Search Results (20)

In this study, a simple and efficient hydrothermal strategy was developed to modify reduced graphene oxide (rGO) with copper (II) oxide (CuO) nanoparticles by varying the weight ratio of rGO relative to CuO (rGO@CuO_1:1, rGO@CuO_1:2, and rGO@CuO_2:1). The obtained materials were further characterized using analytical tools. Photocatalytic performance was assessed using adsorption–photocatalysis experiments under a household LED light source (10 W, λ > 400 nm), and the degree of degradation of doxycycline (DOX) was evaluated using UV-Vis spectrophotometer. The highest efficiency of 100% was achieved with a DOX concentration of 70 ppm, rGO@CuO_1:1 dosage of 1 mg/mL, and pH 7 within 30 min of irradiation. The degradation kinetics followed the pseudo-first-order model (R² ~0.99) and the Langmuir adsorption isotherm, indicating that DOX on the surface is governed by a dynamic equilibrium between adsorption and degradation rates. Furthermore, efficacy was tested using real water samples, and the recyclability of the catalyst was evaluated in up to five cycles. Full article

This investigation explores the application of supervised machine learning regression approaches to predict various responses, including penetration, bead width, bead height, hardness, ultimate tensile strength, and percentage elongation in autogenous TIG-, A-TIG-, and TIG-welded joints of SS304H, which is considered as an advanced high-temperature resistant material. The machine learning (ML) models were constructed based on the data gathered from 50 experimental runs, considering eight key input variables: gas flow rate, torch angle, filler material, welding pass, flux application, root gap, arc gap, and heat input. A total of 80% of the collected dataset was used for training the models, while the remaining 20% was reserved for testing their performance. Six ML algorithms—Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting Regression (GBR), and Extreme Gradient Boosting (XGBoost)—were implemented to assess their predictive accuracy. Among these, the XGBoost model has demonstrated the highest predictive capability, achieving R² scores of 0.886 for penetration, 0.926 for width, 0.915 for weld bead height, 0.868 for hardness, 0.906 for ultimate tensile strength, and 0.926 for percentage elongation, along with the lowest values of RMSE, MAE, and MSE across all responses. The outcomes establish that machine learning models, particularly XGBoost, can accurately predict welding characteristics, marking a significant advancement in the optimization of TIG welding parameters. Consequently, integrating such predictive models can substantially enhance the precision, reliability, and overall efficiency of welding processes. Full article

Quantum error correction codes (QECCs) are essential for reliable quantum computing as they protect quantum states against noise and errors. Limited research has explored the resilience of QECCs to biased noise, critical for selecting optimal codes. We examine how different noise types impact QECCs, considering the varying susceptibility of quantum systems to specific errors. Our goal is to identify opportunities to minimize the resources—or overhead—needed for effective error correction. We conduct a detailed study on two QECCs—rotated and unrotated surface codes—under various noise models using simulations. Rotated surface codes generally perform better due to their simplicity and lower qubit overhead. They exceed the noise threshold of current quantum processors, making them more effective at lower error rates. This study highlights a hierarchy in surface code implementation based on resource demand, consistently observed across both code types. Our analysis ranks the code-capacity model as the most pessimistic and the circuit-level model as the most realistic, mapping error thresholds that show surface code advantages. Additionally, higher code distances improve performance without excessively increasing qubit overhead. Tailoring surface codes to align with the target logical error rate and the biased physical error profile is crucial for optimizing reliability and resource use. Full article

Quantum error correction (QEC) plays a crucial role in correcting noise and paving the way for fault-tolerant quantum computing. This field has seen significant advancements, with new quantum error correction codes emerging regularly to address errors effectively. Among these, topological codes, particularly surface codes, stand out for their low error thresholds and feasibility for implementation in large-scale quantum computers. However, these codes are restricted to encoding a single qubit. Lattice surgery is crucial for enabling interactions among multiple encoded qubits or between the lattices of a surface code, ensuring that its sophisticated error-correcting features are maintained without significantly increasing the operational overhead. Lattice surgery is pivotal for scaling QECCs across more extensive quantum systems. Despite its critical importance, comprehending lattice surgery is challenging due to its inherent complexity, demanding a deep understanding of intricate quantum physics and mathematical concepts. This paper endeavors to demystify lattice surgery, making it accessible to those without a profound background in quantum physics or mathematics. This work explores surface codes, introduces the basics of lattice surgery, and demonstrates its application in building quantum gates and emulating multi-qubit circuits. Full article

