Financial Calculation Problems and Countermeasure Analysis of Large-Scale Engineering Construction Projects

The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.

Biomimetic natural biomaterials for tissue engineering and regenerative medicine:new biosynthesis methods,recent advances,and emerging applications

Biomimetic materials have emerged as attractive and competitive alternatives for tissue engineering(TE)and regenerative medicine.In contrast to conventional biomaterials or synthetic materials,biomimetic scaffolds based on natural biomaterial can offer cells a broad spectrum of biochemical and biophysical cues that mimic the in vivo extracellular matrix(ECM).Additionally,such materials have mechanical adaptability,micro-structure interconnectivity,and inherent bioactivity,making them ideal for the design of living implants for specific applications in TE and regenerative medicine.This paper provides an overview for recent progress of biomimetic natural biomaterials(BNBMs),including advances in their preparation,functionality,potential applications and future challenges.We highlight recent advances in the fabrication of BNBMs and outline general strategies for functionalizing and tailoring the BNBMs with various biological and physicochemical characteristics of native ECM.Moreover,we offer an overview of recent key advances in the functionalization and applications of versatile BNBMs for TE applications.Finally,we conclude by offering our perspective on open challenges and future developments in this rapidly-evolving field.

Compositional and Hollow Engineering of Silicon Carbide/Carbon Microspheres as High-Performance Microwave Absorbing Materials with Good Environmental Tolerance

Microwave absorbing materials(MAMs)characterized by high absorption efficiency and good environmental tolerance are highly desirable in practical applications.Both silicon carbide and carbon are considered as stable MAMs under some rigorous conditions,while their composites still fail to produce satisfactory microwave absorption performance regardless of the improvements as compared with the individuals.Herein,we have successfully implemented compositional and structural engineering to fabricate hollow Si C/C microspheres with controllable composition.The simultaneous modulation on dielectric properties and impedance matching can be easily achieved as the change in the composition of these composites.The formation of hollow structure not only favors lightweight feature,but also generates considerable contribution to microwave attenuation capacity.With the synergistic effect of composition and structure,the optimized SiC/C composite exhibits excellent performance,whose the strongest reflection loss intensity and broadest effective absorption reach-60.8 dB and 5.1 GHz,respectively,and its microwave absorption properties are actually superior to those of most SiC/C composites in previous studies.In addition,the stability tests of microwave absorption capacity after exposure to harsh conditions and Radar Cross Section simulation data demonstrate that hollow SiC/C microspheres from compositional and structural optimization have a bright prospect in practical applications.

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.

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.

Interface Engineering of Titanium Nitride Nanotube Composites for Excellent Microwave Absorption at Elevated Temperature

Currently,the microwave absorbers usually suffer dreadful electromagnetic wave absorption(EMWA)performance damping at elevated temperature due to impedance mismatching induced by increased conduction loss.Consequently,the development of high-performance EMWA materials with good impedance matching and strong loss ability in wide temperature spectrum has emerged as a top priority.Herein,due to the high melting point,good electrical conductivity,excellent environmental stability,EM coupling effect,and abundant interfaces of titanium nitride(TiN)nanotubes,they were designed based on the controlling kinetic diffusion procedure and Ostwald ripening process.Benefiting from boosted heterogeneous interfaces between TiN nanotubes and polydimethylsiloxane(PDMS),enhanced polarization loss relaxations were created,which could not only improve the depletion efficiency of EMWA,but also contribute to the optimized impedance matching at elevated temperature.Therefore,the TiN nanotubes/PDMS composite showed excellent EMWA performances at varied temperature(298-573 K),while achieved an effective absorption bandwidth(EAB)value of 3.23 GHz and a minimum reflection loss(RLmin)value of−44.15 dB at 423 K.This study not only clarifies the relationship between dielectric loss capacity(conduction loss and polarization loss)and temperature,but also breaks new ground for EM absorbers in wide temperature spectrum based on interface engineering.

