This study presents an interpretable machine learning framework for prioritizing pavement maintenance and rehabilitation (M R) through domain-integrated feature selection and Pareto-based decision modeling. A tuned Light Gradient Boosting Machine (LightGBM) classifier was trained to predict discrete M R categories across a network of 1,166 pavement sections, achieving strong performance with a test accuracy of 95

A crack or other type of damage causes a sharp discontinuity in the rotational displacement curve of a load-bearing structure. However, if the beam is not sufficiently loaded or the crack depth is very small, the discontinuity may be impossible to detect using conventional methods. To understand cracks in concrete, important parameters such as characteristic length, fracture energy, and critical crack width are used. In this project, the crack width is estimated as either crack mouth opening displacement (CMOD/COD) or crack tip opening displacement (CTOD). This project involves early detection of cracks by sensors and quantification of the cracks with help of algorithms. For the testing, three basic structural members, i.e., concrete cubes, beams, and T-beam are used. Internal cracks are detected by ultrasonic sensors with the help of IoT. A GPS module will be used for finding the position of the cracks and GSM module going to send the SMS to the phone whenever the cracks are formed. To quantify the cracks and show the position of the cracks, algorithms are used. Therefore, to monitor the damages at the early stage thereby avoiding the degradation of the structure, we are proposing a regular monitoring system.

Layered oxide materials are often regarded as prospective positive electrodes for Na-ion batteries owing to their superior electrochemical properties and facile synthesis. In this work, a high-Na-content P3-type cathode (NaMn0.6Ni0.3Cu0.1O2; P3-NMNC) was prepared by the sol-gel technique. These materials exhibited excellent rate performance and specific capacity (discharge specific capacity at 3C being 77% of that at 0.1C). Even at 10C, the cells retained similar to 45 mAh g(-1). The P3-NMNC half-cells were cycled between two voltage ranges, 2.0-4.0 V and 2.0-4.2 V, among which the former exhibited an 83% capacity retention after 200 cycles, which was vastly superior to the latter, where the degradation in the capacity dropped below 80% in just 75 cycles. The dQ/dV vs V plots revealed an irreversible peak above 4.0 V during the first desodiation process, which is attributed to an irreversible anionic redox leading to poor cyclability. Operando synchrotron X-ray diffraction studies revealed a reversible P3 <-> P3 ' <-> O3 transformation in NMNC during sodiation-desodiation. The repeated P3 ' <-> O3 transformations resulted in strain due to changes in lattice parameters causing capacity degradation. The DNa+ was determined using the galvanostatic intermittent titration technique in the order of 10(-12) to 10(-10 )cm2 s(-1). These results underscore the importance of the scarcely explored high-Na-content P3-type layered oxide cathodes toward the advancement of Na-ion batteries.

Pavements must be well maintained with proper utilization of maintenance funds as they are valuable national assets. Deferring pavement maintenance causes enormous financial losses and has a negative impact on the nation's growth. Simultaneous maintenance of existing roads is necessary in a timely way in addition to rapid construction of new road networks. Therefore, it is necessary to assess the state of pavements before deciding the type of maintenance needed, in order to make effective use of road maintenance funds. In the present study an Urban Road in New Delhi was assessed for its structural and functional condition to develop PMMS. The condition of the pavement has been evaluated in terms of pavement indices, such as the Pavement Condition Rating (PCR), and the Structural Capacity Index (SCI). The deterioration of pavement with time is calculated using the deterioration models developed by CRRI in the year 1994, for Asphalt Concrete Roads in Northern India. A 15-year maintenance plan has been proposed for the selected Urban roads. In addition, a life cycle cost analysis has been performed to compare the costs under periodic and condition responsive maintenance strategies. It has been found that the condition responsive maintenance can be carried out at a cost of 4.7

