Short-Range Correlations and Cooling of Ultracold Fermions in the Honeycomb Lattice

We use determinantal quantum Monte Carlo simulations and numerical linked-cluster expansions to study thermodynamic properties and short-range spin correlations of fermions in the honeycomb lattice. We find that, at half filling and finite temperatures, nearest-neighbor spin correlations can be stronger in this lattice than in the square lattice, even in regimes where the ground state in the former is a semimetal or a spin liquid. The honeycomb lattice also exhibits a more pronounced anomalous region in the double occupancy that leads to stronger adiabatic cooling than in the square lattice. We discuss the implications of these findings for optical lattice experiments.Comment: 5 pages, 4 figure

Comparison and aggregation of event sequences across ten cohorts to describe the consensus biomarker evolution in Alzheimer's disease

BACKGROUND: Previous models of Alzheimer's disease (AD) progression were primarily hypothetical or based on data originating from single cohort studies. However, cohort datasets are subject to specific inclusion and exclusion criteria that influence the signals observed in their collected data. Furthermore, each study measures only a subset of AD-relevant variables. To gain a comprehensive understanding of AD progression, the heterogeneity and robustness of estimated progression patterns must be understood, and complementary information contained in cohort datasets be leveraged. METHODS: We compared ten event-based models that we fit to ten independent AD cohort datasets. Additionally, we designed and applied a novel rank aggregation algorithm that combines partially overlapping, individual event sequences into a meta-sequence containing the complementary information from each cohort. RESULTS: We observed overall consistency across the ten event-based model sequences (average pairwise Kendall's tau correlation coefficient of 0.69 ± 0.28), despite variance in the positioning of mainly imaging variables. The changes described in the aggregated meta-sequence are broadly consistent with the current understanding of AD progression, starting with cerebrospinal fluid amyloid beta, followed by tauopathy, memory impairment, FDG-PET, and ultimately brain deterioration and impairment of visual memory. CONCLUSION: Overall, the event-based models demonstrated similar and robust disease cascades across independent AD cohorts. Aggregation of data-driven results can combine complementary strengths and information of patient-level datasets. Accordingly, the derived meta-sequence draws a more complete picture of AD pathology compared to models relying on single cohorts

Bosonic t-J Model in a stacked triangular lattice and its phase diagram

In this paper, we study phase diagram of a system of two-component hard-core bosons with nearest-neighbor (NN) pseudo-spin antiferromagnetic (AF) interactions in a stacked triangular lattice. Hamiltonian of the system contains three parameters one of which is the hopping amplitude $t$ between NN sites, and the other two are the NN pseudo-spin exchange interaction $J$ and the one that measures anisotropy of pseudo-spin interactions. We investigate the system by means of the Monte-Carlo simulations and clarify the low-temperature phase diagram. In particular, we are interested in how the competing orders, i.e., AF order and superfluidity, are realized, and also whether supersolid forms as a result of hole doping into the state of the $\sqrt{3}\times \sqrt{3}$ pseudo-spin pattern with the $120^o$ structure.Comment: 18 pages, 17 figures, Version to appear in J.Phys.Soc.Jp

Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players

We present the concept of fiber-flux density for locally quantifying white matter (WM) fiber bundles. By combining scalar diffusivity measures (e.g., fractional anisotropy) with fiber-flux measurements, we define new local descriptors called Fiber-Flux Diffusion Density (FFDD) vectors. Applying each descriptor throughout fiber bundles allows along-tract coupling of a specific diffusion measure with geometrical properties, such as fiber orientation and coherence. A key step in the proposed framework is the construction of an FFDD dissimilarity measure for sub-voxel alignment of fiber bundles, based on the fast marching method (FMM). The obtained aligned WM tract-profiles enable meaningful inter-subject comparisons and group-wise statistical analysis. We demonstrate our method using two different datasets of contact sports players. Along-tract pairwise comparison as well as group-wise analysis, with respect to non-player healthy controls, reveal significant and spatially-consistent FFDD anomalies. Comparing our method with along-tract FA analysis shows improved sensitivity to subtle structural anomalies in football players over standard FA measurements

Low noise SQUID Based NDE with Non-magnetic scanning system in unshielded environment

