Large-scale physical simulation of injection and production of hot dry rock in Gonghe Basin,Qinghai Province,China

Based on the independently developed true triaxial multi-physical field large-scale physical simulation system of in-situ injection and production,we conducted physical simulation of long-term multi-well injection and production in the hot dry rocks of the Gonghe Basin,Qinghai Province,NW China.Through multi-well connectivity experiments,the spatial distribution characteristics of the natural fracture system in the rock samples and the connectivity between fracture and wellbore were clarified.The injection and production wells were selected to conduct the experiments,namely one injection well and two production wells,one injection well and one production well.The variation of several physical parameters in the production well was analyzed,such as flow rate,temperature,heat recovery rate and fluid recovery.The results show that under the combination of thermal shock and injection pressure,the fracture conductivity was enhanced,and the production temperature showed a downward trend.The larger the flow rate,the faster the decrease.When the local closed area of the fracture was gradually activated,new heat transfer areas were generated,resulting in a lower rate of increase or decrease in the mining temperature.The heat recovery rate was mainly controlled by the extraction flow rate and the temperature difference between injection and production fluid.As the conductivity of the leak-off channel increased,the fluid recovery of the production well rapidly decreased.The influence mechanisms of dominant channels and fluid leak-off on thermal recovery performance are different.The former limits the heat exchange area,while the latter affects the flow rate of the produced fluid.Both of them are important factors affecting the long-term and efficient development of hot dry rock.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

Shenqi Fuzheng injection alleviates chemotherapy-induced cachexia by restoring glucocorticoid signaling in hypothalamus

Chemotherapy-induced cachexia(CIC)is a debilitating condition characterized by weight loss,muscle atrophy,and anorexia[1].While peripheral mechanisms of cachexia have been extensively studied,the involvement of the central nervous system(CNS)in CIC is often overlooked.Chemotherapeutic drugs cause stress responses and inflammation,which may impact the hypothalamus and disrupt systemic energy and neuroendocrine functions.Understanding hypothalamic roles in regulating these processes can provide insights into CIC's mechanisms and aid in developing novel therapies.

Does HSP27 injection induce glaucoma damage in mice?

In a further aging society,excellent eyesight is an integral part of overall well-being and quality of life.Preserving good vision is crucial to maintaining mobility,independence,and mental health.There can be several reasons for visual impairment in elderly people,these include age-related macular degeneration,the leading cause of vision loss among older adults,cataract,glaucoma,diabetic retinopathy,retinal detachment,and others.

Numerical Simulation of Asphaltene Precipitation and Deposition during Natural Gas and CO_(2) Injection

Asphaltene deposition is a significant problem during gas injection processes,as it can block the porous medium,the wellbore,and the involved facilities,significantly impacting reservoir productivity and ultimate oil recovery.Only a few studies have investigated the numerical modeling of this potential effect in porous media.This study focuses on asphaltene deposition due to natural gas and CO_(2) injection.Predictions of the effect of gas injection on asphaltene deposition behavior have been made using a 3D numerical simulation model.The results indicate that the injection of natural gas exacerbates asphaltene deposition,leading to a significant reduction in permeability near the injection well and throughout the reservoir.This reduction in permeability strongly affects the ability of gas toflow through the reservoir,resulting in an improvement of the displacement front.The displacement effi-ciency of the injection gas process increases by up to 1.40%when gas is injected at 5500 psi,compared to the scenario where the asphaltene model is not considered.CO_(2) injection leads to a miscible process with crude oil,extracting light and intermediate components,which intensifies asphaltene precipitation and increases the viscosity of the remaining crude oil,ultimately reducing the recovery rate.

Tofacitinib combined with local low-dose ixekizumab injection benefits those with peripheral psoriatic arthritis

Dear Editor,Treating psoriatic arthritis(PsA)is always difficult.Systemic treatments can be administered either orally or through intramuscular and intra-articular injection,including conventional synthetics,biologics and targeted synthetic disease-modifying antirheumatic drugs[1].The alternatives,topical external therapies,are not effective on joint lesions due to drug permeability issues.Drugs injected into the articular cavity are also unsuitable for small peripheral joint lesions,the most common manifestations of PsA.The limited treatment options for PsA present a challenge.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

Experimental study of the influencing factors and mechanisms of the pressure-reduction and augmented injection effect by nanoparticles in ultra-low permeability reservoirs

Nanoparticles(NPs)have gained significant attention as a functional material due to their ability to effectively enhance pressure reduction in injection processes in ultra-low permeability reservoirs.NPs are typically studied in controlled laboratory conditions,and their behavior in real-world,complex environments such as ultra-low permeability reservoirs,is not well understood due to the limited scope of their applications.This study investigates the efficacy and underlying mechanisms of NPs in decreasing injection pressure under various injection conditions(25—85℃,10—25 MPa).The results reveal that under optimal injection conditions,NPs effectively reduce injection pressure by a maximum of 22.77%in core experiment.The pressure reduction rate is found to be positively correlated with oil saturation and permeability,and negatively correlated with temperature and salinity.Furthermore,particle image velocimetry(PIV)experiments(25℃,atmospheric pressure)indicate that the pressure reduction is achieved by NPs through the reduction of wall shear resistance and wettability change.This work has important implications for the design of water injection strategies in ultra-low permeability reservoirs.