Pavement condition classification based on different condition parameters is one of the primary challenges in any effective Pavement Management System (PMS) and its use as a decision aid tool is inevitable. Agencies adopt different condition classification and assessment model based on the availability of resources for data collection and their ability to address pavement issues prevalent in the area. However, a system for pavement condition classification is not yet well established in India. Therefore, the present study develops a 0–100 scale Pavement Condition Rating Index (PCRI) for condition classification of asphalt pavements in India. The development of proposed condition rating index is based on expert opinions and existing guidelines. Six sub-indices were developed for cracking, ravelling, patching, potholes, rutting and roughness using curve fitting based on threshold values. Further the subindices were combined to PCRI using weight factors obtained by Analytical Hierarchy Procedure (AHP). The application of developed Pavement Condition Rating Index (PCRI) model is presented in terms of condition classification and priority rating. The PCRI was found to give similar results in terms of priority ranking when compared with widely recognised HDM4 tool. Further, a sensitivity analysis using Pawn index method was performed and it was found that developed PCRI model is highly sensitive towards the number of potholes.

[00l] grain-oriented 0.95K(0.5)Bi(0.5)TiO(3)-0.05BiAlO(3) (named K5BA-T)ceramics were prepared via the reactive template grain growth (RTGG)and tape casting technique. High-aspect-ratio K5BA powder was preparedusing a plate-shape 4-layer aurivillius oxide (K0.5Bi4.5Ti4O15) powder as the template. Theeffects of grain morphology modification and texturing on the structural,dielectric, and piezoelectric properties of K5BA-T were systematicallyinvestigated. The average plate size of similar to 6.5 mu m witha thickness of similar to 400 nm was observed in the K5BA sample. X-raydiffraction (XRD) and bulk texture measurements confirmed the texturingof K5BA-T in the [00l] crystallographic directionwith a calculated Lotgering factor of similar to 80%. Two anomalies inthe temperature-dependent dielectric plot of the poled K5BA-T samplesignified additional poling-induced phase transition. A lower valueof room-temperature (RT) dielectric constant (epsilon(r))of similar to 200 (at 1 MHz) and a higher piezoelectric charge coefficient(d (33)) of similar to 145 pCN(-1) were obtained in the poled K5BA-T ceramic compared to that of the0.95K(0.5)Bi(0.5)TiO(3)-0.05BiAlO(3) ceramic with randomly oriented grains (named K5BA-R). Consequently,the piezoelectric voltage coefficient (g (33)) estimated for the textured ceramic showed a 650% increment (g (33) similar to 80 x 10(-3) V mN(-1)) over the K5BA-R sample (g (33) similar to 12.5 x 10(-3) V mN(-1)). The transduction coefficient (d (33)center dot g (33)) of K5BA-T ceramicwas calculated to be similar to 11 600 x 10(-15) m(2) N-1, which is nearly 9 times highercompared to its random counterpart. Further, a piezodevice fabricatedusing poled ceramic for energy harvesting showed an output voltageof similar to 7 V with a current response of similar to 2 mu A undernormal finger-tapping motion.

Airfield pavements need to be maintained regularly to ensure smooth and safer airport operations and to keep pavement conditions long-lasting. The airfield Pavement Management System (APMS) is a systematic tool for this purpose. Depending upon the functional condition of the pavement, APMS tools allow timely detection of pavement surface defects during the preliminary stages of deterioration and prevent serious pavement distresses that will require extensive uneconomical repairs in the future. Without regular maintenance, pavements may not reach their intended structural lifespan. Timely pavement maintenance and repairs are important to ensure adequate load carrying capacity, good pavement friction for the safe operation of aircraft, better riding quality in all weather conditions, and minimal intrusion of foreign object debris (FOD). In this paper, the authors are intended to discuss the international APMS development practices and details of various functional condition indicators such as Pavement Condition Index (PCI), Boeing Bump Index (BBI), FOD Potential Index, etc. currently used to develop APMS in India to assess the existing pavement condition and to arrive at the needs for maintenance & rehabilitation (M&R). This paper discusses the detailed methodology adopted for the APMS including data collection techniques, distress parameters to be considered for airfield pavement evaluation, data analysis and storage tools and adoption of maintenance and rehabilitation strategies for Indian airports.

