Synergistic anionic/zwitterionic mixed surfactant system with high emulsification efficiency for enhanced oil recovery in low permeability reservoirs

Emulsification is one of the important mechanisms of surfactant flooding. To improve oil recovery for low permeability reservoirs, a highly efficient emulsification oil flooding system consisting of anionic surfactant sodium alkyl glucosyl hydroxypropyl sulfonate(APGSHS) and zwitterionic surfactant octadecyl betaine(BS-18) is proposed. The performance of APGSHS/BS-18 mixed surfactant system was evaluated in terms of interfacial tension, emulsification capability, emulsion size and distribution, wettability alteration, temperature-resistance and salt-resistance. The emulsification speed was used to evaluate the emulsification ability of surfactant systems, and the results show that mixed surfactant systems can completely emulsify the crude oil into emulsions droplets even under low energy conditions. Meanwhile,the system exhibits good temperature and salt resistance. Finally, the best oil recovery of 25.45% is achieved for low permeability core by the mixed surfactant system with a total concentration of 0.3 wt%while the molar ratio of APGSHS:BS-18 is 4:6. The current study indicates that the anionic/zwitterionic mixed surfactant system can improve the oil flooding efficiency and is potential candidate for application in low permeability reservoirs.

Conventional Geothermal Systems and Unconventional Geothermal Developments: An Overview

This paper provides an overview of conventional geothermal systems and unconventional geothermal developments as a common reference is needed for discussions between energy professionals. Conventional geothermal systems have the heat, permeability and fluid, requiring only drilling down to °C, normal heat flow or decaying radiogenic granite as heat sources, and used in district heating. Medium-temperature (MT) 100°C - 190°C, and high-temperature (HT) 190°C - 374°C resources are mostly at plate boundaries, with volcanic intrusive heat source, used mostly for electricity generation. Single well capacities are °C - 500°C) and a range of depths (1 m to 20 Km), but lack permeability or fluid, thus requiring stimulations for heat extraction by conduction. HVAC is 1 - 2 m deep and shallow geothermal down to 500 m in wells, both capturing °C, with °C are either advanced by geothermal developers at <7 Km depth (Enhanced Geothermal Systems (EGS), drilling below brittle-ductile transition zones and under geothermal fields), or by the Oil & Gas industry (Advanced Geothermal Systems, heat recovery from hydrocarbon wells or reservoirs, Superhot Rock Geothermal, and millimeter-wave drilling down to 20 Km). Their primary aim is electricity generation, relying on closed-loops, but EGS uses fractures for heat exchange with earthquake risks during fracking. Unconventional approaches could be everywhere, with shallow geothermal already functional. The deeper and hotter unconventional alternatives are still experimental, overcoming costs and technological challenges to become fully commercial. Meanwhile, the conventional geothermal resources remain the most proven opportunities for investments and development.

A Review on Engineering Design for Enhancing Interfacial Contact in Solid-State Lithium–Sulfur Batteries

The utilization of solid-state electrolytes(SSEs)presents a promising solution to the issues of safety concern and shuttle effect in Li–S batteries,which has garnered significant interest recently.However,the high interfacial impedances existing between the SSEs and the electrodes(both lithium anodes and sulfur cathodes)hinder the charge transfer and intensify the uneven deposition of lithium,which ultimately result in insufficient capacity utilization and poor cycling stability.Hence,the reduction of interfacial resistance between SSEs and electrodes is of paramount importance in the pursuit of efficacious solid-state batteries.In this review,we focus on the experimental strategies employed to enhance the interfacial contact between SSEs and electrodes,and summarize recent progresses of their applications in solidstate Li–S batteries.Moreover,the challenges and perspectives of rational interfacial design in practical solid-state Li–S batteries are outlined as well.We expect that this review will provide new insights into the further technique development and practical applications of solid-state lithium batteries.

