Reliable predictions for structured and corrupted data

The burgeoning use of machine learning models has spurred the use of diverse datasets that are collated, processed, and analyzed in various manners. To facilitate storage and analysis, data is often stored in a structured format. Structured data is characterized by an organizational structure or specific constraints on certain features. Such implicit or explicit constraints impose extra considerations for building predictive models based on such data, and current methodologies grapple with capturing the complex relationships inherent in the data. Factors like measurement errors, faulty equipment, or adversarial attacks can also result in the corruption of training data, making it challenging to achieve high performance. This thesis presents several approaches that can provide reliable predictions from data in a variety of complex formats while simultaneously ensuring a model’s reliability. First, a probabilistic quantile forecasting framework is introduced to tackle the challenges associated with forecasting large-scale time series that are subject to hierarchical or grouped constraints. This framework reconciles time series across various aggregation levels, taking into account any imposed constraints. It also dynamically amalgamates heterogeneous forecasting models specifically customized for different time series. Additionally, a multilevel clustering approach is proposed to mitigate computational costs associated with a vast number of forecasts. The next set of contributions lies in novel interpretable and robust Machine Learning approaches to ensure that trustworthy inferences are drawn from corrupted data. This includes counterfactual explanations and strategies to guard against outliers and adversarial examples, offering assurances of the monotonic property of neural networks, and devising robust estimations for datasets with missing values. Finally, a conformal prediction method with conditional coverage guarantees in the asymptotic limit is introduced to furnish adaptive and informative prediction intervals for heterogeneous data free of distributional assumptions. Collectively, these contributions bolster our ability to provide reliable predictions for data with complex structures or quality issues. Moreover, they hold vast potential for applications in various sectors, including healthcare and finance.Electrical and Computer Engineerin

Gyrokinetic simulation of pedestal turbulence using GENE

We present here a study based on gyrokinetic simulations (using GENE) to model turbulence in the pedestals on several well-diagnosed shots: two H-modes on DIII-D and one I-mode on Alcator C-Mod. We match frequencies, power balance, and other transport characteristics in multiple channels with the observations. The observed quasi-coherent fluctuations on the DIII-D shots are identified as Micro Tearing Modes (MTM). The MTMs match frequency and power balance (together with heat loss from Electron Temperature Gradient (ETG) driven turbulence), and cause low transport in the particle, ion heat and impurity particle transport channels – consistent with observed inter-ELM evolution of ion and electron temperature, electron and impurity density or transport analysis of those channels. We find the Weakly Coherent Mode on C-Mod I-mode to be an electrostatic Ion Temperature Gradient/Impurity density gradient (ITG/Impurity) driven mode. The ITG/Impurity mode match frequency and the impurity confinement time observed on the I-mode. Electron scale turbulence, ETG, provides energy transport to match power balance. A novel concept called the transport fingerprints is used throughout this work, which greatly assists in identifying the instabilities. This work shows that the concept should be very valuable in many future investigations of pedestal turbulence.Physic

Two-zero Textures of the Majorana Neutrino Mass Matrix and Current Experimental Tests

In view of the latest T2K and MINOS neutrino oscillation data which hint at a relatively large theta_13, we perform a systematic study of the Majorana neutrino mass matrix M_nu with two independent texture zeros. We show that three neutrino masses (m_1, m_2, m_3) and three CP-violating phases (delta, rho, sigma) can fully be determined from two neutrino mass-squared differences (delta m^2, Delta m^2) and three flavor mixing angles (theta_12, theta_23, theta_13). We find that seven patterns of M_nu (i.e., A_{1,2}, B_{1,2,3,4} and C) are compatible with current experimental data at the 3-sigma level, but the parameter space of each pattern is more strictly constrained than before. We demonstrate that the texture zeros of M_nu are stable against the one-loop quantum corrections, and there exists a permutation symmetry between Patterns A_1 and A_2, B_1 and B_2 or B_3 and B_4. Phenomenological implications of M_nu on the neutrinoless double-beta decay and leptonic CP violation are discussed, and a realization of those texture zeros by means of the Z_n flavor symmetries is illustrated.Comment: 41 pages, including 4 tables and 14 figures, more discussions added, to appear in JHE

