),are persistent environmental pollutants with potential toxicological effects on human health.The aim ...Poly-and perfluoroalkyl substances(PFAS),including perfluorooctanoic acid(PFOA)and perfluorooctane sul-fonate(PFOS),are persistent environmental pollutants with potential toxicological effects on human health.The aim of this study was to investigate the impact of PFOS and PFOA on the effectiveness of selected drugs used in the treatment of prostate cancer based on in vitro tests on cell lines.Three cell lines were used in the study:two human prostate cancer cells(DU-145 and PC3)and one human normal prostate cell line(PNT1A).Using dose-response experiments,it was observed that PFAS had differential effects on cancer and normal cells.At low concentrations,PFOA and PFOS stimulated the proliferation of cancer cells,particularly PC3,while higher concentrations led to reduced viability.In normal cells,PFOS exhibited greater cytotoxicity compared to PFOA.Furthermore,PFOS enhanced docetaxel cytotoxicity in PC3 cells but reduced its efficacy in DU-145 cells.Similarly,PFOA diminished cabazitaxel effectiveness in DU-145 cells,suggesting PFAS-drug interactions may depend on the cell type,drug,and PFAS concentration.Results suggest that PFAS may influence cellular processes through receptor-mediated pathways,oxidative stress modulation,and protein binding,altering drug bioavailability and cellular uptake.The study also highlights the non-monotonic dose-response relationships observed in PFAS-treated cells.These findings raise concerns about the potential risks associated with PFAS exposure,particularly in the context of cancer treatment.Future studies should focus on long-term,low-dose PFAS exposure,the use of primary cells,and the molecular mechanisms driving these interactions to better inform therapeutic strategies.展开更多
Corn starch(CS)is a renewable,biodegradable polysaccharide valued for its film-forming ability,yet native CS films exhibit lowmechanical strength,highwater sensitivity,and limited thermal stability.This study improves...Corn starch(CS)is a renewable,biodegradable polysaccharide valued for its film-forming ability,yet native CS films exhibit lowmechanical strength,highwater sensitivity,and limited thermal stability.This study improves CS-based films by blending with poly(vinyl alcohol)(PVA)or glycerol(GLY)and using citric acid(CA)as a green,non-toxic cross-linker.Composite films were prepared by casting CS–PVA or CS-GLY with CA at 0%-0.20%(w/w of starch).The influence of CA on physicochemical,mechanical,optical,thermal,and water barrier properties was evaluated.CA crosslinking markedly enhanced the tensile strength,water resistance,and thermal stability of CS-PVA films while increasing transparency in CS–GLY films.At 0.20%CA,the composite achieved 34.99MPa tensile strength,reducedwater vapor permeability,andminimized water uptake.FTIR confirmed ester bond formation between CAand hydroxyl groups of CS,PVA,and GLY,whereas thermal analysis showed higher decomposition temperatures and lower weight loss in crosslinked films.Increasing CA levels also decreased opacity and improved light transmittance,indicating greater homogeneity and reduced crystallinity.This dual-polymer matrix combined with a natural crosslinking strategy provides a sustainable route to high-performance,biodegradable CS-based packaging materials.展开更多
Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remain...Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.展开更多
The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors,due to the limited capabilities of sensors,which also produce...The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors,due to the limited capabilities of sensors,which also produce poor computer vision results.The common image denoising techniques tend to remove significant image details and also remove noise,provided they are based on space and frequency filtering.The updated framework presented in this paper is a novel denoising model that makes use of Boruta-driven feature selection using a Long Short-Term Memory Autoencoder(LSTMAE).The Boruta algorithm identifies the most useful depth features that are used to maximize the spatial structure integrity and reduce redundancy.An LSTMAE is then used to process these selected features and model depth pixel sequences to generate robust,noise-resistant representations.The system uses the encoder to encode the input data into a latent space that has been compressed before it is decoded to retrieve the clean image.Experiments on a benchmark data set show that the suggested technique attains a PSNR of 45 dB and an SSIM of 0.90,which is 10 dB higher than the performance of conventional convolutional autoencoders and 15 times higher than that of the wavelet-based models.Moreover,the feature selection step will decrease the input dimensionality by 40%,resulting in a 37.5%reduction in training time and a real-time inference rate of 200 FPS.Boruta-LSTMAE framework,therefore,offers a highly efficient and scalable system for depth image denoising,with a high potential to be applied to close-range 3D systems,such as robotic manipulation and gesture-based interfaces.展开更多
Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of...Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.展开更多
Hydrothermal carbonization(HTC)is a promising techno-economic method for biomass waste valorization owing to its advantages over other thermochemical processes.This study focused on carbon sequestration from sugarcane...Hydrothermal carbonization(HTC)is a promising techno-economic method for biomass waste valorization owing to its advantages over other thermochemical processes.This study focused on carbon sequestration from sugarcane bioethanol distillery wastewater via HTC and chemical activation to produce activated carbon(AC).The resulting AC was then applied as an active material for supercapacitor electrodes.The introduction of redox molecules,such as 1,4-anthraquinone(AQ)and 9,10-phenanthrenequinone(PQ),on AC increased charge storage capability via redox transformation and enhanced the electrochemical performance of the supercapacitor elec-trode.Electrochemical testing showed that AC loaded with 16 wt%PQ achieved the highest specific capacitance of 488.21 F g^(-1) with remarkable capacitance retention of 95.3% after 1000 charge-discharge cycles.N-doped AC obtained from the HTC of wastewater and melamine presented a slightly enhanced specific capacitance.Various commercial LEDs with a voltage range of 1.8-3.0 V were illuminated simultaneously by connecting them to two series of symmetric supercapacitors,demonstrating the potential application of our proposed strategy in energy storage systems.This study proposes a simple and efficient strategy to utilize wastewater and achieve net-zero emission goals in a Bio-Circular-Green Economy model.展开更多
