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"Ganesh, T."
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A Brief Review of Transparent Conducting Oxides (TCO): The Influence of Different Deposition Techniques on the Efficiency of Solar Cells
Global-warming-induced climate changes and socioeconomic issues increasingly stimulate reviews of renewable energy. Among energy-generation devices, solar cells are often considered as renewable sources of energy. Lately, transparent conducting oxides (TCOs) are playing a significant role as back/front contact electrodes in silicon heterojunction solar cells (SHJ SCs). In particular, the optimized Sn-doped In2O3 (ITO) has served as a capable TCO material to improve the efficiency of SHJ SCs, due to excellent physicochemical properties such as high transmittance, electrical conductivity, mobility, bandgap, and a low refractive index. The doped-ITO thin films had promising characteristics and helped in promoting the efficiency of SHJ SCs. Further, SHJ technology, together with an interdigitated back contact structure, achieved an outstanding efficiency of 26.7%. The present article discusses the deposition of TCO films by various techniques, parameters affecting TCO properties, characteristics of doped and undoped TCO materials, and their influence on SHJ SC efficiency, based on a review of ongoing research and development activities.
Journal Article
Temples and bats in a homogeneous agriculture landscape: Importance of microhabitat availability, disturbance and land use for bat conservation
Cave-dwelling bats widely use anthropogenic structures such as temples in south Asia as roosting and nursery sites. Such roosts are constantly under threat, even more so after the COVID-19 pandemic. Despite the importance of such roosts, there is no detailed understanding of what makes temples favorable for bats and the critical factors for their persistence. Here we relate temple microhabitat characteristics and land use around ancient temples (>400 years) to bat species richness and abundance in the Tamiraparani river basin of south India. Temples were selected for sampling along the river basin based on logistics and permission to access them. We counted bats at the roost in the mornings and late afternoons from inside the temples. Temple characteristics such as dark rooms, walkways, crevices, towers, and disturbances to the roosts were recorded. Based on European Space Agency land use classifications, we recorded land use such as crops, trees, scrub, grassland, urban areas, and water availability within a 5 km radius of the temple. Generalized Linear Mixed Models were used to relate the counts in temples with microhabitats and land use. We sampled 59 temples repeatedly across 5 years which yielded a sample of 246 survey events. The total number of bats counted was 20,211, of which Hipposideros speoris was the most common (9,715), followed by Rousettus leschenaultii (5,306), Taphozous melanopogon (3,196), Megaderma lyra (1,497), Tadarida aegyptiaca (303), Pipistrellus sp . (144) and Rhinopoma hardwickii (50). About 39% of the total bats occurred in dark rooms and 51% along walkways. Species richness and total abundance were related to the availability of dark rooms and the number of buildings in the temple. Land use elements only had a weak effect, but scrub and grassland, even though they were few, are critical for bats. We conclude that retaining undisturbed dark rooms with small exits in temples and other dimly lit areas and having natural areas around temples are vital for bat conservation.
Journal Article
The forests and elephants of Wayanad
The Wayanad district of Kerala, India, is an important conservation and cultural landscape located in the Western Ghats biodiversity hotspot. It is a slightly east-sloping plateau with a unique geographical feature of small rolling hills interspersed with low-lying swamps and meandering streams. Extensive deforestation that occurred in the last century has severely fragmented and degraded the forest of Wayanad, leaving it as a mosaic of forests, wetlands, croplands and towns. The remaining forests in Wayanad are part of the Brahmagiri–Nilgiri–Eastern Ghats Elephant Landscape (NEG), which holds the single largest contiguous population of Asian elephants globally. The NEG is prone to seasonal fluctuation in resource availability, where a large tract of dry forest reduces its carrying capacity for elephants during summer. The Wayanad forests are a critical microhabitat for elephants in the NEG due to availability of fodder and perennial water sources during summer. Despite the importance of this region for elephants, the forest is ‘degrading’ drastically that will have a far-reaching impact on the long-term conservation of elephants in the NEG. Similarly, human–elephant conflict is on the rise and it is one of the biggest threats to the conservation of elephants and the well-being of rural communities in Wayanad. In this article we identify the current conservation issues and recommend future management of Asian elephants and their habitat in Wayanad.
Journal Article
Diabetic Retinopathy Is a Predictor of Progression of Diabetic Kidney Disease: A Systematic Review and Meta-Analysis
Aims and Objectives. This systematic review and meta-analysis aimed to assess the predictive value of diabetic retinopathy (DR) for progression of diabetic kidney disease (DKD). Methods. A systematic search was conducted on PubMed, Embase, and the Google scholar for eligible studies through September 2021. The quality of selected articles was assessed using JBI checklist. Higgins and Thompson’s I2 statistic was used to see the degree of heterogeneity. Based on degree of heterogeneity, fixed or random effects model was used to estimate pooled effect using inverse variance method. Results were expressed as hazard ratios and odds ratios with 95% CIs. Results. After scrutinizing 18017 articles, data from ten relevant studies (seven prospective and three retrospective) was extracted. DR was significantly associated with DKD progression with a pooled HR of 2.42 (95% CI: 1.70–3.45) and a pooled OR of 2.62 (95% CI: 1.76–3.89). There was also a significant association between the severity of DR and risk of progression of DKD with a pooled OR of 2.13 (95% CI: 1.82–2.50) for nonproliferative DR and 2.56 (95% CI: 2.93–.33) for proliferative DR. Conclusion. Our study suggests that presence of DR is a strong predictor of risk of kidney disease progression in DKD patients. Furthermore, the risk of DKD progression increases with DR severity. Screening for retinal vascular changes could potentially help in prognostication and risk-stratification of patients with DKD.
