Showing papers by "Indian Institute of Technology Indore published in 2023"

Pressure Signal-Based Analysis of Anomalies in Switching Behavior of a Two-Way Directional Control Valve

Abstract: Abstract Solenoid operated direction control valves, responsible for regulating the flow of fluid in hydraulic circuit highly relies on the control current for their actuation. The control currents supplied to the solenoid generate the electromagnetic force required for switching of valves by mechanical movement of spools inside. The deterioration in control current leads to the degradation in electromagnetic force and thus the spool takes longer to initiate as well as terminate the switching phenomenon. This delay or lag potentially causes the pressure, flow and power fluctuation, and unintended impacts on the system. This article presents a comparative analysis of detecting these anomalies by acquiring pressure signals across the valve using extreme gradient boosting (XGBoost) and one-dimensional convolution neural network (CNN). Four handcrafted statistical features and four fractal dimensions train XGBoost whereas 1D CNN with six hidden layers utilizes the raw signal of net pressure change across the valve. XGBoost predicts the switching behavior at an accuracy of 99.68%, and 1D CNN performs at its maximum possible accuracy (100%). The very narrow gap signifies the nearly equal significance of both of these different category classifiers. As XGBoost cannot handle the raw signals, the pre-processing increases the time consumption while 1D CNN does not require deep architecture and efficiently maps the complexity of the hydraulic system using pressure signals.

Characterization of novel trench-isolated LGADs for 4D tracking

Abstract: In recent years, Low Gain Avalanche Detectors (LGADs) have shown the capability of timing measurements in the tens of ps range for minimum ionizing particles. However, the segmentation of LGADs creates regions with no gain and provides a hindrance in achieving 100% fill factor (FF) for many applications and using LGADs as 4-dimensional (4D) tracking devices. The new LGAD design based on the trench isolation technique (TI-LGAD) is very promising in reducing the no-gain region and hence increased FF which in turn makes them capable of 4D tracking. This paper describes the features of a new TI-LGAD sensors production by FBK, in which the no-gain region is reduced significantly by replacing Junction Termination Extension (JTE) and p-stop implant with slender trenches. A new R&D batch is produced in FBK within the RD50 collaboration, in which several border layouts and fabrication processes are implemented. The new TI-LGAD batch enables a systematic study to select the best fabrication process and border layout. In this paper, the electrical and laser characterization, isolation between pixels, and the results on the measurement of no-gain region between pixels are presented.

Vertically Aligned Nanoplates of Atomically Precise Co₆S₈ Cluster for Practical Arsenic Sensing

Abstract: Two-dimensional nanostructures with atomically precise building blocks have potential applications in catalysis and sensing. However, structural instability and surface reactivity limit their practical use. In this work, we demonstrate the formation of vertically aligned nanoplates of the [Co6S8DPPE6Cl6] cluster (Co6 in short), protected by 1,2-bis(diphenylphosphino)ethane, using ambient electrospray deposition (ESD). Charged microdroplets of Co6 formed by ESD on a water surface created such nanostructures. Preferential arrangement of clusters in the nanoplates with enhanced surface area results in sensitive and selective electrochemical response toward arsenite down to 5 parts per billion, in tap water. Density functional theory calculations reveal the preferential binding of arsenite with Co6. Our work points to a practical application of atomically precise clusters of large societal relevance.

Biomolecular Condensates Regulate Enzymatic Activity under a Crowded Milieu: Synchronization of Liquid–Liquid Phase Separation and Enzymatic Transformation

