Indirect unitarity violation entangled with matter effects in reactor antineutrino oscillations

If finite but tiny masses of the three active neutrinos are generated via the canonical seesaw mechanism with three heavy sterile neutrinos, the 3\times 3 Pontecorvo-Maki-Nakagawa-Sakata neutrino mixing matrix V will not be exactly unitary. This kind of indirect unitarity violation can be probed in a precision reactor antineutrino oscillation experiment, but it may be entangled with terrestrial matter effects as both of them are very small. We calculate the probability of \overline{\nu}_e \to \overline{\nu}_e oscillations in a good analytical approximation, and find that, besides the zero-distance effect, the effect of unitarity violation is always smaller than matter effects, and their entanglement does not appear until the next-to-leading-order oscillating terms are taken into account. Given a 20-kiloton JUNO-like liquid scintillator detector, we reaffirm that terrestrial matter effects should not be neglected but indirect unitarity violation makes no difference, and demonstrate that the experimental sensitivities to the neutrino mass ordering and a precision measurement of \theta_{12} and \Delta_{21} \equiv m^2_2 - m^2_1 are robust.Comment: 21 pages, 6 figures, version to be published in PLB, more discussions adde

Differential quadrature solutions to dynamic response of cylindrical shell subjected to thermal shock

The dynamic response of the cylindrical shell subjected to thermal shock is investigated. Based on the classical shell theory, dynamic governing equations of thin shell with the simply supported edges under thermal shock are derived by using Hamilton principle. The temperature field, the thermal axial force and the thermal bending moment are obtained in combination of Laplace transform and series expansion when the internal surface of shell is subjected to thermal shock loading. Considering of the axisymmetric deformation, the transient displacements and thermal stresses of the shell are obtained using the differential quadrature method. The effects of the thermal shock load and the geometrical parameters of the cylindrical shell on the central deflection, the axial displacement, the bending configurations and the transient thermal stresses are analyzed

Polarization-Independent Metasurface Lens Based on Binary Phase Fresnel Zone Plate

Based on the binary phase Fresnel zone plate (FZP), a polarization-independent metasurface lens that is able to focus incident light with any polarization state, including circular, linear, and elliptical polarizations, has been proposed and investigated. We demonstrate that the metasurface lens consisting of metal subwavelength slits can operate in a wide bandwidth in the visible range, and has a higher focusing efficiency than that of an amplitude FZP lens without phase modulation. A multi-focus FZP metasurface lens has also been designed and investigated. The proposed lens can provide potential applications in integrated nanophotonic devices without polarization limitations

Robust global sliding model control for water-hull-propulsion unit interaction systems - part 2: model validation

Unexpected severe hull deformation caused by wave loads poses alignment problem to the propulsion shaft line in large scale ships, which would significantly influence the dynamical performance of the marine propulsion system. How to suppress negative disturbance imposed by the interaction between water-hull-propulsion and ensure the normal operation of the marine propulsion system is a challenging task. To address this issue, a new global sliding model control (GSMC) for marine water-hull-propulsion unit systems is proposed and investigated to obtain more accurate control performance in a series of researches. In Part 1 the GSMC controller has been developed and the bounded nonlinear model uncertainties have been derived based on the experiments and sea trial. In this work the upper boundary of 1,85 % was introduced into the GSMC controller to derive the total control law realising the robust control of the marine propulsion system. Numerical simulations based on the real bulk carrier parameters show a high effectiveness of the GSMC for speed tracking, compared with the traditional sliding model controller and Proportional Integral Derivative (PID) controller. By the proposed and investigated control system in this paper may be developed a simple practical-effective robust control strategy for marine propulsion systems subject to some complex unknown uncertainties through further investigations, validations and modification

A multi-wavelength observation and investigation of six infrared dark clouds

Context. Infrared dark clouds (IRDCs) are ubiquitous in the Milky Way, yet they play a crucial role in breeding newly-formed stars. Aims. With the aim of further understanding the dynamics, chemistry, and evolution of IRDCs, we carried out multi-wavelength observations on a small sample. Methods. We performed new observations with the IRAM 30 m and CSO 10.4 m telescopes, with tracers ${\rm HCO^+}$, HCN, ${\rm N_2H^+}$, ${\rm C^{18}O}$, DCO$^+$, SiO, and DCN toward six IRDCs G031.97+00.07, G033.69-00.01, G034.43+00.24, G035.39-00.33, G038.95-00.47, and G053.11+00.05. Results. We investigated 44 cores including 37 cores reported in previous work and seven newly-identified cores. Toward the dense cores, we detected 6 DCO$^+$, and 5 DCN lines. Using pixel-by-pixel spectral energy distribution (SED) fits of the $\textit{Herschel}$ 70 to 500 $\mu$m, we obtained dust temperature and column density distributions of the IRDCs. We found that ${\rm N_2H^+}$ emission has a strong correlation with the dust temperature and column density distributions, while ${\rm C^{18}O}$ showed the weakest correlation. It is suggested that ${\rm N_2H^+}$ is indeed a good tracer in very dense conditions, but ${\rm C^{18}O}$ is an unreliable one, as it has a relatively low critical density and is vulnerable to freezing-out onto the surface of cold dust grains. The dynamics within IRDCs are active, with infall, outflow, and collapse; the spectra are abundant especially in deuterium species. Conclusions. We observe many blueshifted and redshifted profiles, respectively, with ${\rm HCO^+}$ and ${\rm C^{18}O}$ toward the same core. This case can be well explained by model "envelope expansion with core collapse (EECC)".Comment: 24 pages, 11 figures, 4 tables. To be published in A&A. The resolutions of the pictures are cut dow

