Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Dip-Coating Temperature Upon Film Thickness in Chemical Solution Deposition

Chemical solution deposition (CSD) is widely used to fabricate YBCO superconducting and oxide buffer layers for high-temperature coated conductors. Controlling film thickness is important in the CSD technology and can be conducted through several methods. This study proposes a new method of adjusting the temperature of dip-coating. A precursor solution was prepared for fabrication of a YBCO layer. The temperatures of the precursor solution and substrate were fixed at 0 <inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula>C, 10 <inline-formula> <tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula>C, 20 <inline-formula><tex-math notation="LaTeX"> $^{\circ }$</tex-math></inline-formula>C, or 30 <inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math> </inline-formula>C during dip-coating by using a water bath system. Film thickness was measured by scanning electron microscopy after pyrolysis. The average thickness of the pyrolyzed films decreased from 265 to 158 nm when the dip-coating temperature increased from 0 <inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math> </inline-formula>C to 30 <inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula>C, therefore verifying the feasibility of the new method for thickness control. The nonuniformity of thickness distribution along the withdrawal direction was detected and discussed. The influence of temperature on solution viscosity and film thickness was analyzed based on the equation of thickness dependence in dip-coating. The proposed method for thickness control could contribute to increasing the synthesis window in thin-film fabrication through CSD.
Characterization of the impregnation by a cementitious matrix of five glass multi-filament yarns

ABSTRACT Textile reinforced concretes use multifilament yarns as reinforcement. Their mechanical properties are mainly governed by the impregnation of the yarns by the cementitious matrix. Two experimental methods that allow the level of impregnation of the yarn to be quantified are presented. These methods were tested on five different glass yarns, for three preparation methods that induce different level of impregnation. The results are discussed and compared to qualitative characterisation obtained from scanning electronic microscopy, which allows us to link them with the impregnation.
Epidemiology of viral respiratory infections in Australian working-age adults (20–64 years): 2010–2013

Abstract Acute respiratory infections cause significant morbidity and mortality accounting for 5.8 million deaths worldwide. In Australia, influenza-like illness (ILI), defined as cough, fever and fatigue is a common presentation in general practice and results in reduced productivity and lost working days. Little is known about the epidemiology of ILI in working-age adults. Using data from the ASPREN influenza surveillance network in Australia (2010–2013) we found that working-age adults made up 45.2% of all ILI notifications with 55% of samples positive for at least one respiratory virus. Viruses most commonly detected in our study included influenza A (20.6%), rhinovirus (18.6%), influenza B (6.2%), human meta-pneumovirus (3.4%), respiratory syncytial virus (3.1%), para-influenza virus (2.6%) and adenovirus (1.3%). We also demonstrated that influenza A is the predominant virus that increases ILI (by 1.2% per month for every positive influenza A case) in working-age adults during autumn–winter months while other viruses are active throughout the year. Understanding the epidemiology of viral respiratory infections through a year will help clinicians make informed decisions about testing, antibiotic and antiviral prescribing and when the beginning of the ‘flu season’ can be more confidently predicted.
A New Concept for Experiment Program Planning for the Fusion Experiment Wendelstein 7-X

The control and data acquisition system (CODAC system) for the fusion experiment Wendelstein 7-X is designed for miscellaneous operational scenarios: short pulses with arbitrary intervals, steady-state long pulse operation and arbitrary sequences of short phases with different characteristics in one discharge. The data structures for a description of experiment runs are very complex and comprehensive. A special editor is necessary to guide the user through the different phases of experiment program planning. A more abstract and physics-oriented description of the required machine and plasma behaviour is a suitable way to handle the complexity and to make the experiment program definition process effective and easier. This contribution introduces a concept for experiment planning based on a so called segment program boxes (SEGPROGBOX). The planned work flow of the experiment program creation will be discussed after an introduction of the SEGPROGBOX design.
Optimization of RNN-Based Speech Activity Detection

