Strategy For Construction Research Articles

Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion.

Brain-computer interface (BCI) for motor imagery is an advanced technology used in the field of medical rehabilitation. However, due to the poor accuracy of electroencephalogram feature classification, BCI systems often misrecognize user commands. Although many state-of-the-art feature selection methods aim to enhance classification accuracy, they usually overlook the interrelationships between individual features, indirectly impacting the accuracy of feature classification. To overcome this issue, we propose an adaptive feature learning model that employs a Riemannian geometric approach to generate a feature matrix from electroencephalogram signals, serving as the model's input. By integrating the enhanced adaptive L1 penalty and weighted fusion penalty into the sparse learning model, we select the most informative features from the matrix. Specifically, we measure the importance of features using mutual information and introduce an adaptive weight construction strategy to penalize regression coefficients corresponding to each variable adaptively. Moreover, the weighted fusion penalty balances weight differences among correlated variables, reducing the model's overreliance on specific variables and enhancing accuracy. The performance of the proposed method was validated on BCI Competition IV datasets IIa and IIb using the support vector machine. Experimental results demonstrate the effectiveness and superiority of the proposed model compared to the existing models.

An Improved Body Force Model to Simulate Blade Loading Variation Under Various Operating Conditions in Transonic Axial Flow Compressor

Abstract In order to analyze the unsteady aerodynamic response of compressors with limited computational resources, the development of the body force (BF) model has been pursued for decades. This model can simulate the effects of the compressor blade on the flow by applying a three-dimensional (3D) force field. Indeed, the accuracy of the BF model simulation highly depends on the construction strategy of BF field. However, for a transonic compressor, the influence of shock waves on the spatial distribution of blade loading is significant, which makes the construction of an appropriate BF field challenging. To solve this issue, an accurate BF model is proposed to describe the effects of the blade on the flow with high spatial fidelity in transonic compressors. For verification, a typical transonic fan rotor, NASA-Rotor 67, is selected. The numerical results calculated by the new BF model are compared with those obtained by the Reynolds-averaged Navier–Stokes (RANS) solver. According to the results, the new model can accurately capture the distribution of blade loading in the transonic blade channel at various operating conditions, eventually leading to a good prediction of compressor performance and the radial distribution of flow parameters downstream of the rotor. Moreover, this study discusses the causes of modeling errors and presents the application of the model in inlet distortion simulation at the end.

An integrated digital design and construction approach for falsework-minimal masonry vaults

Masonry vaults, mechanically efficient structures, are challenging to build because they require significant tailored falsework as temporary structures for centering, guidework, and scaffolding, which decreases construction productivity and increases financial cost and environmental impact. Traditional building techniques combined with recent digital technologies can eliminate such temporary construction. An integrated digital design and construction approach that leverages the benefits of four construction strategies (namely, thin-tile vaulting, loxodrome tessellation, augmented reality, and prefabricated spine) within a 4D funicular design framework is presented in this paper and illustrated by a large-scale demonstrator, innixAR. This structure demonstrates that the combination of the vernacular craft of thin-tile vaulting with augmented reality technology to produce a digital guidework, informing a 4D funicular design process that considers the entire construction sequence from a prefabricated spine, minimizes the required falsework, making the construction of masonry vaults more efficient and affordable. This approach is benchmarked against alternative conventional vault falsework. Combining thin-tile vaulting and prefabricated spine allowed a reduction of 82% of the falsework mass, making transport lighter. Whereas combining digital guidework and prefabricated spine allowed a reduction of 91% of the falsework elements, making assembly faster. This research contributes to the development of structures that are efficient both mechanically and constructionally.

