Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Biobanking for Advancing Breast Cancer Research

Longitudinal patient biospecimens and data advance breast cancer research through enabling precision medicine approaches for identifying risk, early diagnosis, improved disease management and targeted therapy. Cancer biobanks must evolve to provide not only access to high-quality annotated biospecimens and rich associated data, but also the tools required to harness these data. We present the Breast Cancer Now Tissue Bank centre at the Barts Cancer Institute as an exemplar of a dynamic biobanking ecosystem that hosts and links longitudinal biospecimens and multimodal data including electronic health records, genomic and imaging data, offered alongside integrated data sharing and analytics tools. We demonstrate how such an ecosystem can inform precision medicine efforts in breast cancer research.
Non-Nutritive Suckling System for Real-Time Characterization of Intraoral Vacuum Profile in Full Term Neonates

Infant breastfeeding diagnostics remain subjective due to the absence of instrumentation to objectively measure and understand infant oral motor skills and suckling characteristics. Qualitative diagnostic exams, such as the digital suck assessment which relies upon a clinician’s gloved finger inserted into the infant’s mouth, produce a diversity of diagnoses and intervention pathways due to their subjective nature. In this paper, we report on the design of a non-nutritive suckling (NNS) system which quantifies and analyzes quantitative intraoral vacuum and sucking patterns of full-term neonates in real time. In our study, we evaluate thirty neonate suckling profiles to demonstrate the technical and clinical feasibility of the system. We successfully extract the mean suck vacuum, maximum suck vacuum, frequency, burst duration, number of sucks per burst, number of sucks per minute, and number of bursts per minute. In addition, we highlight the discovery of three intraoral vacuum profile shapes that are found to be correlated to different levels of suckling characteristics. These results establish a framework for future studies to evaluate oromotor dysfunction that affect the appearance of these signals based on established normal profiles. Ultimately, with the ability to easily and quickly capture intraoral vacuum data, clinicians can more accurately perform suckling assessments to provide timely intervention and assist mothers and infants towards successful breastfeeding outcomes.
Using Computer Vision and Artificial Intelligence to Track the Healing of Severe Burns

Burn care management includes assessing the severity of burns accurately, especially distinguishing superficial partial thickness (SPT) burns from deep partial thickness (DPT) burns, in the context of providing definitive, downstream treatment. Moreover, the healing of the wound in the sub-acute care setting requires continuous tracking to avoid complications. Artificial intelligence (AI) and computer vision (CV) provide a unique opportunity to build low-cost and accessible tools to classify burn severity and track changes of wound parameters, both in the clinic by physicians and nurses, and asynchronously in the remote setting by the patient themselves. Wound assessments can be achieved by AI-CV using the principles of Image-Guided Therapy (IGT) using high-quality 2D colour images. Wound parameters can include wound 2D spatial dimension and the characterization of wound colour changes which demonstrates physiological changes such as presentation of eschar/necrotic tissue, pustulence, granulation tissue and scabbing. Here we present the development of AI-CV-based Skin Abnormality Tracking Algorithm (SATA) pipeline.Additionally we provide proof-of-concept results on a severe localized burn tracked for a 6-week period in clinic, and an additional 2-week period of home monitoring.
Journal of Empirical Finance

During the pandemic, households accumulated savings in their deposit accounts as a result of a reduction in their spending, which occurred due to the restrictions on their mobility. This led to a significant increase in bank deposits for banks located in counties with a larger reduction in spending. Banks, in turn, used these additional funds to issue more real estate loans. This implies that policies that might affect household spending would lead to changes in the volume of deposits in the banking system, which have consequences on banks’ loan supply.
Electro-osmotic flow near a surface charge discontinuity

Electro-osmotic flows in the vicinity of surface charge density transitions are studied using a two-dimensional model problem. The analysed configuration consists of an electrolyte solution in contact with a dielectric planar wall, on which the density transition is approximated by a finite jump. The flow field in the semi-infinite fluid domain is driven by an external electric field which is applied parallel to the charged wall, in the direction of the jump. The problem is analysed using both the thin-Debye-layer (TDL) formulation, which does not resolve the fine details of the Debye-layer structure, and an approximate electrokinetic model.
Parametric Analysis of Ride Comfort for Tilting Railway Vehicles Running on Irregular Curved Tracks

