Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability Analysis and Stabilization of Fuzzy State Space Models

Die Dissertation von Kunping Zhu Stability Analysis and Stabilization of Fuzzy State Space Models (ISBN-10: 3-8322-5552-4, ISBN-13: 978-3-8322-5552-7) wurde parallel im Shaker Verlag veroffentlicht Abstract: Fuzzy control has achieved numerous successful industrial applications. However, stability analysis for fuzzy control systems remains a difficult problem, and most of the critical comments on fuzzy control are due to the lack of a general method for its stability analysis. Although significant research efforts have been made in the literature, appropriate tools for this issue have yet to be found. This thesis focuses on the problem of stability of fuzzy control systems. Both linguistic fuzzy models and T-S fuzzy models are discussed. The main work of this thesis can be summarized as follows: (1). A necessary and sufficient condition for the global stability of linguistic fuzzy models is given by means of congruence of fuzzy relational matrices. (2). A hyperellipsoid-based approach is proposed for stability analysis and control synthesis of a class of T-S (affine) fuzzy models with support-bounded fuzzy sets in the rule base. (3). Approaches of BMI-based fuzzy controller designs are proposed for the stabilization of T-S fuzzy models. (4). For the general T-S type fuzzy systems with norm-bounded uncertainties and time-varying delays, sufficient robust stabilization conditions are presented by employing the PDC-based fuzzy state feedback controllers. On stability analysis of T-S fuzzy models, most reported results based on the method of common quadratic Lyapunov functions require that each subsystem of the fuzzy models be stable in order to guarantee the stability of the overall systems. This restriction is overcome in our results by means of employing the structural information in the fuzzy rules.
Students’ Behavioral Patterns in a Computational Thinking Interactive Task: Using Process Data in ICILS 2018 with Sequence Mining

Organized by the International Association for the Evaluation of Educational Achievement (IEA), the International Computer and Information Literacy Study (ICILS) in 2018 extends the evaluation of students’ computer and information literacy (CIL) skills and introduces a novel assessment of students’ computational thinking (CT) skills. CT skills are defined as the ability to recognize, analyze, and describe real-world problems so their solutions can be operationalized within programming tasks. Eligible process data recorded during students programming a CT problem-solving task could provide a new angle to understand how students learn, interact, and adapt their CT skills to solve digital tasks in the programming environment. The aim of this study is two-fold: given limited availability of process data in fine-grained level, we focus on testlet level, namely, to extract behavioral patterns from the whole CT unit. First, to cluster the behavioral patterns into meaningful groups, thus extract representative time allocation patterns through the items within one CT unit, and second to evaluate the CT skills by each latent group to identify the most optimal pattern across countries. The current study focuses on a total of 31,344 students of nine countries and regions who were assigned to the CT modules, “Farm Drone,” in ICILS 2018. Two sub-studies were conducted in this project: (1) We conducted a cluster analysis on timing and process-related variables, to group students with homogeneous patterns and map with students’ CT and CIL latent scores and background variables across countries. (2) We focus on command efficiency, correctness, and time allocation patterns from process data to calculate the sequence distance and extract representative patterns from the way that students solve the coding tasks throughout the unit. This sub-study focuses on better understanding how students with missing responses allocated their time and pinpoints potential reasons why they missed certain items.
Debt sustainability and debt management in Indonesia – lessons from China

While Indonesia and China have relatively similar economic histories as low-income countries in the 1960s, China’s economic growth and economic transformation has been more successful. The paper examines some of the differences in policy, including Indonesia’s used of foreign capital that resulted in the crisis of 1997/98. On the other hand, China used foreign direct investment to build successfully its economy. China's economic growth results from a gradual micro-first approach. Apart from that, China consistently employed its National Plan to ensure the positive impact of strong government power. Indonesia used a similar approach in the lead up to the 1997/98 crisis but with weak bureaucracy and high levels of corruption. In addition to the reform approach and government power, we see the divergence of the banking sector in both countries. Chinese has state-owned banking with a specific role to finance national aims. As the banking sector has contributed significantly, the government can minimize debt absorption, mainly for infrastructure. On the other hand, the Indonesian banking sector only does business activities, particularly after the 1997/98 crisis. China has a substantial tax ratio (above 15%) contributed by the domestic resource-driven economy. A level above 15% is sufficient for a country to fulfil the basic needs of citizens and businesses and put a country on a growth path. We consider that sound and monetary sector stability also contribute to managing foreign debt. China has a massive foreign reserve that impacts currency stability. On the other hand, China foreign debt is relatively low, representing only 14% of GDP on average.
European Centers Prospective Observational Study in 20 Onyx (CAMEO) Trial: Results of a Cerebral Aneurysm Multicenter European