Optimizing Portfolio Construction Using Nifty India Manufacturing Index: A Risk-Return Analysis with Python

This paper presents a comprehensive analysis of portfolio construction strategies aimed at maximizing risk-adjusted returns for investors. Utilizing historical data on stock returns and risks, a meticulous selection process was employed to identify 15 stocks with superior risk-return profiles. These stocks were chosen based on their outperformance relative to the dataset's average measures, prioritizing returns higher than the dataset average and risks lower than average risk levels. The selected stocks, representing a diverse range of manufacturing-related businesses, formed the cornerstone of an optimal portfolio designed to minimize sector-specific risks while maximizing growth potential. Through rigorous portfolio optimization techniques, including Markowitz's mean-variance optimization, the study identified an optimal portfolio allocation with a return of 50.22% and volatility of 13.33%. Insights from the study offer valuable perspectives for investors seeking realistic and sustainable wealth accumulation strategies. The research also identifies avenues for future exploration, including the integration of alternative asset classes, behavioral finance insights, and advancements in risk management technologies. This study demonstrates the effectiveness of Python in financial analysis and portfolio optimization while furthering the theory of portfolios and providing valuable guidance for making investment decisions. Keywords: Returns, Risk, Volatility, Optimal Portfolio Construction, Manufacturing Sector, Markowitz Portfolio Theory,

Integrated construction of stretchable supercapacitor with outstanding deformation stability and flame retardancy

The fast development of wearable electronics requires urgently stretchable energy storage devices, but conventional stretchable energy-storage devices suffer from poor dynamic deformation stability. The key is to create a new construction strategy of "electrode/electrolyte interface integration". Herein, we have proposed a clever strategy that combines layer-by-layer electrospinning with a self-selected vapor-phase polymerization (VPP) method to assemble the integrated stretchable supercapacitors (ISSCs). Furthermore, the interface stability enhancement mechanism is revealed through experimental and theoretical simulations, showing that the synergistic effect of molecular chain entanglement and mechanical meshing endows excellent anti-deformation stability of ISSCs. As a result, the as-assembled ISSCs deliver excellent dynamic deformation electrochemical stability with 99.5 % capacitance retention after 500 stretching cycles at strain and outstanding flame retardancy (limiting oxygen index (LOI) up to 48.1 % at a film thickness of only 0.22 mm). The innovative integrated design strategy endows a systematic construction plan for the scalable fabrication of wearable organic energy storage devices.

Dilemma of Teaching Chinese Abroad: Constructive Teaching Strategies for TCSL Teachers

Dilemma of Teaching Chinese Abroad: Constructive Teaching Strategies for TCSL Teachers

A Novel SDN-Based Architecture of Task Offloading in Mobile Ad-Hoc Cloud

As the core function of mobile Ad-hoc cloud, task offloading has always been a research hotspot of mobile cloud computing, and the construction, offloading decision, task division and scheduling strategies of mobile Ad-hoc cloud directly affect the performance of offloading. In this paper, we propose a new mobile Ad-hoc cloud architecture based on SDN solving the performance bottleneck of opportunistic task offloading. The proposed solution constructs terminal clusters in Ad-hoc cloud to provide users with offloading service, and makes offloading decision and task allocation through SDN controller to achieve the effectiveness of task allocation and the rationality of resource scheduling. Simulation results show that compared with traditional scheduling method, our method has the advantages in offloading ratio and execution efficiency, and can be more effectively used in dynamic mobile edge network environment, to improve network performance and user service satisfaction.

Enhancing Green Port Construction through Advanced Computing: An Evolutionary Game Model under Social Accountability and Government Supervision

Ports, as pivotal hubs for global resource consumption and pollution emissions, have garnered considerable attention in the pursuit of sustainability. Despite the Chinese government’s efforts in promoting the green construction of ports and a growing public awareness of environmental protection, progress remains sluggish, with pollution and energy consumption issues still rampant. This paper introduces an evolutionary game model that leverages advanced computing techniques, including big data analytics and simulation, to optimize green port construction strategies, supervision, and enforcement under the lens of social accountability. By applying the Jacobi matrix for analyzing equilibrium paths at diverse initial settings and conducting simulations under various scenarios of punishment intensity and social accountability probabilities, this study unveils that high social accountability likelihoods naturally incentivize ports towards green practices. Conversely, in low accountability scenarios, differentiated outcomes emerge from imposing penalties on ports and local governments. Notably, increasing penalties on ports substantially elevates green construction standards, whereas local government penalties exhibit only transient efficacy. Furthermore, leveraging artificial intelligence for predictive analysis and simulation demonstrates the critical role of technological advancements in enhancing green port construction. The study proposes augmenting penalties on ports, amplifying social oversight, and diminishing green construction costs via port consortia as strategic measures to expedite China’s transition to green ports.