Background diseases and the number of previous intravitreal aflibercept injections on immediate intraocular pressure increase and vitreous reflux rate in phakic eyes

●AIM:To evaluate the effect of background diseases and number of previous intravitreal aflibercept injections(IVAIs)on immediate intraocular pressure(IOP)increase and vitreous reflux(VR)rate and to evaluate the correlation of both age and axial length with immediate IOP increase and VR rate.●METHODS:This study included 105 patients with cystoid macular edema secondary to retinal vein occlusion,35 patients with diabetic macular edema,69 patients with neovascular age-related macular degeneration(nAMD),and 12 patients with myopic choroidal neovascularization,which underwent first-time IVAI.The correlation of immediate IOP increase and VR rates with the four background diseases was investigated.Moreover,the correlation of age with immediate IOP increase and VR rate as well as correlation of axial length with immediate IOP increase and VR rate were evaluated.Further,54 patients with nAMD were treated with IVAI>10 times(multiple IVAIs).Moreover,the correlation of immediate IOP increase and VR rates with first-time and multiple IVAIs in nAMD was determined.●RESULTS:The immediate IOP increase(P=0.16)and VR rates(P=0.50)were almost similar among the four background diseases.The immediate postinjection IOP and age,VR rate and age,immediate postinjection IOP and axial length,or VR rate and axial length were not correlated in the four background diseases.The immediate IOP increase(P=0.66)and VR rates(P=0.28)did not significantly differ between first-time and multiple IVAIs in nAMD.●CONCLUSION:Background diseases and number of previous IVAIs have no effect on immediate IOP increase and VR rate.Further,age and axial length have no correlation on immediate IOP increase and VR rate.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Intravitreal injection practice patterns among Chinese ophthalmologists

AIM:To describe the practice patterns of intravitreal injections(IVIs)among ophthalmologists in China.METHODS:This was a cross-sectional online survey.Ophthalmologists who had performed accumulated more than 100 injections were contacted by the Brightness Center,a hospital-based national network,to complete an anonymous,24-question,internet-based survey.They were surveyed on practices in injection techniques,pre-,and post-injections procedures.RESULTS:A total of 333 ophthalmologists from 28 provinces/municipalities/autonomous regions responded to the survey(50.68%response rate).The 91.29%of the respondents evaluated systemic risk factors by medical history,electrocardiogram(ECG)and blood test.All the respondents used pre-injection prophylactic antibiotics.Most checked intraocular pressure(IOP,99.1%)and blood pressure(96.1%)before injections.A majority of the respondents performed injections in the operating room(98.8%),wore masks(99.7%),gloves(99.4%)and sterile surgical clothing(96.1%),performed topical anesthetics(97.9%),and applied povidone-iodine(95.8%)pre-injection.The 61.26%of the respondents dilated pupil.About half of the respondents(51.05%)performed bilateral injections in the same setting.Superior temporal quadrant(40.54%)was the most frequent site of injection.Around three quarters used 30-gauge needles.Most respondents(97.9%)measured the site of injection from limbus.More than half(53.45%)performed conjunctiva displacement prior to injection.The 32.43%of the respondents checked IOP post-injection and 87.99%physicians checked hand motion(HM)or counting fingers(CF)after injection,while 36.94%observed optic nerve perfusion.All participants used topical antibiotics post-injections.Most physicians(91.89%)reviewed patients on the following day.CONCLUSION:This study provides a description of the real-world practice patterns in IVIs in China and offers critical information regarding education and training of ophthalmologists and amendment of local society guidelines.

Cross-upgrading of biomass hydrothermal carbonization and pyrolysis for high quality blast furnace injection fuel production:Physicochemical characteristics and gasification kinetics analysis

The paper proposes a biomass cross-upgrading process that combines hydrothermal carbonization and pyrolysis to produce high-quality blast furnace injection fuel.The results showed that after upgrading,the volatile content of biochar ranged from 16.19%to 45.35%,and the alkali metal content,ash content,and specific surface area were significantly reduced.The optimal route for biochar pro-duction is hydrothermal carbonization-pyrolysis(P-HC),resulting in biochar with a higher calorific value,C=C structure,and increased graphitization degree.The apparent activation energy(E)of the sample ranges from 199.1 to 324.8 kJ/mol,with P-HC having an E of 277.8 kJ/mol,lower than that of raw biomass,primary biochar,and anthracite.This makes P-HC more suitable for blast furnace injection fuel.Additionally,the paper proposes a path for P-HC injection in blast furnaces and calculates potential environmental benefits.P-HC of-fers the highest potential for carbon emission reduction,capable of reducing emissions by 96.04 kg/t when replacing 40wt%coal injec-tion.