Abstract: Cellular crowding plays a key role in regulating the enzymatic reactivity in physiological conditions, which is challenging to realize in the dilute phase. Enzymes drive a wide range of complex metabolic reactions with high efficiency and selectivity under extremely heterogeneous and crowded cellular environments. However, the molecular interpretation behind the enhanced enzymatic reactivity under a crowded milieu is poorly understood. Herein, using the horseradish peroxidase (HRP) and glucose oxidase (GOx) cascade pair, we demonstrate for the first time that macromolecular crowding induces liquid-liquid phase separation (LLPS) via the formation of liquid-like condensates/droplets and thereby increases the intrinsic catalytic efficiencies of HRP and GOx. Both these enzymes undergo crowding induced homotypic LLPS via enthalpically driven multivalent electrostatic as well as hydrophobic interactions. Using a set of kinetic and microscopic experiments, we show that precise synchronization of spontaneous LLPS and enzymatic transformations is key to realize the enhanced enzymatic activity under the crowded environments. Our findings reveal an unprecedented enhancement (91- to 205-fold) in the catalytic efficiency (kcat/Km) of HRP at pH 4.0 within the droplet phase relative to that in the bulk aqueous phase in the presence of different crowders. In addition, we have shown that other enzymes also undergo spontaneous LLPS under macromolecular crowding, signifying the generality of this phenomenon under the crowded environments. More importantly, coalescence driven highly regulated GOx/HRP cascade reactions within the fused droplets have been demonstrated with enhanced activity and specificity under the crowded environments. The present discovery highlights the active role of membraneless condensates in regulating the enzymatic efficacy for complex metabolic reactions under the crowded cellular environments and may find significant importance in the field of biocatalysis.

Thermal Performance Analysis of Phase Change Material-Based Plate Finned Heat Sinks for Thermal Management Applications

Abstract: This experimental investigation focuses on employing phase change material (PCM) based heat sinks for passive thermal management system. PEG-6000 was inhibited as the PCM for the investigation. Four different configurations of plate fins, which acts as enhancers of thermal conductivity, (1) plate fin, (2) plate fins, (3) plate fins and (4) plate fins for three different heat fluxes 2.0, 2.5, and 3.0 kW/m2. The propagation of melt front of heat sinks is investigated with the help of a digital camera. The analysis of time–temperature distribution for three values of heat flux and the operating time enhancement for different combination of fins is carried out. Results from the investigation show that due to the increased fin number, the temperature of the base of the heat sink was kept to a comparatively low value for a more extended period, than heat sinks with no fins. The highest increase in operation time is achieved with a heat flow of 3.0 kW/m2 in the case of four finned heat sink.

GujAGra: An Acyclic Graph to Unify Semantic Knowledge, Antonyms, and Gujarati–English Translation of Input Text

Abstract: Word sense disambiguation, Machine Translation (MT), and part-of-speech tagging are just a few of the Natural Language Processing (NLP) applications where Large-scale lexical resources are required. These resources are regarded as treasure in such system applications. As a result, it is critical that these sources include accurate information. These lexical resources for Indian languages have already been generated digitally and are being constructed on a vast scale known as WordNet. WordNet perhaps seems to be the lexical resource that may be applied for a wide range of NLP applications, from digital dictionaries to automated machine translation. This article depicts Gujarati WordNet semantic relations as an acyclic graph. It also illustrates the process of creating links between Gujarati synsets and their English equivalents, and vice versa.

Simplified Damping Modification Factor for Vertical Response Spectra

Abstract: Damping modification factor of vertical response spectra (DMFV) for 1%, 2%, 8% and 10% damping levels with that at 5% of the critical is explored for a period range of 0–4.0 s. The dependence of DMFV on seismological parameters (magnitude, epicentral distance and soil type) is studied and is shown to be weak and insignificant for practical purposes. Simplified relation for computing DMFV as a function of the period is proposed irrespective of any seismological parameters.

Experimental Investigation on Phase Change Material Enhanced Pin Finned Heat Sinks for Thermal Management Applications

Abstract: Present research reports the experimental investigation to evaluate the thermal performance of nano-enhanced phase change material (NePCM) embedded with finned and unfinned heat sinks. Nano-particles of metal oxides (CuO and Al2O3) have been used with phase change material (paraffin wax) embedded with aluminium heat sinks. The thermal performance of various heat sinks formed on the different shapes of pin fins (square and circular) has been investigated considering the fixed fractional volume of fins (9%). Trails are conducted for a constant heat flux of (q′′ = 2.5 kW/m2) considering two different concentrations of nano-particles (∅ = 0.5 and 1%). Results report that for target temperature of 85 °C, thermal performance of square pin finned heat sink is superior when compared to other configurations of heat sinks. For temperature above 80 °C, heat sink without any fins gives better results. The highest enhancement ratio of 4.1 is reported from the heat sink with square pin fin for a set point temperature of 65 °C. Optimization of NePCM material and fins shape can enhance the overall thermal performance of phase change material-based heat sinks for passive thermal management systems.