Long-Range Imaging LiDAR with Multiple Denoising Technologies

The ability to capture and record high-resolution images over long distances is essential for a wide range of applications, including connected and autonomous vehicles, defense and security operations, as well as agriculture and mining industries. Here, we demonstrate a self-assembled bistatic long-range imaging LiDAR system. Importantly, to achieve high signal-to-noise ratio (SNR) data, we employed a comprehensive suite of denoising methods including temporal, spatial, spectral, and polarization filtering. With the aid of these denoising technologies, our system has been validated to possess the capability of imaging under various complex usage conditions. In terms of distance performance, the test results achieved ranges of over 4000 m during daylight with clear weather, 19,200 m at night, 6700 m during daylight with haze, and 2000 m during daylight with rain. Additionally, it offers an angular resolution of 0.01 mrad. These findings demonstrate the potential to offer comprehensive construction strategies and operational methodologies to individuals seeking long-range LiDAR data.

Brief Analysis of the Short Video Communication Strategy of "Xiaogang Story"

"Xiaogang Story" is the story of Xiaogang Village and a portrayal of China's rural reform process over the past 44 years. Starting from the perspective of the red countryside, this article innovatively constructs the content of the short video "Xiaogang Story" based on historical records and "Xiaogang Spirit", and studies the content narrative of the short video communication of "Xiaogang Story" with the mass media interaction model as the main axis. With production, communication channels, recipients, communication effects and optimization mechanisms, explore the path and situation of the short video communication of "Xiaogang Story", with a view to making constructive strategies for the media communication of "Xiaogang Story" in the new era of socialism nature, forward-looking, practical thinking and guidance, and give full play to the high-energy motivation and mission of the "Xiaogang Spirit".

Optimizing Anode Construction for Improved Performance in Ecological Floating Bed Microbial Electrochemical System (ECOFB-MES): Engineering Application and Construction Strategy

Optimizing Anode Construction for Improved Performance in Ecological Floating Bed Microbial Electrochemical System (ECOFB-MES): Engineering Application and Construction Strategy

Spheroid construction strategies and application in 3D bioprinting

Spheroid construction strategies and application in 3D bioprinting

SMS2DC: Synchronous mobile sinks scheduling for data collection in internet of things‐enabled wireless sensor networks

SummaryEnergy‐efficient data collection in wireless sensor networks (WSNs) is crucial due to the limited battery capacity of sensor nodes (SNs). Using a mobile sink (MS) for data collection can lower the energy consumption of SNs to avoid relaying in WSNs. However, a single MS is not a feasible solution for large‐scale WSNs, so it was necessary to use multiple MSs to collect data. A synchronous MS scheduling strategy for data collection (SMS2DC) is proposed in this paper, which uses two types of MS, a local MS to collect data from SN and a global MS to collect data from local MS. In this process, we begin by partitioning the network based on chemical reaction optimization. For each partition, a MS is assigned and scheduled using a path construction strategy according to a geometric path construction approach. In addition, a global MS is scheduled based on a local MS trajectory by identifying the most appropriate collision point to collect data. As a result, the algorithm increases data collection accuracy while minimizing network data loss. The asymptotic time complexity of the proposed SMS2DC algorithm needed . The comparison results show the superiority of the proposed SMS2DC strategy under multiple scenarios under various deployment conditions.