Mechanistic insights into stepwise activation of malachite for enhancing surface reactivity and flotation performance

Malachite is a common copper oxide mineral that is often enriched using the sulfidization-xanthate flotation method.Currently,the direct sulfidization method cannot yield copper concentrate products.Therefore,a new sulfidization flotation process was developed to promote the efficient recovery of malachite.In this study,Cu^(2+) was used as an activator to interact with the sample surface and increase its reaction sites,thereby strengthening the mineral sulfidization process and reactivity.Compared to single copper ion activation,the flota-tion effect of malachite significantly increased after stepwise Cu^(2+) activation.Zeta potential,X-ray photoelectron spectroscopy(XPS),time-of-flight secondary ion mass spectroscopy(ToF-SIMS),scanning electron microscopy and energy dispersive spectrometry(SEM-EDS),and atomic force microscopy(AFM)analysis results indicated that the adsorption of S species was significantly enhanced on the mineral surface due to the increase in active Cu sites after Cu^(2+) stepwise activation.Meanwhile,the proportion of active Cu-S spe-cies also increased,further improving the reaction between the sample surface and subsequent collectors.Fourier-transform infrared spec-troscopy(FT-IR)and contact angle tests implied that the xanthate species were easily and stably adsorbed onto the mineral surface after Cu^(2+) stepwise activation,thereby improving the hydrophobicity of the mineral surface.Therefore,the copper sites on the malachite sur-face after Cu^(2+) stepwise activation promote the reactivity of the mineral surface and enhance sulfidization flotation of malachite.

Atomically Substitutional Engineering of Transition Metal Dichalcogenide Layers for Enhancing Tailored Properties and Superior Applications

Transition metal dichalcogenides(TMDs)are a promising class of layered materials in the post-graphene era,with extensive research attention due to their diverse alternative elements and fascinating semiconductor behavior.Binary MX2 layers with different metal and/or chalcogen elements have similar structural parameters but varied optoelectronic properties,providing opportunities for atomically substitutional engineering via partial alteration of metal or/and chalcogenide atoms to produce ternary or quaternary TMDs.The resulting multinary TMD layers still maintain structural integrity and homogeneity while achieving tunable(opto)electronic properties across a full range of composition with arbitrary ratios of introduced metal or chalcogen to original counterparts(0–100%).Atomic substitution in TMD layers offers new adjustable degrees of freedom for tailoring crystal phase,band alignment/structure,carrier density,and surface reactive activity,enabling novel and promising applications.This review comprehensively elaborates on atomically substitutional engineering in TMD layers,including theoretical foundations,synthetic strategies,tailored properties,and superior applications.The emerging type of ternary TMDs,Janus TMDs,is presented specifically to highlight their typical compounds,fabrication methods,and potential applications.Finally,opportunities and challenges for further development of multinary TMDs are envisioned to expedite the evolution of this pivotal field.

Effects of fracture evolution and non-Darcy flow on the thermal performance of enhanced geothermal system in 3D complex fractured rock

In fractured geothermal reservoirs,the fracture networks and internal fluid flow behaviors can significantly impact the thermal performance.In this study,we proposed a non-Darcy rough discrete fracture network(NR-DFN)model that can simultaneously consider the fracture evolution and non-Darcy flow dynamics in studying the thermo-hydro-mechanical(THM)coupling processes for heat extraction in geothermal reservoir.We further employed the model on the Habanero enhanced geothermal systems(EGS)project located in Australia.First,our findings illustrate a clear spatial-temporal variation in the thermal stress and pressure perturbations,as well as uneven spatial distribution of shear failure in 3D fracture networks.Activated shear failure is mainly concentrated in the first fracture cluster.Secondly,channeling flow have also been observed in DFNs during heat extraction and are further intensified by the expansion of fractures driven by thermal stresses.Moreover,the combined effect of non-Darcy flow and fracture evolution triggers a rapid decline in the resulting heat rate and temperature.The NR-DFN model framework and the Habanero EGS's results illustrate the importance of both fracture evolution and non-Darcy flow on the efficiency of EGS production and have the potential to promote the development of more sustainable and efficient EGS operations for stakeholders.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