Outer membrane proteins and vesicles as promising vaccine candidates against <i>Vibrio</i> spp. infections

Abstract: Indiscriminate use of antibiotics to treat bacterial infections has brought unmanageable antibiotic-resistant strains into existence. Vibrio spp. represents one such gram-negative enteric pathogenic group with more than 100 species, infecting humans and fish. The Vibrio spp. is demarcated into two groups, one that causes cholera and the other producing non-cholera or vibriosis infections. People who encounter contaminated water are at risk, but young children and pregnant women are the most vulnerable. Though controllable, Vibrio infection still necessitates the development of preventative measures, such as vaccinations, that can lessen the severity of the infection and reduce reliance on antibiotic use. With emerging multi-drug resistant strains, efforts are needed to develop newer vaccines, such as subunit-based or outer membrane vesicle-based. Thus, this review strives to bring together available information about Vibrio spp. outer membrane proteins and vesicles, encompassing their structure, function, and immunoprotective role.

Atypical Site Effects and Insufficiency of the Conventional Seismic Site Classification Methods: Experimental observations in the Geological Deposits of the Kashmir Valley (NW Himalayas), Jammu and Kashmir

Abstract: Kashmir Valley is one of the two administrative divisions of the Jammu and Kashmir region, lying within the Himalayan belt at the confluence of the Indian and Eurasian tectonic plates. It is an elongated basin filled with deep sedimentary deposits in the central portion, bounded by the Himalayan Mountain ranges at the periphery. The Pleistocene Karewa deposits overlain by the Recent Alluvium form the major types of sediments in the valley, showing a thickness of over 1300m (Burbank and Johnson, 1982). To evaluate the seismic response of these geological deposits, we recorded microtremors and performed multichannel analysis of surface waves (MASW) testing at ~190 sites using TROMINO&#174; equipment. Horizontal-to-vertical-spectral ratio (HVSR) curves and dispersion curves were respectively developed from the raw data, which were further used to estimate the site fundamental frequency (f0) and H/V amplitude (A) as well as average shear wave velocity over 30m depth (VS,30). A comparison of f0 and A with VS at each site was conducted to assess the suitability of codal provisions (NEHRP, EC8, etc.) and the specified amplification factors.We found certain issues with the use of VS,30 as the sole parameter for estimating the expected amplification at a site for seismic design. A direct correlation between amplification and stiffness (Vs30) at the sites was not attained, as opposed to the most common assumption in the prevalent code-based site classifications. Low amplification can be expected even at soft soil sites (NEHRP E) in the absence of an impedance contrast, and vice versa in stiff deposits. Observations in the deep sedimentary deposits in the valley show the importance of the contribution of deeper stratigraphy beyond the assumed 30m depth in the codes. Moreover, the notion of f0 being directly proportional to Vs30 irrespective of the geological conditions is not true. Besides, rock sites (NEHRP A and B) may not always present the conventional flat HVSR response, instead, significant high frequency amplifications can occur due to weathered or fractured material. Test results also revealed unusually high amplitudes within the fractured portion of a fault zone, signifying that the assumption of all rock sites being safe in terms of negligible amplifications may not be entirely correct. Topographic amplifications near basin edges, hill slopes, and within small valleys resulted in broad peaks over wide frequency range in the HVSR curves, which cannot be explained through the limited information contained in the Vs30 parameter.These incongruities observed at various sites in the Kashmir region point out the inadequacy of the site classifications based on the single-parameter (Vs30)approach, which do not always explain the actual amplifications observed during earthquakes in different geological conditions. The results obtained in the Kashmir Valley, backed by the similar arguments provided in literature (e.g., Lombardo and Rigano, 2006; Castellaro et al., 2008; Rovelli et al., 2009; Panzera et al., 2014; etc.), clearly indicate the need for adopting alternate site classification schemes (Di Alessandro et al., 2012; Pitilakis et al., 2019; Paolucci et al., 2021).&#160;