Ionization Engineering of Hydrogels Enables Highly Efficient Salt‑Impeded Solar Evaporation and Night‑Time Electricity Harvesting

Interfacial solar evaporation holds immense potential for brine desalination with low carbon footprints and high energy utilization.Hydrogels,as a tunable material platform from the molecular level to the macroscopic scale,have been considered the most promising candidate for solar evaporation.However,the simultaneous achievement of high evaporation efficiency and satisfactory tolerance to salt ions in brine remains a challenging scientific bottleneck,restricting the widespread application.Herein,we report ionization engineering,which endows polymer chains of hydrogels with electronegativity for impeding salt ions and activating water molecules,fundamentally overcoming the hydrogel salt-impeded challenge and dramatically expediting water evaporating in brine.The sodium dodecyl benzene sulfonate-modified carbon black is chosen as the solar absorbers.The hydrogel reaches a ground-breaking evaporation rate of 2.9 kg m−2 h−1 in 20 wt%brine with 95.6%efficiency under one sun irradiation,surpassing most of the reported literature.More notably,such a hydrogel-based evaporator enables extracting clean water from oversaturated salt solutions and maintains durability under different high-strength deformation or a 15-day continuous operation.Meantime,on the basis of the cation selectivity induced by the electronegativity,we first propose an all-day system that evaporates during the day and generates salinity-gradient electricity using waste-evaporated brine at night,anticipating pioneer a new opportunity for all-day resource-generating systems in fields of freshwater and electricity.

Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

Trace Cobalt Doping and Defect Engineering of High Surface Area α-Ni(OH)_(2) for Electrocatalytic Urea Oxidation

Owing to the intrinsically sluggish kinetics of urea oxidation reaction(UOR)involving a six-electron transfer process,developing efficient UOR electrocatalyst is a great challenge remained to be overwhelmed.Herein,by taking advantage of 2-Methylimidazole,of which is a kind of alkali in water and owns strong coordination ability to Co^(2+)in methanol,trace Co(1.0 mol%)addition was found to induce defect engineering onα-Ni(OH)_(2)in a dual-solvent system of water and methanol.Physical characterization results revealed that the synthesized electrocatalyst(WM-Ni_(0.99)Co_(0.01)(OH)_(2))was a kind of defective nanosheet with thickness around 5-6 nm,attributing to the synergistic effect of Co doping and defect engineering,its electron structure was finely altered,and its specific surface a rea was tremendously enlarged from 68 to 172.3 m^(2)g^(-1).With all these merits,its overpotential to drive 10 mA cm^(-2)was reduced by 110 mV.Besides,the interfacial behavior of UOR was also well deciphered by operando electrochemical impedance spectroscopy.

Biomaterials and tissue engineering in traumatic brain injury:novel perspectives on promoting neural regeneration

Traumatic brain injury is a serious medical condition that can be attributed to falls, motor vehicle accidents, sports injuries and acts of violence, causing a series of neural injuries and neuropsychiatric symptoms. However, limited accessibility to the injury sites, complicated histological and anatomical structure, intricate cellular and extracellular milieu, lack of regenerative capacity in the native cells, vast variety of damage routes, and the insufficient time available for treatment have restricted the widespread application of several therapeutic methods in cases of central nervous system injury. Tissue engineering and regenerative medicine have emerged as innovative approaches in the field of nerve regeneration. By combining biomaterials, stem cells, and growth factors, these approaches have provided a platform for developing effective treatments for neural injuries, which can offer the potential to restore neural function, improve patient outcomes, and reduce the need for drugs and invasive surgical procedures. Biomaterials have shown advantages in promoting neural development, inhibiting glial scar formation, and providing a suitable biomimetic neural microenvironment, which makes their application promising in the field of neural regeneration. For instance, bioactive scaffolds loaded with stem cells can provide a biocompatible and biodegradable milieu. Furthermore, stem cells-derived exosomes combine the advantages of stem cells, avoid the risk of immune rejection, cooperate with biomaterials to enhance their biological functions, and exert stable functions, thereby inducing angiogenesis and neural regeneration in patients with traumatic brain injury and promoting the recovery of brain function. Unfortunately, biomaterials have shown positive effects in the laboratory, but when similar materials are used in clinical studies of human central nervous system regeneration, their efficacy is unsatisfactory. Here, we review the characteristics and properties of various bioactive materials, followed by the introduction of applications based on biochemistry and cell molecules, and discuss the emerging role of biomaterials in promoting neural regeneration. Further, we summarize the adaptive biomaterials infused with exosomes produced from stem cells and stem cells themselves for the treatment of traumatic brain injury. Finally, we present the main limitations of biomaterials for the treatment of traumatic brain injury and offer insights into their future potential.