The Falling Weight Deflectometer (FWD) has long been recognized as a reliable tool for the evaluation of the structural adequacy of flexible pavements. Numerous structural condition indices (SCI) have been developed to further assess pavement health based on FWD data. However, most existing indices have focused on deflection bowl parameters or relied on subgrade California Bearing Ratio (CBR) and layer thicknesses, which can be challenging to obtain accurately. Notably, the full deflection bowl data, ranging from central deflection (D0) up to 1800 mm sensor deflection, has not yet been utilized in the development of a comprehensive structural condition index. In this study, the limitations of existing methods are addressed by presenting a user-friendly approach for network-level assessment of asphalt pavements that incorporates the entire deflection bowl. It has been suggested by existing research that the area under the deflection bowl provides a more accurate representation of pavement structural health, forming the basis of the proposed method. The collection of field data to validate the efficacy of the proposed approach is involved in the current study, and its performance is compared to traditional assessment methods. By leveraging the full range of deflection data, the accuracy and efficiency of network-level evaluations are enhanced through the user-friendly approach presented in this paper, ultimately facilitating improved decision-making in pavement management and maintenance. The proposed method, which offers a simplified, comprehensive assessment tool accounting for the full range of deflection data, advances flexible pavement structural health monitoring. The potential of this novel approach to significantly impact the field of pavement health monitoring is noteworthy, providing practitioners with a more accurate and efficient means of evaluating and prioritizing interventions at the network level, ultimately contributing to more sustainable and cost-effective infrastructure management.

The development of mixed structures is increasingly becoming an efficient way to improve the performance of layered oxide cathodes for sodium-ion batteries. Herein, the Na0.8Mn0.6Ni0.3Cu0.1O2 (NMNC) cathodes with varying fractions of P2/O3-type phases are prepared by adjusting the calcination conditions. The Rietveld refinement of X-ray diffraction (XRD) data confirms the increase in O3 phase fraction from 7 % to 27 % with the increase in calcination temperature from 850 °C to 950 °C. The sample prepared at 850 °C (NMNC-850) exhibits the highest specific capacity (139 mAh g−1, 100 mAh g−1, and 80 mAh g−1 at 0.1C, 1C, and 4C, respectively) and best rate performance among all samples in addition to an excellent cyclability with capacity retention of ~85 % after 100 cycles in 1.5–4.2 V range. The increase in the O3 phase fraction leads to a drastic degradation of rate performance. The galvanostatic intermittent titration technique confirms a diffusion coefficient of 5.13 × 10−13–5.25 × 10−10 cm2 s−1 in biphasic NMNC-850 sample. Ex-situ XRD studies confirm a reversible P2/O3 → P2/P3 → P2/O3 transformation in NNMC-850 during cycling. The improved electrochemical performance is attributed to the presence of non-identical neighboring phases in suppressing the phase transformations during cycling.

Airports are vital national resources. Airfield Pavements within an airport represents a large capital investment in infrastructural development made by a country. Timely and appropriate maintenance and rehabilitation of such in-service facilities are essential to provide an all-weather surface for safe and regular operations of the aircraft. Pavement maintenance is done based on functional and structural pavement condition evaluation. This paper presents a case study dealing with functional evaluation of airfield pavements of a small sized airport in India. The considered airport consists of two runway, seven link taxiways, three apron areas and an isolation bay with different surface types. Present paper reports the methodology adopted for the functional condition evaluation of the airfield pavements with help of Automated Road Survey System. Further, the evaluated pavement condition was quantified in terms of Pavement Condition Index (PCI) as per the ASTM D5340 with help of PAVER and GIS based software. GIS was used for preparing inventory database and base maps for the concerned pavements which were then used in PAVER software for determining the PCI. The airfield pavement network within the airport was divided into a four-level hierarchy consisting of the network, branch, section and sample. The obtained PCI rating shows that the overall condition of the airfield pavements within the considered airport is satisfactory to good, however some of the areas have distresses that needs to be repaired by localized maintenance.

