A combined method using Lattice Boltzmann Method(LBM)and Finite Volume Method(FVM)to simulate geothermal reservoirs in Enhanced Geothermal System(EGS)

With the development of industrial activities,global warming has accelerated due to excessive emission of CO_(2).Enhanced Geothermal System(EGS)utilizes deep geothermal heat for power generation.Although porous medium theory is commonly employed to model geothermal reservoirs in EGS,Hot Dry Rock(HDR)presents a challenge as it consists of impermeable granite with zero porosity,potentially distorting the physical interpretation.To address this,the Lattice Boltzmann Method(LBM)is employed to simulate CO_(2)flow within geothermal reservoirs and the Finite Volume Method(FVM)to solve the energy conservation equation for temperature distribution.This combined method of LBM and FVM is imple-mented using MATLAB.The results showed that the Reynolds numbers(Re)of 3,000 and 8,000 lead to higher heat extraction rates from geothermal reservoirs.However,higher Re values may accelerate thermal breakthrough,posing challenges to EGS operation.Meanwhile,non-equilibrium of density in fractures becomes more pronounced during the system's life cycle,with non-Darcy's law becoming significant at Re values of 3,000 and 8,000.Density stratification due to buoyancy effects significantly impacts temperature distribution within geothermal reservoirs,with buoyancy effects at Re=100 under gravitational influence being noteworthy.Larger Re values(3,000 and 8,000)induce stronger forced convection,leading to more uniform density distribution.The addition of proppant negatively affects heat transfer performance in geothermal reservoirs,especially in single fractures.Practical engineering considerations should determine the quantity of proppant through detailed numerical simulations.

Extracting water body data based on SDWI and threshold segmentation:A case study in permafrost area surrounding Salt Lake in Hoh Xil,Qinghai-Tibet Plateau,China

There are a large number of lakes,rivers,and other natural water bodies distributed in the permafrost area of the Qinghai-Tibet Plateau(QTP).The changes in water bodies will affect the distribution of water resources in sur-rounding areas and downstream areas,resulting in environmental impact and bringing potential flood disasters,which will induce more serious issues and problems in alpine and high-altitude areas with a fragile habitat(such as the QTP in China).Generally,effective,reasonable,and scientific monitoring of large-scale water bodies can not only document the changes in water bodies intuitively,but also provide important theoretical reference for subsequent environmental impact prediction,and disaster prevention and mitigation in due course of time.The large-scale water extraction technology derived from the optical remote sensing(RS)image is seriously affected by clouds,bringing about large differences among the extracted water result products.Synthetic aperture radar(SAR)RS technology has the unique advantage characteristics of all-weather,all-day,strong penetration,and not being affected by clouds,which is hopeful in extracting water body data,especially for days with cloudy weather.The data extraction of large-scale water bodies based on SAR images can effectively avoid the errors caused by clouds that become prevalent at present.In this paper,the Hoh Xil Salt Lake on the QTP and its surrounding five lakes are taken as the research objects.The 2-scene Sentinel-1 SAR image data covering the whole area on 22 August 2022 was used to verify the feasibility of extracting water body data in permafrost zones.Furthermore,on 22 August 2022,the wealth here was cloudy,which made the optical RS images,e.g.,Sentinel-2 images full of clouds.The results show that:using the Sentinel-1 image and threshold segmentation method to extract water body data is efficient and effective with excellent results in permafrost areas.Concretely,the Sentinel-1 dual-polarized water index(SDWI),calculated by combining dual vertical–vertical(VV)polarized and verti-cal–horizontal(VH)polarized data is a useful index for water extraction and the result is better than each of the VV or VH polarized images.