Big, Fast Vortices in the d-RVB theory of High Temperature Superconductivity

The effect of proximity to a Mott insulating phase on the superflow properties of a d-wave superconductor is studied using the slave boson-U(1) gauge theory model. The model has two limits corresponding to superconductivity emerging either out of a 'renormalized fermi liquid' or out of a non-fermi-liquid regime. Three crucial physical parameters are identified: the size of the vortex \textit{as determined from the supercurrent it induces;} the coupling of the superflow to the quasiparticles and the 'nondissipative time derivative' term. As the Mott phase is approached, the core size as defined from the supercurrent diverges, the coupling between superflow and quasiparticles vanishes, and the magnitude of the nondissipative time derivative dramatically increases. The dissipation due to a moving vortex is found to vary as the third power of the doping. The upper critical field and the size of the critical regime in which paraconductivity may be observed are estimated, and found to be controlled by the supercurrent length scale

Vortices in a Thin Film Superconductor with a Spherical Geometry

We report results from Monte Carlo simulations of a thin film superconductor in a spherical geometry within the lowest Landau level approximation. We observe the absence of a phase transition to a low temperature vortex solid phase with these boundary conditions; the system remains in the vortex liquid phase for all accessible temperatures. The correlation lengths are measured for phase coherence and density modulation. Both lengths display identical temperature dependences, with an asymptotic scaling form consistent with a continuous zero temperature transition. This contrasts with the first order freezing transition which is seen in the alternative quasi-periodic boundary conditions. The high temperature perturbation theory and the ground states of the spherical system suggest that the thermodynamic limit of the spherical geometry is the same as that on the flat plane. We discuss the advantages and drawbacks of simulations with different geometries, and compare with current experimental conclusions. The effect of having a large scale inhomogeneity in the applied field is also considered.Comment: This replacment contains substantial revisions: the new article is twice as long with new and different results on the thermodynamic limit on the sphere plus a full discussion on the alternative boundary conditions used in simulations in the LLL approximation. 19 pages, 12 encapsulated PostScript figures, 1 JPEG figure, uses RevTeX (with epsf

The Interplay Between GUT and Flavour Symmetries in a Pati-Salam x S4 Model

Both Grand Unified symmetries and discrete flavour symmetries are appealing ways to describe apparent structures in the gauge and flavour sectors of the Standard Model. Both symmetries put constraints on the high energy behaviour of the theory. This can give rise to unexpected interplay when building models that possess both symmetries. We investigate on the possibility to combine a Pati-Salam model with the discrete flavour symmetry $S_4$ that gives rise to quark-lepton complementarity. Under appropriate assumptions at the GUT scale, the model reproduces fermion masses and mixings both in the quark and in the lepton sectors. We show that in particular the Higgs sector and the running Yukawa couplings are strongly affected by the combined constraints of the Grand Unified and family symmetries. This in turn reduces the phenomenologically viable parameter space, with high energy mass scales confined to a small region and some parameters in the neutrino sector slightly unnatural. In the allowed regions, we can reproduce the quark masses and the CKM matrix. In the lepton sector, we reproduce the charged lepton masses, including bottom-tau unification and the Georgi-Jarlskog relation as well as the two known angles of the PMNS matrix. The neutrino mass spectrum can present a normal or an inverse hierarchy, and only allowing the neutrino parameters to spread into a range of values between $\lambda^{-2}$ and $\lambda^2$, with $\lambda\simeq0.2$. Finally, our model suggests that the reactor mixing angle is close to its current experimental bound.Comment: 62 pages, 4 figures; references added, version accepted for publication in JHE

Synergistic Effect of Functionalized Nickel Nanoparticles and Quercetin on Inhibition of the SMMC-7721 Cells Proliferation