Quantitative analysis of LULC changes and their effects on carbon stock and sequestration is important for mitigating climate change. Therefore, this study examines carbon stock and sequestration in relation to LULC changes using the Land Change Modeler (LCM) and Ecosystem Services Modeler (ESM) in tropical dry deciduous forests of West Bengal, India. The LULC for 2006, 2014, and 2021 were classified using Google Earth Engine (GEE), while LULC changes and predictions were analyzed using LCM. Carbon stock and sequestration for present and future scenarios were estimated using ESM. The highest carbon was stored in forest land (124.167 Mg/ha), and storage outside the forest declined to 13.541 Mg/ha for agricultural land and 0–8.123 Mg/ha for other lands. Carbon stock and economic value decreased from 2006 to 2021, and are likely to decrease further in the future. Forest land is likely to contribute to 94% of future carbon loss in the study region, primarily due to its conversion into agricultural land. The implementation of multiple-species plantations, securing tenure rights, proper management practices, and the strengthening of forest-related policies can enhance carbon stock and sequestration. These spatial-temporal insights will aid in management strategies, and the methodology can be applied to broader contexts. Full article

The present work studies the response to hygrothermal ageing of natural fibre composites (NFCs) against synthetic fibre composites when using three different types of polymers as matrices. For ageing, coupons were fully immersed in distilled water at 23, 40, and 60 °C for a total ageing period of 56 days. Flax fibre-reinforced composites, using two recyclable polymer systems: (i) a bio-based recyclable epoxy and (ii) an acrylic-based liquid thermoplastic resin, were tested against conventional glass fibre-reinforced composites employing a synthetic (petroleum-based) epoxy. Different fibre/polymer matrix material combinations were tested to evaluate the effects of hygrothermal ageing degradation on the reinforcement, matrix, and fibre/matrix interface. The hygrothermal ageing response of unaged and aged composite coupons was assessed in terms of flexural and viscoelastic performance, physicochemical properties, and microscopy (SEM—Scanning Electron Microscopy). Full article

Doppler sodar measurements were made at the tropical Indian station, i.e., Gadanki (13.5° N, 79. 2° E). According to wind climatologies, the wind pattern changes from month to month. In July and August, the predominant wind direction during the monsoon season was the southwest. In September, it was the northwest and south. While the winds in November came from the northeast, they came from the northwest and southwest in October. The winds in December were out of the southeast. The diurnal cycle of winds at 60-m above the ground was visible, with disturbed wind directions in September and October. This may be connected to the Indian subcontinent’s southeastern monsoon recession. To better understand the monsoon circulation on a monthly basis, the present work is innovative in that it uses high-resolution winds measured using the Doppler sodar at the atmospheric boundary layer. The convergence of a sea breeze and the background wind might result in a sudden change in wind direction, and forecasting such a chaotic atmospheric event is crucial in the aviation sector. As a result, the wind shear that is produced may pose a serious threat to airplanes that are landing. In the current study, we present a few cases of sea breeze intrusions. The physics underlying these intrusions may help modelers better understand these chaotic wind structures and use them as inputs in their models. Based on surface-based atmospheric characteristics, there have been two reports of deep sea breeze intrusions that we report in this research. The sea breeze days were marked by substantial (moderate) drops in temperature (dewpoint temperatures) and increased wind speed and relative humidity. The India Meteorological Department (IMD) rainfall data showed a rise in precipitation over this location on 23 July (4.8 mm) and 24 July (9.5 mm) when sea breeze intrusions over Gadanki were noticed. Sea breeze intrusions could have brought precipitation (intrusion-laden precipitation) to this area due to conducive meteorological conditions. A simple schematic model is proposed through a diagrammatic illustration that explains how a sea breeze triggers precipitation over adjacent locations to the seacoast. The skew-T log-P diagrams have been drawn using the balloon-borne radiosonde measured atmospheric data over Chennai (a nearby location to Gadanki) to examine the thermodynamic parameters to gain insights into the underlying mechanisms and meteorological conditions during sea breeze intrusion events. It is found that the convective available potential energy (CAPE), which is presented as a thermos diagram, was associated with large values on 23 July and 24 July (898 J/kg and 1250 J/kg), which could have triggered thunderstorms over Chennai. Full article