Strong field ionization of molecules on the surface of nanosystems

Besides the diverse investigations on the interactions between intense laser fields and molecular systems,extensive research has been recently dedicated to exploring the response of nanosystems excited by well-tailored femtosecond laser fields.Due to the fact that nanostructures hold peculiar effects when illuminated by laser pulses,the underlying mechanisms and the corresponding potential applications can make significant improvements in both fundamental research and development of novel techniques.In this review,we provide a summarization of the strong field ionization occurring on the surface of nanosystems.The molecules attached to the nanoparticle surface perform as the precursor in the ionization and excitation of the whole nanosystem,the fundamental processes of which are yet to be discovered.We discuss the influence on nanoparticle constituents,geometric shapes and sizes,as well as the specific waveforms of the excitation laser fields.The intriguing characteristics observed in surface ion emission reflect how enhanced near field affects the localized ionizations and nanoplasma expansions,thereby paving the way for further precision controls on the light-and-matter interactions in the extreme spatial temporal levels.

Development and Validation of an Automatic Ultrawide-Field Fundus Imaging Enhancement System for Facilitating Clinical Diagnosis:A Cross-Sectional Multicenter Study

In ophthalmology,the quality of fundus images is critical for accurate diagnosis,both in clinical practice and in artificial intelligence(AI)-assisted diagnostics.Despite the broad view provided by ultrawide-field(UWF)imaging,pseudocolor images may conceal critical lesions necessary for precise diagnosis.To address this,we introduce UWF-Net,a sophisticated image enhancement algorithm that takes disease characteristics into consideration.Using the Fudan University ultra-wide-field image(FDUWI)dataset,which includes 11294 Optos pseudocolor and 2415 Zeiss true-color UWF images,each of which is rigorously annotated,UWF-Net combines global style modeling with feature-level lesion enhancement.Pathological consistency loss is also applied to maintain fundus feature integrity,significantly improving image quality.Quantitative and qualitative evaluations demonstrated that UWF-Net outperforms existing methods such as contrast limited adaptive histogram equalization(CLAHE)and structure and illumination constrained generative adversarial network(StillGAN),delivering superior retinal image quality,higher quality scores,and preserved feature details after enhancement.In disease classification tasks,images enhanced by UWF-Net showed notable improvements when processed with existing classification systems over those enhanced by StillGAN,demonstrating a 4.62%increase in sensitivity(SEN)and a 3.97%increase in accuracy(ACC).In a multicenter clinical setting,UWF-Net-enhanced images were preferred by ophthalmologic technicians and doctors,and yielded a significant reduction in diagnostic time((13.17±8.40)s for UWF-Net enhanced images vs(19.54±12.40)s for original images)and an increase in diagnostic accuracy(87.71%for UWF-Net enhanced images vs 80.40%for original images).Our research verifies that UWF-Net markedly improves the quality of UWF imaging,facilitating better clinical outcomes and more reliable AI-assisted disease classification.The clinical integration of UWF-Net holds great promise for enhancing diagnostic processes and patient care in ophthalmology.

A salt-induced tackifying polymer for enhancing oil recovery in highsalinity reservoirs:Synthesis,evaluation,and mechanism

Polymerflooding is an effective method widely applied for enhancing oil recovery(EOR)by reducing the mobility ratio between theinjected water and crude oil.However,traditional polymers encounter challenges in high salinity reservoirs due to their salt sensitivity.Toovercome this challenge,we synthesized a zwitterion polymer(PAMNS)with salt-induced tackifying property through copolymerization ofacrylamide and a zwitterion monomer,methylacrylamide propyl-N,N-dimethylbutylsulfonate(NS).NS monomer is obtained from thereaction between 1,4-butanesultone and dimethylamino propyl methylacrylamide.In this study,the rheological properties,salt responsiveness,and EOR efficiency of PAMNS were evaluated.Results demonstrate that PAMNS exhibits desirable salt-induced tackifyingcharacteristics,with viscosity increasing up to 2.4 times as the NaCl concentration reaches a salinity of 30×10^(4)mg L^(-1).Furthermore,highvalence ions possess a much stronger effect on enhancing viscosity,manifested as Mg^(2+)>Ca^(2+)>Na^(+).Molecular dynamics simulations(MD)andfluid dynamics experiment results demonstrate that PAMNS molecules exhibit a more stretched state and enhanced intermolecularassociations in high-salinity environments.It is because of the salt-induced tackifying,PAMNS demonstrates superior performance inpolymerflooding experiments under salinity ranges from 5×10^(4)mg L^(-1)to 20×10^(4)mg L^(-1),leading to 10.38–19.83%higher EOR thantraditional polymers.