Speech activity detection (SAD) is an essential component of automatic speech recognition systems impacting the overall system performance. This paper investigates an optimization process for recurrent neural network (RNN) based SAD. This process optimizes all system parameters including those used for feature extraction, the NN weights, and the back-end parameters. Three cost functions are considered for SAD optimization: the frame error rate, the NIST detection cost function, and the word error rate of a downstream speech recognizer. Different types of RNN models and optimization methods are investigated. Three types of RNNs are compared: a basic RNN, long short-term memory (LSTM) network with peepholes, and a coordinated-gate LSTM (CG-LSTM) network introduced by Gelly and Gauvain. Well suited for nondifferentiable optimization problems, quantum-behaved particle swarm optimization is used to optimize feature extraction and posterior smoothing, as well as for the initial training of the neural networks. Experimental SAD results are reported on the NIST 2015 SAD evaluation data as well as REPERE and AMI meeting corpora. Speech recognition results are reported on the OpenKWS’13 test data. For all tasks and conditions, the proposed optimization method significantly improves the SAD performance and among all the tested SAD methods the CG-LSTM model gives the best results.
Multi-Sensor Integration for Indoor 3D Reconstruction

Outdoor maps and navigation information delivered by modern services and technologies like Google Maps and Garmin navigators have revolutionized the lifestyle of many people. Motivated by the desire for similar navigation systems for indoor usage from consumers, advertisers, emergency rescuers/responders, etc., many indoor environments such as shopping malls, museums, casinos, airports, transit stations, offices, and schools need to be mapped. Typically, the environment is first reconstructed by capturing many point clouds from various stations and defining their spatial relationships. Currently, there is a lack of an accurate, rigorous, and speedy method for relating point clouds in indoor, urban, satellite-denied environments. This thesis presents a novel and automatic way for fusing calibrated point clouds obtained using a terrestrial laser scanner and the Microsoft Kinect by integrating them with a low-cost inertial measurement unit. The developed system, titled the Scannect, is the first joint static-kinematic indoor 3D mapper.
Protein structure modeling and refinement by global optimization in CASP12

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence‐structure alignment, three‐dimensional (3D) chain building, and side‐chain re‐modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue‐residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template‐based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded.
H∞ control of quantum feedback control systems with time delay

In a quantum feedback control loop, it is often confronted with time delays mainly originated from the transition delay of signals, which may cause quantum feedback control systems unstable. The purpose of this paper is to deal with a problem of quantum measurement-based feedback control systems subject to feedback-loop time delays. A physical model for a quantum measurement-based feedback control system with time delay is presented for the H∞ control. Fundamental properties such as dissipation, gain and stability for this model are presented and characterized using linear matrix inequalities (LMIs). A numerical procedure is proposed for H∞ controller designs for our model. An example is given to illustrate our numerical procedure.
The manufacturing blueprint environment: Bringing intelligence into manufacturing

Manufacturers today are rapidly moving into a business climate that is characterized by the ability to fulfill orders on demand by doing business through short-term networks where they negotiate value-adding processes dynamically – taking into account quality, time, price, viability, sustainability, and other dimensions. This necessitates the use of novel technologies to help manufacturers connect their data, processes, systems, personnel and equipment to enable smart factories. This paper proposes a new manufacturing paradigm, called manufacturing blueprints, which allows manufacturers to move from a traditional product-centric business model to a fully digital, knowledge-based and service-centric one. Using this paradigm, manufacturers are able to combine manufacturing and equipment data and knowledge, production systems and processes to form a smart manufacturing network to diversify products and build new markets.
Surgical Considerations of Intractable Mesial Temporal Lobe Epilepsy

Surgery of temporal lobe epilepsy is the best opportunity for seizure freedom in medically intractable patients. The surgical approach has evolved to recognize the paramount importance of the mesial temporal structures in the majority of patients with temporal lobe epilepsy who have a seizure origin in the mesial temporal structures. For those individuals with medically intractable mesial temporal lobe epilepsy, a selective amygdalohippocampectomy surgery can be done that provides an excellent opportunity for seizure freedom and limits the resection to temporal lobe structures primarily involved in seizure genesis.
Magnetic-Coupling Characteristics Investigation of a Dual-Rotor Fault-Tolerant PMSM