Importance of Four-Phonon Interactions in Lattice Thermal Conductivity and Thermoelectrics: A Case Study

Abstract: The theoretical determination of thermoelectric (TE) properties of a material depends upon the considered order of phonon interactions within the system. While three-phonon interactions have been used widely, four-phonon interactions should be considered in cases where lattice thermal conductivity (κL) is overestimated by three-phonon-based calculations, leading to a lower figure of merit (ZT). Here, we have evaluated bulk and bilayer systems of orthorhombic and hexagonal GeS as potential TE materials. The o-GeS and h-GeS bulk systems show higher ZT values of 0.96 than their respective bilayer systems. The effect of four-phonon scattering has been calculated in the o-GeS and h-GeS bilayer systems, revealing that κL is more dominant in the o-GeS bilayer. This disparity can be attributed to the presence of a larger phonon band gap in the o-GeS bilayer compared to the h-GeS bilayer. The percentage change in κL upon considering a higher order four-phonon scattering also increases with temperature. The four-phonon interactions lead to lower κL and higher ZT values of 0.508 for the o-GeS bilayer along the y-axis at 900 K. These findings show the vitality of considering higher order four-phonon interactions in calculating the lattice thermal conductivity and ZT values for such materials.

Influence of large-scale climate modes and local hydrometeorological factors in predicting basin scale rainfall and streamflow: A Bayesian network approach

Abstract: This article reports the findings of a recent study by Das and Chanda (2022), wherein a Bayesian Network (BN) approach was applied to analyze the influence of large-scale climate modes and local hydro-meteorological variables on streamflow and rainfall in four river basins in India. Bayesian Networks (BN) offers a thorough conditional independence structure that can improve comprehension and forecasting of hydroclimatic systems. This served as the main impetus for the work, which explored the relative contributions of large-scale climate modes and local hydro-meteorological variables for the prediction of rainfall and streamflow at the basin scale. Once the conditional independence structure is developed, variables possessing a &#8216;directed arc&#8217; from the target variable were selected as the potential predictors for developing the prediction models. The results showed that the most important predictors for streamflow were rainfall, u-wind, and soil moisture, while the most important predictors for rainfall were u-wind, air temperature, geo-potential height, precipitable water, vertical velocity, and relative humidity. The analysis also revealed that the influence of large-scale climate modes on the target variables was generally insignificant, except for the Pacific Decadal Oscillation and El-Ni&#241;o Southern Oscillation. Furthermore, the network structure showed that about 87 and 97% of the initial inputs are redundant. The accuracy of the prediction models are comparable across all of the basins and is higher for rainfall (Refined index of agreement (MD) ranging from 0.61 to 0.81) than for streamflow (MD ranging from 0.61 to 0.78). The study also found that dry, intermediate, and wet months can be satisfactorily classified using two drought indices, the Standardized Drought Index (SDI) for streamflow and the Standardized Precipitation Anomaly Index (SPAI) for rainfall.Keywords: Large-scale climate modes, local hydro-meteorological variables, Bayesian Networks (BN), Standardized Drought Index (SDI), Standardized Precipitation Anomaly Index (SPAI)Reference:Das P, Chanda K (2022) A Bayesian network approach for understanding the role of large-scale and local hydro-meteorological variables as drivers of basin-scale rainfall and streamflow. Stoch Environ Res Risk Assess 2:. https://doi.org/10.1007/s00477-022-02356-2