Mass Transfer-Promoted Fe^(2+)/Fe^(3+)Circulation Steered by 3D Flow-Through Co-Catalyst System Toward Sustainable Advanced Oxidation Processes

Realizing fast and continuous generation of reactive oxygen species(ROSs)via iron-based advanced oxidation processes(AOPs)is significant in the environmental and biological fields.However,current AOPs assisted by co-catalysts still suffer from the poor mass/electron transfer and non-durable promotion effect,giving rise to the sluggish Fe^(2+)/Fe^(3+)cycle and low dynamic concentration of Fe^(2+)for ROS production.Herein,we present a three-dimensional(3D)macroscale co-catalyst functionalized with molybdenum disulfide(MoS_(2))to achieve ultra-efficient Fe^(2+)regeneration(equilibrium Fe^(2+)ratio of 82.4%)and remarkable stability(more than 20 cycles)via a circulating flow-through process.Unlike the conventional batch-type reactor,experiments and computational fluid dynamics simulations demonstrate that the optimal utilization of the 3D active area under the flow-through mode,initiated by the convectionenhanced mass/charge transfer for Fe^(2+)reduction and then strengthened by MoS_(2)-induced flow rotation for sufficient reactant mixing,is crucial for oxidant activation and subsequent ROS generation.Strikingly,the flow-through co-catalytic system with superwetting capabilities can even tackle the intricate oily wastewater stabilized by different surfactants without the loss of pollutant degradation efficiency.Our findings highlight an innovative co-catalyst system design to expand the applicability of AOPs based technology,especially in large-scale complex wastewater treatment.

Scene 3-D Reconstruction System in Scattering Medium

Research on neural radiance fields for novel view synthesis has experienced explosive growth with the development of new models and extensions.The NeRF(Neural Radiance Fields)algorithm,suitable for underwater scenes or scattering media,is also evolving.Existing underwater 3D reconstruction systems still face challenges such as long training times and low rendering efficiency.This paper proposes an improved underwater 3D reconstruction system to achieve rapid and high-quality 3D reconstruction.First,we enhance underwater videos captured by a monocular camera to correct the image quality degradation caused by the physical properties of the water medium and ensure consistency in enhancement across frames.Then,we perform keyframe selection to optimize resource usage and reduce the impact of dynamic objects on the reconstruction results.After pose estimation using COLMAP,the selected keyframes undergo 3D reconstruction using neural radiance fields(NeRF)based on multi-resolution hash encoding for model construction and rendering.In terms of image enhancement,our method has been optimized in certain scenarios,demonstrating effectiveness in image enhancement and better continuity between consecutive frames of the same data.In terms of 3D reconstruction,our method achieved a peak signal-to-noise ratio(PSNR)of 18.40 dB and a structural similarity(SSIM)of 0.6677,indicating a good balance between operational efficiency and reconstruction quality.