The ride comfort of a tilting railway vehicle moving on curved tracks with rail irregularities is studied. Using the nonlinear creep model and Kalker's linear theory, the governing differential equations of motion for a tilting railway vehicle running on irregular tracks are first derived. The tilting railway vehicle is modeled by a 27 degree-of-freedom (DOF) car system, considering the lateral displacement, vertical displacement, roll angle and yaw angle of both the wheelsets and bogie frames, as well as the lateral displacement, roll angle and yaw angle of the car body. Based on the international standard ISO 2631-1, the effect of vehicle speed on the ride comfort index of the tilting vehicle is investigated for various tilting angles, using both linear and nonlinear creep models, and various radii of curved tracks, as well as for various suspension parameters. Finally, the ride comfort indices computed with rail irregularities are found to be higher than those with no rail irregularities, indicating that the effect of rail irregularities on the ride comfort of a tilting vehicle cannot be disregarded in practice.
Two-stage Control Strategy for Structure Optimization of Faulted Distribution System with Distributed Generation

Abstract In this article, a structure optimization strategy is designed for the faulted distribution system with distributed generation. The strategy is composed of two stages: the island partition and the remaining network reconfiguration. In the first stage, single-source electrical betweenness is proposed, and a partition model is built on the basis of variable network structure characteristics and flexible load features. Then binary decision method has been introduced to transform the original partition problem into a “satisfiability problem,” which can be solved in two steps, and the initial partition results are obtained using the implicit enumeration method, followed by static survivability check, interruptible load modification, and reactive compensation calculation. In this manner, the final scheme for the island partition is obtained. After that, based on the ant colony algorithm, the remaining network is reconstructed in the second stage. The effectiveness of the proposed strategy is verified by case studies in two test systems.
On the Wave Spectrum Generated by Tropical Heating

AbstractConvective heating profiles are computed from one month of rainfall rate and cloud-top height measurements using global Tropical Rainfall Measuring Mission and infrared cloud-top products. Estimates of the tropical wave response to this heating and the mean flow forcing by the waves are calculated using linear and nonlinear models. With a spectral resolution up to zonal wavenumber 80 and frequency up to 4 cpd, the model produces 50%–70% of the zonal wind acceleration required to drive a quasi-biennial oscillation (QBO). The sensitivity of the wave spectrum to the assumed shape of the heating profile, to the mean wind and temperature structure of the tropical troposphere, and to the type of model used is also examined. The redness of the heating spectrum implies that the heating strongly projects onto Hough modes with small equivalent depth. Nonlinear models produce wave flux significantly smaller than linear models due to what appear to be dynamical processes that limit the wave amplitude. Both no.
Markovian Learning Processes

Real-valued Markov processes with steps of the form $\Delta X_n = \theta _i (\lambda _i - X_n )$ or $\Delta X_n = \delta _i $, $i = 1, \cdots ,v$, arise frequently in the theory of human and animal learning. This paper first surveys results pertaining to the asymptotic behavior of such processes as $n \to \infty $. Next, general theorems are given that cover limiting behavior as $n \to \infty $ and, simultaneously, $\theta _i \to 0$ or $\delta _i \to 0$. Finally, an example of a two-dimensional learning process $X_n$ is presented.
Magnetic Studies on New Mixed-Valence Phosphates Zn 2 + Fe 3 + 2 (P 2 O 7 ) 2 and Zn 2 + 0.5 Cu 2 + 0.5 Fe 3 + 2 (P 2 O 7 ) 2

