Active Foundational Models for Fault Diagnosis of Electrical Motors

Fault detection and diagnosis of electrical motors are of utmost importance in ensuring the safe and reliable operation of several industrial systems. Detection and diagnosis of faults at the incipient stage allows corrective actions to be taken in order to reduce the severity of faults. The existing data-driven deep learning approaches for machine fault diagnosis rely extensively on huge amounts of labeled samples, where annotations are expensive and time-consuming. However, a major portion of unlabeled condition monitoring data is not exploited in the training process. To overcome this limitation, we propose a foundational model-based Active Learning framework that utilizes less amount of labeled samples, which are most informative and harnesses a large amount of available unlabeled data by effectively combining Active Learning and Contrastive Self-Supervised Learning techniques. It consists of a transformer network-based backbone model trained using an advanced nearest-neighbor contrastive self-supervised learning method. This approach empowers the backbone to learn improved representations of samples derived from raw, unlabeled vibration data. Subsequently, the backbone can undergo fine-tuning to address a range of downstream tasks, both within the same machines and across different machines. The effectiveness of the proposed methodology has been assessed through the fine-tuning of the backbone for multiple target tasks using three distinct machine-bearing fault datasets. The experimental evaluation demonstrates a superior performance as compared to existing state-of-the-art fault diagnosis methods with less amount of labeled data.Comment: 30 pages, 2 figures, 7 table

A contemporary review on drought modeling using machine learning approaches

Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to predict the weather, especially the minimum temperature using backpropagation algorithms. The favourite ML techniques for weather forecasting include singular vector machines (SVM), support vector regression, random forest, decision tree, logistic regression, Naive Bayes, linear regression, gradient boosting tree, k-nearest neighbours (KNN), the adaptive neuro-fuzzy inference system, the feed-forward neural networks, Markovian chain, Bayesian network, hidden Markov models, and autoregressive moving averages, evolutionary algorithms, deep learning and many more. This paper presents a recent review of the literature using ML in drought prediction, the drought indices, dataset, and performance metrics

Studies on an alkali-thermostable xylanase from Aspergillus fumigatus MA28

An alkalitolerant fungus, Aspergillus fumigatus strain MA28 produced significant amounts of cellulase-free xylanase when grown on a variety of agro-wastes. Wheat bran as the sole carbon source supported higher xylanase production (8,450 U/L) than xylan (7,500 U/L). Soybean meal was observed to be the best nitrogen source for xylanase production (9,000 U/L). Optimum medium pH for xylanase production was 8 (9,800 U/L), though, significant quantities of the enzyme was also produced at pH 7 (8,500 U/L), 9 (8,200 U/L) and 10 (4,600 U/L). The xylanase was purified by ammonium sulphate precipitation and carboxymethyl cellulose chromatography, and was found to have a molecular weight of 14.4 kDa with a Vmax of 980 μmol/min/mg of protein and a Km of approximately 4.9 mg/mL. The optimum temperature and pH for enzyme activity was 50 °C and pH 8, respectively. However, the enzyme also showed substantial residual activity at 60–70 °C (53–75%) and at alkaline pH 8–9 (56–88%)

Molecular Evolution of Aminoacyl tRNA Synthetase Proteins in the Early History of Life

Aminoacyl-tRNA synthetases (aaRS) consist of several families of functionally conserved proteins essential for translation and protein synthesis. Like nearly all components of the translation machinery, most aaRS families are universally distributed across cellular life, being inherited from the time of the Last Universal Common Ancestor (LUCA). However, unlike the rest of the translation machinery, aaRS have undergone numerous ancient horizontal gene transfers, with several independent events detected between domains, and some possibly involving lineages diverging before the time of LUCA. These transfers reveal the complexity of molecular evolution at this early time, and the chimeric nature of genomes within cells that gave rise to the major domains. Additionally, given the role of these protein families in defining the amino acids used for protein synthesis, sequence reconstruction of their pre-LUCA ancestors can reveal the evolutionary processes at work in the origin of the genetic code. In particular, sequence reconstructions of the paralog ancestors of isoleucyl- and valyl- RS provide strong empirical evidence that at least for this divergence, the genetic code did not co-evolve with the aaRSs; rather, both amino acids were already part of the genetic code before their cognate aaRSs diverged from their common ancestor. The implications of this observation for the early evolution of RNA-directed protein biosynthesis are discussed.National Science Foundation (U.S.) (Grant DEB 0830024)National Science Foundation (U.S.) (Grant DEB 0936234)United States. National Aeronautics and Space Administration (NASA Postdoctoral Fellowship