Minor Issues Escalated to Critical Levels in Large Samples: A Permutation-Based Fix

In the big data era, the need to reevaluate traditional statistical methods is paramount due to the challenges posed by vast datasets. While larger samples theoretically enhance accuracy and hypothesis testing power without increasing false positives, practical concerns about inflated Type-I errors persist. The prevalent belief is that larger samples can uncover subtle effects, necessitating dual consideration of p-value and effect size. Yet, the reliability of p-values from large samples remains debated. This paper warns that larger samples can exacerbate minor issues into significant errors, leading to false conclusions. Through our simulation study, we demonstrate how growing sample sizes amplify issues arising from two commonly encountered violations of model assumptions in real-world data and lead to incorrect decisions. This underscores the need for vigilant analytical approaches in the era of big data. In response, we introduce a permutation-based test to counterbalance the effects of sample size and assumption discrepancies by neutralizing them between actual and permuted data. We demonstrate that this approach effectively stabilizes nominal Type I error rates across various sample sizes, thereby ensuring robust statistical inferences even amidst breached conventional assumptions in big data. For reproducibility, our R codes are publicly available at: \url{https://github.com/ubcxzhang/bigDataIssue}

Short-Term Power Demand Forecasting Using Blockchain-Based Neural Networks Models

With the rapid development of blockchain technology, blockchain-based neural network short-term power demand forecasting has become a research hotspot in the power industry. This paper aims to combine neural network algorithms with blockchain technology to establish a trustworthy and efficient short-term demand forecasting model. By leveraging the distributed ledger and immutability features of blockchain, we ensure the security and reliability of power demand data. Meanwhile, short-term power demand forecasting research using neural networks has the potential to increase the stability of the power system and offer opportunities for improved operations. In this paper, the root mean-square-error model evaluation indicator was used to compare the back propagation (BP) neural network algorithm and the traditional forecasting algorithm. The evaluation was performed on the randomly selected five household power datasets. The results show that, by comparing the long short-term memory network (LSTM) model with the BP neural network model, it was determined that the average prediction impact increases by about 25.7% under stable power demand. The short-term power prediction model of the BP neural network has the average error values more than two times lower than the traditional prediction model. It was shown that the use of the BP neural network algorithm and blockchain could increase the accuracy of short-term power demand forecasting, allowing the neural network-based algorithm to be implemented and taken into account in the research on short-term power demand forecasting

Strong association of lumbar disk herniation with diabetes mellitus: a 12-year nationwide retrospective cohort study

BackgroundDespite reports on the association between diabetes mellitus (DM) and lumbar disk herniation (LDH), large-scale, nationwide studies exploring this relationship are lacking. We aimed to examine the profiles of DM in individuals with LDH and explore the potential mechanisms underlying the development of these disorders.MethodsThis retrospective, population-based study was conducted between 2008 and 2019 using data from the National Health Insurance (NHI) research database in Taiwan. The primary outcome was the date of initial LDH diagnosis, death, withdrawal from the NHI program, or end of the study period.ResultsIn total, 2,662,930 individuals with and 16,922,546 individuals without DM were included in this study; 719,068 matched pairs were established following propensity score matching (1:1 ratio) for sex, age, comorbidities, smoking, alcohol consumption, antihyperglycemic medications, and index year. The adjusted risk for developing LDH was 2.33-fold (95% confidence interval: 2.29−2.37; P<0.001), age-stratified analysis revealed a significantly greater risk of LDH in every age group, and both males and females were approximately twice as likely to develop LDH in the DM compared with non-DM cohort. Individuals with DM and comorbidities had a significantly higher risk of developing LDH than those without, and the serial models yielded consistent results. Treatment with metformin, sulfonylureas, meglitinides, thiazolidinediones, dipeptidyl peptidase-4 inhibitors, or alpha-glucosidase inhibitors was associated with a more than 4-fold increased risk of LDH in the DM cohort. DM was strongly associated with the long-term development of LDH; over the 12-year follow-up period, the cumulative risk of LDH was significantly higher in patients with than without DM (log-rank P<0.001).ConclusionDM is associated with an increased risk of LDH, and advanced DM may indicate a higher risk of LDH

Quenching and flow of charm and bottom quarks via semi-leptonic decay of DD and BB mesons in Pb+Pb collisions at the LHC

Heavy flavor particles provide important probes of the microscopic structure and thermodynamic properties of the quark-gluon plasma (QGP) produced in high-energy nucleus-nucleus collisions. We study the energy loss and flow of charm and bottom quarks inside the QGP via the nuclear modification factor ($R_\mathrm{AA}$) and elliptic flow coefficient ($v_2$) of their decayed leptons in heavy-ion collisions at the LHC. The dynamical evolution of the QGP is performed using the (3+1)-dimensional viscous hydrodynamics model CLVisc; the evolution of heavy quarks inside the QGP is simulated with our improved Langevin model that takes into account both collisional and radiative energy loss of heavy quarks; the hadronization of heavy quarks is simulated via our hybrid coalescence-fragmentation model; and the semi-leptonic decay of $D$ and $B$ mesons is simulated via PYTHIA. By using the same spatial diffusion coefficient for charm and bottom quarks, we obtain smaller $R_\mathrm{AA}$ and larger $v_2$ of charm decayed leptons than bottom decayed leptons, indicating stronger energy loss of charm quarks than bottom quarks inside the QGP within our current model setup.Comment: 9 pages, 4 figure