Structural studies of Zn 2 + Fe 3 + 2 (P 2 O 7 ) 2 and Cu 0.5 Zn 0.5 Fe 2 (P 2 O 7 ) 2 were made using powder X-ray diffraction and refined by Rietveld method. Both phosphates crystallize in an orthorhombic structure with Pnma space group. Magnetometry measurements showed that below T N = 5.6 (1), Zn 2 + Fe 3 + 2 (P 2 O 7 ) 2 becomes antiferromagnetic and the T N = 14 K is attributed to Cu 0.5 Zn 0.5 Fe 2 (P 2 O 7 ) 2 . M¨ossbauer studies at room temperature and low temperature were performed in both samples.
Molecular dynamics simulation of self-diffusion coefficient and its relation with temperature using simple Lennard-Jones potential

The diffusion coefficient is indispensable to chemical engineering design and research. In practical engineering and research, there is still a great lack of available data. Therefore, methods need to be developed to solve this problem. In this paper, a molecular dynamics simulation method is used to predict the self-diffusion coefficient for a simple fluid by using the Green– Kubo relation (VACF) and the Einstein relation (MSD). The simulation results are in good agreement with experimental findings except for an error of about 10%. The algorithm average of the two methods (AV) reduces the error to 7%. The relationship of the diffusion coefficient with temperature has also been simulated. According to the simulation data, whose correlation is all above 0.99, the diffusion coefficient agrees well with temperature following the Arrenhius relationship. Activation energy for self-diffusion has been calculated and the result were 1258(VACF), 1272(MSD), and 1265(AV) J/mol separately. © 2008 Wiley Periodicals, Inc. Heat Trans Asian Res, 37(2): 86–93, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/htj.20191
Interannual deviations of long-term data from observations and contrasting with reanalysis data from the oceanic station at Islas Marías, Nayarit, Mexico

We prepared a synthesis of historical weather conditions for Isla Maria Madre (1922-1989) to reflect conditions that impact the mainland of Mexico. Observations were compared with regional reanalysis (RR) data in the same area. The results indicate that air temperature, atmospheric pressure, relative humidity, and precipitation in both sources of data display the annual signal. Observations and RR data show differences in climate analysis, mainly in the phase of air temperature and relative humidity. These differences can be explained by the smoothness and the methods used to estimate the RR data.
Pricing Barrier and Bermudan Style Options Under Time-Changed L evy Processes: Fast Hilbert Transform Approach

We construct efficient and accurate numerical algorithms for pricing discretely monitored barrier and Bermudan style options under time-changed Levy processes by applying the fast Hilbert transform method to the log-asset return dimension and quadrature rule to the dimension of log-activity rate of stochastic time change. Some popular stochastic volatility models, like the Heston model, can be nested in the class of time-changed Levy processes. The computational advantages of the fast Hilbert transform approach over the usual fast Fourier transform method, like exponential decay of errors in terms of the step size in the transform and avoidance of recovering option prices at the monitoring time instants, can be extended to pricing barrier style options under time-changed Levy processes. We manage to compute the fair value of a dividend-ruin model with both embedded reflecting (dividend) barrier and absorbing (ruined) barrier. We also consider pricing of Bermudan options in conjunction with the determination of the associated critical asset prices. Our numerical tests demonstrate high level of accuracy, efficiency and reliability of the fast Hilbert transform approach when compared to other numerical schemes in the literature.
Back analysis procedures for the interpretation of field measurements in geomechanics

SUMMARY A survey is presented of some recent developments of the numerical techniques for back analysis in the field of geomechanics, with particular reference to tunnelling problems. In the spirit of Terzaghi's observational design method, these techniques are seen as practical tools for interpreting the available field measurements, in order to reduce the uncertainties that in many instances affect the parameters governing the solution of complex geomechanics problems. Both deterministic and probabilistic viewpoints are considered and some significant applications to practical problems are illustrated.
Design, fabrication, and characterization of Fresnel lens array with spatial filtering for passive infrared motion sensors

