Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-photon detector arrays for time-resolved fluorescence imaging

Time-correlated single photon counting techniques have recently established themselves in numerous fields of research. In particular, for fluorescence lifetime imaging, time-correlated single photon counting is often considered the absolute reference in terms of accuracy and image quality. However, the lack of significant detector arrays capable of single photon sensitivity and precise photon timing with sub-nanosecond resolution has imposed the use of optical scanning to acquire fluorescence lifetime images. As a consequence, the acquisition times are often prohibitively long and the image acquisition of fast phenomena or the rendering of live and moving objects very difficult to achieve. This thesis presents a new type of detector array capable of single photon sensitivity, low noise and accurate photon timing. The core detector technology is based on single photon avalanche diode structures. Given both the complexity of achieving sub-nanosecond time resolution on many parallel pixels and the large amount of data time-resolved imagers produce, the use of advanced electronic fabrication process is inevitable. Thus the design of high performance single photon detectors in deep-submicron (130 nm) CMOS is investigated, leading to excellent photon detection probability (up to 15 – 35 %, depending on bias and wavelength), low noise (a few tens of Hertz) and a photon timing jitter of 125 ps. The fabrication of these detectors has opened the way to the integration of complex electronics on pixel level. A time discriminator implemented as a compact time-to-digital converter was designed relying on a two-level interpolator approach. A global clock provides a stable, coarse resolution while an in-pixel delay line allows for a finer time resolution of 119 ps. The combination of single photon detector and time discriminator, with the addition of some read-out and glue electronics, enabled the fabricating of a small (50 × 50 µm), scalable pixel for integration in a larger array. An array consisting of 32 × 32 pixels was implemented and thoroughly characterized. With a timing mismatch of only a few tens of picoseconds across the entire array, a low noise count and good sensitivity, the array is well suited for various time-correlated applications, and FLIM in particular. The large data rate (up to 10.24 Gb/s) of the 1024 parallel acquisition channels is handled by a motherboard with significant computing power in the form of two FPGA's. An on-board data compression scheme is implemented by creating a histogram of photon arrival times for each individual pixel within the array, allowing for an efficient data transfer out of the motherboard. Finally, the suitability and efficiency of the proposed detector array for fluorescence lifetime imaging is shown with a wide variety of measurements, from high time-resolution single detector measurements to wide-field fluorescence lifetime image acquisition. Fluorescence lifetimes were resolved with high accuracy for very short acquisition times, down to a few hundreds of milliseconds for the parallel acquisition on all pixels.
Statistical Simulation of Reentry Capsule Aerodynamics in Hypersonic Near-Continuum Flows

Abstract : Current challenges and problems pertaining to the development and application of the DSMC method for high-altitude aerodynamics are discussed. Attention is paid to issues related to the efficiency and accuracy of the method in the near-continuum regime, as well as its use for modeling of rarefied flows with real gas effects. Accurate prediction of force and heat aerodynamic characteristics of reentry vehicles and spacecraft requires comprehensive investigation of hypersonic flows in the near-continuum regime. A powerful software system SMILE, which uses the direct simulation Monte Carlo method as a numerical approach and is built basing on the contemporary knowledge in this field, is developed to solve advanced problems of high-altitude aerothermodynamics. Effective numerical algorithms and physically grounded models of real gas effects are implemented in SMILE. Aerodynamics of promising reentry capsule in the near-continuum regime is considered as an example.
Autocalibrating vision guided navigation of unmanned air vehicles via tactical monocular cameras in GPS denied environments

This thesis presents a novel robotic navigation strategy by using a conventional tactical monocular camera, proving the feasibility of using a monocular camera as the sole proximity sensing, object avoidance, mapping, and path-planning mechanism to fly and navigate small to medium scale unmanned rotary-wing aircraft in an autonomous manner. The range measurement strategy is scalable, self-calibrating, indoor-outdoor capable, and has been biologically inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals (particularly bats), designed to assume operations in previously unknown, GPS-denied environments. It proposes novel electronics, aircraft, aircraft systems, systems, and procedures and algorithms that come together to form airborne systems which measure absolute ranges from a monocular camera via passive photometry, mimicking that of a human-pilot like judgement. The research is intended to bridge the gap between practical GPS coverage and precision localization and mapping problem in a small aircraft. In the context of this study, several robotic platforms, airborne and ground alike, have been developed, some of which have been integrated in real-life field trials, for experimental validation. Albeit the emphasis on miniature robotic aircraft this research has been tested and found compatible with tactical vests and helmets, and it can be used to augment the reliability of many other types of proximity sensors.
Complete Characterization of Gorbunov and Pinsker Nonanticipatory Epsilon Entropy of Multivariate Gaussian Sources: Structural Properties

