Abstract

The importance of algorithms and data structures in computer science curricula has been amply recognized.For many students, however, gaining a good understanding of algorithms remains a challenge.Because of the automated nature of sequential algorithms there is an inherent tension in directly applying the ‘learning by doing’ approach. This partly explains the limitations of efforts like algorithm animationand code tracing.Algodynamics, the approach we propose and advocate, situates algorithms within the framework of transi-tion systems and their dynamics and offers an attractive approach for teaching algorithms. Algodynamics starts with the premise that the key ideas underlying an algorithm can be identified and packaged into interactive transition systems. The algorithm when ‘opened up’, reveals a transition system, shorn of most control aspects, enriched instead with interaction. The design of an algorithm can be carried out by constructing a series of interactive systems, progressively trading interactivity with automation. The setransition systems constitute a family of notional machines.We illustrate the algodynamics approach by considering Bubblesort. A sequence of five interactive tran-sition systems culminate in the classic Bubblesort algorithm. The exercise of constructing the individualsystems also pays off when coding Bubblesort: a highly modular implementation whose primitives are bor-rowed from the transition systems. The transition systems used for Bubblesort have been implemented as interactive experiments. These web based implementations are easy to build. The simplicity and flexibility afforded by the algodynamics framework makes it an attractive option to teach algorithms in an interactive way.

Abstract

Rice blast disease is a major threat to rice production worldwide; the causative pathogenic fungus Magnaporthe oryzae induces rice (Oryza sativa) plants to undergo molecular changes that help them to circumvent this fungal attack. Transcriptome studies have demonstrated that many genes are involved in the defense response of rice to M. oryzae, but most of these studies focused on the screening of differentially expressed genes and the studies did not investigate the interactions among genes. We examined the interaction of rice and M. oryzae in a network context. Two near-isogenic lines were profiled at different time-points. Using transcriptome data obtained from an RNASeq analysis, a network based on the relationships among genes was developed through weighted gene co-expression network analysis. The analysis of degree centrality identified numerous hub genes and potential key regulators that control the rice response, providing new insights into the molecular network underlying the resistance of rice to M. oryzae infection. Additionally, a protein-protein interaction network was derived to identify complexes that might physically interact. For example, complexes of OsbHLH148/OsJAZ, OsMYB4 and some components of the phenylpropanoid pathway, as well as MYB/bHLH

Abstract

With increasing computing power, capacity and internet connectivity, the ability to learn has crossed classroom boundaries in the form of online learning. The adoption rate and effectiveness of online learning continues to be an area of research. Collaborative and Cooperative (CoCo) learning involves a joint effort by students to understand and solve problems or tasks. Adoption of open source software has also increased with technology-aided collaboration and cooperation. Leveraging the practices of crowdsourced software development, we propose CoCo Learning approach for technical education using virtual labs. About 145 undergraduate engineering students from various institutes participated in our study for a period of one full semester. About 92% of the students conducted an average of 24 virtual experiments with this approach. Nearly 90% of the faculty from these institutes also confirmed that their students' understanding of courses has improved while delivering tangible software artifacts as outcomes.

Abstract

The Standard Model (SM), when extended with a leptoquark (LQ) and right-handed neutrinos, can have interesting new implications for Higgs physics. We show that sterile neutrinos can induce a boost to the down-type quark Yukawa interactions through a diagonal coupling associated with the quarks and a scalar LQ of electromagnetic charge 1/3. The relative change is moderately larger in the case of the first two generations of quarks, as they have vanishingly small Yukawa couplings in the SM. The enhancement in the couplings would also lead to a non-negligible contribution from the quark fusion process to the production of the 125 GeV Higgs scalar in the SM, though the gluon fusion always dominates. However, this may not be true for a general scalar. As an example, we consider a scenario with a SM-gauge-singlet scalar ϕ where an O (1) coupling between ϕ and the LQ is allowed. The ϕ q q Yukawa …

Abstract

Upon nitrogen starvation, Schizosaccharomyces pombe exit the mitotic cell cycle and become irreversibly committed to the completion of meiosis program. Meiotic cell divisions are coordinated with sporulation events to produce haploid spores. In the last few decades, experiments on fission yeast have revealed different molecular players involved in two meiotic cell divisions, meiosis I (MI) and meiosis II (MII). How the MI entry, MI-to-MII transition, and MII exit occur because of the dynamics of the regulatory network is not well understood. In this work, we developed a comprehensive mathematical model of the network that describes the temporal dynamics of meiotic progression. The model accounts for the phenotypes of several experimental data (single and multiple mutations). We demonstrate the control strategy involving multiple feedback loops to yield two successive division cycles. The differential regulation of …