Stationarity assessment of hydroclimatic variables for a tropical river basin

Abstract: Understanding the space-time variations and dependency between hydroclimatic variables is vital for predicting future changes towards adaptive water resources management in a changing climate. Globally, it is observed that the mean and extreme hydroclimatic conditions are experiencing a significant shift under a changing climate, which affects the spatio-temporal distribution of floods and droughts. However, climate change studies seldom talk about the time invariance of the characteristics of a hydroclimatic time series. This research assesses the time invariance of the statistical properties of hydroclimatic variables (such as rainfall, temperature, streamflow and their derived indices) for a tropical river basin (i.e., the Tapi River basin) in India. Climate change profoundly impacts tropical river systems. Hence, assessing and detecting stationarity in hydrologic processes for such a river basin is imperative to predicting future changes. In this study, we have analyzed nine hydroclimatic variables representing the mean and extreme rainfall, temperature and streamflow. The hydroclimatic indices have been statistically examined to detect stationarity, homogeneity, and trends. A non-overlapping block stratified random sampling approach has been applied to identify the time invariance of hydroclimatic indices. The stationarity assessment approach investigates the similarities in the median, variance, distribution, and statistical moments of the continuous time series data. Based on the results of this study, weak and strict stationarity can be identified. The findings have significant ramifications for the planning and design of hydraulic structures, stormwater networks, flood mitigation, and disaster management for the Tapi basin.

An immunoinformatics analysis: design of a multi-epitope vaccine against <i>Cryptosporidium hominis</i> by employing heat shock protein triggers the innate and adaptive immune responses

Abstract: Cryptosporidium hominis, an anthropologically transferred species in the Cryptosporidium genus, represents many clinical studies in several countries. Its growth in the recent decade is primarily owing to epidemiologic studies. This parasite has complicated life cycles that require differentiation through a variety of phases of development and passage across two or more hosts throughout their lifetimes. As they move from host to host and environment to environment, pathogenic organisms are continually exposed to unexpected changes in the circumstances under which they develop. Heat shock proteins (HSPs) are targets of the host immune response; they are involved in the progression of diseases and play a significant part in this process. It has been discovered that the immunodominant immunogenic antigens in parasite infections HSPs. In this study, we have generated a multi-epitope vaccine against Cryptosporidium hominis (C. hominis) by using heat shock proteins. The epitopes that were selected had a substantial binding affinity for the B- and T-cell reference set of alleles, a high antigenicity score, a nature that was not allergic, a high solubility, non-toxicity and good binders. The epitopes were incorporated into a chimeric vaccine by using appropriate linkers. In order to increase the immunogenicity of the connected epitopes and effectively activate both innate and adaptive immunity, an adjuvant was attached to the epitopes. We have also analyzed the physiochemical characteristics of the vaccine which were satisfactory and then lead to the development of a 3D model. In addition, the binding confirmation of the vaccine to the TLR-4 innate immune receptor was also determined using molecular docking and molecular dynamics (MD) simulation. The results of this simulation show that the vaccine has a strong binding affinity for TLR4, which indicates that the vaccine is highly effective. In general, the vaccine that has been described here has a good potential for inducing protective and targeted immunogenicity, however, this hypothesis is contingent upon more experimental testing.Communicated by Ramaswamy H. Sarma.

Lithospheric imaging beneath North India using surface wave tomography

Abstract: We provide a shear wave velocity model of the Indo-Gangetic plain (IGP) that extends down to a depth of 100 km.&#160; Using vertical component seismograms of 108 broadband (BB) stations (50 and 58) of IRIS-DMC and National Centre for Seismological (NCS) respectively, located in and around the Northern Indian plate. The group velocity dispersion of the Rayleigh wave has been picked along&#160; ~3000 paths across the study region over a period range of 8 to 80s. To construct the 3D shear wave velocity structure, we employ a two-step surface wave tomography procedure. In the first step, regionalized dispersion maps are prepared for each period of correlation length of 60km, and subsequently, we employ the Markov chain Monte Carlo (McMC) trans-dimensional Bayesian inversion algorithm to obtain the shear wave velocity structure. In regionalized dispersion maps, at short periods (~8s) we see slow velocity in northern IGP and region reported thick basement (~6km) from previous studies. For moving towards increasing periods map indicate slow velocity anomalies in the Himalayan and Tibetan plateau region are associated with a thick crust (>50) in contrast to the typical crust (~40km) of IGP. The fast and slow velocities areas are identified which are associated with the Indian shield and thick crust in the Himalayas. Further, we inverted regionalized geographical locations to get shear wave velocity at each point to make a 3D lithospheric model. We have used 20 chains with 600k burn-in phase and 300k in the main phase for sampling the posterior distribution and from the final posterior distribution best 500k models with of 5% deviation has been selected after removing those model that has outlier chains with unrealistic models.Keywords:&#160; Surface waves, Bayesian inversion, Seismic tomography, Northwestern Himalayas.

