Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement of dC vector analyzing power and cross sections at COSY for EDM polarimetry

The JEDI (Jülich Electric Dipole moment Investigations) collaboration performs a set of experiments at the COSY storage ring of the Forschungszentrum Jülich in Germany, within the R&D phase to search for the Electric Dipole Moments (EDMs) of charged particles. A measurement of proton and deuteron EDMs is a sensitive probe of yet unknown CP violation. An EDM observation would also be an indication for physics beyond the Standard Model. The method of charged particle EDM search will exploit stored polarized beams in order to observe a miniscule rotation of the polarization axis as a function of time due to the interaction of a finite EDM with large electric fields. Key challenge is the provision of a sensitive and efficient method to determine the tiny change of the beam polarization. Elastic scattering of the beam particles on carbon nuclei will provide the polarimetry reaction. For this reason and as an input for future Monte-Carlo simulations, a good knowledge of the vector analyzing power and the unpolarized elastic cross section of deuterons scattered off a carbon target is very important to be able to determine the deuteron polarization. Over the course our experiment, the analyzing power and the differential cross section was measured using six different beam energies starting from 170 MeV up to 380 MeV deuterons.
A computerized image analysis framework for dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with applications to breast cancer

OF THE DISSERTATION A Computerized Image Analysis Framework for Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) with Applications to Breast Cancer by Shannon Christine Agner Dissertation Director: Anant Madabhushi Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides a wealth of information about the anatomy of the breast, particularly in the setting of breast cancer diagnosis. In addition to the images it provides regarding the architecture of breast tissue, it also provides functional information about blood flow by means of the DCE study. The sensitivity of DCE-MRI has been reported at close to 100%, so the difficult tasks for the radiologist in reviewing breast DCE-MRI are: (1) discerning between which lesions are benign and which are malignant; and (2) doing so for a patient study that involves hundreds of images and is 4-dimensional. Because of the great detail and volume of information DCE-MRI provides, computational methods for both extracting and analyzing information derived from the images are useful in distilling the entire patient study down to the most salient images and features for the radiologist to examine. In this dissertation, computer-based methods developed for analyzing the data acquired in a breast DCE-MRI patient study are described. In the first part, pre-processing methods used for aligning the images of the timedependent DCE study are explained. Because segmentation is important for describing
A Microsystem and Model for Continuous Immunomagnetic Cell Sorting

We present a magnetically-biased microfluidic system concept for sorting magnetically labeled cells from unlabeled biomaterial. The microsystem consists of two inlets that feed respective microchannels that terminate at separate outlets. Labeled and unlabeled cells flow into the system through one inlet/channel, and the labeled cells are sorted into the other channel by the magnetic force provided by an integrated soft-magnetic element. We study cell transport in the microsystem using a model that takes into account the magnetic, fluidic and gravitational forces on the cells. We apply the model to a specific microsystem design and study the sorting of magnetically labeled leukocytes. Our analysis indicates that the system is capable of rapid and efficient sorting.
HIV-Related Stigmatization in Treatment Settings: Effects on Patient Comfort, Risk Disclosure, and Treatment Decisions

The major focus for the present study was to examine the effects of provider stigmatization on the medical care of HIV+ patients, by using an experimental paradigm and examining a conceptual framework to clarify the relationship between provider stigmatization and negative treatment outcomes. Initial qualitative findings from focus groups (n = 18) indicated that several key elements of stigmatizing treatment experiences included judgmental and condescending language, patient avoidance, increased physical distance between patient and provider during conversations and procedures, and use of extra, unnecessary precautions (e.g. use of extra gloves, masks). These provider behaviors were experimentally manipulated and incorporated into computerized vignettes containing audio and visual stimuli depicting “typical” medical appointments. In the experimental phase, participants (n = 90) were randomly assigned to view either a highly stigmatizing or a non-stigmatizing treatment vignette and then subsequently rate their willingness to engage in HIV care. Findings indicated that patients assigned to the highly stigmatizing condition were the most unwilling to engage in HIV care as demonstrated in lower intentions to remain in care, disclose sexual and substance use risk behaviors, and discuss medication adherence difficulties. As hypothesized, the effect of the experimental stigma condition on patients’ willingness to engage in care was mediated by patients’ feelings of comfort and their perceptions of stigma within the patient-provider interaction. Findings from the present study may help to inform the development of interventions to assist healthcare providers in creating more positive treatment experiences for their HIV+ patients to improve implementation of self care and reduction
Another type of dimensions of modules and rings