Applying Customized Convolutional Neural Network to Kidney Image Volumes for Kidney Disease Detection

Kidney infection is a severe medical issue affecting individuals worldwide and increasing mortality rates.Chronic Kidney Disease(CKD)is treatable during its initial phases but can become irreversible and cause renal failure.Among the various diseases,the most prevalent kidney conditions affecting kidney function are cyst growth,kidney tumors,and nephrolithiasis.The significant challenge for the medical community is the immediate diagnosis and treatment of kidney disease.Kidney failure could result from kidney disorders like tumors,stones,and cysts if not often identified and addressed.Computer-assisted diagnostics are necessary to support clinicians’and specialists’medical assessments due to the rising prevalence of chronic renal illness,the lack of experts,and the rising rates of assessment and monitoring,mainly in developing nations.Artificial Intelligence(AI)approaches such as machine,and deep learning has been used in literature for kidney disease detection;however,they still lack performance.This paper implements a deep learning-based Convolutional Neural Network(CNN)model for the classification and prognosis of kidney disease.We use a benchmark Computed Tomography(CT)kidney dataset for experimentation.The data is pre-processed,and then CNN extracts the features from the images.Results reveal that the proposed approach accurately classifies kidney disease with a considerable accuracy of 0.992%,0.994%precision,0.982%recall,and 0.987%F1-score.This study suggests using the proposed fine-tuned CNN model for kidney disease detection.

On Some Problems of Extracting the Root from a Given Finite Language

Based on the standard definition of the product (concatenation), the natural non-negative degree of the language is introduced. Root extraction is the reverse operation to it, and it can be defined in several different ways. Despite the simplicity of the formulation of the problem of extracting the root, the authors could not find any description of it in the literature (as well as on the Internet), including even its formulation. Most of the material in this article is devoted to the simplest version of the formulation: the root of the 2nd degree for the 1-letter alphabet, but many of the provisions of the article are generalized to more complex cases. Apparently, for a possible future description of a polynomial algorithm for solving at least one of the described statements of root extraction problems, it is first necessary to really analyze in detail such a special case, that is: either describe the necessary polynomial algorithm, or, conversely, show that the problem belongs to the class of NP-complete problems. Thus, in this article, we do not propose a polynomial algorithm for the problems under consideration;however, the models described here should help in constructing appropriate heuristic algorithms for their solution. A detailed description of the possible further application of such heuristic algorithms is beyond the scope of this article. .

A Method Suitable for Extracting Genomic DNA from Animal and Plant——Modified CTAB Method

[Objective] The study aimed to introduce a rapid and effective method that is suitable for extracting genomic DNA from animal and plant. [ Method ] The genomic DNAs were extracted from tender leaves of 24 peanut cuhivars and from the liver, lung and kidney of white mouse through the specifically modified CTAB method. The DNAs were run on agarose gel, next detected by DNA/Protein analyzer. Finally PCR amplification was conducted to detect the quality of DNAs extracted using the modified CTAB method. [ Result] The clear and orderly bands were observed in gel detection, and the values of OD200/OD200 for DNAs extracted via modified CTAB method were between 1.77 - 1.83. The DNAs performed well in PCR amplification. [ Conclusion] The DNAs extracted by modified CTAB method could satisfy the requirement of PCR amplification.

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

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

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

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

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

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

Modified CTAB Method for Extracting Genomic DNA from Wheat Leaf

ObjectiveThe aim was to seek for a rapid DNA minipreparation method from wheat leaf. MethodThe total DNA of wheat leaf was extracted using CTAB, SDS and boiling water, separately, with some modifications. Integrity and purity of nucleic acids were detected through agarose gel electrophoresis, ultraviolet absorption and PCR. ResultThe DNA extracted by the modified CTAB method had high quality and purity, and was not degraded. Two hundreds of DNA samples could be extracted each workday by per capita using this method; and the PCR detection of wheat transgenic plants showed that amplified bands of target gene were clear, without false-positive, and the test results were satisfactory. The DNA purity and concentration extracted by modified SDS method were not as good as that extracted by modified CTAB method, but it also met the DNA requirements of major molecular research. The DNA quantity extracted by modified boiling method was small and there were a lot of impurities in it, PCR detection of this DNA showed no amplified band. ConclusionModified CTAB method is a simple and rapid method for DNA minipreparation from wheat leaf, and was suitable for PCR amplification and other molecular biology researches.

