An Efficient Model for Forest Fire Detection using Deep Convolutional Neural Networks

Forest fires are a significant natural disaster that causes extensive damage to both human and wildlife habitats. Early detection and management of forest fires are critical in preventing potential losses. In recent years, deep learning-based approaches have emerged as promising solutions for forest fire detection. This paper proposes a deep learning-based approach for forest fire detection using SqueezeNet model.The proposed approach utilizes still images captured from forest areas under different weather conditions to classify whether an image contains a fire or not. The models were trained and tested using accuracy, precision, and recall metrics. The experimental results show that SqueezeNet achieve high precision, and recall in detecting forest fires.SqueezeNet is a Convolutional Neural Networks (CNN) architecture designed to reduce the number of parameters and computations required in a deep learning model while maintaining high accuracy in image classification tasks.

A novel seed plants gene regulates oxidative stress tolerance in arabidopsis thaliana

Oxidative stress can lead to plant growth retardation, yield loss, and death. The atr7 mutant of Arabidopsis thaliana exhibits pronounced tolerance to oxidative stress. Using positional cloning, confirmed by knockout and RNA interference (RNAi) lines, we identified the atr7 mutation and revealed that ATR7 is a previously uncharacterized gene with orthologs in other seed plants but with no homology to genes in lower plants, fungi or animals. Expression of ATR7-GFP fusion shows that ATR7 is a nuclear-localized protein. RNA-seq analysis reveals that transcript levels of genes encoding abiotic- and oxidative stress-related transcription factors (DREB19, HSFA2, ZAT10), chromatin remodelers (CHR34), and unknown or uncharacterized proteins (AT5G59390, AT1G30170, AT1G21520) are elevated in atr7. This indicates that atr7 is primed for an upcoming oxidative stress via pathways involving genes of unknown functions. Collectively, the data reveal ATR7 as a novel seed plants-specific nuclear regulator of oxidative stress response

A novel seed plants gene regulates oxidative stress tolerance in arabidopsis thaliana

Oxidative stress can lead to plant growth retardation, yield loss, and death. The atr7 mutant of Arabidopsis thaliana exhibits pronounced tolerance to oxidative stress. Using positional cloning, confirmed by knockout and RNA interference (RNAi) lines, we identified the atr7 mutation and revealed that ATR7 is a previously uncharacterized gene with orthologs in other seed plants but with no homology to genes in lower plants, fungi or animals. Expression of ATR7-GFP fusion shows that ATR7 is a nuclear-localized protein. RNA-seq analysis reveals that transcript levels of genes encoding abiotic- and oxidative stress-related transcription factors (DREB19, HSFA2, ZAT10), chromatin remodelers (CHR34), and unknown or uncharacterized proteins (AT5G59390, AT1G30170, AT1G21520) are elevated in atr7. This indicates that atr7 is primed for an upcoming oxidative stress via pathways involving genes of unknown functions. Collectively, the data reveal ATR7 as a novel seed plants-specific nuclear regulator of oxidative stress response

Persistent left superior vena cava: a case report and review of literature

Persistent left superior vena cava is rare but important congenital vascular anomaly. It results when the left superior cardinal vein caudal to the innominate vein fails to regress. It is most commonly observed in isolation but can be associated with other cardiovascular abnormalities including atrial septal defect, bicuspid aortic valve, coarctation of aorta, coronary sinus ostial atresia, and cor triatriatum. The presence of PLSVC can render access to the right side of heart challenging via the left subclavian approach, which is a common site of access utilized when placing pacemakers and Swan-Ganz catheters. Incidental notation of a dilated coronary sinus on echocardiography should raise the suspicion of PLSVC. The diagnosis should be confirmed by saline contrast echocardiography

A novel seed plants gene regulates oxidative stress tolerance in arabidopsis thaliana

Oxidative stress can lead to plant growth retardation, yield loss, and death. The atr7 mutant of Arabidopsis thaliana exhibits pronounced tolerance to oxidative stress. Using positional cloning, confirmed by knockout and RNA interference (RNAi) lines, we identified the atr7 mutation and revealed that ATR7 is a previously uncharacterized gene with orthologs in other seed plants but with no homology to genes in lower plants, fungi or animals. Expression of ATR7-GFP fusion shows that ATR7 is a nuclear-localized protein. RNA-seq analysis reveals that transcript levels of genes encoding abiotic- and oxidative stress-related transcription factors (DREB19, HSFA2, ZAT10), chromatin remodelers (CHR34), and unknown or uncharacterized proteins (AT5G59390, AT1G30170, AT1G21520) are elevated in atr7. This indicates that atr7 is primed for an upcoming oxidative stress via pathways involving genes of unknown functions. Collectively, the data reveal ATR7 as a novel seed plants-specific nuclear regulator of oxidative stress response