This paper derives the optimal test channel distribution and the complete characterization of the classical Gorbunov and Pinsker (1973), Gorbunov and Pinsker (1974) nonanticipatory epsilon entropy of multivariate Gaussian Markov sources with square-error fidelity, which remained an open problem since 1974. The paper also formulates a state dependent nonanticipatory epsilon entropy, in which past reproductions are available to the decoder and not to the encoder, the test channel is specified with respect to an auxiliary (state) random process, and the reproduction process is a causal function of past reproduction and the auxiliary random process. This variation is analogous to the Wyner and Ziv (1976) and Wyner (1978) rate distortion function (RDF), of memoryless sources. It is shown that the operational rate of zero-delay codes, with past reproductions available to the decoder but not to the encoder is bounded below by the state dependent nonanticipatory epsilon entropy rate. For the case of multivariate Gaussian Markov sources with square-error fidelity, the optimal test channel distribution and the complete characterization of the state dependent of nonanticipatory epsilon entropy are derived, and also shown that that the two nonanticipatory epsilon entropies coincide. The derivations are new; they are based on structural properties of the stochastic realizations of the reproduction process that induce the optimal test channel distributions. They are derived using, achievable lower bounds on information theoretic measures, properties of mean-square estimation theory, Hadamard’s inequality, and canonical correlation coefficients of a tuple of multivariate jointly Gaussian random processes. Applications of the nonanticipatory epsilon entropy and its state dependent variation are discussed to the areas of control of unstable Gaussian systems over limited memory channels, design of causal estimators for Gaussian Markov sources with a fidelity criterion, computation of the rate loss of causal and zero-delay codes of Gaussian Markov sources with respect to non-causal codes.
Deployment Analysis of a Deployable Truss Structure

The deployment of a tetrahedral truss structure with spring driving system is a fast process. A deployment experiment of the tetrahedral truss structure has been designed to study the deployment dynamic characteristics of this tetrahedral truss structure. Using a high-speed camera and a force transducer, we can obtain the spatial positions of the three freedom joints and the impact force of the fixed joint, respectively. For further study the deployment dynamics of this structure, we have provided an analytical model constructed by ADAMS. By using two objective functions, the parameter optimization was performed and the numerical results were compared well with the experimental results. The reliability of the analytical model to analyse this deployable truss structure has been proved. The results provide an analytical model to study the deployment dynamics and provide an insight into the deployment mechanism of this deployable structure. Keywords-tetrahedral truss; high-speed camera; deployment analytical model; deployment experiment
Combination of the Glutaminyl Cyclase Inhibitor PQ912 (Varoglutamstat) and the Murine Monoclonal Antibody PBD-C06 (m6) Shows Additive Effects on Brain Aβ Pathology in Transgenic Mice

Compelling evidence suggests that pyroglutamate-modified Aβ (pGlu3-Aβ; AβN3pG) peptides play a pivotal role in the development and progression of Alzheimer’s disease (AD). Approaches targeting pGlu3-Aβ by glutaminyl cyclase (QC) inhibition (Varoglutamstat) or monoclonal antibodies (Donanemab) are currently in clinical development. Here, we aimed at an assessment of combination therapy of Varoglutamstat (PQ912) and a pGlu3-Aβ-specific antibody (m6) in transgenic mice. Whereas the single treatments at subtherapeutic doses show moderate (16–41%) but statistically insignificant reduction of Aβ42 and pGlu-Aβ42 in mice brain, the combination of both treatments resulted in significant reductions of Aβ by 45–65%. Evaluation of these data using the Bliss independence model revealed a combination index of ≈1, which is indicative for an additive effect of the compounds. The data are interpreted in terms of different pathways, in which the two drugs act. While PQ912 prevents the formation of pGlu3-Aβ in different compartments, the antibody is able to clear existing pGlu3-Aβ deposits. The results suggest that combination of the small molecule Varoglutamstat and a pE3Aβ-directed monoclonal antibody may allow a reduction of the individual compound doses while maintaining the therapeutic effect.
Computer integrated work-space quality improvement of the C4 parallel robot CMM based on kinematic error model for using in intelligent measuring

