Miracle-dz/UniFAR-FTUs huggingface dataset:
Title Forecasting Influenza Epidemics in Hong Kong

Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A (H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased; the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and
Simulations of Massive Star Cluster Formation and Feedback in Turbulent Giant Molecular Clouds

Abstract Using the AMR code ENZO we are simulating the formation of massive star clusters within turbulent Giant Molecular Clouds (GMCs). Here we discuss the simulations from the first stages of building realistic turbulent GMCs, to accurate star formation, and ultimately comprehensive feedback. These simulations aim to build a better understanding of how stars affect GMCs, helping to answer the questions of how long GMCs live and why only a small fraction of the GMC gas becomes stars.
Statistical Inference in Adaptive Group Sequential Trials with the Standardized Mean Difference as Effect Size

Abstract We consider the standardized difference of normal means as the outcome measure for comparing two independent groups, say experimental E and control C. This scale- and translation-invariant effect measure enables a convenient specification of a noninferiority margin in applications. Starting with a family of null hypotheses, we derive adaptive group sequential confidence intervals keeping the predefined confidence coefficient. The interval at the end of the trial determines whether and which null hypotheses can be rejected. During the course of the trial, the sample size can be calculated in a completely adaptive way based on the unblinded data of previously performed stages. Concrete rules for sample size updating are provided. Moreover, in each interim analysis, it is possible to change the planning from showing noninferiority to showing superiority or vice versa without affecting the overall type I error. A real data example is worked out in detail and the change in the sample size planning from showing noninferiority to showing superiority is considered during the ongoing trial. In Monte Carlo simulations, we investigate the practical properties of the proposed intervals.
Group sequential methods in the design and analysis of clinical trials

SUMMARY In clinical trials with sequential patient entry, fixed sample size designs are unjustified on ethical grounds and sequential designs are often impracticable. One solution is a group sequential design dividing patient entry into a number of equal-sized groups so that the decision to stop the trial or continue is based on repeated significance tests of the accumulated data after each group is evaluated. Exact results are obtained for a trial with two treatments and a normal response with known variance. The design problem of determining the required size and number of groups is also considered. Simulation shows that these normal results may be adapted to other types of response data. An example shows that group sequential designs can sometimes be statistically superior to standard sequential designs.
THE BLUE STARS ABOVE THE TURN-OFF IN M67: HORIZONTAL BRANCH OR BLUE STRAGGLERS?

The nature of the pseudohorizontal branch in the galactic cluster M67 is investigated. A differential technique is used to determine the masses of these stars relative both to the turnoff-point stars and to the ZAMS. The pseudohorizontal-branch stars are found to have masses in the range 1.3 < 93'tP. )'0 < 2.5; a mass lower than or equal to the tumoffpoint mass seems to be ruled out. This result suggests that these stars are analogs of the blue stragglers found in other galactic clusters rather than Population I analogs of Population II blue horizontal-branch stars. As by-products of this investigation, the zero-age main sequence is calibrated in terms of effective temperature and log g for the fi-(h-y) and fl-c1 planes; a value of reddening of = 0.04 or = 0.06 is derived for M 67 and the metal content of the M 67 stars is estimated to be solar or slightly lower. Key words: galactic clusters - stellar evolution - blue stragglers
Modified Stranski–Krastanov growth in stacked layers of self-assembled islands

In a stack of vertically aligned Stranski–Krastanov grown islands, the critical thickness for planar growth for all but the initial dot layer is reduced, if the thickness of the spacer layer ts is smaller than a certain value t0. We present structural and photoluminescence results on the basis of the extensively studied lattice-mismatched material system Si/Ge.
Contents Refined for Implentmenting Association Learning of Students with Modern Techniques

The period of junior high school is a good time to train the students to increase their understanding about learning methods and to study their school subjects in an associated manner. In this paper, an example about association learning is exhibited with a modern technique – electrospraying, which is regarded as a supporting base. A series of school subjects such as “science”, “mathematics”, “physics”, “chemistry” and “practice” can be realized contents refined with electrospraying as teaching materials, which should be also useful for provoking the students’ study interests and enriching their learning contents. Meanwhile, some advanced learning methods such as analogical learning and integrated learning (linking theory with practice) can be also shown to them. Modern techniques can be used as teaching materials for all levels of education, including the teaching on the students in junior high school. Certainly, they can be also utilized as school-based training materials to their teachers for personal individual developments. Keywords—Association learning; Electrospraying; Junior high school; School subjects
A SYSTEMIC STUDY OF MONETARY SYSTEMS