A cubic-phase distribution is applied in the design, fabrication and characterization of inexpensive Fresnel lens arrays for passive infrared motion sensors. The resulting lens array produces a point spread function (PSF) capable of distinguish the presence of humans from pets by the employment of the so-called wavefront coding method. The cubic phase distribution used in the design can also reduce the optical aberrations present in the system. This aberration control allows a high tolerance in the fabrication of the lenses and in the alignment errors of the sensor. In order to proof the principle, a lens was manufactured on amorphous hydrogenated carbon thin film, by well-known micro fabrication process steps. The optical results demonstrates that the optical power falling onto the detector surface is attenuated for targets that present a mass that is horizontally distributed in space (e.g. pets) while the optical power is enhanced for targets that present a mass vertically distributed in space (e.g. humans). Then a mould on steel was fabricated by laser engraving, allowing large-scale production of the lens array in polymeric material. A polymeric lens was injected and its optical transmittance was characterized by Fourier Transform Infrared Spectrometry technique, which has shown an adequate optical transmittance in the 8-14 μm wavelength range. Finally the performance of the sensor was measured in a climate-controlled test laboratory constructed for this purpose. The results show that the sensor operates normally with a human target, with a 12 meter detection zone and within an angle of 100 degrees. On the other hand, when a small pet runs through a total of 22 different trajectories no sensor trips are observed. The novelty of this work is the fact that the so-called pet immunity function was implemented in a purely optical filtering. As a result, this approach allows the reduction of some hardware parts as well as decreasing the software complexity, once the information about the intruder is optically processed before it is transduced by the pyroelectric sensor.
Numerical MHD modeling of propagation of interplanetary shock through the magnetosheath

[1] Propagation of an interplanetary (IP) shock through the bow shock and magnetosheath is studied using numerical results of a three-dimensional MHD model of the magnetosheath. According to already published theoretical studies, a fast forward shock passing through the bow shock would generate a train of new discontinuities including a slow expansion wave, a contact discontinuity, and a slow reversed shock. We have found that these particular discontinuities propagate with similar velocities and thus they cannot be distinguished in our calculations, and we observe one discontinuity that combines properties of all of them. We suggest that the same would be true for an analysis of experimental data. We have simulated three different ways of the magnetopause response to the IP shock. A comparison of these runs reveals that the magnetopause reaction defines the mode of reflected waves. Assuming a fast earthward motion of the magnetopause, about 240 km s−1 or more, we obtain that a fast rarefaction wave would propagate from the magnetopause toward the bow shock, while a slower magnetopause motion would result in a fast reversed shock. On the other hand, the speed of the IP shock propagation does not depend on the magnetopause response, and all three model runs confirm a deceleration of the modeled IP shock front in the magnetosheath in course of its motion from the subsolar region to the magnetosheath flanks.
A behavioural Bayes approach for sample size determination in cluster randomized clinical trials

Summary. Cluster randomized clinical trials are increasingly popular to evaluate disease control interventions for communities. In these trials health interventions are allocated randomly to complete clusters or groups rather than to individual subjects. Sample size calculation for cluster randomized clinical trials has been largely based on classical theory, taking account of between‐cluster variation, and of type I and II errors. It is desirable to use an approach which maximizes the expected net benefit, but there is as yet no established methodology along these lines. Gittins and Pezeshk presented an expected net benefit approach to sample size determination. We extend that approach to cluster randomized clinical trials.
THE LINEARIZED BREGMAN

One of the key steps in compressed sensing is to solve the basis pursuit problem min u ∈ R n {(cid:1) u (cid:1) 1 : Au = f } . Bregman iteration was very successfully used to solve this problem in [40]. Also, a simple and fast iterative algorithm based on linearized Bregman iteration was proposed in [40], which is described in detail with numerical simulations in [35]. A convergence analysis of the smoothed version of this algorithm was given in [11]. The purpose of this paper is to prove that the linearized Bregman iteration proposed in [40] for the basis pursuit problem indeed converges.
A posteriori compensation of the systematic error due to polynomial interpolation in digital image correlation