Heat treatment is applied towood to improve various properties of thematerial.Thepresent study focuses on the colour changes of wood veneer samples due to heat treatment.Native wood species fromJapan and Europe,such a...Heat treatment is applied towood to improve various properties of thematerial.Thepresent study focuses on the colour changes of wood veneer samples due to heat treatment.Native wood species fromJapan and Europe,such as Japanese oak(Quercus mongolica var.crispula),field maple(Acer campestre)and Scots pine(Pinus sylvestris)were used in the experiments.A laboratory-type oven was used to apply the heat at a temperature of 190○C,in the presence of oxygen,for different periods,gradually increasing from 5 to 40 min.The CIELab system(a colour space defined by the International Commission on Illumination)and Near Infrared Spectroscopy(NIR)were employed to evaluate the colour modifications on the samples.As expected,the heat treatment affected the colour of the samples.The lightness index decreased across the three wood species during the treatment.The chroma coordinates changed for pine and maple,while little change occurred in Japanese oak.The overall total colour differences reached their maximum at the final 40-min interval for all wood types.Based on the NIR evaluation,it was found that drastic thermal denaturation of cellulose was unlikely to occur,and the changes in the intermolecular interaction of water affected the colour of the specimens.The data and information of this study could be useful for industrial applications where the veneer of such species is desired.Such heat-treated veneers can be considered as value-added products in furniture manufacturing as well as restoration of furniture units where such veneer is used as an overlay.展开更多
Unconfined Compressive Strength(UCS)is a key parameter for the assessment of the stability and performance of stabilized soils,yet traditional laboratory testing is both time and resource intensive.In this study,an in...Unconfined Compressive Strength(UCS)is a key parameter for the assessment of the stability and performance of stabilized soils,yet traditional laboratory testing is both time and resource intensive.In this study,an interpretable machine learning approach to UCS prediction is presented,pairing five models(Random Forest(RF),Gradient Boosting(GB),Extreme Gradient Boosting(XGB),CatBoost,and K-Nearest Neighbors(KNN))with SHapley Additive exPlanations(SHAP)for enhanced interpretability and to guide feature removal.A complete dataset of 12 geotechnical and chemical parameters,i.e.,Atterberg limits,compaction properties,stabilizer chemistry,dosage,curing time,was used to train and test the models.R2,RMSE,MSE,and MAE were used to assess performance.Initial results with all 12 features indicated that boosting-based models(GB,XGB,CatBoost)exhibited the highest predictive accuracy(R^(2)=0.93)with satisfactory generalization on test data,followed by RF and KNN.SHAP analysis consistently picked CaO content,curing time,stabilizer dosage,and compaction parameters as the most important features,aligning with established soil stabilization mechanisms.Models were then re-trained on the top 8 and top 5 SHAP-ranked features.Interestingly,GB,XGB,and CatBoost maintained comparable accuracy with reduced input sets,while RF was moderately sensitive and KNN was somewhat better owing to reduced dimensionality.The findings confirm that feature reduction through SHAP enables cost-effective UCS prediction through the reduction of laboratory test requirements without significant accuracy loss.The suggested hybrid approach offers an explainable,interpretable,and cost-effective tool for geotechnical engineering practice.展开更多
The Internet ofThings(IoT)is a new model that evolved with the rapid progress of advanced technology and gained tremendous popularity due to its applications.Anomaly detection haswidely attracted researchers’attentio...The Internet ofThings(IoT)is a new model that evolved with the rapid progress of advanced technology and gained tremendous popularity due to its applications.Anomaly detection haswidely attracted researchers’attention in the last few years,and its effects on diverse applications.This review article covers the various methods and tools developed to perform the task efficiently and automatically in a smart city.In this work,we present a comprehensive literature review(2011 onwards)of three major types of anomalies:network anomalies,sensor anomalies,and videobased anomalies,along with their methods and software tools.Furthermore,anomaly detection methods such as machine learning and deep learning are presented in this work,highlighting their detection strategy techniques,features,applications,issues,and challenges.Moreover,a generic algorithmis also developed to ease the user achieve the taskmore specifically by targeting a specific domain aswell as approach.Comparative studies of three anomalymethods and their analysis identify research discovery areas with their applications.As a result,researchers and practitioners can familiarize themselves with the existing methods for solving real problems,improving methods,and developing new optimum methods for anomaly detection in diverse applications.展开更多
