Miracle-dz/UniFAR-FTUs huggingface dataset:
Using real‐world data to predict health outcomes—The prediction design: Application and sample size planning

The gold standard for investigating the efficacy of a new therapy is a (pragmatic) randomized controlled trial (RCT). This approach is costly, time‐consuming, and not always practicable. At the same time, huge quantities of available patient‐level control condition data in analyzable format of (former) RCTs or real‐world data (RWD) are neglected. Therefore, alternative study designs are desirable. The design presented here consists of setting up a prediction model for determining treatment effects under the control condition for future patients. When a new treatment is intended to be tested against a control treatment, a single‐arm trial for the new therapy is conducted. The treatment effect is then evaluated by comparing the outcomes of the single‐arm trial against the predicted outcomes under the control condition. While there are obvious advantages of this design compared to classical RCTs (increased efficiency, lower cost, alleviating participants’ fear of being on control treatment), there are several sources of bias. Our aim is to investigate whether and how such a design—the prediction design—may be used to provide information on treatment effects by leveraging external data sources. For this purpose, we investigated under what assumptions linear prediction models could be used to predict the counterfactual of patients precisely enough to construct a test and an appropriate sample size formula for evaluating the average treatment effect in the population of a new study. A user‐friendly R Shiny application (available at: https://web.imbi.uni‐heidelberg.de/PredictionDesignR/) facilitates the application of the proposed methods, while a real‐world application example illustrates them.
Postoperative optimization of cochlear implantation for single sided deafness and asymmetric hearing loss: a systematic review

Objective Identify and evaluate the effectiveness of methods for improving postoperative cochlear implant (CI) hearing performance in subjects with single-sided deafness (SSD) and asymmetric hearing loss (AHL). Data Sources Embase, PubMed, Scopus. Review Methods Systematic review and narrative synthesis. English language studies of adult CI recipients with SSD and AHL reporting a postoperative intervention and comparative audiometric data pertaining to speech in noise, speech in quiet and sound localization were included. Results 32 studies met criteria for full text review and 6 (n = 81) met final inclusion criteria. Interventions were categorized as: formal auditory training, programming techniques, or hardware optimization. Formal auditory training (n = 10) found no objective improvement in hearing outcomes. Experimental CI maps did not improve audiologic outcomes (n = 9). Programed CI signal delays to improve synchronization demonstrated improved sound localization (n = 12). Hardware optimization, including multidirectional (n = 29) and remote (n = 11) microphones, improved sound localization and speech in noise, respectively. Conclusion Few studies meeting inclusion criteria and small sample sizes highlight the need for further study. Formal auditory training did not appear to improve hearing outcomes. Programming techniques, such as CI signal delay, and hardware optimization, such as multidirectional and remote microphones, show promise to improve outcomes for SSD and AHL CI users.
The diverging role of CDC14B: from mitotic exit in yeast to cell fate control in humans

CDC14, originally identified as crucial mediator of mitotic exit in budding yeast, belongs to the family of dual‐specificity phosphatases (DUSPs) that are present in most eukaryotes. Contradicting data have sparked a contentious discussion whether a cell cycle role is conserved in the human paralogs CDC14A and CDC14B but possibly masked due to redundancy. Subsequent studies on CDC14A and CDC14B double knockouts in human and mouse demonstrated that CDC14 activity is dispensable for mitotic progression in higher eukaryotes and instead suggested functional specialization. In this review, we provide a comprehensive overview of our current understanding of how faithful cell division is linked to phosphorylation and dephosphorylation and compare functional similarities and divergences between the mitotic phosphatases CDC14, PP2A, and PP1 from yeast and higher eukaryotes. Furthermore, we review the latest discoveries on CDC14B, which identify this nuclear phosphatase as a key regulator of gene expression and reveal its role in neuronal development. Finally, we discuss CDC14B functions in meiosis and possible implications in other developmental processes.
Aspects of M-theory and quantum information