A Simple and Quick Method of Extracting Genomic DNA from Wheat Leaves

[ Objective] The aim was to seek a simple and quick method of extracting genomic DNA from wheat leaves. [ Method] Taking tender leaves of wheat as test materials, total DNA of transgenic wheat was extracted by using modified CTAB method. The extracted DNA was detected by 0.8% agarose gel electrophoresis. [ Result] DNA purity of extracted genome DNA from wheat was high and no degradation phenomenon using modified CTAB method, and was suitable for carrying out normal PCR amplification. [ Conclusion] This study provides a simple and quick method for extracting DNA from wheat with a spot of material.

A Review on Sources,Extractions and Analysis Methods of a Sustainable Biomaterial:Tannins

Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.

An Improved Method of Extracting Artemisia abrotanum Genomic DNA

[ Objective ] The objective of this study is to explore a rapid and efficient method of extracting genomic DNA from Artemisia abrotanum. [ Method] Three methods of Cutting Method, Liquid Nitrogen Method and Quartz Sand Method based on SDS method were employed to extract Artemisia abrotanum genomlc DNA from tender leaf at seedling stage, tender spike and old leaf at heading stage. The obtained DNAs were detected by absorbance detection, agarose gel and PCR amplification. [ Result ] Cutting Method performed better than the other two methods compared in purity, extracting cycle and cost, accordingly more suitable for PCR amplification. The results also show that young spike is the best material for extracting genomic DNA from Artemisia Annua.

Biomaterials-based anti-inflammatory treatment strategies for Alzheimer's disease

The current therapeutic drugs for Alzheimer's disease only improve symptoms,they do not delay disease progression.Therefo re,there is an urgent need for new effective drugs.The underlying pathogenic factors of Alzheimer's disease are not clear,but neuroinflammation can link various hypotheses of Alzheimer's disease;hence,targeting neuroinflammation may be a new hope for Alzheimer's disease treatment.Inhibiting inflammation can restore neuronal function,promote neuro regeneration,reduce the pathological burden of Alzheimer's disease,and improve or even reverse symptoms of Alzheimer's disease.This review focuses on the relationship between inflammation and various pathological hypotheses of Alzheimer's disease;reports the mechanisms and characteristics of small-molecule drugs(e.g.,nonsteroidal anti-inflammatory drugs,neurosteroids,and plant extracts);macromolecule drugs(e.g.,peptides,proteins,and gene therapeutics);and nanocarriers(e.g.,lipid-based nanoparticles,polymeric nanoparticles,nanoemulsions,and inorganic nanoparticles)in the treatment of Alzheimer's disease.The review also makes recommendations for the prospective development of anti-inflammatory strategies based on nanocarriers for the treatment of Alzheimer's disease.

Phosphotungstic acid ionic liquid for efficient photocatalytic desulfurization:Synthesis,application and mechanism

An efficient mass transfer process is a critical factor for regulating catalytic activity in a photocatalytic desulfurization system.Herein,a phosphotungstic acid(HPW)active center is successfully composited with a quaternary ammonium phosphotungstate-based hexadecyltrimethylammonium chloride ionic liquid(CTAC-HPW)by the ion exchange method for the photocatalytic oxidative desulfurization of dibenzothiophene sulfide.The keggin structure of HPW and highly mass transfer performance of organic cations synergistically enhanced the photocatalytic activity towards the effective convertion of dibenzothiophene(DBT)with the excitation of visible light.The deep desulfurization(<10 mg·kg^(-1))is attained within 30 min,and well stability is demonstrated within 25 cycles.Moreover,the CTAC-HPW photocatalyst projects well selectivity to interference from coexisting compounds such as olefins and aromatic hydrocarbons and universality of dibenzothiophenes,for example,4-methyldibenzothiophene(4-MDBT)and 4,6-dimethyldibenzothiophene(4,6-DMDBT).Ultimately,a possible photocatalytic desulfurization mechanism is proposed according to the Gaschromatography-mass spectrometry(GC-MS),proving that the final product is the corresponding sulfone.The trapping experiment and electron spin resonance(ESR)analysis confirmed that h^(+)and,COOH played critical roles in the oxidation process.The work offers a practicable strategy for efficiently converting DBT to DBTO_(2) with added value.