Journal Article
Narrative review of artificial intelligence in diabetic macular edema: Diagnosis and predicting treatment response using optical coherence tomography
Diabetic macular edema (DME), being a frequent manifestation of DR, disrupts the retinal symmetry. This event is particularly triggered by vascular endothelial growth factors (VEGF). Intravitreal injections of anti-VEGFs have been the most practiced treatment but an expensive option. A major challenge associated with this treatment is determining an optimal treatment regimen and differentiating patients who do not respond to anti-VEGF. As it has a significant burden for both the patient and the health care providers if the patient is not responding, any clinically acceptable method to predict the treatment outcomes holds huge value in the efficient management of DME. In such situations, artificial intelligence (AI) or machine learning (ML)-based algorithms come useful as they can analyze past clinical details of the patients and help clinicians to predict the patient's response to an anti-VEGF agent. The work presented here attempts to review the literature that is available from the peer research community to discuss solutions provided by AI/ML methodologies to tackle challenges in DME management. Lastly, a possibility for using two different types of data has been proposed, which is believed to be the key differentiators as compared to the similar and recent contributions from the peer research community.
Journal Article
PRpnp, a novel dual activity PNP family protein improves plant vigour and confers multiple stress tolerance in Citrus aurantifolia
Summary Under field conditions, plants are often simultaneously exposed to several abiotic and biotic stresses resulting in significant reductions in growth and yield; thus, developing a multi‐stress tolerant variety is imperative. Previously, we reported the neofunctionalization of a novel PNP family protein, Putranjiva roxburghii purine nucleoside phosphorylase (PRpnp) to trypsin inhibitor to cater to the needs of plant defence. However, to date, no study has revealed the potential role and mechanism of either member of this protein group in plant defence. Here, we overexpressed PRpnp in Citrus aurantifolia which showed nuclear‐cytoplasmic localization, where it functions in maintaining the intracellular purine reservoir. Overexpression of PRpnp significantly enhanced tolerance to salt, oxidative stress, alkaline pH, drought and two pests, Papilio demoleus and Scirtothrips citri in transgenic plants. Global gene expression studies revealed that PRpnp overexpression up‐regulated differentially expressed genes (DEGs) related to ABA‐ and JA‐biosynthesis and signalling, plant defence, growth and development. LC–MS/MS analysis validated higher endogenous ABA and JA accumulation in transgenic plants. Taken together, our results suggest that PRpnp functions by enhancing the endogenous ABA and JA, which interact synergistically and it also inhibits trypsin proteases in the insect gut. Also, like other purine salvage genes, PRpnp also regulates CK metabolism and increases the levels of CK‐free bases in transgenic Mexican lime. We also suggest that PRpnp can be used as a potential candidate to develop new varieties with improved plant vigour and enhanced multiple stress resistance.
Journal Article
Incident reporting and learning in radiation oncology: Need of the hour
Though the radiotherapy equipment manufacturing industry have learnt valuable lessons from the past incidences and have incorporated several redundant safety features in their products, one cannot assure a perfectly safe product. Besides that, human inattentions and mistakes cannot be ruled out. The American Association of Physicists in Medicine (AAPM) has formed a Task Group (TG 100) with a mandate to identify a structured systematic quality assurance program approach that balances patient safety and quality versus resources commonly available and strike a good balance between prescriptiveness and flexibility. [7] Such a system of identifying and learning from errors by developing a nationwide public mandatory reporting system and through voluntary reporting systems is recommended in the four-tiered approach formulated by the Institute of Medicine (IOM) to improve patient safety.
Journal Article
Hierarchical CoMn-LDH and Heterostructured Composites for Advanced Supercapacitors and Electrocatalysis Applications
In the present study, self-assembled hierarchical CoMn-LDH, CoMn@CuZnS, and CoMn@CuZnFeS heterostructured composites were synthesized for bifunctional applications. As an electrode for a supercapacitor, CoMn-LDH demonstrated superior areal and specific capacitance of 5.323 F cm−2 (279.49 mAh/g) at 4 mA cm−2, comparable to or even higher than other LDHs. The assembled AC//CoMn-LDH hybrid supercapacitor device further demonstrated better stability with 63% original capacitance over 20,000 cycles. Later, as a catalyst, CoMn-LDH, CoMn@CuZnS, and CoMn@CuZnFeS electrodes revealed better performance, with overpotentials of 340, 350, and 366 and −199, −215, and −222 mV to attain 10 mA cm−2 of current density for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), respectively. Moreover, for CoMn-LDH, small Tafel slopes of 102 and 128 mV/dec were noticed for OER and HER with good stability compared to heterostructured electrodes.
Journal Article
An Efficient Multispectral Image Classification and Optimization Using Remote Sensing Data
A significant amount of effort and cost is required to collect training samples for remote sensing image classifications. The study of remote sensing and how to read multispectral images is becoming more important. High-dimensional multispectral images are created by the various bands that show how materials behave. The need for more information about things and the improvement of sensor resolutions have led to the creation of multispectral data with a higher size. In recent years, it has been shown that the high dimensionality of these data makes it hard to preprocess them in multiple ways. Recent research has demonstrated that one of the most crucial methods to address this issue is by adopting a variety of learning strategies. But as the data gets more complicated, these methodologies are not adequate to support. The proposed methodology shows that the classification experiment using remote sensing images indicates the maximum likelihood classifier with different deep learning models; weight vector (WV) AdaBoost and ADAM can greatly limit overfitting, and it obtains high classification accuracy. Proposed VGG16 and Inception v3 increase classification accuracy along with optimization process produce 96.08%.
Journal Article