Abstract. It is well known that displacement components estimated using digital image correlation are affected by a systematic error due to the polynomial interpolation required by the numerical algorithm. The magnitude of bias depends on the characteristics of the speckle pattern (i.e., the frequency content of the image), on the fractional part of displacements and on the type of polynomial used for intensity interpolation. In literature, B-Spline polynomials are pointed out as being able to introduce the smaller errors, whereas bilinear and cubic interpolants generally give the worst results. However, the small bias of B-Spline polynomials is partially counterbalanced by a somewhat larger execution time. We will try to improve the accuracy of lower order polynomials by a posteriori correcting their results so as to obtain a faster and more accurate analysis.
Bilinear calibration of coaxial transmission/reflection cells for permittivity measurement of low-loss liquids

Several parameters describing the quality of petrochemical products can be revealed from the permittivity spectrum of the product. This requires that the permittivity be measured with high sensitivity, so the calibration of measurement cells is of great importance. In this work calibration techniques for the transmission/reflection method for complex permittivity determination of low-loss liquids are studied. It is shown that a bilinear transformation can be used to determine the scattering parameters at the reference planes from the measured scattering parameters of a coaxial transmission/reflection cell. The permittivity of a sample in the cell can then be calculated with high precision from the reference plane parameters. The de-embedding procedure consists of determining three calibration coefficients by measuring three samples with known permittivities. Measurements on low-loss liquids and crude oils confirm the performance of the calibration procedure. The technique is compared to a simpler calibration method and the choice of calibration fluids to ensure broad-band measurements is discussed.
Breathing coherent phonons and caps fragmentation in carbon nanotubes following ultrafast laser pulses

The response of carbon nanotubes to femtosecond laser pulses is studied with a nonadiabatic simulation technique, which accounts for the evolution of electronic and ionic degrees of freedom, and for the coupling with the external electromagnetic field. As a direct result of electronic excitation, three coherent breathing phonon modes are excited: two radial vibrations localized in the caps and cylindrical body, and one longitudinal vibration coupled to the nanotube length. Under high absorbed energies (but below 2.9 eV/atom, the graphite's ultrafast fragmentation threshold), the resulting oscillatory motion leads to the opening of nanotube caps. Following the cap photofragmentation the nanotube body remains intact for the rest of the 2 ps simulation time.
State‐space Models with Finite Dimensional Dependence

We consider nonlinear state‐space models, where the state variable (ζt) is Markov, stationary and features finite dimensional dependence (FDD), i.e. admits a transition function of the type: π(ζt|ζt−1) =π(ζt)a′(ζt)b(ζt−1), where π(ζt) denotes the marginal distribution of ζt, with a finite number of cross‐effects between the present and past values. We discuss various characterizations of the FDD condition in terms of the predictor space and nonlinear canonical decomposition. The FDD models are shown to admit explicit recursive formulas for filtering and smoothing of the observable process, that arise as an extension of the Kitagawa approach. The filtering and smoothing algorithms are given in the paper.
F‐tests for Hypotheses with Block Matrices and Under Conditions of Orthogonality in the General Multivariate Gauss‐Markoff Model

The multivariate general Gauss-Markoff (MGM) model (U, XB, ∑⊗σ2V) when the matrices V ≥ 0 and ∑ > 0 are known and the scalar σ2 > 0 is unknown, is considered. The present paper is a continuation of two earlier works (Oktaba, 1988a, b). If XB = X1Σ + X2Δ, then the F-test for verification the hypothesis WΣA = 0 is presented. Moreover, under conditions of orthogonality the decomposition of the matrix SA (ŁBCA)′L−(ŁBCA) into the sum of s = r(L) matrices is given, where ŁBCA is the estimator of the parametric estimable functions ŁBCA, Cov (ŁBCA) = A′ ∑⊗σ2L = ŁC4Ł′, B = (X′T−X)−X′T−U, C4 = (X′T−X)−M, where M = M′ is any arbitrary matrix such that R(X) ⊂ R(T), T=V+XMX′; T− is any c-inverse. R(A) is the linear space generated by the colums of A. Then under additional assumption on normality of U the statistics F for testing ŁBA = 0 is deduced. Under conditions of normality of U and decomposition of SA, the statistics F1, …, Fs for the hypotheses jiBA = 0 (i = 1,…, s) are established.