The spread of SARS-CoV-2 as an emerging novel coronavirus disease (COVID-19) had progressed as a worldwide pandemic since the end of 2019. COVID-19 affects firstly lungs tissues which are known for their very slow reg...The spread of SARS-CoV-2 as an emerging novel coronavirus disease (COVID-19) had progressed as a worldwide pandemic since the end of 2019. COVID-19 affects firstly lungs tissues which are known for their very slow regeneration. Afterwards, enormous cytokine stimulation occurs in the infected cells immediately after a lung infection which necessitates good management to save patients. Exosomes are extracellular vesicles of nanometric size released by reticulocytes on maturation and are known to mediate intercellular communications. The exosomal cargo serves as biomarkers in diagnosing various diseases;moreover, exosomes could be employed as nanocarriers in drug delivery systems. Exosomes look promising to combat the current pandemic since they contribute to the immune response against several viral pathogens. Many studies have proved the potential of using exosomes either as viral elements or host systems that acquire immune-stimulatory effects and could be used as a vaccine or drug delivery tool. It is essential to stop viral replication, prevent and reverse the massive storm of cytokine that worsens the infected patients’ situations for the management of COVID-19. The main benefits of exosomes could be;no cells will be introduced, no chance of mutation, lack of immunogenicity and the damaged genetic material that could negatively affect the recipient is avoided. Additionally, it was found that exosomes are static with no ability for in vivo reproduction. The current review article discusses the possibilities of using exosomes for detecting novel coronavirus and summarizes state of the art concerning the clinical trials initiated for examining the use of COVID-19 specific T cells derived exosomes and mesenchymal stem cells derived exosomes in managing COVID-19.展开更多
The work described here is based on a comparative study of carotenoids and fatty acids extracted from Synechococcus sp. with (1) pure supercritical CO2, (2) CO2 with 5% (v/v) ethanol as cosolvent and (3) ultrasound-as...The work described here is based on a comparative study of carotenoids and fatty acids extracted from Synechococcus sp. with (1) pure supercritical CO2, (2) CO2 with 5% (v/v) ethanol as cosolvent and (3) ultrasound-assisted extraction using N, N-dimethylformamide (DMF). The effects of extraction conditions on supercritical CO2 extraction with and within cosolvent were analyzed at different temperatures (40℃, 50℃ and 60℃) and pressures (200, 300 and 400 bars). SFE with CO2 proved to be the most selective method for the extraction of β-carotene, but under these conditions the contents of zeaxanthin and fatty acids were only comparable to or lower than those obtained with techniques that use SFE cosolvent. The SFE technique with CO2 and ethanol simultaneously extracted β-carotene and zeaxanthin and not only increased the concentrations of fatty acids obtained, but also helped to remove fatty acids (palmitoleic and linolenic acid) that were not obtained with pure CO2. Comparison of the supercritical technology with the ultrasound-assisted extraction (UAE) shows that the former technique is the most appropriate due to the fact that ethanol is generally regarded as a safe solvent in comparison to DMF.展开更多
The development of biotechnology-based active pharmaceutical ingredients, such as GLP-1 analogs, brought changes in type 2 diabetes treatment options. For better therapeutic efficiency, these active pharmaceutical ing...The development of biotechnology-based active pharmaceutical ingredients, such as GLP-1 analogs, brought changes in type 2 diabetes treatment options. For better therapeutic efficiency, these active pharmaceutical ingredients require appropriate administration, without the development of adverse effects or toxicity. Therefore, it is required to develop several quantification methods for GLP-1 analogs products, in order to achieve the therapeutic goals, among which ELISA and HPLC arise. These methods are developed, optimized and validated in order to determine GLP-1 analogs, not only in final formulation of the active pharmaceutical ingredient, but also during preclinical and clinical trials assessment. This review highlights the role of ELISA and HPLC methods that have been used during the assessment for GLP-1 analogs, especially for exenatide.展开更多
Nanotechnology has received much interest nowadays. It isdefined as techniques, methods or processes to fabricate nanoscalestructures with size less than 100 nm. The deliveryof a compound via skin offers many advantag...Nanotechnology has received much interest nowadays. It isdefined as techniques, methods or processes to fabricate nanoscalestructures with size less than 100 nm. The deliveryof a compound via skin offers many advantages including beingpain-free, ease of administration, avoidance of hepatic firstpassmetabolism and low cost. However, the major barrier ofthis route is the stratum corneum, which is the outermostlayer of the epidermis. Thus effective nanodelivery systemsare essential and no wonder why these systems reveal significantroles in delivery of cosmetics, drugs and biologicalproducts via topical routes these days. There are a variety ofnanodelivery systems for topical route. However, this presentationcovers polymeric nanoparticles and amphiphilicassociationstructures, which are the systems of the author’sparticular interest.展开更多
Assessing and analyzing the impact of science and technology on international relations is now a specific area for foreign policy analystsin the digital era. Progress in science and technology developing concurrently ...Assessing and analyzing the impact of science and technology on international relations is now a specific area for foreign policy analystsin the digital era. Progress in science and technology developing concurrently with the global revolution in information and the transition to a multipolar world have thrust upon international relations the imperative to establish a global technology alliance. This includes creation of a global technology fund, renovation of the global technology transfer, and the broadening of global cloud technology resource.展开更多