As the frontiers of physics steadily progress into the 21st century we should bear in mind that the conceptual edifice of 20th-century physics has at its foundations two mutually incompatible theories; quantum mechanics and Einstein’s general theory of relativity. While general relativity refuses to succumb to quantum rule, black holes are raising quandaries that strike at the very heart of quantum theory. M-theory is a compelling candidate theory of quantum gravity. Living in eleven dimensions it encompasses and connects the five possible 10-dimensional superstring theories. However, Mtheory is fundamentally non-perturbative and consequently remains largely mysterious, offering up only disparate corners of its full structure. The physics of black holes has occupied centre stage in uncovering its non-perturbative structure. The dawn of the 21st-century has also played witness to the birth of the information age and with it the world of quantum information science. At its heart lies the phenomenon of quantum entanglement. Entanglement has applications in the emerging technologies of quantum computing and quantum cryptography, and has been used to realize quantum teleportation experimentally. The longest standing open problem in quantum information is the proper characterisation of multipartite entanglement. It is of utmost importance from both a foundational and a technological perspective. In 2006 the entropy formula for a particular 8-charge black hole appearing in M-theory was found to be given by the ’hyperdeterminant’, a quantity introduced by the mathematician Cayley in 1845. Remarkably, the hyperdeterminant also measures the degree of tripartite entanglement shared by three qubits, the basic units of quantum information. It turned out that the different possible types of three-qubit entanglement corresponded directly to the different possible subclasses of this particular black hole. This initial observation provided a link relating various black holes and quantum information systems. Since then, we have been examining this two-way dictionary between black holes and qubits and have used our knowledge of M-theory to discover new things about multipartite entanglement and quantum information theory and, vice-versa, to garner new insights into black holes and M-theory. There is now a growing dictionary, which translates a variety of phenomena in one language to those in the other. Developing these fascinating relationships, exploiting them to better understand both M-theory and quantum entanglement is the goal of this thesis. In particular, we adopt the elegant mathematics of octonions, Jordan algebras and the Freudenthal triple system as our guiding framework. In the course of this investigation we will see how these fascinating algebraic structures can be used to quantify entanglement and define new black hole dualities.
ATMOSPHERIC CHARACTERIZATION OF GIANT EXOPLANETS IN EXTREME ENVIRONMENTS

Title of dissertation: ATMOSPHERIC CHARACTERIZATION OF GIANT EXOPLANETS IN EXTREME ENVIRONMENTS Ashlee Wilkins, Doctor of Philosophy, 2017 Dissertation directed by: Professor Drake Deming Department of Astronomy The study of planets around other stars has entered a science-rich era of characterization, in which detailed information about individual planets can be inferred from observations beyond discovery and confirmation, which only yield bulk properties like mass or radius. Characterization probes more revealing quantities such as chemical abundances, albedo, and temperature/pressure profiles, allowing us to address larger questions of planet formation mechanisms, planetary evolution, and, eventually, presence of biosignature gases. The primary method for characterization of close-in planets is transit spectroscopy. My dissertation comprises transiting exoplanet case studies using the Hubble Space Telescopes Wide-Field Camera-3 (HST /WFC3) as a tool of exoplanet characterization in a near-infrared band dominated by broad water absorption. Much of my efforts went toward a characterization of the WFC3 systematic effects that must be mitigated to extract the incredibly small (tens to 200 parts per million) signals. The case study subjects in this dissertation are CoRoT-2b (in emission), WASP-18b (in transmission and emission), and HATS-7b (in transmission), along with some partial/preliminary analyses of HAT-p-3b and HD 149026b (both in transmission). I also present an analysis of transit timing of WASP-18b with HST and other observatories as another clue to its evolution as a close-in, extremely massive planet purported to be spiraling in to its host star. The five planets range from super Neptunes to Super-Jupiter in size/mass. The observability of such planets – i.e. giants across a continuum of mass/size in extreme local environments close to their respective host stars, – is a unique opportunity to probe planet formation and evolution, as well as atmospheric structures in a high-irradiation environment. This genre of observations reveal insights into aerosols in the atmosphere; clouds and/or hazes can significantly impact atmospheric chemistry and observational signatures, and the community must better understand the phenomenon of aerosols in advance of the next generation of space observatories, including JWST and WFIRST. In conducting these case studies as part of larger collaborations and HST observing campaigns, my work aids in the advancement of exoplanet atmosphere characterization from single, planetby-planet, case studies, to an understanding of the large, hot, gaseous planets as a population. Atmospheric Characterization of Giant Exoplanets in Extreme Environments
Forecasting the Contribution of Polarized Extragalactic Radio Sources in CMB Observations