A five-phase dual-rotor permanent-magnet synchronous motor (PMSM) used for electric vehicles is investigated in this paper. The dual-rotor PMSM consists of an inner motor and an outer motor, which share a common stator yoke. The magnetic coupling exists not only within the interphases, but also between the inner and outer motors, which leads to control complexity and affects performance and fault-tolerant capability of the motor. Thus, the electromagnetic characteristics, particularly the magnetic-coupling characteristics of the dual-rotor PMSM, are investigated based on magnetic circuit and finite-element methods. The influences of magnetic coupling caused by the structural arrangement (pole/slot combination, magnetization type of PMs, armature reaction, common stator yoke thickness, and winding structure) are analyzed in this paper. Then, a magnetic decoupling design is introduced for the five-phase dual-rotor PMSM. A prototype was manufactured and tested to verify the validity and accuracy of the process presented in this paper.
Distributed Optimal Energy Management for Energy Internet

In this paper, a novel energy management framework for energy Internet with many energy bodies is presented, which features multicoupling of different energy forms, diversified energy roles, and peer-to-peer energy supply/demand, etc. The energy body as an integrated energy unit, which may have various functionalities and play multiple roles at the same time, is formulated for the system model development. Forecasting errors, confidence intervals, and penalty factor are also taken into account to model renewable energy resources to provide tradeoff between optimality and possibility. Furthermore, a novel distributed-consensus alternating direction method of multipliers (ADMM) algorithm, which contains a dynamic average consensus algorithm and distributed ADMM algorithm, is presented to solve the optimal energy management problem of energy Internet. The proposed algorithm can effectively handle the problems of power-heat-gas-coupling, global constraint limits, and nonlinear objective function. With this effort, not only the optimal energy market clearing price but also the optimal energy outputs/demands can be obtained through only local communication and computation. Simulation results are presented to illustrate the effectiveness of the proposed distributed algorithm.
A probabilistic retransmission protocol on a relaying network

Relaying protocols are usually deterministic, i.e. they commute from one action to the next one in a predefined manner, depending on the success of the transmission. This paper demonstrates the advantages that probabilistic protocols (i.e. the next action to be undertaken depends on some probability) may have in this context. The whole study is performed on a simple source-relay-destination network, the relay working in demodulate and forward mode, in order to obtain insights on the interaction between relaying and HARQ. So far, probabilistic protocols have been mainly proposed for higher layers of communication systems, but are applied here to physical and MAC layers. Since it contains only two parameters, we demonstrate that our probabilistic protocol can easily be tuned for best performance using a Finite State Markov Chain (FSMC), and that it brings improvement over deterministic protocols in the same scenario.
MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors <inline-formula><tex-math notation="LaTeX">$\mathbf{W}$</tex-math><alternatives> <inline-graphic xlink:href="kannan-ieq1-2767592.gif"/></alternatives></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\mathbf{H}$</tex-math><alternatives><inline-graphic xlink:href="kannan-ieq2-2767592.gif"/> </alternatives></inline-formula>, for the given input matrix <inline-formula><tex-math notation="LaTeX">$\mathbf{A}$ </tex-math><alternatives><inline-graphic xlink:href="kannan-ieq3-2767592.gif"/></alternatives></inline-formula>, such that <inline-formula><tex-math notation="LaTeX">$\mathbf{A}\approx \mathbf{W}\mathbf{H}$</tex-math><alternatives> <inline-graphic xlink:href="kannan-ieq4-2767592.gif"/></alternatives></inline-formula>. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms that iteratively solves alternating non-negative least squares (NLS) subproblems for <inline-formula><tex-math notation="LaTeX">$\mathbf{W}$ </tex-math><alternatives><inline-graphic xlink:href="kannan-ieq5-2767592.gif"/></alternatives></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\mathbf{H}$</tex-math><alternatives> <inline-graphic xlink:href="kannan-ieq6-2767592.gif"/></alternatives></inline-formula>. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1424 Evolution of Interactions Involving Intrinsically Disordered Proteins

