Potable Water Identification with Machine Learning: An Exploration of Water Quality Parameters

In this research, we aim to determine the water potability using three machine learning classification algorithms: decision tree, gradient boosting and bagging classifier. These algorithms were trained and tested on a dataset of water quality measurements. The outcomes of the experiment showed that the gradient boosting algorithm achieved the highest F1-score of 0.78 among all the algorithms. This indicates that the gradient boosting algorithm was most effective in correctly identifying both the safe and contaminated water samples. The results of this study demonstrate that gradient boosting is a promising approach for determining water potability and can be used as a reliable method for water quality assessment

Quivers, YBE and 3-manifolds

We study 4d superconformal indices for a large class of N=1 superconformal quiver gauge theories realized combinatorially as a bipartite graph or a set of "zig-zag paths" on a two-dimensional torus T^2. An exchange of loops, which we call a "double Yang-Baxter move", gives the Seiberg duality of the gauge theory, and the invariance of the index under the duality is translated into the Yang-Baxter-type equation of a spin system defined on a "Z-invariant" lattice on T^2. When we compactify the gauge theory to 3d, Higgs the theory and then compactify further to 2d, the superconformal index reduces to an integral of quantum/classical dilogarithm functions. The saddle point of this integral unexpectedly reproduces the hyperbolic volume of a hyperbolic 3-manifold. The 3-manifold is obtained by gluing hyperbolic ideal polyhedra in H^3, each of which could be thought of as a 3d lift of the faces of the 2d bipartite graph.The same quantity is also related with the thermodynamic limit of the BPS partition function, or equivalently the genus 0 topological string partition function, on a toric Calabi-Yau manifold dual to quiver gauge theories. We also comment on brane realization of our theories. This paper is a companion to another paper summarizing the results.Comment: 61 pages, 16 figures; v2: typos correcte

Analysis and Classification of Breast Cancer Disease Via Different Datasets and Classifier Models

Nowadays, Tumour is one of the important reasons of human death worldwide, producing about 9.6 million people in 2018. BC (breast cancer) is the common reason for cancer deaths in females. BC is a type of cancer that can be treated when detected early. The main motive of this analysis is to detect cancer early in life using ML (machine learning) techniques. The features of the people included in the WDBC (Wisconsin diagnostic breast cancer) and Coimbra BC datasets were classified by SVOF-KNN, KNN, and Naïve Bayes techniques. The pre-processing data phase was applied to the datasets before classification. After the data pre-processing steps, three classification methods were applied to the data. Specificity and Sensitivity rates were used to calculate the success of the techniques. As an outcome of the BC diagnosis classification, the SVOF-KNN technique was found with a 91 percent specificity rate and 90 percent sensitivity rate. When the outcomes attained from feature extraction and selection are calculated. It is seen that feature extraction, selection, and data pre-processing techniques improve the specificity and sensitivity rate of the detection system

Altered Regulation of Contraction-Induced Akt/mTOR/p70S6k Pathway Signaling in Skeletal Muscle of the Obese Zucker Rat

Increased muscle loading results in the phosphorylation of the 70 kDa ribosomal S6 kinase (p70S6k), and this event is strongly correlated with the degree of muscle adaptation following resistance exercise. Whether insulin resistance or the comorbidities associated with this disorder may affect the ability of skeletal muscle to activate p70S6k signaling following an exercise stimulus remains unclear. Here, we compare the contraction-induced activation of p70S6k signaling in the plantaris muscles of lean and insulin resistant obese Zucker rats following a single bout of increased contractile loading. Compared to lean animals, the basal phosphorylation of p70S6k (Thr389; 37.2% and Thr421/Ser424; 101.4%), Akt (Thr308; 25.1%), and mTOR (Ser2448; 63.0%) was higher in obese animals. Contraction increased the phosphorylation of p70S6k (Thr389), Akt (Ser473), and mTOR (Ser2448) in both models however the magnitude and kinetics of activation differed between models. These results suggest that contraction-induced activation of p70S6k signaling is altered in the muscle of the insulin resistant obese Zucker rat