The effect of functionalized nickel (Ni) nanoparticles capped with positively charged tetraheptylammonium on cellular uptake of drug quercetin into hepatocellular carcinoma cells (SMMC-7721) has been explored in this study via microscopy and electrochemical characterization as well as MTT assay. Meanwhile, the influence of Ni nanoparticles and/or quercetin on cell proliferation has been further evaluated by the real-time cell electronic sensing (RT-CES) study. Our observations indicate that Ni nanoparticles could efficiently improve the permeability of cancer cell membrane, and remarkably enhance the accumulation of quercetin in SMMC-7721 cells, suggesting that Ni nanoparticles and quercetin would facilitate the synergistic effect on inhibiting proliferation of cancer cells

Nonzero |Ue3| from charged lepton corrections and the atmospheric neutrino mixing angle

After the successful determination of the reactor neutrino mixing angle \theta_13 ~ 0.16 \neq 0, a new feature suggested by the current neutrino oscillation data is a sizeable deviation of the atmospheric neutrino mixing angle \theta_23 from \pi/4. Using the fact that the neutrino mixing matrix U = U_e^\dagger U_\nu, where U_e and U_\nu result from the diagonalisation of the charged lepton and neutrino mass matrices, and assuming that U_\nu has a i) bimaximal (BM), ii) tri-bimaximal (TBM) form, or else iii) corresponds to the conservation of the lepton charge L' = L_e - L_\mu - L_\tau (LC), we investigate quantitatively what are the minimal forms of U_e, in terms of angles and phases it contains, that can provide the requisite corrections to U_\nu so that \theta_13, \theta_23 and the solar neutrino mixing angle \theta_12 have values compatible with the current data. Two possible orderings of the 12 and the 23 rotations in U_e, "standard" and "inverse", are considered. The results we obtain depend strongly on the type of ordering. In the case of "standard" ordering, in particular, the Dirac CP violation phase \delta, present in U, is predicted to have a value in a narrow interval around i) \delta ~ \pi in the BM (or LC) case, ii) \delta ~ 3\pi/2 or \pi/2 in the TBM case, the CP conserving values \delta = 0, \pi, 2\pi being excluded in the TBM case at more than 4\sigma

Somatic mutation and gain of copy number of PIK3CA in human breast cancer

INTRODUCTION: Phosphatidylinositol 3-kinases (PI3Ks) are a group of lipid kinases that regulate signaling pathways involved in cell proliferation, adhesion, survival, and motility. Even though PIK3CA amplification and somatic mutation have been reported previously in various kinds of human cancers, the genetic change in PIK3CA in human breast cancer has not been clearly identified. METHODS: Fifteen breast cancer cell lines and 92 primary breast tumors (33 with matched normal tissue) were used to check somatic mutation and gene copy number of PIK3CA. For the somatic mutation study, we specifically checked exons 1, 9, and 20, which have been reported to be hot spots in colon cancer. For the analysis of the gene copy number, we used quantitative real-time PCR and fluorescence in situ hybridization. We also treated several breast cancer cells with the PIK3CA inhibitor LY294002 and compared the apoptosis status in cells with and without PIK3CA mutation. RESULTS: We identified a 20.6% (19 of 92) and 33.3% (5 of 15) PIK3CA somatic mutation frequency in primary breast tumors and cell lines, respectively. We also found that 8.7% (8 of 92) of the tumors harbored a gain of PIK3CA gene copy number. Only four cases in this study contained both an increase in the gene copy number and a somatic mutation. In addition, mutation of PIK3CA correlated with the status of Akt phosphorylation in some breast cancer cells and inhibition of PIK3CA-induced increased apoptosis in breast cancer cells with PIK3CA mutation. CONCLUSION: Somatic mutation rather than a gain of gene copy number of PIK3CA is the frequent genetic alteration that contributes to human breast cancer progression. The frequent and clustered mutations within PIK3CA make it an attractive molecular marker for early detection and a promising therapeutic target in breast cancer