We combine the latest data sets obtained with different surveys to study the frequency dependence of polarized emission coming from extragalactic radio sources (ERS). We consider data over a very wide frequency range starting from 1.4 GHz up to 217 GHz. This range is particularly interesting since it overlaps the frequencies of the current and forthcoming cosmic microwave background (CMB) experiments. Current data suggest that at high radio frequencies (ν ≥ 20 GHz) the fractional polarization of ERS does not depend on the total flux density. Conversely, recent data sets indicate a moderate increase of polarization fraction as a function of frequency, physically motivated by the fact that Faraday depolarization is expected to be less relevant at high radio frequencies. We compute ERS number counts using updated models based on recent data, and we forecast the contribution of unresolved ERS in CMB polarization spectra. Given the expected sensitivities and the observational patch sizes of forthcoming CMB experiments, about ∼200 (up to ∼2000) polarized ERS are expected to be detected. Finally, we assess that polarized ERS can contaminate the cosmological B-mode polarization if the tensor-to-scalar ratio is <0.05 and they have to be robustly controlled to de-lens CMB B-modes at the arcminute angular scales.
Human Histology after Structure Preservation Cochlear Implantation via Round Window Insertion

Current surgical techniques aim to preserve intracochlear structures during cochlear implant (CI) insertion to maintain residual cochlear function. The optimal technique to minimize damage, however, is still under debate. The aim of this study is to histologically compare insertional trauma and intracochlear tissue formation in humans with a CI implanted via different insertion techniques.
Development and verification of the Menopause Emotional Symptom Questionnaire

This study confirms that the novel Menopause Emotional Symptom Questionnaire is a valid tool for screening for and measuring emotional symptoms in menopausal women in Korea. Abstract Objective A detailed, well-validated scale for measuring emotional symptoms in menopausal women is lacking. We aimed to develop the Menopause Emotional Symptom Questionnaire (MESQ) and to confirm its reliability and validity among Koreans. Methods Eighteen primary items based on previous research results were selected using exploratory factor analysis and confirmatory factor analysis (CFA). New data, including answers to the novel MESQ, Menopause Rating Scale, Kupperman Index, Beck Depression Inventory-II, and Beck Anxiety Inventory, were collected from 200 perimenopausal women and 100 young men through a research company. Exploratory factor analysis and CFA were performed again to determine whether the MESQ accurately measures emotional symptoms in perimenopausal women. Receiver operating characteristic curve and k-means cluster analyses were used to identify the most appropriate cutoff value. Results The MESQ showed high internal consistency (Cronbach α = 0.926), and the CFA revealed that the factor structure comprised two subscales: nine items for mood/anxiety symptoms and four items for sleep symptoms. A high correlation between the total MESQ score and total scores of the existing scales was confirmed, indicating high convergence validity. Comparison of the mean MESQ scores between men and women showed significant sex difference, indicating secure known-group validity. The cutoff point of the total MESQ score between the high-risk and low-risk groups was 26. Conclusions The novel MESQ has high validity and reliability, and this study confirmed that the MESQ is a valid tool for screening for and measuring emotional symptoms in menopausal women in Korea.
Roles of auxin pathways in maize biology