Fivebranes and 4-manifolds

We describe rules for building 2d theories labeled by 4-manifolds. Using the proposed dictionary between building blocks of 4-manifolds and 2d N=(0,2) theories, we obtain a number of results, which include new 3d N=2 theories T[M_3] associated with rational homology spheres and new results for Vafa-Witten partition functions on 4-manifolds. In particular, we point out that the gluing measure for the latter is precisely the superconformal index of 2d (0,2) vector multiplet and relate the basic building blocks with coset branching functions. We also offer a new look at the fusion of defect lines / walls, and a physical interpretation of the 4d and 3d Kirby calculus as dualities of 2d N=(0,2) theories and 3d N=2 theories, respectivelyComment: 81 pages, 18 figures. v2: misprints corrected, clarifications and references added. v3: additions and corrections about lens space theory, 4-manifold gluing, smooth structure

Application of Poly(amidoamine) Dendrimers for Use in Bionanomotor Systems

The study and utilization of bionanomotors represents a rapid and progressing field of nanobiotechnology. Here, we demonstrate that poly(amidoamine) (PAMAM) dendrimers are capable of supporting heavy meromyosin dependent actin motility of similar quality to that observed using nitrocellulose, and that microcontact printing of PAMAM dendrimers can be exploited to produce tracks of active myosin motors leading to the restricted motion of actin filaments across a patterned surface. These data suggest that the use of dendrimer surfaces will increase the applicability of using protein biomolecular motors for nanotechnological applications

Quivers, words and fundamentals

40 pages + Appendices, 9 figures40 pages + Appendices, 9 figure

Aging-Associated Dysfunction of Akt/Protein Kinase B: S-Nitrosylation and Acetaminophen Intervention

Background: Aged skeletal muscle is characterized by an increased incidence of metabolic and functional disorders, which if allowed to proceed unchecked can lead to increased morbidity and mortality. The mechanism(s) underlying the development of these disorders in aging skeletal muscle are not well understood. Protein kinase B (Akt/PKB) is an important regulator of cellular metabolism and survival, but it is unclear if aged muscle exhibits alterations in Akt function. Here we report a novel dysfunction of Akt in aging muscle, which may relate to S-nitrosylation and can be prevented by acetaminophen intervention. Principal Findings: Compared to 6- and 27-month rats, the phosphorylation of Akt (Ser473 and Thr308) was higher in soleus muscles of very aged rats (33-months). Paradoxically, these increases in Akt phosphorylation were associated with diminished mammalian target of rapamycin (mTOR) phosphorylation, along with decreased levels of insulin receptor beta (IR-b), phosphoinositide 3-kinase (PI3K), phosphatase and tensin homolog deleted on chromosome 10 (PTEN) and phosphorylation of phosphoinositide-dependent kinase-1 (PDK1) (Ser241). In vitro Akt kinase measurements and ex vivo muscle incubation experiments demonstrated age-related impairments of Akt kinase activity, which were associated with increases in Akt S-nitrosylation and inducible nitric oxide synthase (iNOS). Impairments in Akt function occurred parallel to increases in myocyte apoptosis and decreases in myocyte size and the expression of myosin and actin. These age-related disorders were attenuated by treating aged (27-month) animals with acetaminophen (30 mg/kg body weight/day) for 6- months. Conclusions: These data demonstrate that Akt dysfunction and increased S-nitrosylation of Akt may contribute to ageassociated disorders in skeletal muscle and that acetaminophen may be efficacious for the treatment of age-related muscle dysfunction

Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice

Dense prediction tasks typically employ encoder-decoder architectures, but the prevalent convolutions in the decoder are not image-adaptive and can lead to boundary artifacts. Different generalized convolution operations have been introduced to counteract this. We go beyond these by leveraging guidance data to redefine their inherent notion of proximity. Our proposed network layer builds on the permutohedral lattice, which performs sparse convolutions in a high-dimensional space allowing for powerful non-local operations despite small filters. Multiple features with different characteristics span this permutohedral space. In contrast to prior work, we learn these features in a task-specific manner by generalizing the basic permutohedral operations to learnt feature representations. As the resulting objective is complex, a carefully designed framework and learning procedure are introduced, yielding rich feature embeddings in practice. We demonstrate the general applicability of our approach in different joint upsampling tasks. When adding our network layer to state-of-the-art networks for optical flow and semantic segmentation, boundary artifacts are removed and the accuracy is improved.Comment: To appear at GCPR 201