1D Velocity Model for NW India in and Around Delhi

Abstract: We derive a 1D crustal velocity model based on P- and S-wave residual time arrivals at the national seismological network maintained by National Center for Seismology (NCS) for NW India around Delhi between latitude range 22º N to 33º N and longitude range 73ºE to 80ºE, which separates interplate area in the north and intraplate area in the south. Available models are mostly from regional studies having low crustal resolution. We use 413 earthquakes in all, which are chosen based on the maximum number of stations, minimum azimuthal gap, and root mean square travel time. We use VELEST code to invert the 1D velocity model, hypocenter locations, and station delays. The Indo-Gangetic (IG11) model is used as a starting model, and in this model, we further created 500 initial models by adding random perturbation ± 10%. We also evaluate the effect of different Moho depths (i.e., 38, 43, and 48 km). We selected the preferred model based on how the models converge and on the travel time residuals. The minimum residual travel time of P- and S-arrivals indicated crustal thickness as 43 km. Further, this model can be used for seismicity and 3D seismic tomographic studies of the area.

How unexpected was the Spring 2022 South Asian Heatwave

Abstract: Persistent heatwaves cause severe impacts on the ecosystem and society, including increased mortality, and widespread snow and glacier melting. These impacts are expected to escalate in a warmer world, which is likely to witness more frequent and intense heatwaves. South Asia (SA), home to one-fifth of the global population and the largest freshwater resource on the earth, is a hotspot of extreme heatwaves and vulnerable to severe impacts. The region recently experienced its hottest March and April of the century in the year 2022. Here, we use high-resolution, long-term ERA5 (1959&#8211;2022) and CPC (1979&#8211;2022) data to show that the temperatures in Northwestern South Asia were about 5&#176;C higher than the climatology, which corresponds to about 2.5 standard deviations above the mean. Using maximum temperature-based CTX90pct definition of heatwaves, we show the 42-day-long heatwave in the month of March and April 2022 ranked the most severe heatwave recorded in the available observation period of 65 years. The heatwave engulfed half of Northwest SA, approximately 1.6 million km2, with an average intensity of 1.8&#176;C. The high-temperature driven snow melting during the heatwave nearly vanished the year&#8217;s snowpack, which normally lasts till June. With further analysis, we find that the heatwave was initiated by a persistent anticyclonic blocking associated with a sub-tropical Rossby wave, while it was exacerbated by strong positive land-atmosphere feedback due to lack of soil moisture and latent heat. Our findings provide valuable insights into understanding the changes and impacts of heatwaves in the mountainous areas of SA.

Alginate Based Carriers for Topical Drug Delivery

Abstract: Topical drug delivery is a promising approach for drug susceptible to degradation on oral administration or drug undergoing first pass effect. Topical delivery allows the drug to reach target site in effective concentration without drug lose, minimizing drug dose, frequency and cost load. In addition, topical delivery also offers localized drug delivery for treatment of various health disorders like skin infections, chronic wound, skin carcinoma etc. Biopolymers use in topical formulation is a promising strategy for design of safe and efficient drug delivery systems (DDS). Alginate is such a potent biopolymer with diverse advantages over synthetic polymers, including natural abundance, economic cost, biodegradability, biocompatibility, cyto-compatibility, no toxicity, and hydrophilicity. Alginate also has intrinsic bioactivity like anti-inflammatory and antimicrobial properties that may give synergistic effect with drug. Furthermore, due to its structural diversity, alginate allows for surface functionalization to give versatility in biomedical and pharmaceutical applications. Alginate can be effectively employed for the formulation of various DDS such as gels, dermal patches, films, microneedles, nanofibrous scaffolds, nanoparticles, and microparticles, for topical applications.