Abstract Self-organizing systems are defined as able to change their structure, according to need, within specific equivalence classes. Once hierarchical levels and their value functions are assigned, requirements of invariance under transformations within an equivalence class can be used as a principle to determine the population of each level. This program is carried out in complete detail for the monetary system. It has been possible to deduce the distribution law that specifies how many “coins” for each level must stay in circulation; this law agrees well with empirically observed data from about ten different countries. It is also possible to understand the processes of reorganization of monetary systems induced by inflation, i.e. the disappearance of coins of low value and the simultaneous issue of coins or higher value.
Transverse impedance of tapered transitions with elliptical cross section

We study the transverse geometric impedance of elliptical cross-section tapers in the lowfrequency ‘‘inductive regime. ’’ We have followed a dual approach: computer simulations have been carried out using the finite element electromagnetic code GDFIDL and analytic results for the dipolar and quadrupolar components of the impedance have been derived extending a perturbation technique introduced by Stupakov. Our work provides new insight into the behavior of the impedance of axially asymmetric tapered structures at low frequency. In particular, we clarify the frequency range characterizing the inductive regime, suggesting new criteria relating the extent of the inductive regime for dipolar and quadrupolar components of the impedance to the dimensions of the minimal cross section of a tapered transition.
Swarat Chaudhuri " Panda " " Gibbon " perturbation perturbation " How are you ?

In recent years, the notion of local robustness (or robustness for short) has emerged as a desirable property of deep neural networks. Intuitively, robustness means that small perturbations to an input do not cause the network to performmisclassifications. In this paper, we present a novel algorithm for verifying robustness properties of neural networks. Our method synergistically combines gradient-based optimization methods for counterexample search with abstraction-based proof search to obtain a sound and (δ -)complete decision procedure. Our method also employs a data-driven approach to learn a verification policy that guides abstract interpretation during proof search. We have implemented the proposed approach in a tool called Charon and experimentally evaluated it on hundreds of benchmarks. Our experiments show that the proposed approach significantly outperforms three state-of-the-art tools, namely AI2, Reluplex, and Reluval. CCS Concepts • Theory of computation → Abstraction; • Computing methodologies → Neural networks;
Correlation Estimation Using Concomitants of Order Statistics from Bivariate Normal Samples

We assume (X, Y) has a bivariate normal distribution with all the five parameters unknown and that the data consist of the Y values and the ranks of associated X values generated from a random sample of size n. Our goal is to investigate the estimators of the correlation coefficient based on this type of incomplete bivariate sample. We consider several estimators and use simulation to examine their properties and obtain their estimated relative efficiencies. We show that an estimator based on ratios of linear functions of concomitants of order statistics and their order statistics is highly efficient.
Distance estimates to five open clusters based on 2mass data of red clump giants

Abstract Red clump (RC) giants are excellent standard candles in the Milky Way and the Large Magellanic Cloud. The near-infrared K-band intrinsic luminosity of RC giants exhibits only a small variance and a weak dependence on chemical composition and age. In addition, RCs are often easily recognizable in the color–magnitude diagrams of open clusters, which renders them extremely useful distance indicators for some intermediate-age or old open clusters. Here we determine the distance moduli of five Galactic open clusters covering a range of metallicities and ages, based on RC giants in the cluster regions using 2mass photometric data. We compare our result with those from main-sequence fitting and also briefly discuss the advantages and disadvantages of RC-based cluster distance determination.
Quantitative study of interface roughness replication in multilayers using x‐ray reflectivity and transmission electron microscopy

The recently appeared distorted wave Born approximation formalism is used for quantitative determination of interface roughness replication and lateral correlation length in periodical multilayered structures. The results obtained from x‐ray diffraction are in very good agreement with analysis of cross‐section transmission electron micrographs. We interpret transparently the obtained parameters and demonstrate the ability of the low‐angle x‐ray diffraction methodology for nondestructive and quantitative studying of interface roughness in magnetic multilayers.
A least squares method for fitting head fields by parametric equations