The study explores the factors influencing attitude towards agricultural technology adoption among Permanent Food Production Park(PFPP)program participants in West Malaysia and the factors that influence their attitud...The study explores the factors influencing attitude towards agricultural technology adoption among Permanent Food Production Park(PFPP)program participants in West Malaysia and the factors that influence their attitudes.The PFPP program is one of the programs introduced by the government of Malaysia with the objectives of increasing food production,as well as supporting local agriculture entrepreneurs.The study employed a cross-sectional study design and has been conducted in four West Malaysian states with a sample of size of 275 respondents.The results indicated that the respondents had a positive attitude towards technology adoption and factors such as knowledge and skill,benefit,education level,years of experience in agriculture and gross income had influenced their attitude.展开更多
Metallurgical sector plays an important role in the economy of each country because steel products present essential raw material for basic industries. Changes in the sectors of iron, steel and non-ferrous metals and ...Metallurgical sector plays an important role in the economy of each country because steel products present essential raw material for basic industries. Changes in the sectors of iron, steel and non-ferrous metals and the current development of technology forces the steel mills increased productivity, reduce production costs while ensuring to obtain a product with the required properties and to improve the competitiveness of enterprises in the global market. Currently, the most popular in meeting these requirements, enjoys a method of integration which combines individual operations into one integrated whole. The use of modem, perfectly designed, fully automated design of mechanical, hydraulic and measurement allowed us to achieve an innovative line of production. This article presents the general characteristics of the steel industry and a description of the latest integrated technology currently used in foundries and rolling mills. It also presents examples of the use of integrated technologies in metallurgy and the effects of economic, environmental and quality resulting from their use on an industrial scale.展开更多
The notoriety of the shortage of qualified professionals in the engineering segment to meet the existing projects and also the future ones is worrying the academic community. These challenges show how the lack of appr...The notoriety of the shortage of qualified professionals in the engineering segment to meet the existing projects and also the future ones is worrying the academic community. These challenges show how the lack of appropriate courses and low expenses with incentives to research and extension programs can affect the formation of the future engineer. Therefore, universities have the mission to develop teaching, research and extension, offering to the students new opportunities for diverse technical training, scientific and humanist formation. It is noted, however, that such activities in many engineering courses, especially scientific research, are not being prioritized by the universities. In light of this, the present paper aims to register measure and evaluate the participation of the students in scientific initiation in the four engineering courses of the Faculty of Engineering of the Minas Gerais State University. Sticking to the disparities presented by the four courses studied, in relation to the participation in research projects, the results showed a greater engagement of students of Environmental Engineering and Mining Engineering courses regarding the other engineering courses. In addition, a better divulgation and a greater involvement of teachers in projects were identified as the main recurring challenges to the access in scientific research by the students of this institution.展开更多
Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources,chemical mechanisms,and transport processes of ...Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources,chemical mechanisms,and transport processes of air pollution in land,sea,and atmosphere.We present an overview of coastal ocean boundary layer detection technology and equipment in China and summarize the progress and main achievements in recent years.China has developed a series of coastal ocean boundary layer detection technologies,including Light Detection and Ranging(LIDAR),turbulent exchange analyzer,air-sea flux analyzer,stereoscopic remote sensing of air pollutants,and oceanic aerosol detection equipment to address the technical bottleneck caused by harsh environmental conditions in coastal ocean regions.Advances in these technologies and equipment have provided scientific assistance for addressing air pollution issues and understanding land-sea-atmosphere interactions over coastal ocean regions in China.In the future,routine atmospheric observations should cover the coastal ocean boundary layer of China.展开更多
文摘Nanotechnology has revolutionized drug delivery,particularly through nanoformulations of phytoconstituents,enhancing their therapeutic potential.Despite their broad bioactivities,plant-based compounds often suffer from poor bioavailability and stability.Nanoformulations address these limitations by improving solubility,targeted delivery,and controlled release.This approach opens new possibilities for treating chronic diseases like cancer,diabetes,and neurodegenerative disorders.This review aims to examine recent advancements in nanotechnology-based formulation strategies designed to enhance the delivery,stability,and therapeutic efficacy of phytochemicals and also discusses regulatory issues,safety concerns,scalability,and cost-effectiveness.Emphasis was placed on nanoformulation techniques employed for key phytoconstituents such as curcumin,resveratrol,epigallocatechin gallate,and quercetin.The most commonly employed nanocarriers included polymeric nanoparticles,solid lipid nanoparticles,and liposomes.These formulations significantly improved the solubility,stability,and controlled release profiles of phytochemicals.In vitro and in vivo studies demonstrated enhanced anti-inflammatory,anticancer,and antioxidant activities.Moreover,surface-modified and targeted nanoparticles showed promise in increasing site-specific targeting and enhancing bioavailability of the encapsulated compounds.Nanoformulations present a promising strategy for overcoming the pharmacokinetic limitations of phytochemicals.Despite encouraging preclinical results,further studies are needed to address issues related to long-term safety,clinical efficacy,and regulatory approval for successful clinical translation.