BACKGROUND AND PURPOSE: This study was designed to investigate the safety and efficacy of the Onyx liquid embolic system in treating a selected population of patients with intracranial aneurysms that presented difficulties for surgical or endovascular alternatives. METHODS: A prospective observational study was conducted in 20 European centers enrolling a consecutive series of 119 patients with 123 aneurysms judged suitable for Onyx treatment. The series consists of findings collected in 97 of 119 patients with 100 of 123 aneurysms, because one center declined to provide data to the study sponsor or allow outside audit. Clinical and angiographic outcomes were recorded at discharge, 3 months, and 12 months. All adverse events and re-treatments were recorded. Seventy-nine aneurysms were large or giant. RESULTS: Twelve-month follow-up angiography findings were available for 71 aneurysms. This angiographic follow-up showed complete occlusion in 56 (79%) aneurysms, subtotal occlusion in nine (13%), and incomplete occlusion in six (8%). Procedure-or device-related permanent neurologic morbidity at final follow-up was present in eight of 97 patients. Seven patients died: two deaths were procedure related; one, disease related; and four, unrelated causes. Seventy-five of the 82 patients alive and with follow-up at 12 months were at Rankin 2 or better status. Delayed occlusion of the parent vessel occurred in nine patients; delayed occlusion was asymptomatic in five and resulted in permanent neurologic deficit in two. CONCLUSION: In selected patients with aneurysms that are unsuitable for coil treatment or in whom previous treatment has failed to occlude the aneurysm, Onyx treatment offers an endovascular alternative. Aneurysm occlusion rates are superior to reported rates of coil occlusion, and treatment morbidity is comparable to that of published prospective data on endovascular results for this subgroup of patients.
Plasma Start-up Experiments on the TST-2 Spherical Tokamak

Plasma start-up without the use of a central solenoid (CS) with a large flux swing capability is a critical issue in fusion research. In the TST-2 spherical tokamak (ST), non-inductive start-up by waves in the lower-hybrid frequency range (200 MHz) has been studied using three types of antennas. Presently two capacitively-coupled combline (CCC) antennas located on the outboard side and the top of the plasma are used. The maximum sustained plasma current by the outboard-launch antenna was increased from 16 kA to 25 kA by changing several conditions, such as a higher toroidal magnetic field strength and the installation of top and bottom limiters. Recently we installed a top-launch CCC antenna, by which a good core power deposition is expected due to the upshift of the n || during propagation. Using both antennas a plasma current of 21 kA has been sustained so far. In addition, AC Ohmic heating experiments with frequencies up to 10 kHz were performed. The pre-ionization process was studied in detail. The minimum loop voltage for pre-ionization was +/-0.5 V, which corresponds to +/-0.6 V/m at the inboard limiter. DC current drive experiments showed a DC plasma current component of 1.9 kA.
Mining Redescriptions with Siren

In many areas of science, scientists need to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. For example, in biology, an important task is to identify the bioclimatic constraints that allow some species to survive, that is, to describe geographical regions both in terms of the fauna that inhabits them and of their bioclimatic conditions. In data analysis, the task of automatically generating such alternative characterizations is called redescription mining. If a domain expert wants to use redescription mining in his research, merely being able to find redescriptions is not enough. He must also be able to understand the redescriptions found, adjust them to better match his domain knowledge, test alternative hypotheses with them, and guide the mining process toward results he considers interesting. To facilitate these goals, we introduce Siren, an interactive tool for mining and visualizing redescriptions. Siren allows to obtain redescriptions in an anytime fashion through efficient, distributed mining, to examine the results in various linked visualizations, to interact with the results either directly or via the visualizations, and to guide the mining algorithm toward specific redescriptions. In this article, we explain the features of Siren and why they are useful for redescription mining. We also propose two novel redescription mining algorithms that improve the generalizability of the results compared to the existing ones.
MD Simulation of Water Using a Rigid Body Description Requires a Small Time Step to Ensure Equipartition.

