Theory Techniques Research Articles

Unveiling aqueous lithium-ion batteries via advanced modelling and characterisation: A review

Aqueous lithium-ion batteries (ALIBs) are promising candidates for sustainable energy storage, offering great advantages in safety, cost, and environmental impact over the conventional nonaqueous LIBs. This paper delves into the forefront of ALIB research in electrolyte formulations, electrode materials, and design strategies of ALIBs that have stemmed from the integration of advanced modelling and characterisation techniques. A detailed examination of multiscale modelling approaches, e.g., density functional theory (DFT), molecular dynamics (MD), microscopic and spectroscopic techniques, e.g., X-ray, Raman, and particularly in situ and in operando methods that provide real-time observations of battery processes, is carried out. We note that the synergy between modelling and characterisation techniques have offered unprecedented insights into the fundamental processes governing ALIB performance, however, more methods that have been demonstrated effective in commercial LIBs, can be employed and contribute to resolving the current bottlenecks of ALIBs. The models at mesoscale, continuum-scale and even larger scales can supplement DFT and MD to investigate the electrochemical processes in electrode-electrolyte interface, bulk electrolyte, porous electrodes, and prototype cells, and cooperate with essential measurements to characterise physicochemical properties of aqueous electrolytes, which are not widely discussed. Other microscopic, structural, and multi-physical characterisations, such as scanning transmission electron microscopy, computed tomography, thermography, and acoustic techniques can provide more insights into lithium intercalation, phase change and degradation, inspiring the theory and model development of ALIBs. By amalgamating the current state-of-the-art and existing challenges, this paper paves the way for future prospects in ALIBs.

A comparative analysis of strategic narratives and persuasive language techniques within Iranian and US news media: The study of the joint comprehensive plan of action

This study aims to contribute to the understanding of strategic narrative theory and persuasive language techniques in the Middle Eastern context, particularly focusing on the utilization of these aspects in discussions related to the Joint Comprehensive Plan of Action (JCPOA). The research employs both quantitative and qualitative methods to analyze how the JCPOA was depicted in news media from the US and Iran. The findings reveal that both nations positioned themselves as key proponents of the JCPOA, emphasizing their willingness to collaborate through a more conciliatory approach. Notably, these narratives were underpinned by divergent persuasive language techniques, reflecting the intricate and often conflict-prone dynamics of the Middle East.

An Integrated Dimension Theory and Modulation Signal Bispectrum Technique for Analyzing Bearing Fault in Industrial Fibrizer

Abstract This study investigates the dynamics of roller bearings by utilizing the dimension theory technique to diagnose the bearing clearance faults of revolving machines. The generation of local defects in rotating machines is closely related to the clearance behaviour of the rotor-bearing system. A dynamic model of bearing with dimension theory by matrix method (DTMM) is developed for characteristics of bearing clearance considering the influence of local defects on the inner and outer bearings races. The characteristics of bearing internal radial clearance considering the impact of the defect on the bearing are analyzed. An experimental study has been performed under various operational conditions. The noisy signal is subsequently eliminated using the Modulation Signal Bispectrum (MSB). The efficiency and reliability of the stated approach are evaluated using a specialized bearing test and a run-to-failure fibrizer test. As a result, this technology offers a significant opportunity to execute more cost-effective maintenance work to eliminate the breakdown of machinery.

Crystal structure of alectinib hydrochloride Type I, C30H35N4O2Cl

The crystal structure of alectinib hydrochloride has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Alectinib hydrochloride crystallizes in space group P21/n (#14) with the following parameters: a = 12.67477(7), b = 10.44076(5), c = 20.38501(12) Å, β = 93.1438(7)°, V = 2693.574(18) Å3, and Z = 4 at 295 K. The crystal structure consists of stacks of molecules along the b-axis, and the stacks contain chains of strong N–H⋯Cl hydrogen bonds. One density functional theory calculation moved a proton from an N atom to the Cl, but another calculation yielded a more chemically reasonable result. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®)

Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network

Using game theory techniques, a three-layer planning model (THLPM) for the defense, attack, and operational layers has been established to address malicious damage to pipelines. A robust planning model was developed for situations with uncertain attack resources. In this model, the defense layer protects critical infrastructure within the network to minimize losses. The attack layer targets unprotected facilities based on the defensive strategy. The operational layer formulates the optimal pipeline transmission strategy based on the decisions of the defense and attack layers. By utilizing the duality theorem, the THLPM is transformed into a two-layer planning problem, which is then linearized and solved using a decomposition algorithm. Taking a specific ring-shaped pipeline network as an example, the study analyzes the significant role of backup pipelines in enhancing system resilience and evaluates the offensive and defensive strategies of THLPM. The effectiveness of THLPM in protecting the network was assessed, showing that when defense and attack resources are invested at levels 3 and 10, respectively, operational costs of the network are reduced by 54.2 % compared to a scenario without any defenses. The methods proposed in this paper are applicable to other pipeline systems.

Monthly hydraulic geometry relationship quantification with environmental LAI by utilizing sentinel data: A case in Jingjiang reach of the Yangtze River

This study presents a novel approach for quantifying the dynamics of monthly hydraulic geometry relationships in the Jingjiang reach of the Yangtze River by integrating leaf area index (LAI) data as an indicator of riparian vegetation. A comprehensive system of ordinary differential equations (ODEs) couples traditional power-law hydraulic geometry equations with LAI, capturing the influence of erosion control on channel morphology. The periodic delayed response theory and automatic differentiation techniques are employed to enhance the modeling framework’s capabilities. Calibration and verification demonstrate the models’ effectiveness in capturing overall trends in discharge, width, and depth dynamics, outperforming traditional constant-parameter approaches. However, model predictive abilities are limited under extreme climate conditions due to training on normal climate data. Key assumptions, including the periodic delayed response theory’s neglect of peak discharges, simplified representation of artificial cut-offs, and reliance on remotely sensed data with limited local validation, introduce uncertainties. The proposed modeling framework shows potential for broader application to other river systems with appropriate adjustments. Future research could incorporate additional environmental factors, integrate models across scales, couple with advanced simulation techniques, and expand stability assessments beyond the riverbed index. By addressing related challenges, this integrated approach lays a foundation for enhancing understanding of river morphodynamics and channel stability.

Displacement response waveform restoration of simply supported bridge during train passage using measured acceleration integration based on linear vibration theory

This study proposes a method for restoring the displacement waveform during train passage using the acceleration integration based on linear vibration theory and noise cancellation techniques. This method replaces the low-frequency region affected by noise with a linear theoretical solution; however, this method uses the actual measurement data around the natural frequency, where nonlinearities (such as concrete member cracks and the train–bridge interaction) can be observed. The method identifies only the ratio of single axle weight to modal stiffness. Numerical experiments clarify that the method can estimate the maximum displacement of a bridge from acceleration with an error of approximately 5% or less. Improved prediction accuracy can be achieved using the proposed noise cancellation technique not only in the high-speed range but also into the lower-speed ranges as well. Furthermore, the proposed method is applied to acceleration monitoring data, and results show that the displacement waveform can be restored from the acceleration waveform.

Powder X-ray diffraction of nintedanib esylate hemihydrate, (C31H33N5O4)(C2H5O3S)(H2O)0.5

The crystal structure of nintedanib esylate hemihydrate was refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Nintedanib esylate hemihydrate crystallizes in space group P-1 (#2) with a = 11.5137(1), b = 16.3208(4), c = 19.1780(5) Å, α = 69.0259(12), β = 84.4955(8), γ = 89.8319(6)°, V = 3347.57(3) Å3, and Z = 4 at 295 K. Hydrogen bonds are prominent in the crystal structure. The water molecule forms two medium-strength O–H⋯O hydrogen bonds to one of the esylate anions. The protonated nitrogen atom in each cation forms a N–H⋯O hydrogen bond to an esylate anion. The ring N–H groups form strong intramolecular N–H⋯O hydrogen bonds to carbonyl groups. The ring N–H groups form intramolecular N–H⋯O hydrogen bonds to esylate anions. Many C–H⋅⋅⋅O hydrogen bonds (and one C–H⋯N hydrogen bond), with aromatic C–H, methylene groups and methyl groups as donors, are present. The hydrogen bonding patterns of the two cations differ considerably. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®)

Event-based [formula omitted] load frequency control for fuzzy Markov-jump IPS with wind power under hybrid attacks