Abstract Phytohormones play a central role in plant development and environmental responses. Auxin is a classical hormone that is required for organ formation, tissue patterning, and defense responses. Auxin pathways have been extensively studied across numerous land plant lineages, including bryophytes and eudicots. In contrast, our understanding of the roles of auxin in maize morphogenesis and immune responses is limited. Here, we review evidence for auxin-mediated processes in maize and describe promising areas for future research in the auxin field. Several recent transcriptomic and genetic studies have demonstrated that auxin is a key influencer of both vegetative and reproductive development in maize (namely roots, leaves, and kernels). Auxin signaling has been implicated in both maize shoot architecture and immune responses through genetic and molecular analyses of the conserved co-repressor RAMOSA ENHANCER LOCUS2. Polar auxin transport is linked to maize drought responses, root growth, shoot formation, and leaf morphogenesis. Notably, maize has been a key system for delineating auxin biosynthetic pathways and offers many opportunities for future investigations on auxin metabolism. In addition, crosstalk between auxin and other phytohormones has been uncovered through gene expression studies and is important for leaf and root development in maize. Collectively these studies point to auxin as a cornerstone for maize biology that could be leveraged for improved crop resilience and yield.
An Intelligent Rehabilitation Assessment Method for Stroke Patients Based on Lower Limb Exoskeleton Robot

The 6-min walk distance (6MWD) and the Fugl-Meyer assessment lower-limb subscale (FMA-LE) of the stroke patients provide the critical evaluation standards for the effect of training and guidance of the training programs. However, gait assessment for stroke patients typically relies on manual observation and table scoring, which raises concerns about wasted manpower and subjective observation results. To address this issue, this paper proposes an intelligent rehabilitation assessment method (IRAM) for rehabilitation assessment of the stroke patients based on sensor data of the lower limb exoskeleton robot. Firstly, the feature parameters of the patient were collected, including age, height, and duration, etc. The sensor data of the exoskeleton robot were also collected, including joint angle, joint velocity, and joint torque, etc. Secondly, a gait feature model was constructed to deduce the walking gait parameters of the patient according to the sensor data of the exoskeleton, including the support phase to swing phase ratio, step length and leg lift height of the patient, etc. Then, the 6MWD and FMA-LE values were collected by traditional methods, feature parameters, gait parameters and human-machine interaction parameters (joint torque) of the patient were adopted to train the rehabilitation assessment model. Finally, the assessment model was trained by a machine-learning based algorithm. The new stroke patients’ the 6MWD and FMA-LE values can be predicted by the trained model. The experimental results present that the prediction accuracy for the 6MWD and FMA-LE values reach to 85.19% and 92.66%, respectively.
Modeling fluid transport in 2d paper networks

Paper-based microfluidic devices offer great potential as a low-cost platform to perform chemical and biochemical tests. Commercially available formats such as dipsticks and lateral-flow test devices are widely popular as they are easy to handle and produce fast and unambiguous results. While these simple devices lack precise control over the flow to enable integration of complex functionality for multi-step processes or the ability to multiplex several tests, intense research in this area is rapidly expanding the possibilities. Modeling and simulation is increasingly more instrumental in gaining insight into the underlying physics driving the processes inside the channels, however simulation of flow in paper-based microfluidic devices has barely been explored to aid in the optimum design and prototyping of these devices for precise control of the flow. In this paper, we implement a multiphase fluid flow model through porous media for the simulation of paper imbibition of an incompressible, Newtonian fluid such as when water, urine or serum is employed. The formulation incorporates mass and momentum conservation equations under Stokes flow conditions and results in two coupled Darcy’s law equations for the pressures and saturations of the wetting and non-wetting phases, further simplified to the Richard’s equation for the saturation of the wetting fluid, which is then solved using a Finite Element solver. The model tracks the wetting fluid front as it displaces the non-wetting fluid by computing the time-dependent saturation of the wetting fluid. We apply this to the study of liquid transport in two-dimensional paper networks and validate against experimental data concerning the wetting dynamics of paper layouts of varying geometries.
Proximal Čech Complexes in Approximating Digital Image Object Shapes. Theory and Application