Optimizing Portfolio Allocation in the Indian Defense Sector: A Python-Based Approach

This paper presents a detailed analysis of portfolio construction strategies aimed at maximizing risk-adjusted returns for investors, utilizing Python-based methodologies. By leveraging historical data on stock returns and risks, a meticulous selection process identified 5 stocks with superior risk-return profiles, outperforming the dataset's average measures with higher returns and lower risks. The selected stocks from the defense industry formed the foundation of an optimal portfolio designed to minimize sector-specific risks while maximizing growth potential. Through rigorous portfolio optimization techniques, including Markowitz's mean-variance optimization, an optimal portfolio allocation was identified with a return of 62.40% and volatility of 27.74%. Insights from the study provide valuable perspectives for investors seeking realistic and sustainable wealth accumulation strategies. The research also highlights future avenues for exploration, such as integrating alternative asset classes, incorporating behavioral finance insights, and leveraging advancements in risk management technologies. This study contributes to advancing portfolio theory and offers practical guidance for investment decision-making.This study demonstrates the effectiveness of Python in financial analysis and portfolio optimization while furthering the theory of portfolios and providing valuable guidance for making investment decisions. Keywords: Returns, Risk, Volatility, Optimal Portfolio Construction, Defense Sector, Markowitz Portfolio Theory,

Database selection for shotgun metaproteomic of low-diversity dairy microbiomes

The metaproteomics field has recently gained more and more interest as a valuable tool for studying both the taxonomy and function of microbiomes, including those used in food fermentations. One crucial step in the metaproteomics pipeline is selecting a database to obtain high-quality taxonomical and functional information from microbial communities. One of the best strategies described for building protein databases is using sample-specific or study-specific protein databases obtained from metagenomic sequencing. While this is true for high-diversity microbiomes (such as gut and soil), there is still a lack of validation for different database construction strategies in low-diversity microbiomes, such as those found in fermented dairy products where starter cultures containing few species are used. In this study, we assessed the performance of various database construction strategies applied to metaproteomics on two low-diversity microbiomes obtained from cheese production using commercial starter cultures and analyzed by LC-MS/MS. Substantial differences were detected between the strategies, and the best performance in terms of the number of peptides and proteins identified from the spectra was achieved by metagenomic-derived databases. However, extensive databases constructed from a high number of available online genomes obtained a similar taxonomical and functional annotation of the metaproteome compared to the metagenomic-derived databases. Our results indicate that, in the case of low-diversity dairy microbiomes, the use of publically available genomes to construct protein databases can be considered as an alternative to metagenome-derived databases.

Advances in Shear-Seepage Properties of Rock Mass Filled with Joint Fissure

Since joint fissures are distributed extensively within rock masses, rock masses evolve into "sandwich" shapes when filled with joint fissures under long-term geological action, which causes rock discontinuities and destroys rock stability. This study reviews the advances in the shear-seepage properties of rock masses filled with joint fissures (RMFJFs) under static, quasistatic, and dynamic loads, including laboratory experiments, theoretical analysis, and numerical calculations. Results show that the shear properties of RMFJFs are closely associated with the strength of the fillings, the filling degree, and the roughness of the joints. RMFJFs develop under the stress of surrounding rocks, and their seepage properties are therefore affected by the surrounding stress and the filling degree, the rock layer thickness, and the porosity of the rock or fillings. However, detailed studies on the seepage properties of RMFJFs under cyclic loading, impact loading, and different shear rates are lacking. Finally, the existing problems in the research on the seepage properties of RMFJFs are clarified, a constructive research strategy is proposed, and the related trends are discussed in light of the overall mechanical behavior of RMFJFs.

Sexual Orientation and Gender Identity Construction as a Joint Youth-Parent Project

This study investigated how sexual and gender minority youth and their parents construct goals and strategies relevant to the youth’s sexual orientation and/or gender identity (SOGI). Six youth-parent dyads were studied over 10 months using the qualitative action-project method, which is grounded in contextual action theory. The data consisted of participant conversations, video recall of internal processes, and telephone monitoring. Data analysis resulted in the identification of a youth-parent relationship project for each dyad. Embedded within the broader relationship project were joint actions specific to the youth’s SOGI construction process, such as supporting one another with challenges related to identity disclosures, revisiting the past, and cultivating hope and gratitude. Findings demonstrate a SOGI construction process that is relational, ongoing, dynamic, and infused with goal-directed action. These findings provide insight into youth-parent relationship processes that facilitate the youth’s SOGI construction process.