Abstract We say that a class Q of left R-modules is a monic class if a nonzero submodule of a module in Q is also a module in Q. For a monic class Q, we define a Q-dimension of modules that measures how far modules are from the modules in Q. For a monic class Q of indecomposable modules we characterize rings whose modules have Q-dimension. We prove that for an artinian principal ideal ring the Q-dimension coincides with the uniserial dimension. We also characterize when every module has Q-dimension.
A Meshless WCSPH Boundary Treatment for Open-Channel Flow over Small-Scale Rough Bed

A weakly compressible smoothed particle hydrodynamics (WCSPH) method was developed to model open-channel flow over rough bed. An improved boundary treatment is proposed to quantitatively characterize bed roughness based on the ghost boundary particles (GBPs). In this model, the velocities of GBPs are explicitly calculated by using evolutionary polynomial regression with a multiobjective genetic algorithm. The simulation results show that the proposed boundary treatment can well reflect the influence of wall roughness on the vertical flow structure. A fully developed open channel is established, and its flume length, processing time, and turbulent model are discussed. The mixed-length-based subparticle scale (SPS) turbulence model is adopted to simulate uniform flow in open channel, and this model is compared with the Smagorinsky-based one. For the modified WCSPH model, the results show that the calculated vertical velocity and turbulent shear stress distribution are in good agreement with experimental data and fit better than the calculations obtained from the traditional Smagorinsky-based model.
Analysis and Optimization of Task Granularity on the Java Virtual Machine

Task granularity, i.e., the amount of work performed by parallel tasks, is a key performance attribute of parallel applications. On the one hand, fine-grained tasks (i.e., small tasks carrying out few computations) may introduce considerable parallelization overheads. On the other hand, coarse-grained tasks (i.e., large tasks performing substantial computations) may not fully utilize the available CPU cores, leading to missed parallelization opportunities. In this article, we provide a better understanding of task granularity for task-parallel applications running on a single Java Virtual Machine in a shared-memory multicore. We present a new methodology to accurately and efficiently collect the granularity of each executed task, implemented in a novel profiler (available open-source) that collects carefully selected metrics from the whole system stack with low overhead, and helps developers locate performance and scalability problems. We analyze task granularity in the DaCapo, ScalaBench, and Spark Perf benchmark suites, revealing inefficiencies related to fine-grained and coarse-grained tasks in several applications. We demonstrate that the collected task-granularity profiles are actionable by optimizing task granularity in several applications, achieving speedups up to a factor of 5.90×. Our results highlight the importance of analyzing and optimizing task granularity on the Java Virtual Machine.
Representing Rape Trauma in Film: Moving beyond the Event

Trauma theorists foreground the unrepresentability of trauma; however, with modern innovations in visual representation, such as the photograph and cinema, depictions of trauma have begun to circulate across different mediums for a variety of audiences. These images tend to problematically present the traumatic event rather than the effects of trauma, such as traumatic memory. Specifically, some contemporary Hollywood popular films and television series that include rape as their subject matter often include a rape scene that can evoke affects such as disgust or empathy, and while these affects can last the duration of the film, they fail to shift popular discourses about rape because affect is more productive when it focuses on effects instead of events. As trauma studies has shifted to memory studies in the Humanities, and rape has become more prominent in popular culture through the circulation of personal testimony on social media and memoir, depictions of rape in cinema have slowly started to change from presentations of rape scenes to representations of rape trauma that highlight different affects, such as shame. Using Monster (2003), Girl with the Dragon Tattoo (2011), Room (2015), and the television series, 13 Reasons Why (2017) and Sharp Objects (2018) as case studies, this paper argues that, for an audiovisual depiction of rape to shift popular discourses about rape, it would have to function rhetorically to widen the cultural understanding of rape trauma beyond the event, and demonstrate that rape trauma should be understood as part of the personal, unconscious, cultural, and visual mediation of traumatic memory.
Ship detection from infrared video