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,under project number NBU-FFR-2026-2441-02.
文摘This paper presents Dual Adaptive Neural Topology(Dual ANT),a distributed dual-network metaadaptive framework that enhances ant-colony-based multi-agent coordination with online introspection,adaptive parameter control,and privacy-preserving interactions.This approach improves standard Ant Colony Optimization(ACO)with two lightweight neural components:a forward network that estimates swarm efficiency in real time and an inverse network that converts these descriptors into parameter adaptations.To preserve the privacy of individual trajectories in shared pheromone maps,we introduce a locally differentially private pheromone update mechanism that adds calibrated noise to each agent’s pheromone deposit while preserving the efficacy of the global pheromone signal.The resulting systemenables agents to dynamically and autonomously adapt their coordination strategies under challenging and dynamic conditions,including varying obstacle layouts,uncertain target locations,and time-varying disturbances.Extensive simulations of large grid-based search tasks demonstrated that Dual ANT achieved faster convergence,higher robustness,and improved scalability compared to advanced baselines such asMulti-StrategyACO and Hierarchical ACO.The meta-adaptive feedback loop compensates for the performance degradation caused by privacy noise and prevents premature stagnation by triggering Levy flight exploration only when necessary.
文摘Poly-and perfluoroalkyl substances(PFAS),including perfluorooctanoic acid(PFOA)and perfluorooctane sul-fonate(PFOS),are persistent environmental pollutants with potential toxicological effects on human health.The aim of this study was to investigate the impact of PFOS and PFOA on the effectiveness of selected drugs used in the treatment of prostate cancer based on in vitro tests on cell lines.Three cell lines were used in the study:two human prostate cancer cells(DU-145 and PC3)and one human normal prostate cell line(PNT1A).Using dose-response experiments,it was observed that PFAS had differential effects on cancer and normal cells.At low concentrations,PFOA and PFOS stimulated the proliferation of cancer cells,particularly PC3,while higher concentrations led to reduced viability.In normal cells,PFOS exhibited greater cytotoxicity compared to PFOA.Furthermore,PFOS enhanced docetaxel cytotoxicity in PC3 cells but reduced its efficacy in DU-145 cells.Similarly,PFOA diminished cabazitaxel effectiveness in DU-145 cells,suggesting PFAS-drug interactions may depend on the cell type,drug,and PFAS concentration.Results suggest that PFAS may influence cellular processes through receptor-mediated pathways,oxidative stress modulation,and protein binding,altering drug bioavailability and cellular uptake.The study also highlights the non-monotonic dose-response relationships observed in PFAS-treated cells.These findings raise concerns about the potential risks associated with PFAS exposure,particularly in the context of cancer treatment.Future studies should focus on long-term,low-dose PFAS exposure,the use of primary cells,and the molecular mechanisms driving these interactions to better inform therapeutic strategies.
基金supported through RIIM Competition funding from the Indonesia Endowment Fund for Education Agency,Ministry of Finance of the Republic of Indonesia and National Research and Innovation Agency of Indonesia according to the contract number:61/IV/KS/5/2023 and 2131/UN6.3.1/PT.00/2023.
文摘Corn starch(CS)is a renewable,biodegradable polysaccharide valued for its film-forming ability,yet native CS films exhibit lowmechanical strength,highwater sensitivity,and limited thermal stability.This study improves CS-based films by blending with poly(vinyl alcohol)(PVA)or glycerol(GLY)and using citric acid(CA)as a green,non-toxic cross-linker.Composite films were prepared by casting CS–PVA or CS-GLY with CA at 0%-0.20%(w/w of starch).The influence of CA on physicochemical,mechanical,optical,thermal,and water barrier properties was evaluated.CA crosslinking markedly enhanced the tensile strength,water resistance,and thermal stability of CS-PVA films while increasing transparency in CS–GLY films.At 0.20%CA,the composite achieved 34.99MPa tensile strength,reducedwater vapor permeability,andminimized water uptake.FTIR confirmed ester bond formation between CAand hydroxyl groups of CS,PVA,and GLY,whereas thermal analysis showed higher decomposition temperatures and lower weight loss in crosslinked films.Increasing CA levels also decreased opacity and improved light transmittance,indicating greater homogeneity and reduced crystallinity.This dual-polymer matrix combined with a natural crosslinking strategy provides a sustainable route to high-performance,biodegradable CS-based packaging materials.