Dual-Defect Engineering Strategy Enables High-Durability Rechargeable Magnesium-Metal Batteries

Rechargeable magnesium-metal batteries(RMMBs)are promising next-generation secondary batteries;however,their development is inhibited by the low capacity and short cycle lifespan of cathodes.Although various strategies have been devised to enhance the Mg^(2+)migration kinetics and structural stability of cathodes,they fail to improve electronic conductivity,rendering the cathodes incompatible with magnesium-metal anodes.Herein,we propose a dual-defect engineering strategy,namely,the incorporation of Mg^(2+)pre-intercalation defect(P-Mgd)and oxygen defect(Od),to simultaneously improve the Mg^(2+)migration kinetics,structural stability,and electronic conductivity of the cathodes of RMMBs.Using lamellar V_(2)O_(5)·nH_(2)O as a demo cathode material,we prepare a cathode comprising Mg_(0.07)V_(2)O_(5)·1.4H_(2)O nanobelts composited with reduced graphene oxide(MVOH/rGO)with P-Mgd and Od.The Od enlarges interlayer spacing,accelerates Mg^(2+)migration kinetics,and prevents structural collapse,while the P-Mgd stabilizes the lamellar structure and increases electronic conductivity.Consequently,the MVOH/rGO cathode exhibits a high capacity of 197 mAh g^(−1),and the developed Mg foil//MVOH/rGO full cell demonstrates an incredible lifespan of 850 cycles at 0.1 A g^(−1),capable of powering a light-emitting diode.The proposed dual-defect engineering strategy provides new insights into developing high-durability,high-capacity cathodes,advancing the practical application of RMMBs,and other new secondary batteries.

Phase-engineering modulation of Mn-based oxide cathode for constructing super-stable sodium storage

The Mn-based oxide cathode with enriched crystal phase structure and component diversity can provide the excellent chemistry structure for Na-ion batteries.Nevertheless,the broad application prospect is obstructed by the sluggish Na^(+)kinetics and the phase transitions upon cycling.Herein,we establish the thermodynamically stable phase diagram of various Mn-based oxide composites precisely controlled by sodium content tailoring strategy coupling with co-doping and solid-state reaction.The chemical environment of the P2/P'3 and P2/P3 biphasic composites indicate that the charge compensation mechanism stems from the cooperative contribution of anions and cations.Benefiting from the no phase transition to scavenge the structure strain,P2/P'3 electrode can deliver long cycling stability(capacity retention of 73.8%after 1000 cycles at 10 C)and outstanding rate properties(the discharge capacity of 84.08 mA h g^(-1)at 20 C)than P2/P3 electrode.Furthermore,the DFT calculation demonstrates that the introducing novel P'3 phase can significantly regulate the Na^(+)reaction dynamics and modify the local electron configuration of Mn.The effective phase engineering can provide a reference for designing other high-performance electrode materials for Na-ion batteries.

From VIB‑to VB‑Group Transition Metal Disulfides:Structure Engineering Modulation for Superior Electromagnetic Wave Absorption

The laminated transition metal disulfides(TMDs),which are well known as typical two-dimensional(2D)semiconductive materials,possess a unique layered structure,leading to their wide-spread applications in various fields,such as catalysis,energy storage,sensing,etc.In recent years,a lot of research work on TMDs based functional materials in the fields of electromagnetic wave absorption(EMA)has been carried out.Therefore,it is of great significance to elaborate the influence of TMDs on EMA in time to speed up the application.In this review,recent advances in the development of electromagnetic wave(EMW)absorbers based on TMDs,ranging from the VIB group to the VB group are summarized.Their compositions,microstructures,electronic properties,and synthesis methods are presented in detail.Particularly,the modulation of structure engineering from the aspects of heterostructures,defects,morphologies and phases are systematically summarized,focusing on optimizing impedance matching and increasing dielectric and magnetic losses in the EMA materials with tunable EMW absorption performance.Milestones as well as the challenges are also identified to guide the design of new TMDs based dielectric EMA materials with high performance.