In spite of the progress in treatment strategies, cancer remains a major cause of death worldwide. Therefore, the main challenge should be the early diagnosis of cancer and the design of an optimal therapeutic strategy to increase the patient’s life expectancy as well as the continuation of the search for increasingly active and selective molecules for the treatment of different forms of cancer. In the recent decades, research in the field of natural compounds has increasingly shifted towards advanced and molecular level understandings, thus leading to the development of potent anti-cancer agents. Among them is the diterpene lactone andrographolide, isolated from Andrographis paniculata (Burm.f.) Wall. ex Nees that showed shows a plethora of biological activities, including not only anti-cancer activity, but also anti-inflammatory, anti-viral, anti-bacterial, neuroprotective, hepatoprotective, hypoglycemic, and immunomodulatory properties. Andrographolide has been shown to act as an anti-tumor drug by affecting specific molecular targets that play a part in the development and progression of several cancer types including breast, lung, colon, renal, and cervical cancer, as well as leukemia and hepatocarcinoma. This review comprehensively and systematically summarized the current research on the potential anti-cancer properties of andrographolide highlighting its mechanisms of action, pharmacokinetics, and potential side effects and discussing the future perspectives, challenges, and limitations of use. Full article

Agricultural crops are facing a continuous threat due to biotic and abiotic stresses, thus, limiting the crop productivity, and thereby, threatening food security. Plant roots attract several kinds of microbes that induce resistance in plants against these stresses by enhancing the activity of the antioxidant enzymes, phenolic and other non-phenolic compounds, and thereby, have a beneficial effect on plants. Vast research has been carried out on biocontrol agents to manage soil-borne plant pathogens, but there has been limited success in the development of region-specific, commercially viable microbial inoculants. The present research was framed with a view to screen and evaluate native Pseudomonads from the rhizosphere of different crops in lateritic soils and their exploitation in biotic and abiotic stress management under the red and lateritic zone of West Bengal. In the lateritic area of West Bengal, the lowest pH as well as the highest culturable rhizobacterial population was found in the soil of Bankura. Among all the isolated rhizobacteria, 43.33% were found to be moderately antagonistic against three different soil-borne plant pathogens viz., Rhizoctonia solani, Sclerotinia sclerotiorum and Sclerotium rolfsii—while only 6.67% were found to be very highly antagonistic against these soil-borne plant pathogens. Augmented seeds of tomato, cowpea and French bean with native rhizobacteria enhanced the vigour index and 16.67% of the isolates were found to have a high value of vigour index in the normal and acid stress conditions. Based on acid tolerance, antagonistic activity and the seed vigour assay, a total of 13 isolates from 97 of lateritic area were selected. Out of the 13 selected isolates, 7 were positive for protease and lipase production, 8 isolates were positive for the production of HCN, siderophore and salicylic acid production and 9 isolates were found to be positive for IAA, phosphate solubilisation, amylase and chitinase production. Species of beneficial Pseudomonads such as Pseudomonas aeruginosa, P. fluorescens, P. Plecoglossicida, P. helmanticensis, P. geniculate, P. baetica and P. putida were found. Five isolates were used to study the effect on plant growth in terms of germination (%), root and shoot length, as well as fresh root and shoot weight and disease patterns in terms of pre- and post-emergence damping-off under the semi-field condition. Full article