基金This study is financed by the European Union-NextGenerationEU,through the National Recovery and Resilience Plan of the Republic of Bulgaria,Project No.BG-RRP-2.013-0001.
文摘Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.
文摘The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors,due to the limited capabilities of sensors,which also produce poor computer vision results.The common image denoising techniques tend to remove significant image details and also remove noise,provided they are based on space and frequency filtering.The updated framework presented in this paper is a novel denoising model that makes use of Boruta-driven feature selection using a Long Short-Term Memory Autoencoder(LSTMAE).The Boruta algorithm identifies the most useful depth features that are used to maximize the spatial structure integrity and reduce redundancy.An LSTMAE is then used to process these selected features and model depth pixel sequences to generate robust,noise-resistant representations.The system uses the encoder to encode the input data into a latent space that has been compressed before it is decoded to retrieve the clean image.Experiments on a benchmark data set show that the suggested technique attains a PSNR of 45 dB and an SSIM of 0.90,which is 10 dB higher than the performance of conventional convolutional autoencoders and 15 times higher than that of the wavelet-based models.Moreover,the feature selection step will decrease the input dimensionality by 40%,resulting in a 37.5%reduction in training time and a real-time inference rate of 200 FPS.Boruta-LSTMAE framework,therefore,offers a highly efficient and scalable system for depth image denoising,with a high potential to be applied to close-range 3D systems,such as robotic manipulation and gesture-based interfaces.
基金supported by the Chung-Ang University Research Grants in 2023.Alsothe work is supported by the ELLIIT Excellence Center at Linköping–Lund in Information Technology in Sweden.
文摘Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.
基金supported by Thailand Science Research and Inno-vation(TSRI)Fundamental Fund,fiscal year 2024(TUFF14/2567)by the Research Unit in Bioenergy and Catalysis(Thammasat University)+2 种基金partially supported by Thailand Science Research and Innovation(TSRI)under Project No.180677funded by Hub Talent:Sustainable Materials for Circular Economy,National Research Council of Thailand(NRCT)supported by Synchrotron Light Research Institute(SLRI:Beamline 3.2b).
文摘Hydrothermal carbonization(HTC)is a promising techno-economic method for biomass waste valorization owing to its advantages over other thermochemical processes.This study focused on carbon sequestration from sugarcane bioethanol distillery wastewater via HTC and chemical activation to produce activated carbon(AC).The resulting AC was then applied as an active material for supercapacitor electrodes.The introduction of redox molecules,such as 1,4-anthraquinone(AQ)and 9,10-phenanthrenequinone(PQ),on AC increased charge storage capability via redox transformation and enhanced the electrochemical performance of the supercapacitor elec-trode.Electrochemical testing showed that AC loaded with 16 wt%PQ achieved the highest specific capacitance of 488.21 F g^(-1) with remarkable capacitance retention of 95.3% after 1000 charge-discharge cycles.N-doped AC obtained from the HTC of wastewater and melamine presented a slightly enhanced specific capacitance.Various commercial LEDs with a voltage range of 1.8-3.0 V were illuminated simultaneously by connecting them to two series of symmetric supercapacitors,demonstrating the potential application of our proposed strategy in energy storage systems.This study proposes a simple and efficient strategy to utilize wastewater and achieve net-zero emission goals in a Bio-Circular-Green Economy model.
文摘Heat treatment is applied towood to improve various properties of thematerial.Thepresent study focuses on the colour changes of wood veneer samples due to heat treatment.Native wood species fromJapan and Europe,such as Japanese oak(Quercus mongolica var.crispula),field maple(Acer campestre)and Scots pine(Pinus sylvestris)were used in the experiments.A laboratory-type oven was used to apply the heat at a temperature of 190○C,in the presence of oxygen,for different periods,gradually increasing from 5 to 40 min.The CIELab system(a colour space defined by the International Commission on Illumination)and Near Infrared Spectroscopy(NIR)were employed to evaluate the colour modifications on the samples.As expected,the heat treatment affected the colour of the samples.The lightness index decreased across the three wood species during the treatment.The chroma coordinates changed for pine and maple,while little change occurred in Japanese oak.The overall total colour differences reached their maximum at the final 40-min interval for all wood types.Based on the NIR evaluation,it was found that drastic thermal denaturation of cellulose was unlikely to occur,and the changes in the intermolecular interaction of water affected the colour of the specimens.The data and information of this study could be useful for industrial applications where the veneer of such species is desired.Such heat-treated veneers can be considered as value-added products in furniture manufacturing as well as restoration of furniture units where such veneer is used as an overlay.