A Study on Enhancing Chip Detection Efficiency Using the Lightweight Van-YOLOv8 Network

In pursuit of cost-effective manufacturing,enterprises are increasingly adopting the practice of utilizing recycled semiconductor chips.To ensure consistent chip orientation during packaging,a circular marker on the front side is employed for pin alignment following successful functional testing.However,recycled chips often exhibit substantial surface wear,and the identification of the relatively small marker proves challenging.Moreover,the complexity of generic target detection algorithms hampers seamless deployment.Addressing these issues,this paper introduces a lightweight YOLOv8s-based network tailored for detecting markings on recycled chips,termed Van-YOLOv8.Initially,to alleviate the influence of diminutive,low-resolution markings on the precision of deep learning models,we utilize an upscaling approach for enhanced resolution.This technique relies on the Super-Resolution Generative Adversarial Network with Extended Training(SRGANext)network,facilitating the reconstruction of high-fidelity images that align with input specifications.Subsequently,we replace the original YOLOv8smodel’s backbone feature extraction network with the lightweight VanillaNetwork(VanillaNet),simplifying the branch structure to reduce network parameters.Finally,a Hybrid Attention Mechanism(HAM)is implemented to capture essential details from input images,improving feature representation while concurrently expediting model inference speed.Experimental results demonstrate that the Van-YOLOv8 network outperforms the original YOLOv8s on a recycled chip dataset in various aspects.Significantly,it demonstrates superiority in parameter count,computational intricacy,precision in identifying targets,and speed when compared to certain prevalent algorithms in the current landscape.The proposed approach proves promising for real-time detection of recycled chips in practical factory settings.

Resilience Augmentation in Unmanned Weapon Systems via Multi-Layer Attention Graph Convolutional Neural Networks

The collective Unmanned Weapon System-of-Systems(UWSOS)network represents a fundamental element in modern warfare,characterized by a diverse array of unmanned combat platforms interconnected through hetero-geneous network architectures.Despite its strategic importance,the UWSOS network is highly susceptible to hostile infiltrations,which significantly impede its battlefield recovery capabilities.Existing methods to enhance network resilience predominantly focus on basic graph relationships,neglecting the crucial higher-order dependencies among nodes necessary for capturing multi-hop meta-paths within the UWSOS.To address these limitations,we propose the Enhanced-Resilience Multi-Layer Attention Graph Convolutional Network(E-MAGCN),designed to augment the adaptability of UWSOS.Our approach employs BERT for extracting semantic insights from nodes and edges,thereby refining feature representations by leveraging various node and edge categories.Additionally,E-MAGCN integrates a regularization-based multi-layer attention mechanism and a semantic node fusion algo-rithm within the Graph Convolutional Network(GCN)framework.Through extensive simulation experiments,our model demonstrates an enhancement in resilience performance ranging from 1.2% to 7% over existing algorithms.

Theoretical analysis and engineering application of controllable shock wave technology for enhancing coalbed methane in soft and low‑permeability coal seams

Coalbed methane(CBM)is a significant factor in triggering coal and gas outburst disaster,while also serving as a clean fuel.With the increasing depth of mining operations,coal seams that exhibit high levels of gas content and low permeability have become increasingly prevalent.While controllable shockwave(CSW)technology has proven effective in enhancing CBM in laboratory settings,there is a lack of reports on its field applications in soft and low-permeability coal seams.This study establishes the governing equations for stress waves induced by CSW.Laplace numerical inversion was employed to analyse the dynamic response of the coal seam during CSW antireflection.Additionally,quantitative calculations were performed for the crushed zone,fracture zone,and effective CSW influence range,which guided the selection of field test parameters.The results of the field test unveiled a substantial improvement in the gas permeability coefficient,the average rate of pure methane flowrate,and the mean gas flowrate within a 10 m radius of the antireflection borehole.These enhancements were notable,showing increases of 3 times,13.72 times,and 11.48 times,respectively.Furthermore,the field test performed on the CSW antireflection gas extraction hole cluster demonstrated a noticeable improvement in CBM extraction.After antireflection,the maximum peak gas concentration and maximum peak pure methane flow reached 71.2%and 2.59 m^(3)/min,respectively.These findings will offer valuable guidance for the application of CSW antireflection technology in soft and low-permeability coal seams.