The ship detection in infrared video has wide application value in fishery administration, port monitoring and other fields. Traditional background modeling methods, such as GMM(Gaussian mixture model), Codebook, and ViBe, will make more false detection in the ship detection from the infrared ocean video because of the impact of the waves. The paper proposes a new algorithm to detect ships in the infrared ocean video. The algorithm framework adopts the Top-Hat operation to preprocess the infrared image to filter the clutter effectively, then improves Vibe algorithm to detect the moving ship target. Experimental results show that the method can effectively suppress the background noise and get better detection results.
Verification of a Motion Cueing Strategy for Stall Recovery Training in a Commercial Transport Simulator

This paper veriﬁes a motion cueing strategy for improved pilot stall recovery training in commercial transport simulators. Eight airline transport pilots ﬂew a high-altitude stall recovery task in the NASA B747 level-D-certiﬁed full ﬂight simulator under three diﬀerent motion conﬁgurations: no motion, baseline motion, and enhanced motion. For each motion condition, pilots performed the task with both baseline aircraft dynamics and aircraft dynamics enhanced with lateral-directional characteristics of the airplane at angle of attack approaching stall. Motion conﬁguration signiﬁcantly aﬀected: 1) pilot opinions on the helpfulness of motion in performing the task, 2) the maximum roll angle in the stall maneuver, 3) the minimum load factor in the recovery, 4) the number of secondary stick shakers in the stall recovery, and 5) the maximum airspeed in the recovery. The two diﬀerent aircraft dynamics signiﬁcantly aﬀected: 1) pilot opinions on the noticeability of the banking roll oﬀ near the stall and 2) the maximum roll angle in the stall maneuver. These results indicate that the relatively minor enhancements to the motion logic of heritage commercial transport simulators presented here can signiﬁcantly improve pilot performance in simulated stall recoveries, and potentially improve stall recovery training.
CPW-FED ULTRA-WIDEBAND DUAL-SENSE CIRCULARLY POLARIZED SLOT ANTENNA

The paper presents a new coplanar waveguide (CPW)-fed ultra-wideband (UWB) dual circularly polarized (CP) slot antenna. For realizing UWB, a wide slot is introduced in the ground plane of the proposed antenna. The circular polarization is achieved by introducing a semi-circular stub in the square ground plane. The antenna contains two symmetrical CPW-fed ports at left and right edges to generate dual circular polarization. The evolution steps of the proposed CP antenna are presented, and antenna parameters are optimized to obtain the desired level of isolation, return loss, and axial ratio bandwidth (ARBW). The measured impedance bandwidth (S11 ≤ −10 dB) of the antenna is 13.5 GHz (2.5–16 GHz); 3-dB ARBW is 75.23% (2.67–5.89 GHz); and isolation greater than 17 dB is obtained in the CP band. The designed dual feed CP antenna has low profile, light weight, compact size, and could be suitable for polarization diversity applications for reducing the effect of multipath fading.
Automated discovery of privacy violations on the web