This paper addresses the H∞ load frequency control problem of interconnected power systems that incorporate high-permeability wind power and face a mixed attack of deception and denial of service. The interconnected power system is modeled as a Takagi–Sugeno (T–S) fuzzy Markov jump system. Given the involvement of wind power, optimizing the utilization of already in-demand communication resources becomes imperative. Thus, a new event-triggering mechanism is adopted to reduce data transmission traffic. Simultaneously, in response to the general network’s vulnerability to network attacks in power systems, a closed-loop system with Markov jump, modeled using the T–S fuzzy approach, is studied. A novel multi-agent Event-Triggering Strategy (ETS) composed of membership functions is proposed to address the mismatch between the membership functions of fuzzy systems and fuzzy controllers, and ensure the consistency of multi-agent systems. Subsequently, employing Lyapunov–Krasovskii theory and stochastic analysis techniques, conditions sufficient to ensure the asymptotic stability of interconnected power systems are derived from linear matrix inequalities. Finally, simulation verification is provided to ensure the accuracy and feasibility of the obtained theory.

Computational method on highly efficient D-π-A-π-D-based different molecular acceptors for organic solar cells applications and non-linear optical behaviour

Eight molecular structures (BT-A1 to BT-A8) with high-performance non-fullerene acceptor (NFA) were selected for organic solar cells (OSCs) and non-linear optical (NLO) applications. Their electronic, photovoltaic (PV) and optoelectronic properties were tuned by adding powerful electron-withdrawing groups to the acceptor (A) of the D-π-A-π-D structure. Using time-dependent density functional theory (TD-DFT) techniques, based on the laws of quantum chemical calculations, the absorption spectra, stability of the highest and lowest-energy molecular orbitals (HOMO/LUMOs), electron density, intramolecular charge transfer (ICT), transition density matrix (TDM), were examined. The binding energy (Eb) and density of states (DOS) were probed to realize the optoelectronic analysis of the structures BT-A1 to BT-A8. Noncovalent interactions (NCIs) based on a reduced density gradient (RDG) were used to describe the nature and strength of D-A interactions in the molecules BT-A1 to BT-A8. The new refined molecules BT-A1 to BT-A8 exhibited strong absorbance bands between 408–721 nm and high electron transfer contribution (ETC) ranges between 87–96 %, along with the smallest excitation energies (Ex) between 1.71–3.55 eV in the solvent dichloromethane. Dipolar moment strengths ranging from 0.38 to 4.72 Debye in both the excited and ground states have determined with good solubility properties of BT-A1 to BT-A8 in polar solvent. Highly effective charge mobilities and prevention of charge recombination have been demonstrated by the electron (0.18–0.41 eV) and hole RE values (0.13–0.89 eV) for the new compounds. Power conversion efficiencies (PCE) of BT-A1 to BT-A8 were nearly the same because of better outcomes compared to the molecules in the BT. Compared to poly[4.8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b: 4,5-b']dithiophene-2,6- diyl-alt-(4–2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2–6-diyl)] (PTB7-Th), the open circuit voltages (Voc) of compounds BT-A1 to BT-A8 were ranged from 1.52 to 2.13 eV. The polarizability (α) and hyperpolarizability (β) of the molecules BT-A1 to BT-A8 were used to determine the non-linear optical (NLO) properties. The results showed that BT-A2, BT-A6 and BT-A7 have good NLO activity. This computational analysis demonstrates the superiority of the molecules with NFA. Hence the compounds are advised for the use in production of high-performance OSCs and NLO activity.

On controllability for Sobolev-type fuzzy Hilfer fractional integro-differential inclusions with Clarke subdifferential

In this paper, our main purpose is to search and obtain the controllability for Sobolev-type fuzzy Hilfer fractional integro-differential inclusions with Clarke subdifferential. Some sufficient conditions for the controllability results of this inclusion problem are proposed by using related techniques of fuzzy set theory, Sobolev-type, fractional calculus and Clarke subdifferential. The theorem of the controllability results is proved by Bohnenblust–Karlin fixed point theorem. In addition, we show an example to explain the controllability results of this inclusion problem.