Abstract. A Non-magnetic scanning Robotic system with special EMC considerations has been designed for SQUID-Based NDE of room temperature stationary samples in unshielded environment. Considerable efforts have been made to cancel out noise of the system which resulted in detection of two major noise sources. Characterizing the noise contribution of the involved parts, a minor noise component was found to be due to the robot and the other due to liquid nitrogen bubbling in some frequencies which could be avoided by choosing proper excitation frequency. Using our NDE system we performed a NDE scan of hidden cracks in aluminum plates with white noise level of 50 μΦ 0 /Hz -1/2 . Introduction Nondestructive evaluation systems have found applications far beyond accessing damages and cracks in industrial products and structures. There is tremendous potential in employing a high-Tc Superconducting Quantum Interference Device (SQUID) for non-destructive evaluation (NDE) of metallic structures. For eddy current NDE, SQUIDs can be used with an excitation magnetic field to image cracks or material erosion deep in conducting structures. Demand for practical nondestructive evaluation of large-scale objects has prompted systems with freely movable SQUID sensors against them. However because of the sensitivity of the SQUID to rotation in an external magnetic field or translation in an external field gradient, the signal-tonoise ratio of the SQUID sensor is adversely affected in a portable system. To suppress the frequent spurious signals, in most conventional SQUID-NDE systems the object is moved under a rigidly fixed SQUID sensor in a stationary cryogenic dewar, while the sensor is covered by magnetic shielding. Independent groups have worked on the realization of SQUID sensor that can freely move in ambient environment. Isawa et al reported a traveling SQUID-NDE for low-Tc sensor in [1]. Our experimental results have shown that SQUID signal is affected by commercial scanning systems because of their materials and high capability for electromagnetic noise induction. Recently we developed a practical NDE system with portable high-Tc rf-SQUID for inspection of stationary targets based on a designed nonmagnetic low noise robo

Comments on the d-wave pairing mechanism for cuprate high TcT_c superconductors: Higher is different?

The question of pairing glue for the cuprate superconductors (SC)is revisited and its determination through the angle resolved photo-emission spectroscopy (ARPES) is discussed in detail. There are two schools of thoughts about the pairing glue question: One argues that superconductivity in the cuprates emerges out of doping the spin singlet resonating valence bond (RVB) state. Since singlet pairs are already formed in the RVB state there is no need for additional boson glue to pair the electrons. The other instead suggests that the d-wave pairs are mediated by the collective bosons like the conventional low $T_c$ SC with the alteration that the phonons are replaced by another kind of bosons ranging from the antiferromagnetic (AF) to loop current fluctuations. An approach to resolve this dispute is to determine the frequency and momentum dependences of the diagonal and off-diagonal self-energies directly from experiments like the McMillan-Rowell procedure for the conventional SC. In that a simple d-wave BCS theory describes superconducting properties of the cuprates well, the Eliashberg analysis of well designed high resolution experimental data will yield the crucial frequency and momentum dependences of the self-energies. This line of approach using ARPES are discussed in more detail in this review, and some remaining problems are commented.Comment: Invited review article published in the Journal of Korean Physical Society; several typos corrected and a few comments and references adde

5-HTR3 and 5-HTR4 located on the mitochondrial membrane and functionally regulated mitochondrial functions

5-HT has been reported to possess significant effects on cardiac activities, but activation of 5-HTR on the cell membrane failed to illustrate the controversial cardiac reaction. Because 5-HT constantly comes across the cell membrane via 5-HT transporter (5-HTT) into the cytoplasm, whether 5-HTR is functional present on the cellular organelles is unknown. Here we show 5-HTR3 and 5-HTR4 were located in cardiac mitochondria, and regulated mitochondrial activities and cellular functions. Knock down 5-HTR3 and 5-HTR4 in neonatal cardiomyocytes resulted in significant increase of cell damage in response to hypoxia, and also led to alternation in heart beating. Activation of 5-HTR4 attenuated mitochondrial Ca2+ uptake under the both normoxic and hypoxic conditions, whereas 5-HTR3 augmented Ca2+ uptake only under hypoxia. 5-HTR3 and 5-HTR4 exerted the opposite effects on the mitochondrial respiration: 5-HTR3 increased RCR (respiration control ratio), but 5-HTR4 reduced RCR. Moreover, activation of 5-HTR3 and 5-HTR4 both significantly inhibited the opening of mPTP. Our results provided the first evidence that 5-HTR as a GPCR and an ion channel, functionally expressed in mitochondria and participated in the mitochondria function and regulation to maintain homeostasis of mitochondrial [Ca2+], ROS, and ATP generation efficiency in cardiomyocytes in response to stress and O2 tension