文摘Unconfined Compressive Strength(UCS)is a key parameter for the assessment of the stability and performance of stabilized soils,yet traditional laboratory testing is both time and resource intensive.In this study,an interpretable machine learning approach to UCS prediction is presented,pairing five models(Random Forest(RF),Gradient Boosting(GB),Extreme Gradient Boosting(XGB),CatBoost,and K-Nearest Neighbors(KNN))with SHapley Additive exPlanations(SHAP)for enhanced interpretability and to guide feature removal.A complete dataset of 12 geotechnical and chemical parameters,i.e.,Atterberg limits,compaction properties,stabilizer chemistry,dosage,curing time,was used to train and test the models.R2,RMSE,MSE,and MAE were used to assess performance.Initial results with all 12 features indicated that boosting-based models(GB,XGB,CatBoost)exhibited the highest predictive accuracy(R^(2)=0.93)with satisfactory generalization on test data,followed by RF and KNN.SHAP analysis consistently picked CaO content,curing time,stabilizer dosage,and compaction parameters as the most important features,aligning with established soil stabilization mechanisms.Models were then re-trained on the top 8 and top 5 SHAP-ranked features.Interestingly,GB,XGB,and CatBoost maintained comparable accuracy with reduced input sets,while RF was moderately sensitive and KNN was somewhat better owing to reduced dimensionality.The findings confirm that feature reduction through SHAP enables cost-effective UCS prediction through the reduction of laboratory test requirements without significant accuracy loss.The suggested hybrid approach offers an explainable,interpretable,and cost-effective tool for geotechnical engineering practice.
文摘The Internet ofThings(IoT)is a new model that evolved with the rapid progress of advanced technology and gained tremendous popularity due to its applications.Anomaly detection haswidely attracted researchers’attention in the last few years,and its effects on diverse applications.This review article covers the various methods and tools developed to perform the task efficiently and automatically in a smart city.In this work,we present a comprehensive literature review(2011 onwards)of three major types of anomalies:network anomalies,sensor anomalies,and videobased anomalies,along with their methods and software tools.Furthermore,anomaly detection methods such as machine learning and deep learning are presented in this work,highlighting their detection strategy techniques,features,applications,issues,and challenges.Moreover,a generic algorithmis also developed to ease the user achieve the taskmore specifically by targeting a specific domain aswell as approach.Comparative studies of three anomalymethods and their analysis identify research discovery areas with their applications.As a result,researchers and practitioners can familiarize themselves with the existing methods for solving real problems,improving methods,and developing new optimum methods for anomaly detection in diverse applications.
文摘The spread of SARS-CoV-2 as an emerging novel coronavirus disease (COVID-19) had progressed as a worldwide pandemic since the end of 2019. COVID-19 affects firstly lungs tissues which are known for their very slow regeneration. Afterwards, enormous cytokine stimulation occurs in the infected cells immediately after a lung infection which necessitates good management to save patients. Exosomes are extracellular vesicles of nanometric size released by reticulocytes on maturation and are known to mediate intercellular communications. The exosomal cargo serves as biomarkers in diagnosing various diseases;moreover, exosomes could be employed as nanocarriers in drug delivery systems. Exosomes look promising to combat the current pandemic since they contribute to the immune response against several viral pathogens. Many studies have proved the potential of using exosomes either as viral elements or host systems that acquire immune-stimulatory effects and could be used as a vaccine or drug delivery tool. It is essential to stop viral replication, prevent and reverse the massive storm of cytokine that worsens the infected patients’ situations for the management of COVID-19. The main benefits of exosomes could be;no cells will be introduced, no chance of mutation, lack of immunogenicity and the damaged genetic material that could negatively affect the recipient is avoided. Additionally, it was found that exosomes are static with no ability for in vivo reproduction. The current review article discusses the possibilities of using exosomes for detecting novel coronavirus and summarizes state of the art concerning the clinical trials initiated for examining the use of COVID-19 specific T cells derived exosomes and mesenchymal stem cells derived exosomes in managing COVID-19.
文摘The work described here is based on a comparative study of carotenoids and fatty acids extracted from Synechococcus sp. with (1) pure supercritical CO2, (2) CO2 with 5% (v/v) ethanol as cosolvent and (3) ultrasound-assisted extraction using N, N-dimethylformamide (DMF). The effects of extraction conditions on supercritical CO2 extraction with and within cosolvent were analyzed at different temperatures (40℃, 50℃ and 60℃) and pressures (200, 300 and 400 bars). SFE with CO2 proved to be the most selective method for the extraction of β-carotene, but under these conditions the contents of zeaxanthin and fatty acids were only comparable to or lower than those obtained with techniques that use SFE cosolvent. The SFE technique with CO2 and ethanol simultaneously extracted β-carotene and zeaxanthin and not only increased the concentrations of fatty acids obtained, but also helped to remove fatty acids (palmitoleic and linolenic acid) that were not obtained with pure CO2. Comparison of the supercritical technology with the ultrasound-assisted extraction (UAE) shows that the former technique is the most appropriate due to the fact that ethanol is generally regarded as a safe solvent in comparison to DMF.