A clinical decision support system using rough set theory and machine learning for disease prediction

ObjectiveTechnological advances have led to drastic changes in daily life, and particularly healthcare, while traditional diagnosis methods are being replaced by technology-oriented models and paper-based patient healthcare records with digital files. Using the latest technology and data mining techniques, we aimed to develop an automated clinical decision support system (CDSS), to improve patient prognoses and healthcare delivery. Our proposed approach placed a strong emphasis on improvements that meet patient, parent, and physician expectations. We developed a flexible framework to identify hepatitis, dermatological conditions, hepatic disease, and autism in adults and provide results to patients as recommendations. The novelty of this CDSS lies in its integration of rough set theory (RST) and machine learning (ML) techniques to improve clinical decision-making accuracy and effectiveness. MethodsData were collected through various web-based resources. Standard preprocessing techniques were applied to encode categorical features, conduct min-max scaling, and remove null and duplicate entries. The most prevalent feature in the class and standard deviation were used to fill missing categorical and continuous feature values, respectively. A rough set approach was applied as feature selection, to remove highly redundant and irrelevant elements. Then, various ML techniques, including K nearest neighbors (KNN), linear support vector machine (LSVM), radial basis function support vector machine (RBF SVM), decision tree (DT), random forest (RF), and Naive Bayes (NB), were employed to analyze four publicly available benchmark medical datasets of different types from the UCI repository and Kaggle. The model was implemented in Python, and various validity metrics, including precision, recall, F1-score, and root mean square error (RMSE), applied to measure its performance. ResultsFeatures were selected using an RST approach and examined by RF analysis and important features of hepatitis, dermatology conditions, hepatic disease, and autism determined by RST and RF exhibited 92.85 %, 90.90 %, 100 %, and 80 % similarity, respectively. Selected features were stored as electronic health records and various ML classifiers, such as KNN, LSVM, RBF SVM, DT, RF, and NB, applied to classify patients with hepatitis, dermatology conditions, hepatic disease, and autism. In the last phase, the performance of proposed classifiers was compared with that of existing state-of-the-art methods, using various validity measures. RF was found to be the best approach for adult screening of: hepatitis with accuracy 88.66 %, precision 74.46 %, recall 75.17 %, F1-score 74.81 %, and RMSE value 0.244; dermatology conditions with accuracy 97.29 %, precision 96.96 %, recall 96.96 %, F1-score 96.96 %, and RMSE value, 0.173; hepatic disease, with accuracy 91.58 %, precision 81.76 %, recall 81.82 %, F1-Score 81.79 %, and RMSE value 0.193; and autism, with accuracy 100 %, precision 100 %, recall 100 %, F1-score 100 %, and RMSE value 0.064. ConclusionThe overall performance of our proposed framework may suggest that it could assist medical experts in more accurately identifying and diagnosing patients with hepatitis, dermatology conditions, hepatic disease, and autism.

The Small-N Series in the Zero-Dimensional O(N) Model: Constructive Expansions and Transseries

We consider the zero-dimensional quartic O(N) vector model and present a complete study of the partition function Z(g, N) and its logarithm, the free energy W(g, N), seen as functions of the coupling g on a Riemann surface. We are, in particular, interested in the study of the transseries expansions of these quantities. The point of this paper is to recover such results using constructive field theory techniques with the aim to use them in the future for a rigorous analysis of resurgence in genuine quantum field theoretical models in higher dimensions. Using constructive field theory techniques, we prove that both Z(g, N) and W(g, N) are Borel summable functions along all the rays in the cut complex plane Cπ=C\\R-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb {C}_{\\pi } =\\mathbb {C}{\\setminus } \\mathbb {R}_-$$\\end{document}. We recover the transseries expansion of Z(g, N) using the intermediate field representation. We furthermore study the small-N expansions of Z(g, N) and W(g, N). For any g=|g|eıφ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$g=|g| e^{\\imath \\varphi }$$\\end{document} on the sector of the Riemann surface with |φ|<3π/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$|\\varphi |<3\\pi /2$$\\end{document}, the small-N expansion of Z(g, N) has infinite radius of convergence in N, while the expansion of W(g, N) has a finite radius of convergence in N for g in a subdomain of the same sector. The Taylor coefficients of these expansions, Zn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z_n(g)$$\\end{document} and Wn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$W_n(g)$$\\end{document}, exhibit analytic properties similar to Z(g, N) and W(g, N) and have transseries expansions. The transseries expansion of Zn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z_n(g)$$\\end{document} is readily accessible: much like Z(g, N), for any n, Zn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z_n(g)$$\\end{document} has a zero- and a one-instanton contribution. The transseries of Wn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$W_n(g)$$\\end{document} is obtained using Möbius inversion, and summing these transseries yields the transseries expansion of W(g, N). The transseries of Wn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$W_n(g)$$\\end{document} and W(g, N) are markedly different: while W(g, N) displays contributions from arbitrarily many multi-instantons, Wn(g)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$W_n(g)$$\\end{document} exhibits contributions of only up to n-instanton sectors.