Accelerated Sequential Deposition Reaction via Crystal Orientation Engineering for Low-Temperature,High-Efficiency Carbon-Electrode CsPbBr_(3) Solar Cells

Low-temperature,ambient processing of high-quality CsPbBr_(3)films is demanded for scalable production of efficient,low-cost carbon-electrode perovskite solar cells(PSCs).Herein,we demonstrate a crystal orientation engineering strategy of PbBr_(2)precursor film to accelerate its reaction with CsBr precursor during two-step sequential deposition of CsPbBr_(3)films.Such a novel strategy is proceeded by adding CsBr species into PbBr_(2)precursor,which can tailor the preferred crystal orientation of PbBr_(2)film from[020]into[031],with CsBr additive staying in the film as CsPb_(2)Br_(5)phase.Theoretical calculations show that the reaction energy barrier of(031)planes of PbBr_(2)with CsBr is lower about 2.28 eV than that of(O2O)planes.Therefore,CsPbBr_(3)films with full coverage,high purity,high crystallinity,micro-sized grains can be obtained at a low temperature of 150℃.Carbon-electrode PSCs with these desired CsPbBr_(3)films yield the record-high efficiency of 10.27%coupled with excellent operation stability.Meanwhile,the 1 cm^(2)area one with the superior efficiency of 8.00%as well as the flexible one with the champion efficiency of 8.27%and excellent mechanical bending characteristics are also achieved.

Composition Engineering Opens an Avenue Toward Efficient and Sustainable Nitrogen Fixation

In this work,we open an avenue toward rational design of potential efficient catalysts for sustainable ammonia synthesis through composition engineering strategy by exploiting the synergistic effects among the active sites as exemplified by diatomic metals anchored graphdiyne via the combination of hierarchical high-throughput screening,first-principles calculations,and molecular dynamics simulations.Totally 43 highly efficient catalysts feature ultralow onset potentials(|U_(onset)|≤0.40 V)with Rh-Hf and Rh-Ta showing negligible onset potentials of 0 and-0.04 V,respectively.Extremely high catalytic activities of Rh-Hf and Rh-Ta can be ascribed to the synergistic effects.When forming heteronuclears,the combinations of relatively weak(such as Rh)and relatively strong(such as Hf or Ta)components usually lead to the optimal strengths of adsorption Gibbs free energies of reaction intermediates.The origin can be ascribed to the mediate d-band centers of Rh-Hf and Rh-Ta,which lead to the optimal adsorption strengths of intermediates,thereby bringing the high catalytic activities.Our work provides a new and general strategy toward the architecture of highly efficient catalysts not only for electrocatalytic nitrogen reduction reaction(eNRR)but also for other important reactions.We expect that our work will boost both experimental and theoretical efforts in this direction.

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.

Defect engineering in transition-metal(Fe,Co,andNi)-based electrocatalysts for water splitting

Electrocatalytic water splitting seems to be an efficient strategy to deal with increasingly serious environmental problems and energy crises but still suffers from the lack of stable and efficient electrocatalysts.Designing practical electrocatalysts by introducing defect engineering,such as hybrid structure,surface vacancies,functional modification,and structural distortions,is proven to be a dependable solution for fabricating electrocatalysts with high catalytic activities,robust stability,and good practicability.This review is an overview of some relevant reports about the effects of defect engineering on the electrocatalytic water splitting performance of electrocatalysts.In detail,the types of defects,the preparation and characterization methods,and catalytic performances of electrocatalysts are presented,emphasizing the effects of the introduced defects on the electronic structures of electrocatalysts and the optimization of the intermediates'adsorption energy throughout the review.Finally,the existing challenges and personal perspectives of possible strategies for enhancing the catalytic performances of electrocatalysts are proposed.An in-depth understanding of the effects of defect engineering on the catalytic performance of electrocatalysts will light the way to design high-efficiency electrocatalysts for water splitting and other possible applications.

Large-scale model testing of high-pressure grouting reinforcement for bedding slope with rapid-setting polyurethane

Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.

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.

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.