Abstract

Patterns of DNA methylation are significantly altered in cancers. Interpreting the functional consequences of DNA methylation requires the integration of multiple forms of data. The recent advancement in the next-generation sequencing can help to decode this relationship and in biomarker discovery. In this study, we investigated the methylation patterns of papillary renal cell carcinoma (PRCC) and its relationship with the gene expression using The Cancer Genome Atlas (TCGA) multi-omics data. We found that the promoter and body of tumor suppressor genes, microRNAs and gene clusters and families, including cadherins, protocadherins, claudins and collagens, are hypermethylated in PRCC. Hypomethylated genes in PRCC are associated with the immune function. The gene expression of several novel candidate genes, including interleukin receptor IL17RE and immune checkpoint genes HHLA2, SIRPA and …

Abstract

The homodimeric catabolite activator protein (CAP) regulates the transcription of several bacterial genes based on the cellular concentration of cyclic adenosine monophosphate (cAMP). The binding of cAMP to CAP triggers allosteric communication between the cAMP binding domains (CBD) and DNA binding domains (DBD) of CAP, which entails repositioning of DNA recognition helices (F-helices) in the DBD to dock favorably to the target DNA. Despite considerable progress, much remains to be understood about the mechanistic details of DNA recognition by CAP and about the map of allosteric pathways involved in CAP-mediated gene transcription. The present study uses molecular dynamics and umbrella sampling simulations to investigate the mechanism of cAMP- and DNA-induced changes in the conformation and energetics of F-helices observed during the allosteric regulation of CAP by cAMP and the …

Abstract

Aqueous urea stabilizes the unfolded states of protein due to their ability to solvate both hydrophilic and hydrophobic residues favorably. The nature of interactions that stabilize different types of amino acid side chains in their solvent exposed state is still not understood. To gain insights into the molecular level details of urea interactions with proteins in their unfolded states, we have performed atomistic molecular dynamics simulations and free energy calculations using the thermodynamic integration method on model systems representing side chains of all amino acids in different solvent environments (water and varying concentrations of aqueous urea). A systematic analysis of structural, energetic and dynamic parameters has been done to understand the detailed atomistic mechanism. The main aim of the current study is to unravel the nature of urea-amino acid interactions by emphasizing on the chemical nature …

Abstract

In many real-life classification problems, we may not get exact class labels for training samples. One such example is bandit feedback in multiclass classification. In this setting, we only get to know whether our predicted label is correct or not. Due to which, we are left in uncertainty about the actual class label when we predict the wrong class. This paper proposes exact passive-aggressive online algorithms for multiclass classification under bandit feedback (EPABF). The proposed approach uses an exploration-exploitation strategy to guess the class label in every trial. To update the weights, we solve a quadratic optimization problem under multiple class separability constraints and find the exact solution. We do this by finding active constraints using the KKT conditions of the optimization problem. These constraints form a support set that determines the classes for which the weight vector needs to be updated. We propose three different variants of the weight update rule, which vary based on the aggressiveness to correct the mistake. These are called EPABF, EPABF-I, and EPABF-II. We also provide mistake bounds for the proposed EPABF, EPABF-I, and EPABF-II. Experiments demonstrated that our proposed algorithms perform better than other bandit feedback-based approaches and comparably to the full information approaches.

Abstract

Density functional theory (DFT) based calculations are carried out to study effect of molecular charge on both the binding energy as well as chemical Raman enhancement of deprotonated 4-Mercaptopyridine (ligand) bound to the semiconducting nanocluster, Zn3Se3 and metal substituted nanoclusters, Zn2MSe3 (M: Ag, Cu). Change of molecular charge from 0 to −1 increases binding energy of the ligand for Zn3Se3 cluster and decreases Raman activity of vibrational modes. On the other hand, the ligand bound to the metal substituted nanoclusters, Zn2MSe3 shows minimal decrease in binding energy and a noteworthy enhancement in Raman activity of the vibrational modes, on varying the molecular charge from 0 to −1. Static Raman activities of vibrational modes are analyzed using change of molecular polarizability components with normal coordinates of the modes. An APT (Atomic Polar Tensor) charge based descriptor is used for characterization of the chemical Raman enhancement. The descriptor measures substrate induced charge concentration per unit displacement of an atom involved in a mode of vibration. We also show that significantly enhanced intensity of vibrational modes is associated with atoms of relatively greater magnitudes of the APT charge based descriptor