文摘The development of biotechnology-based active pharmaceutical ingredients, such as GLP-1 analogs, brought changes in type 2 diabetes treatment options. For better therapeutic efficiency, these active pharmaceutical ingredients require appropriate administration, without the development of adverse effects or toxicity. Therefore, it is required to develop several quantification methods for GLP-1 analogs products, in order to achieve the therapeutic goals, among which ELISA and HPLC arise. These methods are developed, optimized and validated in order to determine GLP-1 analogs, not only in final formulation of the active pharmaceutical ingredient, but also during preclinical and clinical trials assessment. This review highlights the role of ELISA and HPLC methods that have been used during the assessment for GLP-1 analogs, especially for exenatide.
文摘Nanotechnology has received much interest nowadays. It isdefined as techniques, methods or processes to fabricate nanoscalestructures with size less than 100 nm. The deliveryof a compound via skin offers many advantages including beingpain-free, ease of administration, avoidance of hepatic firstpassmetabolism and low cost. However, the major barrier ofthis route is the stratum corneum, which is the outermostlayer of the epidermis. Thus effective nanodelivery systemsare essential and no wonder why these systems reveal significantroles in delivery of cosmetics, drugs and biologicalproducts via topical routes these days. There are a variety ofnanodelivery systems for topical route. However, this presentationcovers polymeric nanoparticles and amphiphilicassociationstructures, which are the systems of the author’sparticular interest.
文摘Assessing and analyzing the impact of science and technology on international relations is now a specific area for foreign policy analystsin the digital era. Progress in science and technology developing concurrently with the global revolution in information and the transition to a multipolar world have thrust upon international relations the imperative to establish a global technology alliance. This includes creation of a global technology fund, renovation of the global technology transfer, and the broadening of global cloud technology resource.
文摘The study explores the factors influencing attitude towards agricultural technology adoption among Permanent Food Production Park(PFPP)program participants in West Malaysia and the factors that influence their attitudes.The PFPP program is one of the programs introduced by the government of Malaysia with the objectives of increasing food production,as well as supporting local agriculture entrepreneurs.The study employed a cross-sectional study design and has been conducted in four West Malaysian states with a sample of size of 275 respondents.The results indicated that the respondents had a positive attitude towards technology adoption and factors such as knowledge and skill,benefit,education level,years of experience in agriculture and gross income had influenced their attitude.
文摘Metallurgical sector plays an important role in the economy of each country because steel products present essential raw material for basic industries. Changes in the sectors of iron, steel and non-ferrous metals and the current development of technology forces the steel mills increased productivity, reduce production costs while ensuring to obtain a product with the required properties and to improve the competitiveness of enterprises in the global market. Currently, the most popular in meeting these requirements, enjoys a method of integration which combines individual operations into one integrated whole. The use of modem, perfectly designed, fully automated design of mechanical, hydraulic and measurement allowed us to achieve an innovative line of production. This article presents the general characteristics of the steel industry and a description of the latest integrated technology currently used in foundries and rolling mills. It also presents examples of the use of integrated technologies in metallurgy and the effects of economic, environmental and quality resulting from their use on an industrial scale.
文摘The notoriety of the shortage of qualified professionals in the engineering segment to meet the existing projects and also the future ones is worrying the academic community. These challenges show how the lack of appropriate courses and low expenses with incentives to research and extension programs can affect the formation of the future engineer. Therefore, universities have the mission to develop teaching, research and extension, offering to the students new opportunities for diverse technical training, scientific and humanist formation. It is noted, however, that such activities in many engineering courses, especially scientific research, are not being prioritized by the universities. In light of this, the present paper aims to register measure and evaluate the participation of the students in scientific initiation in the four engineering courses of the Faculty of Engineering of the Minas Gerais State University. Sticking to the disparities presented by the four courses studied, in relation to the participation in research projects, the results showed a greater engagement of students of Environmental Engineering and Mining Engineering courses regarding the other engineering courses. In addition, a better divulgation and a greater involvement of teachers in projects were identified as the main recurring challenges to the access in scientific research by the students of this institution.
基金supported by the National Key Research and Development Program of China(Nos.2018YFC0213106,2018YFC0213101,2018YFC0213102,2018YFC0213103,2018YFC0213104 and 2018YFC0213105)Anhui Provincial Natural Science Foundation(No.2108085QD177)the CASHIPS Director’s Fund(No.YZJJ2021QN07)。
文摘Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources,chemical mechanisms,and transport processes of air pollution in land,sea,and atmosphere.We present an overview of coastal ocean boundary layer detection technology and equipment in China and summarize the progress and main achievements in recent years.China has developed a series of coastal ocean boundary layer detection technologies,including Light Detection and Ranging(LIDAR),turbulent exchange analyzer,air-sea flux analyzer,stereoscopic remote sensing of air pollutants,and oceanic aerosol detection equipment to address the technical bottleneck caused by harsh environmental conditions in coastal ocean regions.Advances in these technologies and equipment have provided scientific assistance for addressing air pollution issues and understanding land-sea-atmosphere interactions over coastal ocean regions in China.In the future,routine atmospheric observations should cover the coastal ocean boundary layer of China.