Online tracking is increasingly invasive and ubiquitous. Tracking protection provided by browsers is often ineffective, while solutions based on voluntary cooperation, such as Do Not Track, haven’t had meaningful adoption. Knowledgeable users may turn to anti-tracking tools, but even these more advanced solutions fail to fully protect against the techniques we study. In this dissertation, we introduce OpenWPM, a platform we developed for flexible and modular web measurement. We’ve used OpenWPM to run large-scale studies leading to the discovery of numerous privacy violations across the web and in emails. These discoveries have curtailed the adoption of tracking techniques, and have informed policy debates and browser privacy decisions. In particular, we present novel detection methods and results for persistent tracking techniques, including: device fingerprinting, cookie syncing, and cookie respawning. Our findings include sophisticated fingerprinting techniques never before measured in the wild. We’ve found that nearly every new API is misused by trackers for fingerprinting. The misuse is often invisible to users and publishers alike, and in many cases was not anticipated by API designers. We take a critical look at how the API design process can be changed to prevent such misuse in the future. We also explore the industry of trackers which use PII-derived identifiers to track users across devices, and even into the offline world. To measure these techniques, we develop a novel bait technique, which allows us to spoof the presence of PII on a large number of sites. We show how trackers exfiltrate the spoofed PII through the abuse of browser features. We find that PII collection is not limited to the web—the act of viewing an email also leaks PII to trackers. Overall, about 30% of emails leak the recipient’s email address to one or more third parties. Finally, we study the ability of a passive eavesdropper to leverage tracking cookies for mass surveillance. If two web pages embed the same tracker, then the adversary iii can link visits to those pages from the same user even if the user’s IP address varies. We find that the adversary can reconstruct 62—73% of a typical user’s browsing history.
Clustering of extremely red objects in the AKARI NEP-deep field

We study the clustering property of extremely red objects (EROs) using Canada–France–Hawaii Telescope (CFHT) surveys with 0.55 deg2 in the AKARI north ecliptic pole (NEP) deep field. EROs are selected by the color criterion of r′ − Ks > 3.66, which is equivalent to (R − Ks)Vega > 5. We conducted the clustering analysis for two magnitude-limited cases, Ks < 20.3 (N = 363) and Ks < 20.9 (N = 727), using two-point angular correlation represented by a single power-law function. By fixing a power-law (with 0.8), the correlation lengths of EROs with Ks < 20.3 and Ks < 20.9 are 9.10 ± 1.86 and 7.81 ± 1.21 h−1 Mpc, respectively. We find that bias factors of EROs with Ks < 20.3 and Ks < 20.9 are 3.19 ± 0.59 and 2.83 ± 0.40, respectively, revealing that EROs reside in dark matter halos heavier than $\sim 10^{13}\, M_{\odot }$. To investigate possible descendants of EROs with Ks < 20.9, we calculate how the bias for dark matter halos that host EROs evolves by accounting for mass growth of halos along the redshift. We find that halos hosting EROs evolve into halos hosting local massive galaxies with 2–$7\, L^{*}$. It suggests that passive EROs with Ks < 20.9 are likely to be progenitors of massive galaxies in the present universe. The comparison between passive EROs (pEROs) and star-forming EROs (sEROs) classified by near-infrared colors shows that pEROs seem to be connected with more massive local galaxies. By fitting spectral energy distributions (SEDs), we estimate active galactic nucleus (AGN) contribution for 68 sEROs which are selected in mid-IR bands. AGN contributions to the IR luminosity are less than $10\%$ except for six sEROs. At least in the IR-selected sEROs, the contribution of AGN seems to be not significant.
Challenges and Trends in Home Automation

Home automation (HA) systems can be considered as an implementation of the internet of everything (IoE) where many devices are linked by intelligent connections in order to improve the quality of life at home. This chapter is dedicated to analyzing current trends and challenges in HA. Energy management, safer homes, and improved control over the house are some of the benefits of HA. However, privacy, security, social disruption, installation/maintenance issues, economic costs, market fragmentation, and low interoperability represent real problems of these IoE solutions. In this regard, the latest proposals in HA try to answer some of these needs with low-cost DIY solutions, wireless solutions, and IP-based HA systems. This chapter proposes a way to deal with the interoperability problem by means of the open-source platform openHAB. It is based on the concept of a home automation bus, an idea that enables the separation of the physical and the functional view of any device, allowing to create a technology-agnostic environment, which is perfect for addressing the interoperability problem.
Finite Element Modelling and updating of welded joint for dynamic study of exhaust structure