Dynamic contrast enhanced ultrasound in differential diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis

BACKGROUND Non-invasive differential diagnosis between hepatocellular carcinoma(HCC)and other liver cancer(i.e.cholangiocarcinoma or metastasis)is highly challenging and definitive diagnosis still relies on histological exam.The patterns of enhancement and wash-out of liver nodules can be used to stratify the risk of malignancy only in cirrhotic patients and HCC frequently shows atypical features.Dynamic contrast-enhanced ultrasound(DCEUS)with standardized software could help to overcome these obstacles,providing functional and quantitative parameters and potentially improving accuracy in the evaluation of tumor perfusion.AIM To explore clinical evidence regarding the application of DCEUS in the differential diagnosis of liver nodules.METHODS A comprehensive literature search of clinical studies was performed to identify the parameters of DCEUS that could relate to histological diagnosis.In accordance with the study protocol,a qualitative and quantitative analysis of the evidence was planned.RESULTS Rise time was significantly higher in HCC patients with a standardized mean difference(SMD)of 0.83(95%CI:0.48-1.18).Similarly,other statistically significant parameters were mean transit time local with a SMD of 0.73(95%CI:0.20-1.27),peak enhancement with a SMD of 0.37(95%CI:0.03-0.70),area wash-in area under the curve with a SMD of 0.47(95%CI:0.13-0.81),wash-out area under the curve with a SMD of 0.55(95%CI:0.21-0.89)and wash-in and wash-out area under the curve with SMD of 0.51(95%CI:0.17-0.85).SMD resulted not significant in fall time and wash-in rate,but the latter presented a trend towards greater values in HCC compared to intrahepatic cholangiocarcinoma.CONCLUSION DCEUS could improve non-invasive diagnosis of HCC,leading to less liver biopsy and early treatment.This quantitative analysis needs to be applied on larger cohorts to confirm these preliminary results.

Enhancing Adaptability, Nutritional Quality in Tropical Tuber Crops: Source for Adaptive Food and Nutrition

The tropical roots and tuber crops (R and T) consist of cassava, sweet potato, yams, elephant foot yam, taro, tannia and a couple of minor tuber crops. Tropical tuber crops are the third most important food crops after cereals and pulses. These crops play a crucial role in providing food and nutritional security to the rural masses in Africa, Latin America and parts of Asia. Cassava and sweet potato rank among the top 10 food crops produced in developing countries and contribute to about 6% of world’s dietary calories. In India, tropical tubers are grown mostly in states like Odisha, West Bengal, Andhra Pradesh, Kerala, Tamil Nadu, Bihar and North East covering 4.5% of the total area under vegetables with 5.7% of the total vegetable production. Low income farmers and most undernourished households in India depend on R and T crops. They value these crops for their high calorie and stable yields under conditions in which other crops may fail. Genetic diversity of major tropical tuber crops provides options for its diverse usage in “multicuisine”, “nutrition”, “feed”, health care” and renewable resources of processing firms. Water productivity is also higher, for example, to produce 1 kg of tubers, sweet potatoes require water (383 l), taro (606 l), yam (343 l), as compared to rice (1673 l), maize (1222 l), wheat (1827 l), etc. Tuber crops are one of most efficient producers of dry matter and edible energy. These crops have potential to reverse soil degradation. Cassava is already recognized as drought tolerant followed by yam. Tubers of taro, elephant foot yam and yams can be stored under zero energy conditions for 6 - 7 months unlike temperate potatoes in cold storage. The natural climatic resilience as well as inherent nutrition attributes, has been explored further. Such studies made these crops more robust to changing climate and as the source of nutrient enriched food bowls. Sweet potato variety Bhu Krishna is the first purple flesh variety in India containing (90 mg/100 g anthocyanin) coupled with starch 22% - 25%. Similarly, the orange flesh Bhu Sona containing beta carotene (14 mg/100 g) coupled with high starch 22% - 24% is the first variety having both high beta carotene and high starch. These varieties are tolerant to salinity and Bhu Krishna is resistant to weevil. Likewise, developed improved taro varieties resistant to biotic blight stress, tolerant to salinity and are enriched with micro nutrients. These improved varieties are used to breed the superior types further. All these climate resilient, nutritionally enriched varieties will have a greater impact on supplementing rainbow food for all. These can address the issues like “food insecurity”, “malnutrition”, diet related issue of mass consumers across the world. The analysis of innovations on enhancing adaptability, nutritional quality with a management matrix would help in strengthening future programme.