ABSTRACT Computer aided optimization and quality improvement of the performance of industrial machinery, without changing the original design, is one of the important challenges of intelligent manufacturing science, especially for robotic systems. In this paper, improving the performance of the new C4 robot serving as a coordinate measuring system (CMM) was considered. Since the efficiency of a robot is directly related to its work-space, calculating the quality improved work-space of this mechanism was studied. The new inverse and forward error models considering 48 error parameters were obtained using inverse kinematics. Afterward, a sensitivity analysis of the mechanism was implemented. Using the inverse kinematics and the discretization method, the work-space was calculated. Applying a new method, singularity tolerance, singular and quasi-singular points of the work-space were determined. In this proposal of a new computer integrated quality improvement algorithm, the work-space was investigated in various aspects including singularity, dexterity, and sensitivity analysis. The comparison between various indices for dexterity analysis was implemented and reliability and accuracy index was presented. Finally, the quality improved work-space was achieved without any physical changes to the structure. Selecting high-quality regions of work-space for operational intelligently can help to gain accurate results in industrial applications especially measuring tasks.
Does establishing a neurovascular unit improve the outcome after surgical clipping for aneurysmal subarachnoid hemorrhage? Results from a 5-year observational study in Kuwait

Background: Failure to prevent rebleeding after cerebral subarachnoid hemorrhage (SAH) is the most frequent reason for high morbidity and mortality of aneurysmal SAH. Our study aims to identify the outcome after surgical clipping of aneurysmal SAH before and after the establishment of the neurovascular unit. The clarifications of the positive turnover in the outcome will be discussed. Methods: A retrospective cohort analysis was carried out on our experience with a controlled group of patients who underwent clipping for ruptured cerebral aneurysms (n = 61) from January 2015 to December 2019. A modified Rankin scale (mRS) was used to determine the outcome after 6 months of follow-up. Results: The median mRS score (i.e., outcome) on admission was 4, whereas it was with a median score of 2 six months after clipping (P ≤ 0.001). Overall, the cases with a good outcome were 63.9% of the sample, while the poor outcome conditions were 36.1%. The most cases with an improved outcome were after introducing the neurovascular unit, representing a transition of aneurysmal clipping practice in our center. The good outcome was changed from 42% to 76.7%, and the poor outcome was changed from 58% to 23.3% (P = 0.019). The crude mortality rate was similar to the rate worldwide (18%), with a noticeable decrease after organizing a neurovascular subspecialty. Conclusion: The outcome after clipping of ruptured SAH can be largely affected by the surgeon’s experience and postoperative intensive care. Organizing a neurovascular team is one of the major factors to achieve good outcomes.
Statistical problems in wireless sensor networks

Wireless Sensor Networks (WSN) are a new technology with many applications, including environmental monitoring, habitat monitoring, surveillance, and health care. In many applications, each sensor records a signal (temperature, vibration, etc) emitted from a target, makes a decision about the target’s presence, and then transmits either the signal or the decision to a central node. Transmission of decisions instead of signals offers significant savings in communication costs, but binary decisions are unreliable in noisy environments. We develop a new algorithm to improve reliability of binary decisions, the Local Vote Decision Fusion (LVDF). Using LVDF, we develop new data fusion algorithms for target detection (making a network-level decision about the presence of a target), target localization (estimating the target’s position), and target tracking (estimating trajectories of multiple moving targets over time). We apply our framework based on binary corrected decisions to two case studies – an experiment involving tracking people and a project of tracking zebras. Our tracking approach based on corrected decisions exhibits a competitive performance even compared to maximum likelihood estimation based on the signals themselves. Motivated by the success of the LVDF algorithm in WSNs, we are currently developing a general classification framework for based on data fusion from correlated classifiers For directions and maps, please see http://math.bu. edu/research/statistics/statseminar.html.
Anatomically constrained deformable 3D reconstruction of intraoperative uterus from preoperative MRI data on uterine fibroid treatment

ABSTRACT Detections of the uterus using preoperative magnetic resonance imaging (MRI) data are required for intraoperative navigation in High-Intensity Focused Ultrasound (HIFU) treatment of uterine fibroids. The modelling of the intraoperative uterus between empty and full bladder anatomy deems to be a crucial step to quantify uterus deformation caused by the bladder-and-rectum-filling (BRF) technique. In this paper, a novel two-stage conditional generative adversarial network (cGAN) is proposed to perform intraoperative uterus deformable reconstruction with anatomical constraints using only single preoperative MRI data, viz. ACDeformRec. The highly constrained anatomy properties are further captured by a novel attention network that formulates high-level uterus segmentation task by incorporating correlations of surrounding organs for more anatomically plausible reconstruction. The experimental result demonstrates the robustness of ACDeformRec by evaluating its performance on 181 clinical datasets and has achieved the lowest reconstruction error of 0.735 ± 0.045 mm with Dice Similarity Coefficient of 94.23% and Normalised Cross Correlation of 97.23%.
Dynamics for robot control: friction modeling and ensuring excitation during parameter identification