An exhaust structure is experienced dynamic loads caused by engine operational and road surface condition that affected its durability and dynamic performance. Hence, the purpose of this study is to perform finite element (FE) modelling of exhaust structure and the used of updating approach to improve its dynamic behaviour. Due to its design, exhaust structure is built-up from several parts connected with welded joints. These welded joints significantly contribute to the dynamic behaviour of the structure. Four types of element connector that are RBE2, CBAR, CBEAM and CELAS have been used to replicate FE model of welded joint on the structure. Modal parameters (natural frequency and mode shape) of the FE model have been obtained from normal mode analysis using finite element analysis (FEA) software, MSC. Nastran/Patran. The precision of numerical predicted result from FEA is compared with its measured counterpart. The measured test data obtained through experimental modal analysis (EMA) using impact hammer and roving accelerometers under free-free boundary conditions. Under correlation process, CBAR element connector was chosen to model the welded joint due to its accurate prediction of natural frequency and contains updating parameters. FE model updating process was performed to improve the correlation between EMA and FEA. Ahead of updating process, sensitivity analysis was done to select the most sensitive updating parameter. As a result, total percentage error of natural frequency for updated CBAR model is reduced significantly from 8.74 % to 3.45 %. Consequently, CBAR element connector was chosen as the most reliable joint element in FE model to represent welded joint on exhaust structure.
Modelling of Lips Movement from Facial Muscles Electromyography Signal and Its Application to Pronunciation Training

We have been developing the pronunciation training system, in which visual instruction about the correct articulation are shown. These instructions are produced based on the formants of speech signal and show the shape of articulator to the learners. They work effectively, but more comprehensible instruction on how to move the articulator is required. We think that the facial muscles that move the articulator are useful to such the instruction. In this report, we attempt to construct lips movement model representing the relationship between the facial muscles activity and the lips movement and discuss the application of this model to pronunciation training.
Physics‐constrained non‐Gaussian probabilistic learning on manifolds

An extension of the probabilistic learning on manifolds (PLoM), recently introduced by the authors, has been presented: In addition to the initial data set given for performing the probabilistic learning, constraints are given, which correspond to statistics of experiments or of physical models. We consider a non‐Gaussian random vector whose unknown probability distribution has to satisfy constraints. The method consists in constructing a generator using the PLoM and the classical Kullback‐Leibler minimum cross‐entropy principle. The resulting optimization problem is reformulated using Lagrange multipliers associated with the constraints. The optimal solution of the Lagrange multipliers is computed using an efficient iterative algorithm. At each iteration, the Markov chain Monte Carlo algorithm developed for the PLoM is used, consisting in solving an Itô stochastic differential equation that is projected on a diffusion‐maps basis. The method and the algorithm are efficient and allow the construction of probabilistic models for high‐dimensional problems from small initial data sets and for which an arbitrary number of constraints are specified. The first application is sufficiently simple in order to be easily reproduced. The second one is relative to a stochastic elliptic boundary value problem in high dimension.
Tunnel ionization of diatomic atmospheric gases (N2, O2) by laser radiation

We present the results of calculation of the rates of tunnel ionization of N2 and O2 molecules from the ground and excited vibrational states by linearly polarized laser radiation. These data are necessary for the theoretical description of filamentation. For N2, we consider ionization from the and shells, which give comparable contributions. For O2, we consider ionization from both the ground and excited electronic terms. We demonstrate that for N2, the ionization rate is maximum when the electric field vector of laser radiation is directed along the molecular axis (for shell) or perpendicular to it (for shell), whereas for the O2 molecule, for both electronic states considered, the rates have maxima when the angle between the electric field and molecular axis is equal to 45°.