Measurement and Modeling of Particle Radiation in Coal Flames

This work aims at developing a methodology that can provide information of in-flame particle radiation in industrial-scale flames. The method is based on a combination of experimental and modeling work. The experiments have been performed in the high-temperature zone of a 77 kWth swirling lignite flame. Spectral radiation, total radiative intensity, gas temperature, and gas composition were measured, and the radiative intensity in the furnace was modeled with an axisymmetric cylindrical radiation model using Mie theory for the particle properties and a statistical narrow-band model for the gas properties. The in-flame particle radiation was measured with a Fourier transform infrared (FTIR) spectrometer connected to a water-cooled probe via fiber optics. In the cross-section of the flame investigated, the particles were found to be the dominating source of radiation. Apart from giving information about particle radiation and temperature, the methodology can also provide estimates of the amount of soot radiation and the maximum contribution from soot radiation compared to the total particle radiation. In the center position in the flame, the maximum contribution from soot radiation was estimated to be less than 40% of the particle radiation. As a validation of the methodology, the modeled total radiative intensity was compared to the total intensity measured with a narrow angle radiometer and the agreement in the results was good, supporting the validity of the used approach

The X-Ray and Radio Loud Fast Blue Optical Transient AT2020mrf: Implications for an Emerging Class of Engine-driven Massive Star Explosions

We present AT2020mrf (SRGe J154754.2+443907), an extra-galactic (z = 0.1353) fast blue optical transient (FBOT) with a rise time of t g,rise = 3.7 days and a peak luminosity of M g,peak = −20.0. Its optical spectrum around peak shows a broad (v ∼ 0.1c) emission feature on a blue continuum (T ∼ 2 × 104 K), which bears a striking resemblance to AT2018cow. Its bright radio emission (ν L ν = 1.2 × 1039 erg s−1; ν rest = 7.4 GHz; 261 days) is similar to four other AT2018cow-like events, and can be explained by synchrotron radiation from the interaction between a sub-relativistic (≳0.07-0.08c) forward shock and a dense environment ( M ̇ ≲ 10 − 3 M ⊙ yr − 1 for v w = 103 km s−1). AT2020mrf occurs in a galaxy with M * ∼ 108 M ⊙ and specific star formation rate ∼10−10 yr−1, supporting the idea that AT2018cow-like events are preferentially hosted by dwarf galaxies. The X-ray luminosity of AT2020mrf is the highest among FBOTs. At 35-37 days, SRG/eROSITA detected luminous (L X ∼ 2 × 1043 erg s−1; 0.3-10 keV) X-ray emission. The X-ray spectral shape (f ν ∝ ν −0.8) and erratic intraday variability are reminiscent of AT2018cow, but the luminosity is a factor of ∼20 greater than AT2018cow. At 328 days, Chandra detected it at L X ∼ 1042 erg s−1, which is >200 times more luminous than AT2018cow and CSS161010. At the same time, the X-ray emission remains variable on the timescale of ∼1 day. We show that a central engine, probably a millisecond magnetar or an accreting black hole, is required to power the explosion. We predict the rates at which events like AT2018cow and AT2020mrf will be detected by SRG and Einstein Probe

Data-Driven Phenotyping of Central Disorders of Hypersomnolence With Unsupervised Clustering

Background and ObjectivesRecent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers.MethodsWe used agglomerative hierarchical clustering, an unsupervised machine learning algorithm, to identify distinct hypersomnolence clusters in the large-scale European Narcolepsy Network database. We included 97 variables, covering all aspects of central hypersomnolence disorders such as symptoms, demographics, objective and subjective sleep measures, and laboratory biomarkers. We specifically focused on subgrouping of patients without cataplexy. The number of clusters was chosen to be the minimal number for which patients without cataplexy were put in distinct groups.ResultsWe included 1,078 unmedicated adolescents and adults. Seven clusters were identified, of which 4 clusters included predominantly individuals with cataplexy. The 2 most distinct clusters consisted of 158 and 157 patients, were dominated by those without cataplexy, and among other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening, and weekend-week sleep length difference. Patients formally diagnosed as having narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these 2 clusters.DiscussionUsing a data-driven approach in the largest study on central disorders of hypersomnolence to date, our study identified distinct patient subgroups within the central disorders of hypersomnolence population. Our results contest inclusion of sleep-onset REM periods in diagnostic criteria for people without cataplexy and provide promising new variables for reliable diagnostic categories that better resemble different patient phenotypes. Cluster-guided classification will result in a more solid hypersomnolence classification system that is less vulnerable to instability of single features