LMS-Verify: abstraction without regret for verified systems programming

Performance critical software is almost always developed in C, as programmers do not trust high-level languages to deliver the same reliable performance. This is bad because low-level code in unsafe languages attracts security vulnerabilities and because development is far less productive, with PL advances mostly lost on programmers operating under tight performance constraints. High-level languages provide memory safety out of the box, but they are deemed too slow and unpredictable for serious system software. Recent years have seen a surge in staging and generative programming: the key idea is to use high-level languages and their abstraction power as glorified macro systems to compose code fragments in first-order, potentially domain-specific, intermediate languages, from which fast C can be emitted. But what about security? Since the end result is still C code, the safety guarantees of the high-level host language are lost. In this paper, we extend this generative approach to emit ACSL specifications along with C code. We demonstrate that staging achieves ``abstraction without regret'' for verification: we show how high-level programming models, in particular higher-order composable contracts from dynamic languages, can be used at generation time to compose and generate first-order specifications that can be statically checked by existing tools. We also show how type classes can automatically attach invariants to data types, reducing the need for repetitive manual annotations. We evaluate our system on several case studies that varyingly exercise verification of memory safety, overflow safety, and functional correctness. We feature an HTTP parser that is (1) fast (2) high-level: implemented using staged parser combinators (3) secure: with verified memory safety. This result is significant, as input parsing is a key attack vector, and vulnerabilities related to HTTP parsing have been documented in all widely-used web servers.</jats:p

Ruy Blas : drama lírico en cuatro actos

In this paper we present research on applying a domain specific high-level abstractions (HLA) development strategy with the aim to “future-proof” a key class of high performance computing (HPC) applications that simulate hydrodynamics computations at AWE plc. We build on an existing high-level abstraction framework, OPS, that is being developed for the solution of multi-block structured mesh-based applications at the University of Oxford. OPS uses an “active library” approach where a single application code written using the OPS API can be transformed into different highly optimized parallel implementations which can then be linked against the appropriate parallel library enabling execution on different back-end hardware platforms. The target application in this work is the CloverLeaf mini-app from Sandia National Laboratory’s Mantevo suite of codes that consists of algorithms of interest from hydrodynamics workloads. Specifically, we present (1) the lessons learnt in re-engineering an industrial representative hydro-dynamics application to utilize the OPS high-level framework and subsequent code generation to obtain a range of parallel implementations, and (2) the performance of the auto-generated OPS versions of CloverLeaf compared to that of the performance of the hand-coded original CloverLeaf implementations on a range of platforms. Benchmarked systems include Intel multi-core CPUs and NVIDIA GPUs, the Archer (Cray XC30) CPU cluster and the Titan (Cray XK7) GPU cluster with different parallelizations (OpenMP, OpenACC, CUDA, OpenCL and MPI). Our results show that the development of parallel HPC applications using a high-level framework such as OPS is no more time consuming nor difficult than writing a one-off parallel program targeting only a single parallel implementation. However the OPS strategy pays off with a highly maintainable single application source, through which multiple parallelizations can be realized, without compromising performance portability on a range of parallel systems

An Ascophyllum nodosum-Derived Biostimulant Protects Model and Crop Plants from Oxidative Stress

Abiotic stresses, which at the molecular level leads to oxidative damage, are major determinants of crop yield loss worldwide. Therefore, considerable efforts are directed towards developing strategies for their limitation and mitigation. Here the superoxide-inducing agent paraquat (PQ) was used to induce oxidative stress in the model species Arabidopsis thaliana and the crops tomato and pepper. Pre-treatment with the biostimulant SuperFifty (SF) effectively and universally suppressed PQ-induced leaf lesions, H2O2 build up, cell destruction and photosynthesis inhibition. To further investigate the stress responses and SF-induced protection at the molecular level, we investigated the metabolites by GC-MS metabolomics. PQ induced specific metabolic changes such as accumulation of free amino acids (AA) and stress metabolites. These changes were fully prevented by the SF pre-treatment. Moreover, the metabolic changes of the specific groups were tightly correlating with their phenotypic characteristics. Overall, this study presents physiological and metabolomics data which shows that SF protects against oxidative stress in all three plant species