Fruits that are rich in nutrients and have antioxidant properties are essentially required for human health. These fruits are quite demanding to use pharmaceutically to produce natural drugs. Tripura, a Northeast state of India, is abundant in wild edible fruits, the nutritional values of which have not yet been fully explored. The nutrient composition and antioxidant properties of 06 (six) wild edible fruits viz. Wild orange (Citrus macroptera), Chinese lard (Hodgsonia macrocarpa Cogn.), Madhabilata (Stixis suaveolens Roxb. Pierre), Wild small black Jamun (Syzygium assamicum), Indian coffee plum (Flacourtia jangomas Lour. Raeusch), and Gamboge (Garcinia gummi-gutta (L.) Robs) were explored and are reported in this paper. All the observations were statistically analyzed and properly presented here. The study reveals that wild orange (220.75 mg/100 g) and Indian coffee plum (223.25 mg/100 g) are vitamin C-rich fruits. Madhabilata has high protein content (0.744%), whereas Gamboge yields an energetic fruit (124.92 Kcal/100 g). The energy parameter has a good correlation with ash (correlation coefficient (r) = 0.68), TSS (r = 0.62), and protein (r = 0.83). Nutrient minerals (mg/100 g), in general, are found quite high in wild orange (Na, 170.4; K, 55.40; Mg, 61.53; Zn, 6.85; Cu, 6.25). There is a good correlation between Na and K (r = 0.58). Antioxidant activity (81.15 μmol/g) and metal chelating capacity (MCC) (39.45 mg/mL) are high in wild orange, and they have an excellent correlation (r = 0.97). It has quite a high value of total phenolic content (TPC) (303.89 mg GAE/g) and total flavonoid content (TFC) (36.78 mg QE/g) as well. TPC and TFC have good correlations with antioxidant parameters (r = 0.81 with TPC and 0.86 with TFC). Chloride (4.35 mg/100 g), nitrate (0.639 μg/100 g), and As(III) (0.27 mg/100 g) contents are found high in Indian coffee plum, Madhabilata, and Wild black Jamun, respectively. Principal component analysis (PCA) revealed that total sugar, zinc (Zn), manganese (Mn), and copper (Cu) are the important indicators to be given emphasis while studying the nutritional value of these minor fruits. Moreover, the results would provide a baseline database for the nutrient profile of these fruits as well as enhance awareness among the masses regarding the value of the fruit, which enhances and conserves the biodiversity of the forest area of Tripura. Full article

Increasing land surface temperature (LST) is one of the major anthropogenic issues and is significantly threatening the urban areas of the world. Therefore, this study was designed to examine the spatial variations and patterns of LST during the different seasons in relation to influencing factors in Kolkata Municipality Corporation (KMC), a city of India. The spatial distribution of LST was analyzed regarding the different surface types and used 25 influencing factors from 6 categories of variables to explain the variability of LST during the different seasons. All-subset regression and hierarchical partitioning analyses were used to estimate the explanatory potential and independent effects of influencing factors. The results show that high and low LST corresponded to the artificial lands and bodies of water for all seasons. In the individual category regression model, surface properties gave the highest explanatory rate for all seasons. The explanatory rates and the combination of influencing factors with their independent effects on the LST were changed for the different seasons. The explanatory rates of integration of all influencing factors were 89.4%, 81.4%, and 88.7% in the summer, transition, and winter season, respectively. With the decreasing of LST (summer to transition, then to winter) more influencing factors were required to explain the LST. In the integrated regression model, surface properties were the most important factor in summer and winter, and landscape configuration was the most important factor in the transition season. LST is not the result of single categories of influencing factors. Along with the effects of surface properties, socio-economic parameters, landscape compositions and configurations, topographic parameters and pollutant parameters mostly explained the variability of LST in the transition (11.22%) and summer season (15.22%), respectively. These findings can help to take management strategies to reduce urban LST based on local planning. Full article

In this work, the effect of silicon carbide (carborundum, SiC), as a boosting agent of the mechanical response of the polycarbonate (PC) polymer, was investigated. The work aimed to fabricate nanocomposites with an improved mechanical performance and to further expand the utilization of 3D printing in fields requiring an enhanced material response. The nanocomposites were produced by a thermomechanical process in various SiC concentrations in order to evaluate the filler loading in the mechanical enhancement. The samples were 3D printed with the material extrusion (MEX) method. Their mechanical performance was characterized, following international standards, by using dynamic mechanical analysis (DMA) and tensile, flexural, and Charpy’s impact tests. The microhardness of the samples was also measured. The morphological characteristics were examined, and Raman spectra revealed their structure. It was found that SiC can improve the mechanical performance of the PC thermoplastic. A 19.5% increase in the tensile strength was found for the 2 wt.% loading nanocomposite, while the 3 wt.% nanocomposite showed a 16% increase in the flexural strength and a 35.9% higher impact strength when compared to the unfilled PC. No processability issues were faced for the filler loadings that have been studied here. Full article