Åberg, E. 2018. Evolution of Interactions Involving Intrinsically Disordered Proteins. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1424. 44 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0226-3. This thesis describes the evolution of intrinsically disordered proteins and their interaction partners. The work presented is a combination of phylogenetic analysis, ancestral reconstruction and biophysical characterization in order to examine the evolutionary trajectory of proteinprotein interactions involving disorder. The intrinsically disordered domains, NCBD and CID are both part of transcriptional co-regulating proteins. In evolution, NCBD existed before the emergence of CID and the most ancient domains display a low affinity complex with many weak contacts and high degree of conformational heterogeneity. Later in evolution, when NCBD and CID co-exists, a few mutations have altered the interaction in a way that the affinity is increased 25-fold and the conformational heterogeneity is decreased. In the same manner, the interaction is further optimized in extant species, resulting in a high affinity complex with less contacts of higher strength and less conformational heterogeneity. The intrinsically disordered transactivation domain of the tumour suppressing protein p53 and its negative regulator MDM2 date back to the beginning of animal life. The interacting domains are either lost or conserved in distinct phyla indicating a tight co-evolution. Phylogenetic trees produced by only including phyla with a conserved interaction domain follow the species evolution. Resurrection of p53 and MDM2 in the vertebrate lineage display an evolution of a high affinity complex in the ancestor of fish and tetrapods to a slightly improved affinity in modern tetrapods but a substantially lower affinity in zebrafish. The p53 protein family, which also includes p63 and p73, diverged from a common ancestor. The individual proteins display altered affinities to MDM2 which is a result of the high sequence divergence between them. The ionic dependence for the interactions is small, and not in line with other studies of disordered proteins. In conclusion, the work in this thesis have contributed with evolutionary analysis and experimental data of interactions involving intrinsically disordered proteins.
A New Job Shop Heuristic Algorithm for Machine Scheduling Problems

The purpose of this research is to present a straightforward and relatively efficient method for solving scheduling problems. A new heuristic algorithm, with the objective of minimizing the makespan, is developed and presented in this paper for job shop scheduling problems (JSP). This method determines jobs’ orders for each machine. The assessment is based on the combination of dispatching rules e.g. the “Shortest Processing Time” of each operation, the “Earliest Due Date” of each job, the “Least Tardiness” of the operations in each sequence and the “First come First Serve” idea. Also, unlike most of the heuristic algorithms, due date for each job, prescribed by the user, is considered in finding the optimum schedule. A multitude of JSP problems with different features are scheduled based on this proposed algorithm. The models are also solved with Shifting Bottleneck algorithm, known as one of the most common and reliable heuristic methods. The result of comparison between the outcomes shows that when the number of jobs are less than or equal to the number of machines, the proposed algorithm concludes smaller, and better, makespan in a significantly lower computational time, which shows the superiority of the suggested algorithm. In addition, for a category when the number of jobs are greater than the number of machines, the suggested algorithm generates more efficient results when the ratio of the number of jobs to the number of machines is less than 2.1. However, in this category for the mentioned ratio to be higher than 2.1, the smaller makespan could be generated by either of the methods, and the results do not follow any particular trend, hence, no general conclusions can be made for this case.
Preferential cholinergic excitation of corticopontine neurons

Pyramidal neurons in layer 5 of the neocortex comprise two broad classes of projection neurons: corticofugal neurons, including corticopontine (CPn) neurons, and intratelencephalic neurons, including commissural/callosal (COM) neurons. These non-overlapping neuron subpopulations represent discrete cortical output channels contributing to perception, decision making, and behavior. CPn and COM neurons have distinct morphological and physiological characteristics, and divergent responses to modulatory transmitters such as serotonin and acetylcholine (ACh). To better understand how ACh regulates cortical output, in slices of mouse prefrontal cortex (PFC) we compared the responsivity of CPn and COM neurons to transient exposure to exogenous or endogenous ACh. In both neuron subtypes, exogenous ACh generated qualitatively similar biphasic responses in which brief hyperpolarization was followed by longer-lasting enhancement of excitability. However, cholinergic inhibition was more pronounced in COM neurons, while excitatory responses were larger and longer lasting in CPn neurons. Similarly, optically triggered release of endogenous ACh from cholinergic terminals preferentially and persistently (for ~40 s) enhanced the excitability of CPn neurons, but had little impact on COM neurons. Cholinergic excitation of CPn neurons involved at least three distinct ionic mechanisms: activation of a calcium-sensitive but calcium-permeable nonspecific cation conductance, suppression of Kv7 channels (the “M-current”), and activation of the calcium-dependent nonspecific cation conductance underlying afterdepolarizations. Our results demonstrate projection-specific selectivity in cholinergic signaling in the PFC, and suggest that transient release of ACh during behavior will preferentially promote corticofugal output.