An Effective Method for Extracting Total RNA from Young Embryo of Seedless Litchi

A total RNA extraction method for young embryo of seedless litchi was introduced. CTAB, Phenol （saturated with water）, chloroform, Guanidine isothioeyanate were used as main extraction reagents. Polyphenolie compounds were removed effectively by added PVP into the extraction buffer solution. RNA was purified intensively by phenol, chloroform extraction, and ethanol deposition after deposited by LiCl. Both the results of formaldehyde denatured agarose gel eleetrophoresis and ultraviolet spectrophotometer analysis showed high integrity and purity of RNA. So the quality of extracted RNA could meet the demand of most molecular biology experiments that require higher quality RNA.

Genomic DNA Isolation by Phenol/Chloroform Extracting Method from Sheep Blood Clot

[ Objective] The aim was to establish the method of extracting genomic DNA from sheep blood clot on the basis of the improvement of method for extracting genomic DNA from tissues. [Method]The genomic DNA with complete primary structure and high purity was obtained from the sheep blood clot after the steps of cutting the sheep blood clot with ophthalmic scissors, cell lysis with tissue DNA extracts and digested by proteinase K, extracting with phenol/chloroform and precipitating with ethanol were performed. [ Result] The concentration of the extracted DNA was 159.90 ±0.70 ng/μl and the ratio of the A260/A280 was 1.80 ＋0.01. The sheep microsatellite locus of BM203 was amplified by using the extracted DNA from the sheep blood clot as template of PCR, and the PCR result was perfect. [Conclusion]This method is simple and feasible, the quantity and quality of the extracted DNA can satisfy the demands for the subsequent researches. It is worth to extending and using for reference.

Experimental investigation on coal pore-fracture variation and fractal characteristics synergistically affected by solvents for improving clean gas extraction

Chemical solvents instead of pure water being as hydraulic fracturing fluid could effectively increase permeability and improve clean methane extraction efficiency.However,pore-fracture variation features of lean coal synergistically affected by solvents have not been fully understood.Ultrasonic testing,nuclear magnetic resonance analysis,liquid phase mass spectrometry was adopted to comprehensively analyze pore-fracture change characteristics of lean coal treated by combined solvent(NMP and CS_(2)).Meanwhile,quantitative characterization of above changing properties was conducted using geometric fractal theory.Relationship model between permeability,fractal dimension and porosity were established.Results indicate that the end face fractures of coal are well developed after CS2and combined solvent treatments,of which,end face box-counting fractal dimensions range from 1.1227 to 1.4767.Maximum decreases in ultrasonic longitudinal wave velocity of coal affected by NMP,CS_(2)and combined solvent are 2.700%,20.521%,22.454%,respectively.Solvent treatments could lead to increasing amount of both mesopores and macropores.Decrease ratio of fractal dimension Dsis 0.259%–2.159%,while permeability increases ratio of NMR ranges from 0.1904 to 6.4486.Meanwhile,combined solvent could dissolve coal polar and non-polar small molecules and expand flow space.Results could provide reference for solvent selection and parameter optimization of permeability-enhancement technology.

A data-driven model of drop size prediction based on artificial neural networks using small-scale data sets

An artificial neural network(ANN)method is introduced to predict drop size in two kinds of pulsed columns with small-scale data sets.After training,the deviation between calculate and experimental results are 3.8%and 9.3%,respectively.Through ANN model,the influence of interfacial tension and pulsation intensity on the droplet diameter has been developed.Droplet size gradually increases with the increase of interfacial tension,and decreases with the increase of pulse intensity.It can be seen that the accuracy of ANN model in predicting droplet size outside the training set range is reach the same level as the accuracy of correlation obtained based on experiments within this range.For two kinds of columns,the drop size prediction deviations of ANN model are 9.6%and 18.5%and the deviations in correlations are 11%and 15%.

Artificial intelligence-driven radiomics study in cancer:the role of feature engineering and modeling

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.Moreover,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical practice.In contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical endpoints.Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research.