Efficacy of acupoint injection in the treatment of chronic eczema and its influence on peripheral blood T cells

BACKGROUND Chronic eczema significantly impacts daily life,social interactions,and quality of life;however,no curative treatment has been identified.AIM To determine the clinical efficacy of acupoint injection for chronic eczema and its influence on peripheral blood T cells.METHODS Eighty patients with chronic eczema treated at our hospital between June 2022 and March 2023 were randomly assigned to a control group(n=40),which received conventional Western medicine treatment,or an observation group(n=40),which received routine Western medicine treatment plus acupoint injection of triamcinolone acetonide.Response and adverse reaction rates,as well as differences in the levels of serum cytokines IFN-γ,IL-2,IL-4,and IL-10 before and after treatment were investigated.RESULTS No difference in overall response rates were found between the observation and control groups(100%vs 90%,respectively;P>0.05);however,the observation group had a higher marked response rate than the control group(87.5%vs 52.5%;P<0.05).Both groups had decreased Eczema Area and Severity Index scores and increased pruritus after treatment(P<0.05),particularly in the observation group(P<0.05).The observation group had an adverse reaction rate of 2.5%(1/40),which did not differ significantly from that of the control group(P>0.05).The observation group exhibited higher post-treatment INF-γand IL-2 but lower IL-4 levels than the control group(P<0.05);however,no significant inter-group difference was observed in post-treatment IL-10 levels(P>0.05).CONCLUSION Acupoint injection of triamcinolone acetonide is safe and effective in treating chronic eczema.Its therapeutic mechanism is related to the regulation of peripheral blood T cell levels,inhibition of inflammatory reactions,and mitigation of immune imbalance.

Self-expanding metal stent for relieving the stricture after endoscopic injection for esophageal varices

BACKGROUND Esophageal stricture is one of the complications after esophageal varices sclero-therapy injection(ESI),and the incidence rate is between 2%-10%.AIM To explore the efficacy of self-expanding metal stent(SEMS)for the stricture after endoscopic injection with cyanoacrylate(CYA)and sclerotherapy for esophageal varices.METHODS We retrospectively analyzed the efficacy of SEMS to improve the stricture after endoscopic injection with CYA and sclerotherapy for esophageal varices in 4 patients from February 2023 to June 2023.RESULTS The strictures were improved in four patients after stenting.The stent was removed after two weeks because of chest pain with embedding into esophageal mucosa in one patient.The stent was removed after one month,however,the stent was reinserted because of the strictures happening again in two patients.The stent was removed after three months,however,the stent was reinserted because of the strictures happening again in one patient.The stent embedded into esophageal mucosa in three patients.There were 3 patients suffered reflux esophagitis,and the acid reflux was relieved by taking hydrotalcite.There was no other complication of esophageal perforation,bleeding from varices or infection.CONCLUSION SEMS may relieve the stricture which happened after endoscopic injection with CYA and sclerotherapy for esophageal varices.However,when we should remove the stent still needs to be explored.

Horizontal well spacing optimization and gas injection simulation for the ultra-low-permeability Yongjin reservoir

Optimal spacing for vertical wells can be effectively predicted with several published methods,but methods suitable for assessing the proper horizontal well spacing are rare.This work proposes a method for calculating the optimal horizontal well spacing for an ultra-low permeability reservoir e the Yongjin reservoir in the Juggar Basin,northwestern China.The result shows that a spacing of 640m is the most economical for the development of the reservoir.To better develop the reservoir,simulation approaches are used and a new model is built based on the calculated well spacing.Since the reservoir has an ultralow permeability,gas injection is regarded as the preferred enhanced oil recovery(EOR)method.Injection of different gases including carbon dioxide,methane,nitrogen and mixed gas are modelled.The results show that carbon dioxide injection is the most efficient and economical for the development of the reservoir.However,if the reservoir produces enough methane,reinjecting methane is even better than injecting carbon dioxide.

A New Heat Transfer Model for Multi-Gradient Drilling with Hollow Sphere Injection

Multi-gradient drilling is a new offshore drilling method.The accurate calculation of the related wellbore temperature is of great significance for the prediction of the gas hydrate formation area and the precise control of the wellbore pressure.In this study,a new heat transfer model is proposed by which the variable mass flow is properly taken into account.Using this model,the effects of the main factors influencing the wellbore temperature are analyzed.The results indicate that at the position where the separation injection device is installed,the temperature increase of the fluid in the drill pipe is mitigated due to the inflow/outflow of hollow spheres,and the temperature drop of the fluid in the annulus also decreases.In addition,a lower separation efficiency of the device,a shallower installation depth and a smaller circulating displacement tend to increase the temperature near the bottom of the annulus,thereby helping to reduce the hydrate generation area and playing a positive role in the prevention and control of hydrates in deepwater drilling.