Hitherto, the discrete identification of quantum spin liquid phase, holy grail of condensed matter physics, remains a challenging task experimentally. However, the precursor of quantum spin liquid state may reflect in the spin dynamics even in the paramagnetic phase over a wide temperature range as conjectured theoretically. Here we report comprehensive inelastic light (Raman) scattering measurements on the Ir based double perovskite, Gd2ZnIrO6, as a function of different incident photon energies and polarization in a broad temperature range. Our results evidenced the spin fractionalization within the paramagnetic phase reflected in the emergence of a polarization independent quasi-elastic peak at low energies with lowering temperature. Also, the fluctuating scattering amplitude measured via dynamic Raman susceptibility increases with lowering temperature and decreases mildly upon entering into long-range magnetic ordering phase, below 23 K, suggesting the magnetic origin of these fluctuations. This anomalous scattering response is thus indicative of fluctuating fractional spin evincing the quantum spin liquid phase in a three-dimensional double perovskite system.

We report comprehensive Raman-scattering measurements on a single crystal of double-perovskite Nd2ZnIrO6 in temperature range of 4-330 K, and spanning a broad spectral range from 20 cm-1 to 5500 cm-1. The paper focuses on lattice vibrations and electronic transitions involving Kramers doublets of the rare-earth Nd3+ ion with local C1 site symmetry. Temperature evolution of these quasi-particle excitations have allowed us to ascertain the intricate coupling between lattice and electronic degrees of freedom in Nd2ZnIrO6. Strong coupling between phonons and crystal-field excitation is observed via renormalization of the self-energy parameter of the phonons i.e. peak frequency and line-width. The phonon frequency shows abrupt hardening and line-width narrowing below ~ 100 K for the majority of the observed first-order phonons. We observed splitting of the lowest Kramers doublets of ground state (4I9/2) multiplets i.e. lifting of the Kramers degeneracy, prominently at low-temperature (below ~ 100 K), attributed to the Nd-Nd/Ir exchange interactions and the intricate coupling with the lattice degrees of freedom. The observed splitting is of the order of ~ 2-3 meV and is consistent with the estimated value. We also observed a large number of high-energy modes, 46 in total, attributed to the intra-configurational transitions between 4f3 levels of Nd3+ coupled to the phonons reflected in their anomalous temperature evolution.

In Eu_{2}ZnIrO_{6}, effectively two atoms are active; i.e., Ir is magnetically active, which results in complex magnetic ordering within the Ir sublattice at low temperature. On the other hand, although Eu is a Van Vleck paramagnet, it is active in the electronic channels involving 4f^{6} crystal-field split levels. Phonons, quanta of lattice vibration involving vibration of atoms in the unit cell, are intimately coupled with both magnetic and electronic degrees of freedom (DOF). Here, we report a comprehensive study focusing on the phonons as well as intraconfigurational excitations in double-perovskite Eu_{2}ZnIrO_{6}. Our studies reveal strong coupling of phonons with the underlying magnetic DOF reflected in the renormalization of the phonon self-energy parameters well above the spin-solid phase (T_{N}∼12K) until temperature as high as ∼3T_{N} evidences broken spin rotational symmetry deep into the paramagnetic phase. In particular, all the observed first-order phonon modes show softening of varying degree below ∼3T_{N}, and low-frequency phonons become sharper, while the high-frequency phonons show broadening attributed to the additional available magnetic damping channels. We also observed a large number of high-energy modes, 39 in total, attributed to the electronic transitions between 4f levels of the rare-earth Eu^{3+} ion and these modes shows anomalous temperature evolution as well as mixing of the crystal-field split levels attributed to the strong coupling of electronic and lattice DOF.

Video generation is an active field of research. With the rise in the amount of available data and economically available processing power in the form of GPUs, deep Learning has been a go-to solution for many real life problems and similarly it is often attempted to solve the problem of video generation using deep learning. Predicting the next set of frames for a given set of frames in a video has seldom been taken up. Each video is composed of a consecutive closely related frames of images. If we consider these frames, the frame in each time-step seems to be related to the frames in the preceding time-steps. Therefore, we have both spatial and temporal data available from any set of consecutive frames in a video. Learning some sort of representation of the images that encodes the spatial data of the images (frames) can be combined with learning how these representations of a particular time-step is related with the next few time-steps is made possible, then prediction of the next few frames for a given set of frames is made possible. Our aim is to propose a simple yet effective model that can achieve this goal.