A discrete-time model of phenotypic evolution

A model is proposed for the phenotypic evolution of a very large population under sustained environmental change and non-overlapping generations, with a single trait considered. Due to an extension of the standard law of quantitative inheritance, each evolutionary mechanism corresponds to a function between random variables associated with distinct stages of the life cycle. Such an approach leads to a two-dimensional map where the dynamics of the phenotypic mean and variance are directly connected. Then, the declining population paradigm is explored in terms of the critical rate of environmental change and using the techniques of the dynamical systems theory. Our results first reveal the opposing pressures on the phenotypic variance due to the conflict between phenotypic load and the ability to pursue the optimum, translated into an optimal value for maximizing the critical rate. Secondly, the introduction of development, through the particular case of linear plasticity, leads to a decreasing degree of stability with the magnitude of plasticity, which means that the recovery time from disturbances is harmed as the plastic effect intensifies, even though no constitutive costs have been assumed, a feature almost as important as the mean fitness to the viability of populations subject to persistent changes. Notwithstanding, the system is stable, and the growth rate benefits from increased plasticity, as expected.

Study of the social, environmental and economic dimensions in rural communities

The objective of this article was to carry out an analysis of public policies related to rural settlements, and correlate them with the Sustainable Development Goals (SDGs) and ESG and present alternatives that contribute to the local development of rural settlements. The methodology used consisted of qualitative research and exploratory analysis with participant observation, conducted in the Vale do Arinos Settlement Project, Line Five, located in the Municipality of Juara, located in the northern region of the state of Mato Grosso. This study analyzed the factors that influence the social, environmental and economic development of rural producers in the aforementioned Settlement Project. To carry out this analysis, the Grounded Theory technique was also applied. This research contributes to the improvement and development of rural settlement communities. When examining Settlement Project, it is clear that rural producers face difficulties in subsisting and thriving, especially in a market characterized by volatility and a lack of appreciation for their products. When relating the SDGs with Project, an unfavorable situation is observed with regard to the social, environmental and economic tripod in this community.

An ameliorated localization algorithm for compensating stratification effect based on improved underwater salp swarm optimization technique

SummaryThe underwater acoustic sensor network is a fundamental source for ocean exploration. The potential applications of underwater acoustic sensor network (UASN) include seismic imaging, disaster prevention, mine reconnaissance, pollution monitoring, exploration of natural resources, and military surveillance. To acquire accurate results, implementing all applications of underwater sensor networks requires an adequate network connection and communication technology. The precise placement of underwater sensor nodes needs to be identified in order to achieve effective communication. To accomplish the requirement, the paper presents an efficient localization algorithm to compensate the stratification effect based on an improved underwater salp swarm optimization technique (LAS‐IUSSOT). To compute the location of sensor nodes with high accuracy, the nodes are initially randomly deployed in three‐dimensional underwater acoustic sensor network (3D‐UASN). After that, the hybridization of centroid‐based localization and the ray theory technique is used, and then, the degree of coplanarity is analyzed among the underwater sensor nodes. Then, the computation of the location of unknown nodes is performed using improved underwater salp swarm optimization technique (IUSSOT) to obtain the optimized location and compensate the impact of the stratification. The comparison of the simulation results of the existing algorithm and the proposed algorithm is performed. The LAS‐IUSSOT achieves 40.46% and 28.00% accuracy in terms of localization of underwater sensor nodes for both the sparse and dense regions in 3D‐UASN. The LAS‐IUSSOT achieves 49.39% and 62.57% accuracy in terms of ranging of underwater sensor nodes for both the sparse and dense regions in 3D‐UASN. Simulation results illustrate that the proposed algorithm outperforms the existing algorithm in terms of localization and ranging accuracy in both sparse and dense regions in 3D‐UASN, root mean square error (RMSE), normalized localization error (NLE), computation time, and convergence rate.

