Bounded PCA based Multi Sensor Image Fusion Employing Curvelet Transform Coefficients

The fusion of thermal and visible images acts as an important device for target detection. The quality of the spectral content of the fused image improves with wavelet-based image fusion. However, compared to PCA-based fusion, most wavelet-based methods provide results with a lower spatial resolution. The outcome gets better when the two approaches are combined, but they may still be refined. Compared to wavelets, the curvelet transforms more accurately depict the edges in the image. Enhancing the edges is a smart way to improve spatial resolution and the edges are crucial for interpreting the images. The fusion technique that utilizes curvelets enables the provision of additional data in both spectral and spatial areas concurrently. In this paper, we employ an amalgamation of Curvelet Transform and a Bounded PCA (CTBPCA) method to fuse thermal and visible images. To evidence the enhanced efficiency of our proposed technique, multiple evaluation metrics and comparisons with existing image merging methods are employed. Our approach outperforms others in both qualitative and quantitative analysis, except for runtime performance. Future Enhancement-The study will be based on using the fused image for target recognition. Future work should also focus on this method’s continued improvement and optimization for real-time video processing

The Confidence-Competence Gap in Large Language Models: A Cognitive Study

Large Language Models (LLMs) have acquired ubiquitous attention for their performances across diverse domains. Our study here searches through LLMs' cognitive abilities and confidence dynamics. We dive deep into understanding the alignment between their self-assessed confidence and actual performance. We exploit these models with diverse sets of questionnaires and real-world scenarios and extract how LLMs exhibit confidence in their responses. Our findings reveal intriguing instances where models demonstrate high confidence even when they answer incorrectly. This is reminiscent of the Dunning-Kruger effect observed in human psychology. In contrast, there are cases where models exhibit low confidence with correct answers revealing potential underestimation biases. Our results underscore the need for a deeper understanding of their cognitive processes. By examining the nuances of LLMs' self-assessment mechanism, this investigation provides noteworthy revelations that serve to advance the functionalities and broaden the potential applications of these formidable language models.Comment: 19 pages, 8 Figures, to be published in a journal (Journal TBD), All Authors contributed equally and were Supervised by Chandra Dhaka

Origin of depressed fill factor in organic solar cells due to S-shape current-voltage characteristics

Often, a depressed fill factor is observed in organic solar cells (OSCs), which is usually known as S-shaped current-voltage (J-V) characteristics. To investigate the origin of the depressed fill factor further, a poly[N-9-heptadecanyl-2,7-carbazole-alt-5,5-(4,7-di-2-thienyl-2,1,3-benzothiadiazole)]:[6,6]-phenyl C71 butyric acid methyl ester based OSC has been characterized through impedance spectroscopy. In addition, the photocurrent vs the applied effective bias plot reveals that the S-shaped J-V characteristics primarily reduce the diffusion current of the device. The present study shows that the diffusion current dominated section of photocurrent reduces with a slope of 2 in the depressed fill factor section given that the slope may further increase as per the impact of the S-shape. The reduction in the diffusion constant (D-n) in the S-shaped region supports the decrease in the diffusion current, which is observed through the photocurrent analysis. It is observed that, in the S-shaped section of the current-voltage characteristics, the transport time for free carriers increases up to 443 mu s. The larger Urbach energy for the active layer of an S-shaped device demonstrates higher subbandgap disorder. Therefore, it is concluded that the accumulation of the charge carriers within the device and disorder in the active layer leads to the S-shaped current-voltage characteristics as well as poor carrier extraction

Epigenetics in depression and gut-brain axis: A molecular crosstalk

Gut-brain axis is a dynamic, complex, and bidirectional communication network between the gut and brain. Changes in the microbiota-gut-brain axis are responsible for developing various metabolic, neurodegenerative, and neuropsychiatric disorders. According to clinical and preclinical findings, the gut microbiota is a significant regulator of the gut-brain axis. In addition to interacting with intestinal cells and the enteric nervous system, it has been discovered that microbes in the gut can modify the central nervous system through metabolic and neuroendocrine pathways. The metabolites of the gut microbiome can modulate a number of diseases by inducing epigenetic alteration through DNA methylation, histone modification, and non-coding RNA-associated gene silencing. Short-chain fatty acids, especially butyrate, are well-known histone deacetylases inhibitors. Similarly, other microbial metabolites such as folate, choline, and trimethylamine-N-oxide also regulate epigenetics mechanisms. Furthermore, various studies have revealed the potential role of microbiome dysbiosis and epigenetics in the pathophysiology of depression. Hence, in this review, we have highlighted the role of gut dysbiosis in epigenetic regulation, causal interaction between host epigenetic modification and the gut microbiome in depression and suggest microbiome and epigenome as a possible target for diagnosis, prevention, and treatment of depression