Ancient horizontal gene transfer and the last common ancestors

Background The genomic history of prokaryotic organismal lineages is marked by extensive horizontal gene transfer (HGT) between groups of organisms at all taxonomic levels. These HGT events have played an essential role in the origin and distribution of biological innovations. Analyses of ancient gene families show that HGT existed in the distant past, even at the time of the organismal last universal common ancestor (LUCA). Most gene transfers originated in lineages that have since gone extinct. Therefore, one cannot assume that the last common ancestors of each gene were all present in the same cell representing the cellular ancestor of all extant life. Results Organisms existing as part of a diverse ecosystem at the time of LUCA likely shared genetic material between lineages. If these other lineages persisted for some time, HGT with the descendants of LUCA could have continued into the bacterial and archaeal lineages. Phylogenetic analyses of aminoacyl-tRNA synthetase protein families support the hypothesis that the molecular common ancestors of the most ancient gene families did not all coincide in space and time. This is most apparent in the evolutionary histories of seryl-tRNA synthetase and threonyl-tRNA synthetase protein families, each containing highly divergent “rare” forms, as well as the sparse phylogenetic distributions of pyrrolysyl-tRNA synthetase, and the bacterial heterodimeric form of glycyl-tRNA synthetase. These topologies and phyletic distributions are consistent with horizontal transfers from ancient, likely extinct branches of the tree of life. Conclusions Of all the organisms that may have existed at the time of LUCA, by definition only one lineage is survived by known progeny; however, this lineage retains a genomic record of heterogeneous genetic origins. The evolutionary histories of aminoacyl-tRNA synthetases (aaRS) are especially informative in detecting this signal, as they perform primordial biological functions, have undergone several ancient HGT events, and contain many sites with low substitution rates allowing deep phylogenetic reconstruction. We conclude that some aaRS families contain groups that diverge before LUCA. We propose that these ancient gene variants be described by the term “hypnologs”, reflecting their ancient, reticulate origin from a time in life history that has been all but erased”.National Science Foundation (U.S.) (Grant DEB 0830024)Exobiology Program (U.S.) (Grant NNX10AR85G)United States. National Aeronautics and Space Administration (Postdoctoral Program

Functional correlates of Apolipoprotein E genotype in Frontotemporal Lobar Degeneration

BACKGROUND: It has been recently demonstrated that in Frontotemporal Lobar Degeneration (FTLD) memory deficits at presentation are commoner than previously thought. Apolipoprotein E (ApoE) genotype, the major genetic risk factor in sporadic late-onset Alzheimer Disease (AD), modulates cerebral perfusion in late middle-age cognitively normal subjects. ApoE ε4 homozygous have reduced glucose metabolism in the same regions involved in AD. The aim of this study was to determine whether ApoE genotype might play a key-role in influencing the cerebral functional pattern as well as the degree of memory deficits in FTLD patients. METHODS: Fifty-two unrelated FTLD patients entered the study and underwent a somatic and neurological evaluation, laboratory examinations, a brain structural imaging study, and a brain functional Single Photon Emission Tomography study. ApoE genotype was determined. RESULTS: ApoE genotype influenced both clinical and functional features in FTLD. ApoE ε4-carriers were more impaired in long-term memory function (ApoE ε4 vs. ApoE non ε4, 6.3 ± 3.9 vs. 10.1 ± 4.2, p = 0.004) and more hypoperfused in uncus and parahippocampal regions (x,y,z = 38,-6,-20, T = 2.82, cluster size = 100 voxels; -32,-12,-28, T= 2.77, cluster size = 40 voxels). CONCLUSION: The present findings support the view that ApoE genotype might be considered a disease-modifying factor in FTLD, thus contributing to define a specific clinical presentation, and might be of relevance for pharmacological approaches

Non-monotonicity on a spatio-temporally defined cyclic task: evidence of two movement types?

We tested 23 healthy participants who performed rhythmic horizontal movements of the elbow. The required amplitude and frequency ranges of the movements were specified to the participants using a closed shape on a phase-plane display, showing angular velocity versus angular position, such that participants had to continuously control both the speed and the displacement of their forearm. We found that the combined accuracy in velocity and position throughout the movement was not a monotonic function of movement speed. Our findings suggest that specific combinations of required movement frequency and amplitude give rise to two distinct types of movements: one of a more rhythmic nature, and the other of a more discrete nature

A Critical Assessment of the Effects of Bt Transgenic Plants on Parasitoids

The ecological safety of transgenic insecticidal plants expressing crystal proteins (Cry toxins) from the bacterium Bacillus thuringiensis (Bt) continues to be debated. Much of the debate has focused on nontarget organisms, especially predators and parasitoids that help control populations of pest insects in many crops. Although many studies have been conducted on predators, few reports have examined parasitoids but some of them have reported negative impacts. None of the previous reports were able to clearly characterize the cause of the negative impact. In order to provide a critical assessment, we used a novel paradigm consisting of a strain of the insect pest, Plutella xylostella (herbivore), resistant to Cry1C and allowed it to feed on Bt plants and then become parasitized by Diadegma insulare, an important endoparasitoid of P. xylostella. Our results indicated that the parasitoid was exposed to a biologically active form of the Cy1C protein while in the host but was not harmed by such exposure. Parallel studies conducted with several commonly used insecticides indicated they significantly reduced parasitism rates on strains of P. xylostella resistant to these insecticides. These results provide the first clear evidence of the lack of hazard to a parasitoid by a Bt plant, compared to traditional insecticides, and describe a test to rigorously evaluate the risks Bt plants pose to predators and parasitoids

Interactions of melatonin with mammalian mitochondria. Reducer of energy capacity and amplifier of permeability transition.

Melatonin, a metabolic product of the amino acid tryptophan, induces a dose-dependent energy drop correlated with a decrease in the oxidative phosphorylation process in isolated rat liver mitochondria. This effect involves a gradual decrease in the respiratory control index and significant alterations in the state 4/state 3 transition of membrane potential (ΔΨ). Melatonin, alone, does not affect the insulating properties of the inner membrane but, in the presence of supraphysiological Ca2+, induces a ΔΨ drop and colloid-osmotic mitochondrial swelling. These events are sensitive to cyclosporin A and the inhibitors of Ca2+ transport, indicative of the induction or amplification of the mitochondrial permeability transition. This phenomenon is triggered by oxidative stress induced by melatonin and Ca2+, with the generation of hydrogen peroxide and the consequent oxidation of sulfydryl groups, glutathione and pyridine nucleotides. In addition, melatonin, again in the presence of Ca2+, can also induce substantial release of cytochrome C and AIF (apoptosis-inducing factor), thus revealing its potential as a pro-apoptotic agent