Models of magnetic recording systems generally require the field of the record head to be calculated. In the interests of speed a simple, but accurate, analytic expression is desirable. In this paper the method of minimization of squared residuals is used to obtain parameters defining a parametric approximation to the head field. As an example parameters are obtained which give best fits to finite pole tip head fields produced by conformal mapping. It is found that a good set of parameters is obtained by separately characterizing the infinite pole length head field and correction terms due to the outer pole edges evaluated at the medium surface. The same method could be used to fit measured data or fields obtained using numerical models. >
Course Selection of Students Based on Collaborative Filtering

The credit system is the need of higher education development. It is the basis and core of the credit system. Therefore, it is necessary to establish a reasonable course recommendation system. Collaborative filtering is a method of group intelligence, which has been successfully applied in many fields such as electronic commerce, video recommendation, etc. A model to recommend the curriculum is established to guide students to choose the right course to improve the learning effect based on a large number of students grades in the educational management system, and that combined with collaborative filtering recommendation technology to find the students who may not pass and give any help as soon as possible, so these improve the level of management of students in the school effectively and lay a solid foundation for improving the quality of teaching. The method is applied to the prediction of student grades, the results show that the absolution deviations between predicted and actual values are within 5. Keywords—Collaborative Filtering; Credit System; Course Selection; Student Management; MAE
Size measurement of a pure phase object

The detection of a transparent object is a technical challenge since phase objects yield only poor contrast if they are imaged on an intensity basis. For performing quantitative measurement the image contrast has to be enhanced. For that, we can exploit additional information on phase or polarisation modifications of the laser probe beam (LPB) crossing through the phase object. We propose a simple method for determining the size of a transparent object based on the reshaping of a laser probe beam which is initially Gaussian in shape. For a given ratio between the size of the incident beam and that of the phase object, the diffracted laser probe beam is transformed in the far-field region into a hollow beam. The detection of the intensity dip in the beam centre is made with a simple photodiode. In practice, the spatial reshaping of the LPB is monitored through the resulting changes in the power transmitted by a pinhole and a stop (opaque disk) set in the far-field of the phase object under study. For convenience, the latter in the experiment is realised by a Spatial Light Modulator (SLM: Holoeye Pluto-NIR). We have considered the influence of various parameters which are the lateral and longitudinal sizes of the phase object, and the pinhole and the stop distances from the phase object under study. The experiment has demonstrated the feasibility of our method and can be extended for the detection of microscopic phase objects. The potential of the proposed technique for quantifying the nanoscale change of the phase object under study could be very useful to study the morphology dynamics of living cells membrane which represents the biophysical properties and health state of the cell.
Radiative Transition Rates in the Ground Configuration of the Phosphorus Sequence from Argon to Ruthenium

New calculations of transition probabilities are presented for forbidden lines in the ground configuration of the phosphorus sequence from Ar to Ru. Relativistic contributions and configuration interaction effects were included in the framework of the HXR and HFR self-consistent-field methods. Energy levels and A values were computed in intermediate coupling with fitted or interpolated semi-empirical energy parameters. The variation in magnetic dipole and electric quadrupole oscillator strengths as a function of Z is extended beyond nickel to Z = 44.
A numerical method to analyze the interaction between sea waves and rubble mound emerged breakwaters

The paper provides some results of a new procedure, developed by MEDUS, to analyze the hydrodynamic aspects of the interactions between maritime emerged breakwaters and waves, by integrating CAD and CFD software. The filtration of the fluid within the interstices of a concrete blocks breakwater is evaluated by integrating the Reynolds Averaged Navier-Stokes equations (RANS) inside the voids rather than making use of the widespread “porous mediaˮ approach. The structure is thus modelled, very much like in the real world or in the physical laboratory testing, by overlapping individual three-dimensional elements (Armour in Accropode, Core-loc or Xbloc, toe protection and filter layer in stones), and then the computational grid is fitted so as to provide enough computational nodes within the flow paths. This approach is meant to match closely the physical laboratory test procedure, and it is oriented at analyzing the hydrodynamic aspects of the phenomenon (overtopping, breaking, Run-up, reflection) as well as the stability of armour elements. Therefore, for the results' validation, the numerical Run-up and reflection effects on virtual breakwater were compared with some empirical formulas and some similar laboratory tests. Key-Words: CFD, Breakwater, Armour, Rubble Mound, Virtual Structures, Wave Run-Up, Wave Reflection, Wave Overtopping.
Approximate output tracking for nonlinear non-minimum phase systems with an application to flight control