Developing Standard Treatment Workflows—way to universal healthcare in India

Primary healthcare caters to nearly 70% of the population in India and provides treatment for approximately 80–90% of common conditions. To achieve universal health coverage (UHC), the Indian healthcare system is gearing up by initiating several schemes such as National Health Protection Scheme, Ayushman Bharat, Nutrition Supplementation Schemes, and Inderdhanush Schemes. The healthcare delivery system is facing challenges such as irrational use of medicines, over- and under-diagnosis, high out-of-pocket expenditure, lack of targeted attention to preventive and promotive health services, and poor referral mechanisms. Healthcare providers are unable to keep pace with the volume of growing new scientific evidence and rising healthcare costs as the literature is not published at the same pace. In addition, there is a lack of common standard treatment guidelines, workflows, and reference manuals from the Government of India. Indian Council of Medical Research in collaboration with the National Health Authority, Govt. of India, and the WHO India country office has developed Standard Treatment Workflows (STWs) with the objective to be utilized at various levels of healthcare starting from primary to tertiary level care. A systematic approach was adopted to formulate the STWs. An advisory committee was constituted for planning and oversight of the process. Specialty experts' group for each specialty comprised of clinicians working at government and private medical colleges and hospitals. The expert groups prioritized the topics through extensive literature searches and meeting with different stakeholders. Then, the contents of each STW were finalized in the form of single-pager infographics. These STWs were further reviewed by an editorial committee before publication. Presently, 125 STWs pertaining to 23 specialties have been developed. It needs to be ensured that STWs are implemented effectively at all levels and ensure quality healthcare at an affordable cost as part of UHC

Fungal diversity notes 929–1035: taxonomic and phylogenetic contributions on genera and species of fungi

This article is the ninth in the series of Fungal Diversity Notes, where 107 taxa distributed in three phyla, nine classes, 31 orders and 57 families are described and illustrated. Taxa described in the present study include 12 new genera, 74 new species, three new combinations, two reference specimens, a re-circumscription of the epitype, and 15 records of sexualasexual morph connections, new hosts and new geographical distributions. Twelve new genera comprise Brunneofusispora, Brunneomurispora, Liua, Lonicericola, Neoeutypella, Paratrimmatostroma, Parazalerion, Proliferophorum, Pseudoastrosphaeriellopsis, Septomelanconiella, Velebitea and Vicosamyces. Seventy-four new species are Agaricus memnonius, A. langensis, Aleurodiscus patagonicus, Amanita flavoalba, A. subtropicana, Amphisphaeria mangrovei, Baorangia major, Bartalinia kunmingensis, Brunneofusispora sinensis, Brunneomurispora lonicerae, Capronia camelliaeyunnanensis, Clavulina thindii, Coniochaeta simbalensis, Conlarium thailandense, Coprinus trigonosporus, Liua muriformis, Cyphellophora filicis, Cytospora ulmicola, Dacrymyces invisibilis, Dictyocheirospora metroxylonis, Distoseptispora thysanolaenae, Emericellopsis koreana, Galiicola baoshanensis, Hygrocybe lucida, Hypoxylon teeravasati, Hyweljonesia indica, Keissleriella caraganae, Lactarius olivaceopallidus, Lactifluus midnapurensis, Lembosia brigadeirensis, Leptosphaeria urticae, Lonicericola hyaloseptispora, Lophiotrema mucilaginosis, Marasmiellus bicoloripes, Marasmius indojasminodorus, Micropeltis phetchaburiensis, Mucor orantomantidis, Murilentithecium lonicerae, Neobambusicola brunnea, Neoeutypella baoshanensis, Neoroussoella heveae, Neosetophoma lonicerae, Ophiobolus malleolus, Parabambusicola thysanolaenae, Paratrimmatostroma kunmingensis, Parazalerion indica, Penicillium dokdoense, Peroneutypa mangrovei, Phaeosphaeria cycadis, Phanerochaete australosanguinea, Plectosphaerella kunmingensis, Plenodomus artemisiae, P. lijiangensis, Proliferophorum thailandicum, Pseudoastrosphaeriellopsis kaveriana, Pseudohelicomyces menglunicus, Pseudoplagiostoma mangiferae, Robillarda mangiferae, Roussoella elaeicola, Russula choptae, R. uttarakhandia, Septomelanconiella thailandica, Spencermartinsia acericola, Sphaerellopsis isthmospora, Thozetella lithocarpi, Trechispora echinospora, Tremellochaete atlantica, Trichoderma koreanum, T. pinicola, T. rugulosum, Velebitea chrysotexta, Vicosamyces venturisporus, Wojnowiciella kunmingensis and Zopfiella indica. Three new combinations are Baorangia rufomaculata, Lanmaoa pallidorosea and Wojnowiciella rosicola. The reference specimens of Canalisporium kenyense and Tamsiniella labiosa are designated. The epitype of Sarcopeziza sicula is re-circumscribed based on cyto- and histochemical analyses. The sexual-asexual morph connection of Plenodomus sinensis is reported from ferns and Cirsium for the first time. In addition, the new host records and country records are Amanita altipes, A. melleialba, Amarenomyces dactylidis, Chaetosphaeria panamensis, Coniella vitis, Coprinopsis kubickae, Dothiorella sarmentorum, Leptobacillium leptobactrum var. calidus, Muyocopron lithocarpi, Neoroussoella solani, Periconia cortaderiae, Phragmocamarosporium hederae, Sphaerellopsis paraphysata and Sphaeropsis eucalypticola

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

S. Ramanujan – The Keats of Mathematics

24-29Here’s a look at the life of a genius, extremely short though it was

Evaluation of the Risk of Drug Addiction with the Help of Fuzzy Sets

The primary focus of this paper is to present a general view of the current applications of fuzzy logic in medical analogy of consumption of drugs. The paper also deals with the origin, structure and composition of fuzzy sets. We particularly review the medical literature using fuzzy logic. Fuzzy set theory can be considered as a suitable formalism to deal with the imprecision intrinsic to many real world problems. Fuzzy set theory provides an appropriate framework for the representation of vague medical concepts and imprecise modes of reasoning. We present two concrete illustrations to investigate the impact of the risk related to drug addictions, like smoking and alcohol drinking and thereby highlighting the social problem related to health