Tellurium Containing Long Lived Emissive Fluorophore for Selective and Visual Detection of Picric Acid through Photo-Induced Electron Transfer.

A novel tellurium (Te) containing fluorophore, 1 and its nickel (2) and copper (3) containing metal organic complex (MOC) have been synthesized to exploit their structural and optical properties and to deploy these molecules as fluorescent probes for the selective and sensitive detection of picric acid (PA) over other commonly available nitro-explosives. Furthermore, density functional theory (DFT) and single crystal X-ray diffraction (SCXRD) techniques revealed the inclusion of "soft" Tellurium (Te) and "hard" Nitrogen (N), Oxygen (O) atoms in the molecular frameworks. Owing to the presence of electron rich "N" and "O" atoms along with "Te" in the molecular framework, 1 could efficiently and selectively sense PA with more than 80 % fluorescence quenching efficiency in organic medium and having detection limit of 4.60 μM. The selective detection of PA compared to other nitro-explosives follows a multi-mechanism based "turn-off" sensing which includes photo-induced electron transfer (PET), electrostatic (π-π stacking and π-anion/cation) interaction, intermolecular hydrogen bonding and inner filter effect (IFE). The test strip study also establishes the sensitivity of 1 for detection of PA.

Research on the Construction of Rural Living Circles in Hilly and Gully Areas of the Loess Plateau: A Case Study of Guanghe County

Ue and practical significance for achieving equitable urban and rural infrastructure within a region and promoting integrated urban-rural development. Employing landscape ecology theory and GIS spatial analysis techniques, this paper comprehensively analyzes the construction of rural living circles in Guanghe County, taking into account the convergence characteristics of residents' daily life trajectories and biological migration movements. The results indicate: (1) Within the "resistance surface" of Guanghe County, easily accessible areas and generally accessible areas account for 69.92% of the total area, while relatively difficult-to-access and hard-to-access areas constitute 30.08% of the total area, with weaker development potential in these regions. (2) Based on the results of the MCR model, a methodological pathway for identifying rural living circles is established. This includes delineating a "four-level, three-category" system for rural living circles in Guanghe County, and proposing a "mandatory allocation + selective allocation" modular customization approach to precisely allocate public service facilities. (3) Building upon the concept of travel "resistance surfaces," the study introduces transportation resistance coefficients to delineate different scales of living circles between river valley plain areas and mountainous areas. The research findings provide a basis for the construction of rural living circles in hilly and gully areas of the Loess Plateau.

Hydrophobic and Tribological Properties of Biomimetic Interfaces

Bionic interfaces have received much attention owing to their attractive hydrophobic and tribological potential. Although a great deal of research has been carried out on biomimetic nanostructures, the basic theory, experimental application, and related techniques of hydrophobicity of biomimetic nanostructures, as well as the relationship between the state of lubricants and friction in tribology have not been fully explored. In this review, based on a brief discussion of the theory of hydrophobicity, the role of two-dimensional bionic structures in the wet state is introduced, and the wetting mechanism and applications are discussed. Then, the synergistic effects and mechanisms of bionic weaving and lubricants in the dry/wet friction state are investigated. In addition, the contribution of bionic structures to the fields of hydrophobicity and tribology further deepens the knowledge and enriches the practical applications of bionic surface weaving.

A practicable geophysical resistivity imaging sensing approach for urban geological water disaster detection: A real-world case study

In the urban environment, the transient electromagnetic method often suffers from severe electromagnetic interference because it employs coils to perceive the electromagnetic field. To address this issue, the DC method employs electrodes to shield the electromagnetic noise in the urban environment. In this paper, a new geophysical resistivity imaging sensing approach based on a DC inversion model is proposed to explore and identify the path of underground water to solve the water disaster problem. A real-world case study is carried out in Xinjiang Region. In order to investigate the underground water conducted path, an electrode network is designed and installed for the buildings of interest to collect the DC electrical current and DC electrical potential data. Then, the proposed method establishes a DC resistivity inversion model based on the forward theory and finite-volume technique to extract the geological information from the collected data and visualize the underground water conducted path. Different from existing popular numerical techniques, such as the finite element and finite difference, the finite-volume technique has clear theoretical explanations to make the obtained geological images understandable. As a result, the underground water path can be directly observed from the geological images calculated by the proposed approach to successfully identify and locate the underground water disaster in real-world applications.