Agroforestry systems (AFS) and practices followed in India are highly diverse due to varied climatic conditions ranging from temperate to humid tropics. The estimated area under AFS in India is 13.75 million ha with the highest concentration being in the states of Uttar Pradesh (1.86 million ha), followed by Maharashtra (1.61 million ha), Rajasthan (1.55 million ha) and Andhra Pradesh (1.17 million ha). There are many forms of agroforestry practice in India ranging from intensified simple systems of monoculture, such as block plantations and boundary planting, to far more diverse and complex systems, such as home gardens. As a result, the biomass production and carbon sequestration potential of AFS are highly variable across different agro-climatic zones of India. Studies pertaining to the assessment of biomass and carbon storage in different agroforestry systems in the Indian sub-continent are scanty and most of these studies have reported region and system specific carbon stocks. However, while biomass and carbon stock data from different AFS at national scale has been scanty hitherto, such information is essential for national accounting, reporting of C sinks and sources, as well as for realizing the benefits of carbon credit to farmers engaged in tree-based production activities. Therefore, the objective of this study was to collate and synthesize the existing information on biomass carbon and SOC stocks associated with agroforestry practices across agro-climatic zones of India. The results revealed considerable variation in biomass and carbon stocks among AFS, as well as between different agro-climatic zones. Higher total biomass (>200 Mg ha⁻¹) was observed in the humid tropics of India which are prevalent in southern and northeastern regions, while lower total biomass (<50 Mg ha⁻¹) was reported from Indo-Gangetic, western and central India. Total biomass carbon varied in the range of 1.84 to 131 Mg ha⁻¹ in the agrihorticulture systems of western and central India and the coffee agroforests of southern peninsular India. Similarly, soil organic carbon (SOC) ranged between 12.26–170.43 Mg ha⁻¹, with the highest SOC in the coffee agroforests of southern India and the lowest in the agrisilviculture systems of western India. The AFS which recorded relatively higher SOC included plantation crop-based practices of southern, eastern and northeastern India, followed by the agrihorticulture and agrisilviculture systems of the northern Himalayas. The meta-analysis indicated that the growth and nature of different agroforestry tree species is the key factor affecting the carbon storage capacity of an agroforestry system. The baseline data obtained across various regions could be useful for devising policies on carbon trading or financing for agroforestry. Full article

The conventional paper-based system for malaria surveillance is time-consuming, difficult to track and resource-intensive. Few digital platforms are in use but wide-scale deployment and acceptability remain to be seen. To address this issue, we created a malaria surveillance mobile app that offers real-time data to stakeholders and establishes a centralised data repository. The MoSQuIT app was designed to collect data from the field and was integrated with a web-based platform for data integration and analysis. The MoSQuIT app was deployed on mobile phones of accredited social health activists (ASHA) working in international border villages in the northeast (NE) Indian states of Assam, Tripura and Arunachal Pradesh for 20 months in a phased manner. This paper shares the challenges and opportunities associated with the use of MoSQuIT for malaria surveillance. MoSQuIT employs the same data entry formats as the NVBDCP’s malaria surveillance programme. Using this app, a total of 8221 fever cases were recorded, which included 1192 (14.5%) cases of P. falciparum malaria, 280 (3.4%) cases of P. vivax malaria and 52 (0.6%) mixed infection cases. Depending on network availability, GPS coordinates of the fever cases were acquired by the app. The present study demonstrated that mobile-phone-based malaria surveillance facilitates the quick transmission of data from the field to decision makers. Geospatial tagging of cases helped with easy visualisation of the case distribution for the identification of malaria-prone areas and potential outbreaks, especially in hilly and remote regions of Northeast India. However, to achieve the full operational potential of the system, operational challenges have to be overcome. Full article

Cyberattacks (CAs) on modern interconnected power systems are currently a primary concern. The development of information and communication technology (ICT) has increased the possibility of unauthorized access to power system networks for data manipulation. Unauthorized data manipulation may lead to the partial or complete shutdown of a power network. In this paper, we propose a novel security unit that mitigates intrusion for an interconnected power system and compensates for data manipulation to augment cybersecurity. The studied two-area interconnected power system is first stabilized to alleviate frequency deviation and tie-line power between the areas by designing a fractional-order proportional integral derivative (FPID) controller. Since the parameters of the FPID controller can also be influenced by a CA, the proposed security unit, named the automatic intrusion mitigation unit (AIMU), guarantees control over such changes. The effectiveness of the AIMU is inspected against a CA, load variations, and unknown noises, and the results show that the proposed unit guarantees reliable performance in all circumstances. Full article