Abstract : To accurately control any mechanism it is necessary to know the relationship between applied forces and the resultant motion. These forces may be simple to compute, as is the case for many single degree of freedom machines; or they may be quite complex. Two steps toward the accurate prediction of motion forces are presented in this thesis: an experimental investigation of friction, and a study of the sensitivity of robot inertial parameter identification methods to noise. The friction study begins with an experimental investigation of the most basic properties required for predictive modeling: repeatability and structure. Friction is found to be surprisingly repeatable; position dependence is found, and a destabilizing effect - the Stribeck effect - is observed at low velocity. The experimental work is specific to a particular mechanism: the PUMA 560 arm; but many of the observations, particularly the study of the Stribeck effect, will extend to a broad class of machines. Using the friction model developed and an inertial model reported elsewhere, open-loop control of the PUMA robot is carried out, demonstrating the accuracy of the friction model. When designing an identification experiment for a system described by nonlinear functions, such as those of manipulator dynamics, it is necessary to consider whether the excitation is sufficient to provide an accurate estimate of the parameters in the presence of experimental noise.
Efficient big data system in the cloud : resource provisioning and scheduling

Big data and big data analysis have achieved tremendous popularity recently. This new generation of systems, beyond conventional data analysis with sampled data, represents a new era in data exploration as well as utilization across petabytes and zettabytes datasets. First proposed by Google, MapReduce has become the de facto standard framework in parallel processing for big data applications. Nevertheless, MapReduce framework is also criticized for its inefficiency in performance. Thus, many studies investigate different aspects of MapRedcue framework to improve its performance. A MapReduce system consumes such resources as computing, memory, disk, network. How these resources are managed determines the performance of a MapReduce system. In this thesis, we investigate several challenges in managing resources for MapReduce system in the cloud. We study resource management at two different levels: Cluster level and Machine level. In cluster level, we investigate challenges in building clusters in the cloud. In machine level, we investigate challenges in scheduling tasks of MapReduce jobs among machines. First, we focus on the resource provisioning problem for building clusters in the cloud. Since running a MapReduce system needs a cluster which consists of a set of networkconnected machines, this infrastructure requirement prevents small companies from making use of big data techniques. Cloud offers these small/mediate companies a choice and cloud providers are delighted to offer this service. However, we find that running MapReduce systems in cloud is not straightforward. MapReduce systems are both computational-intensive and IO-intensive which causes severe interference if machines for building the cluster are fine-chosen. We investigate this interference with detailed measurement, formulate it into a resource provisioning problem and propose a set of
How to improve the inbound flow of an manufacturing company : Analyzing and refining the Customer-driven Purchasing method

Purpose: The purpose of this research is to analyze the CDP-method in order to develop and refine the method. The method is developed and presented in Backstrand (2012), with the aim to strengthen the competitiveness of manufacturing companies. Someone outside of the development context has never, until now and to the researchers knowledge, refined the method.Methodology: A multiple case study with four companies where used. The empirical data collected within the study where used to evaluate the CDP-method and to refine the method. The presented improvement is based on the empirical data and conceptual models developed from theory.Findings: Three improvements were developed. The first of them changed step 8 of the method, the second can´t be tied to a single step and is therefore an overall suggestion, whereas the third provides a new type of analysis within step 6 of the method.Research limitations: The research was conducted at companies where the CDP-method was already implemented. An implementation at a new company could possibly reveal another type of empirical data, which could be interpreted in a different way. The researchers have also detected areas that couldn’t be investigated within this research, these are identified and left for further research.Theoretical implications: Results from this thesis connect the classification of supply risk by Kraljic (1983) with supply chain strategy by Fisher (1997) to enable a new type of analysis. Furthermore, theory within the standardization and over-specification (e.g. Burt, Petcavage & Pinkerton, 2010; Geldeman & van Weele, 2002) is introduced and incorporated in the CDP-method. A third implication is a reinforced focus on strategy in combination with the CDP-method, which is based on theory regarding strategic alignment (e.g. Gattorna & Walter, 1996; Hines, 2004). Managerial implications: The new analysis should, together with the CDP-method as a whole, strengthen adopting companies supply chain and improve internal and external communication.Originality/value: This thesis provides a new set of analysis in the CDP-method that could benefit practitioners.