In simulations of aqueous systems, it is common to freeze the bond vibration and angle bending modes in water to allow for a longer time step δt for integrating the equations of motion. Thus, δt = 2 fs is often used in simulating rigid models of water. We simulate the SPC/E model of water using δt from 0.5 to 3.0 fs and up to 4 fs using hydrogen mass repartitioning. In these simulations, we find that for all but δt = 0.5 fs, equipartition is not obtained between translational and rotational modes, with the rotational modes exhibiting a lower temperature than the translation modes. To probe the reasons for the lack of equipartition, we study the autocorrelation of the translational velocity of the center of mass and the angular velocity of the rigid water molecule, respectively. We find that the rotational relaxation occurs on a timescale comparable to vibrational periods, calling into question the original motivations for freezing the vibrations. Furthermore, a time step with δt ≥ 1 fs is not able to capture accurately the fast rotational relaxation, which reveals its impact as an effective slowing-down of rotational relaxation. The fluctuation-dissipation relation then leads to the conclusion that the rotational temperature should be cooler for δt greater than the reference value of 0.5 fs. Consideration of fluctuation-dissipation in equilibrium molecular dynamics simulations also emphasizes the need to capture the temporal evolution of fluctuations with fidelity and the role of δt in this regard. The time step also influences the solution thermodynamic properties: both the mean system potential energies and the excess entropy of hydration of a soft repulsive cavity are sensitive to δt.
A Model-Based Bayesian Inference Approach for On-Board Monitoring of Rail Roughness Profiles: Application on Field Measurement Data of the Swiss Federal Railways Network

According to the International Union of Railways, railway networks count more than one million kilometers of tracks worldwide, a number that is to rise further as the goal is to promote rail transportation as a sustainable means to face the challenge of increased mobility. However, such a vast expansion further necessitates efficient and reliable infrastructure monitoring schemes able to guarantee the quality and safety of rail transportation. Traditional monitoring approaches, relying on visual inspection and portable measuring devices, cannot rise to the task as they do not allow for continuous inspection of extended portions of rail infrastructure. Therefore, mobile monitoring methodologies based on dedicated diagnostic vehicles have emerged as an alternative. Despite revolutionizing traditional monitoring methods, such vehicles are usually expensive and can only operate under the suspension of regular rail service. In this work, we propose an alternative approach for mobile sensing of railway infrastructure based on on-board monitoring data collected from low-cost vibration sensors, e.g., accelerometers, which can be mounted on in-service trains. Specifically, we focus on identifying the roughness profile of the tracks and propose a fusion of reduced-order vehicle models with a Bayesian inference approach for joint input-state estimation. To enhance the inference, we opt for a prior updating of the vehicle model parameters on the basis of an unscented Kalman filter and available measurements from a diagnostic vehicle. The key contributions of this work are (i) the consideration of the dynamic interaction between trains and tracks, which is usually ignored in rail roughness estimation, (ii) the adoption of reduced train vehicle models that decrease the computational effort of the identification task, (iii) the updating of the vehicle parameters to account for inconsistencies in the model used, and (iv) the application of the proposed methodology to actual acceleration measurements collected from a diagnostic vehicle of the Swiss Federal Railways network.
AAV Vectors Pseudotyped with Capsids from Porcine and Bovine Species Mediate In Vitro and In Vivo Gene Delivery

Adeno-associated virus (AAV) vectors are among the most widely used delivery vehicles for in vivo gene therapy as they mediate robust and sustained transgene expression with limited toxicity. However, a significant impediment to the broad clinical success of AAV-based therapies is the widespread presence of pre-existing humoral immunity to AAVs in the human population. This immunity arises from the circulation of non-pathogenic endemic human AAV serotypes. One possible solution is to use non-human AAV capsids to pseudotype transgene-containing AAV vector genomes of interest. Due to the low probability of human exposure to animal AAVs, pre-existing immunity to animal-derived AAV capsids should be low. Here, we characterize two novel AAV capsid sequences: one derived from porcine colon tissue and the other from a caprine adenovirus stock. Both AAV capsids proved to be effective transducers of HeLa and HEK293T cells in vitro. In vivo, both capsids were able to transduce the murine nose, lung, and liver after either intranasal or intraperitoneal administration. In addition, we demonstrate that the porcine AAV capsid likely arose from multiple recombination events involving human- and animal-derived AAV sequences. We hypothesize that recurrent recombination events with similar and distantly related AAV sequences represent an effective mechanism for enhancing the fitness of wildtype AAV populations.
Comparison of Rapid Maxillary Expansion and Alternate Rapid Maxillary Expansion and Constriction Protocols with Face Mask Therapy