Tailoring the morphology and charge transfer pathways of ultrathin Cd0.8Zn0.2S nanosheets via ionic liquid-modified Ti3C2 MXenes towards remarkable photocatalytic hydrogen evolution

Small-sized CdxZn1–xS solid solution nanomaterial is an important candidate for efficient photocatalytic hydrogen evolution (PHE), but it still suffers from easy agglomeration, severe photo corrosion, and fast photogenerated electron-hole recombination. To tackle these issues, herein, we propose a new strategy to modify CdxZn1–xS nanoreactors by the simultaneous utilization of ionic-liquid)-assisted morphology engineering and MXene-incorporating method. That is, we designed and synthesized a novel hierarchical Cd0.8Zn0.2S/Ti3C2 Schottky junction composite through the in-situ deposition of ultrathin Cd0.8Zn0.2S nanosheets on unique IL-modified Ti3C2 MXenes by a one-pot solvothermal method for efficiently PHE. The unique construction strategy tailors the thickness of ultrathin Cd0.8Zn0.2S nanosheets and prevents them from stacking and agglomeration, and especially, optimizes their charge transfer pathways during the photocatalytic process. Compared with pristine Cd0.8Zn0.2S nanosheets, Cd0.8Zn0.2S/Ti3C2 has abundant photogenerated electrons available on the Ti3C2 surface for proton reduction reaction, owing to the absence of deep-trapped electrons, suppression of electron-hole recombination in Cd0.8Zn0.2S and high-efficiency charge separation at the Cd0.8Zn0.2S/Ti3C2 Schottky junction interface. Moreover, the hydrophilicity, electrical conductivity, visible-light absorption capacity, and surficial hydrogen desorption of Cd0.8Zn0.2S/Ti3C2 heterostructure are significantly improved. As a result, the heterostructure exhibits outstanding photocatalytic stability and super high apparent quantum efficiency, being rendered as one of the best noble-metal-free Cd-Zn-S-based photocatalysts. This work illustrates the mechanisms of morphology control and heterojunction construction in controlling the catalytic behavior of photocatalysts and highlights the great potential of the IL-assisted route in the synthesis of high-performance MXene-based heterostructures for photocatalytic hydrogen evolution.

Palladium(II)-Catalyzed Tandem γ-C(sp2)-H Arylation and Cyclization for the Construction of Natural Product-Like Polycyclic Fused ortho-Quinone Scaffolds.

Here, we report a novel strategy for the direct construction of polycyclic fused ortho-quinone scaffolds through palladium(II)-catalyzed tandem γ-C(sp2)-H arylation and cyclization of arylglyoxals with aryl iodides. This transformation features unique tandem transient directing of γ-C(sp2)-H arylation and cyclization reaction mode, broad substrate scope, especially for the aromatic substrates containing oxygen and sulfur atoms, and avoiding the common issue of aromatization due to the construction of the hexatomic ring.

Helmholtz Plane Reconfiguration Enables Robust Zinc Metal Anode in Aqueous Zinc‐Ion Batteries

AbstractAqueous zinc‐ion batteries are promising for next‐generation energy storage systems. However, the zinc dendrite growth, corrosion, and hydrogen evolution reaction at the electrochemical interface severely impede their further development. Herein, a Zn2+‐rich and H2O‐poor Helmholtz plane is constructed to regulate the electrochemical interface between the zinc anode and the electrolyte. Electrochemical and in situ spectroscopy characterizations reveal that the designed electric double layer with abundant Zn2+ coordination sites and less H2O content can facilitate rapid electron transfer, homogenize Zn2+ deposition, and alleviate the side reactions induced by active H2O. Benefiting from the high reversibility and stability of zinc anode, the Zn||Zn symmetric cell can be cycled over 1000 h at 1 mA cm−2 and the Zn||NH4V4O10 full cell can maintain a capacity of 85.23% for 1000 cycles at 3 A g−1. This work aims at Helmholtz plane reconfiguration and provides a realizable strategy in interface construction for other similar systems.