A Study on the Role of Tourism in Enhancing Personal Mental Health in the Post-Epidemic Era

With the advent of the post-epidemic era,a great wave of tourism has been ushered in everywhere.The relationship between tourism and mental health has become a hot topic in society.This paper investigates the enhancement of people’s mental health after tourism through social survey.Using Hangzhou as the sample collection site,this paper conducted a study on the role of tourism in enhancing personal mental health through descriptive analysis,factor analysis and structural equation modeling,and further specifically analyzed the role of mediating variables.The results showed that:(1)The purpose of tourism is to relax and relieve stress,and the effectiveness of tourism is mainly reflected in the alleviation of emotional conditions;(2)Factor Analysis reduced the dimensionality of personal mental health indicators,and finally obtained four factors,among which the comprehensive behavioral ability and physiological manifestation had the best improvement effect after tourism;(3)The structural equation model shows that the enhancing effect of tourism on mental health originates from the factor of inner psychological characteristic,and this factor works through two paths:Inner Psychological Characteristic-Social Adaptability-Physiological Manifestations-Enhancement of Mental Health by Tourism,and Inner Psychological Characteristic-Comprehensive Behavioral Ability-Enhancement of Mental Health by Tourism;(4)Tourism has an enhancing effect on personal mental health,and the enhancing effect is most significant among the middle-aged and young people who are unmarried and do not have children yet.These results have been reasonably analyzed and explained,and relevant suggestions are put forward.

Geothermo-mechanical alterations due to heat energy extraction in enhanced geothermal systems: Overview and prospective directions

Geothermal energy from deep underground (or geological) formations,with or without its combination with carbon capture and storage (CCS),can be a key technology to mitigate anthropogenic greenhouse gas emissions and meet the 2050 net‐zero carbon emission target.Geothermal resources in low‐permeability and medium‐and high‐temperature reservoirs in sedimentary sequence require hydraulic stimulation for enhanced geothermal systems (EGS).However,fluid migration for geothermal energy in EGS or with potential CO_(2) storage in a CO_(2)‐EGS are both dependent on the in situ flow pathway network created by induced fluid injection.These thermo‐mechanical interactions can be complex and induce varying alterations in the mechanical response when the working fluid is water (in EGS) or supercritical CO_(2)(in CO_(2)‐EGS),which could impact the geothermal energy recovery from geological formations.Therefore,there is a need for a deeper understanding of the heat extraction process in EGS and CO_(2)‐EGS.This study presents a systematic review of the effects of changes in mechanical properties and behavior of deep underground rocks on the induced flow pathway and heat recovery in EGS reservoirs with or without CO_(2) storage in CO_(2) ‐EGS.Further,we proposed waterless‐stimulated EGS as an alternative approach to improve heat energy extraction in EGS.Lastly,based on the results of our literature review and proposed ideas,we recommend promising areas of investigation that may provide more insights into understanding geothermo‐mechanics to further stimulate new research studies and accelerate the development of geothermal energy as a viable clean energy technology.

Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant attention.Previously developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic features.The images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human actions.Poor lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging task.The unimodal-based HAR approaches are not suitable in a real-time environment.Therefore,an updated HAR model is developed using multiple types of data and an advanced deep-learning approach.Firstly,the required signals and sensor data are accumulated from the standard databases.From these signals,the wave features are retrieved.Then the extracted wave features and sensor data are given as the input to recognize the human activity.An Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition process.Additionally,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition process.An experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR model.The EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,respectively.The result proved that the developed model is effective in recognizing human action by taking less time.Additionally,it reduces the computation complexity and overfitting issue through using an optimization approach.