In this work, we have studied the structural and electronic properties of new-type of iron based superconductors ACa(2)Fe(4)As(4)F(2) (A = K, Rb) with first principles density functional theory based calculations. The density of states clearly shows that at Fermi level major contribution comes from iron 3d-orbitals and the contribution from other elements is very small. The electron-phonon coupling constant is found to be similar to 0.33 and similar to 0.4 for KCa2Fe4As4F2 and RbCa2Fe4As4F2, respectively. The estimated values of the upper bound of superconducting transition temperature is found to be similar to 2.4 K and similar to 4.2 K for KCa2Fe4As4F2 and RbCa2Fe4As4F2, respectively, suggesting that superconductingpairing mechanism in these systems have unconventional origin. Band structure calculations shows that ten bands crossesthe Fermi level and the corresponding Fermi surfaces show significant nesting with both hole-like and electron-like pockets.

We have investigated the electronic and thermoelectric properties of CuGaTe2 by combining the first principle calculations with Boltzmaim transport theory. The electronic properties show that CuGaTe2 is a direct band semiconductor with large band gap at F-point. The band gaps are computed by using PBE and mBJ potentials and value obtained with mHJ is much closer to the experimental value. Partial density of states plots show that the hand gap is formed by the hybridization between 3d states of Cu atom, 4s and 4p states of Ga atom and 5p states of Te atom. Very large value (similar to 300 mu VK-1) of Seebeck coefficient is obtained for this compound. Figure-of-merit calculated by using transport coefficients is also found to be very large for the entire temperature range and CuGaTe2 is a good thermoelectric material.

In the present work, we have investigated the thermoelectric properties of CuGaTe2 by combining the first principle calculations with Boltzmann transport theory. CuGaTe2 is found to be a potential thermoelectric material with Seebeck coefficient 275 mu VK-1 at 200K. The thermoelectric properties of the compound can be further improved by doping it with p as well as n-type charge carriers. The heavily p-doped and lightly n-doped, CuGaTe2 provides power factor comparable to that of state-of-art Bi2Te3.

Automatic human activity recognition is being studied widely by researchers for various applications. However, majority of the existing work are limited to recognition of isolated activities, though human activities are inherently continuous in nature with spatial and temporal transitions between various segments. Therefore, there are scopes to develop a robust and continuous Human Activity Recognition (HAR) system. In this paper, we present a novel Coarse-to-Fine framework for continuous HAR using Microsoft Kinect. The activity sequences are captured in the form of 3D skeleton trajectories consisting of 3D positions of 20 joints estimated from the depth data. The recorded sequences are first coarsely grouped into two activity sequences performed during sitting and standing. Next, the activities present in the segmented sequences are recognized into fine-level activities. Activity classification in both stages are performed using Bidirectional Long Short-Term Memory Neural Network (BLSTM-NN) classifier. A total of 1110 continuous activity sequences have been recorded using a combination of 24 isolated human activities. Recognition rates of 68.9% and 64.45% have been recorded using BLSTM-NN classifier when tested using length-modeling and without length-modeling, respectively. We have also computed results for isolated activity recognition performance. Finally, the performance has been compared with existing approaches.

A detail comparison between the results obtained for the electronic and transport properties of YNiBi half-Heusler alloy by local density approximation (LDA) and generalized gradient approximation (GGA) functionals with and without spin–orbit coupling (SOC) is presented. In the presence of SOC both functionals provide ∼30% smaller band gap. The transport coefficients computed without SOC confirm that YNiBi is a promising p-type thermoelectric material. However, with SOC at higher temperature, Seebeck coefficient was found to be negative because of the bipolar effects. Without SOC the computed power factor (PF) is found to be closer to the experimental value, while in the presence of SOC we have obtained comparatively smaller PF. No importance of SOC has been observed in the calculations of transport properties of the compound. The appropriate Ti doping in place of Y is predicted to significantly enhance the thermoelectric properties of YNiBi compound.