Objective: This study compared dentoskeletal and soft tissue changes with face mask (FM) therapy. Rapid maxillary expansion (RME) and alternate rapid maxillary expansion and constriction (Alt-RAMEC) protocols were used with the two different types of expansion appliance, and their effects on the treatment outcome were investigated. Methods: The study consisted of 79 (37 and 42 patients in the RME and Alt-RAMEC groups with FM, respectively) patients who had received FM treatment. The effects of the RME/FM (20 female, 17 male) and Alt-RAMEC/FM (14 female, 28 male) protocols were evaluated using lateral cephalometric films. The chronological ages of the RME/FM and Alt-RAMEC/FM groups were 11.58 and 11.99 years, respectively. In addition, both groups were divided into two subgroups based on the design of the expansion appliance (Spolyar or full coverage type). Differences in all parameters were analyzed using Student’s t-tests. Results: The maxilla significantly moved forward in both the RME/FM and Alt-RAMEC/FM groups (p<0.001). No significant skeletal differences were observed between the groups. Sagittal movement of the upper incisors significantly increased, and the lower incisors significantly retruded in both groups. While similar skeletal changes were found between the Spolyar and full-coverage appliance groups, the upper incisors protruded significantly more in the full-coverage type. Conclusion: RME/FM and Alt-RAMEC/FM therapies were found to be efficient for maxillary protraction and resulted in similar skeletal changes. A full-coverage expansion appliance produced a more upper incisor protrusion than a spherical-type appliance.
PLA-Based Composite Panels Prepared via Multi-Material Fused Filament Fabrication and Associated Investigation of Process Parameters on Flexural Properties of the Fabricated Composite

This study prepares composite panels with three Polylactic acid (PLA)-based materials via the multi-material fused filament fabrication method. The influences of four processing parameters on the mechanical properties of 3D-printed samples are investigated employing the Taguchi method. These parameters include the relative volume ratio, material printing order, filling pattern, and filling density. A “larger is better” signal-to-noise analysis is performed to identify the optimal combination of printing parameters that yield maximum bending strength and bending modulus of elasticity. The results reveal that the optimal combination of printing parameters that maximizes the bending strength involves a volume ratio of 1:1:2, a material sequence of PLA/foam-agent-modified eco-friendly PLA (ePLA-LW)/glass fiber-reinforced eco-friendly PLA (ePLA-GF), a Gyroid filling pattern, and a filling density of 80%, and the optimal combination of printing parameters for maximum bending modulus involves a volume ratio of 1:2:1 with a material sequence of PLA/ePLA-LW/ePLA-GF, a Grid filling pattern, and 80% filling density. The Taguchi prediction method is utilized to determine an optimal combination of processing parameters for achieving optimal flexural performances, and predicted outcomes are validated through related experiments. The experimental values of strength and modulus are 43.91 MPa and 1.23 GPa, respectively, both very close to the predicted values of 46.87 MPa and 1.2 GPa for strength and modulus. The Taguchi experiments indicate that the material sequence is the most crucial factor influencing the flexural strength of the composite panels. The experiment result demonstrates that the flexural strength and modulus of the first material sequence are 67.72 MPa and 1.53 GPa, while the flexural strength and modulus of the third material sequence are reduced to 27.09 MPa and 0.72 GPa, respectively, only 42% and 47% of the first material sequence. The above findings provide an important reference for improving the performance of multi-material 3D-printed products.
Comparison of six fire severity classification methods using Montana and Washington wildland fires

Fire severity classifications are used in the post-fire environment to describe fire effects, such as soil alteration or fuel consumption, on the forest floor. Most of the developed classifications are limited because they address very specific fire effects or post-burn characteristics in the burned environment. However, because fire effects vary so much among soil, hydrology, vegetation, chemistry, particulate, and spatial distribution, it is important to realize that the impressions of burn severity are governed by the method used to classify the fire effects. The objective of this study was to determine (1) how severity classes derived from each tested method compared with the Composite Burn Index, which is a standard field assessment for fire severity that is commonly used in the United States; and (2) how well the fire severity classes obtained from six different classification methods agreed with each other. Comparisons of fire severity classes were made on 289 field plots from 15 fires across Montana and Washington. Severity classes were made for two types of field classifications, including (1) a fire severity matrix (Ryan and Noste 1985), and (2) soil post-fire indices (Jain and others 2012); three remote sensing methods, including (1) the Monitoring Trends in Burn Severity (MTBS) classification (Eidenshink and others 2007), (2) a modification of the relativized differenced normalized burn ratio (RdNBR) classification for plots in the northwestern United States, and (3) the Burned Area Emergency Rehabilitation (BAER/BARC) classification; and a modeling approach created by Keane and others (2010) called FIREHARM. The severity classes derived from these six methods were compared to on-site field assessments of fire severity using the Composite Burn Index (CBI). The two field classifications corresponded best with CBI (Kendal tau b > 0.61, ASE = 0.4). Remote sensing classification classes corresponded to CBI classes only half of the time (Kendal tau b = 0.53, ASE = 0.04). The modeling approach had low to negative correlations with all other methods and the average correspondence among all the classification types was 38%.