An unstable zero-dynamics is a known obstruction to inducing exact asymptotic tracking for an open set of output trajectories with internal stability. This paper proposes a procedure for achieving approximate tracking for a nonlinear system whose linearization possesses real right-half plane zeros. The method is guaranteed to remove the right-half plane zeros while the other zeros remain in their previous location; moreover, it provides information on the class of signals for which good approximate tracking can be obtained. With other methods, the right-half plane zeros are eliminated but the final location of the remaining zeros is not known a priori. The design procedure is illustrated on a trajectory control problem of an aircraft in rapid manoeuvres. Simulations illustrate the computations involved and show that precise lateral and longitudinal manoeuvres can be performed, even in the presence of uncertainties.
Distress of Educators Teaching Nursing Students with Potential Learning Disabilities: A Qualitative Analysis

Clinical training at Japanese nursing universities has an increasing need for individualized learning support for students with potential learning disabilities. Despite a high interest in student support, educators’ difficulties are neglected. This study clarified the difficulties encountered by practical training instructors in delivering clinical training to nursing students with potential learning disabilities. In this descriptive, qualitative study, online focus group interviews were conducted. Participants were nine Japanese nursing university graduates with over five years of clinical education experience. A total of five categories were extracted: searching for measures tailored to students in a short period of time during training; resistance to individualized responses that significantly differ from traditional Japanese collectivist education; conflict over support being perceived as favoring a particular student; hesitation to identify students’ limits; and barriers in the process of supporting difficulties due to the nature of learning disabilities. Practical training instructors experience difficulties and hesitation when teaching students with potential learning disabilities. The practical training instructors need support and educational opportunities as well as students who need help. To overcome these difficulties, university educational staff, as well as students and families, must be educated on the existence and value of support tailored to the characteristics of an individual’s learning disability.
Integrating Sparse Learning-Based Feature Detectors into Simultaneous Localization and Mapping—A Benchmark Study

Simultaneous localization and mapping (SLAM) is one of the cornerstones of autonomous navigation systems in robotics and the automotive industry. Visual SLAM (V-SLAM), which relies on image features, such as keypoints and descriptors to estimate the pose transformation between consecutive frames, is a highly efficient and effective approach for gathering environmental information. With the rise of representation learning, feature detectors based on deep neural networks (DNNs) have emerged as an alternative to handcrafted solutions. This work examines the integration of sparse learned features into a state-of-the-art SLAM framework and benchmarks handcrafted and learning-based approaches by comparing the two methods through in-depth experiments. Specifically, we replace the ORB detector and BRIEF descriptor of the ORBSLAM3 pipeline with those provided by Superpoint, a DNN model that jointly computes keypoints and descriptors. Experiments on three publicly available datasets from different application domains were conducted to evaluate the pose estimation performance and resource usage of both solutions.
Intolerance of Uncertainty and Social Anxiety: An Experimental Investigation

Abstract Intolerance of uncertainty (IU) is a cognitive bias that leads to perception and intolerance of uncertainty and has associated negative cognitive, emotional, and behavioural responses. It plays a strong role in social anxiety disorder (SAD; Counsell et al., 2017). Our experimental study examined the impact of uncertainty related to a social stressor on SAD using a speech task. We examined features of SAD including anticipatory anxiety, anxiety during the task, willingness to perform the task, and avoidance of the task. Undergraduate students (N = 110, 88% female) with significant social anxiety completed a series of questionnaires, then were randomised to one of two conditions related to level of uncertainty about an impromptu speech task. The experimental condition (state IU) did not predict any of the outcome variables, while trait IU significantly predicted anxiety levels. Results indicate that increased uncertainty of a social situation does not impact acute anxiety levels in SAD and reinforce the strong role of trait IU as a transdiagnostic cognitive variable. Neither trait nor state IU predicted the willingness and avoidance variables. Results also highlighted the central role of the experience of anxiety on avoidance behaviours, above cognitive factors such as IU.