This article introduces proximal Cech complexes in approximating object shapes in digital images. The theo- retical framework is based on Cech complexes and proximity spaces. Several topological structures are defined for the Cech nerve based covers of a finite region of Euclidean plane. We define k -petals and k -corollas which are the generalizations of spokes and maximal nuclear clusters. We extend the classical notion of a proximity as a binary relation, to arbitrary number of sets. A new shape signature based on the distribution of orders of Cech nerves is defined. A practical application of this framework in approximating object shapes in digital images is given.
A Data-Driven Approach to Synthesizing Dynamics-Aware Trajectories for Underactuated Robotic Systems

We consider joint trajectory generation and tracking control for under-actuated robotic systems. A common solution is to use a layered control architecture, where the top layer uses a simplified model of system dynamics for trajectory generation, and the low layer ensures approximate tracking of this trajectory via feedback control. While such layered control architectures are standard and work well in practice, selecting the simplified model used for trajectory generation typically relies on engineering intuition and experience. In this paper, we propose an alternative data-driven approach to dynamicsaware trajectory generation. We show that a suitable augmented Lagrangian reformulation of a global nonlinear optimal control problem results in a layered decomposition of the overall problem into trajectory planning and feedback control layers. Crucially, the resulting trajectory optimization is dynamicsaware, in that, it is modified with a tracking penalty regularizer encoding the dynamic feasibility of the generated trajectory. We show that this tracking penalty regularizer can be learned from system rollouts for independently-designed low layer feedback control policies, and instantiate our framework in the context of a unicycle and a quadrotor control problem in simulation. Further, we show that our approach handles the sim-to-real gap through experiments on the quadrotor hardware platform without any additional training. For both the synthetic unicycle example and the quadrotor system, our framework shows significant improvements in both computation time and dynamic feasibility in simulation and hardware experiments.
COHERENT/INCOHERENT MAGNETIZATION DYNAMICS OF NANOMAGNETIC DEVICES FOR ULTRA-LOW ENERGY COMPUTING

xii Chapter 1: Introduction.1 1.1. Nanomagnetic Devices.2 1.2. Magnetostriction and Villari Effect.5 1.3. Single Domain Approximation Modeling of Magnetization Dynamics.5 1.4. Dipole Coupled Nanomagnetic Computing.10 1.5. Micromagnetic Modeling of Magnetization Dynamics.11 1.6. Polarized Neutron Reflectometry.14 1.7. Dissertation Outline.16 Chapter 2: Geometry Effect on Performance of Strain Switched Dipole Coupled Nanomagnetic Logic.18 2.1. Simulation Conditions: Stress Application.21 2.2. Switching Time Estimate.22 2.3. Comparison between the Elliptical and Cylindrical Geometries In Terms Of Switching Time or Switching Speed.23 2.4. Switching Error Estimate.24
On energy extraction from Q-balls and other fundamental solitons

Energy exchange mechanisms have important applications in particle physics, gravity, fluid mechanics, and practically every field in physics. In this letter we show, both in frequency and time domain, that energy enhancement is possible for waves scattering off fundamental solitons (time-periodic localized structures of bosonic fields), without the need for rotation nor translational motion. We use two-dimensional Q-balls as a testbed, providing the correct criteria for energy amplification, as well as the respective amplification factors, and we discuss possible instability mechanisms. Our results lend support to the qualitative picture drawn in ( arXiv:2212.03269 [gr-qc] ); however we show that this enhancement mechanism is not of superradiant-type, but instead a"blueshift-like"energy exchange between scattering states induced by the background Q-ball, which should occur generically for any time-periodic fundamental soliton. This mechanism does not seem to lead to instabilities.