Miracle-dz/UniFAR-FTUs huggingface dataset:
Lifetime and hyperspectral analyses of stem cell nuclei during differentiation

XXI CHAPTER 1 GENERAL INTRODUCTION.1 1.1 – PROJECT OVERVIEW . 1 1.2 – UNDERSTANDING THE ROLE OF NADH AS A NATURALLY OCCURRING FLUOROPHORE IN BIOLOGICAL PROCESSES . 1 1.3 – BIOCHEMICAL SIGNIFICANCE OF NADH . 4 1.4 – REDOX ROLES OF NADH IN EUKARYOTES . 6 1.4. 1 – NADH and its role in Cellular Respiration . 6 1.4. 1.1 – Cytosolic NADH as a Metabolic Regulator in Glycolysis . 7 1.4. 1.2 – Mitochondrial NADH Generation in the Citric Acid Cycle during Cellular Respiration . 8 1.4. 1.3 – Mitochondrial NADH and Respiration in the Electron Transport Chain. 9 1.4. 2 – The role of NADH in Fatty Acid Beta Oxidation . 10 1.4. 3 – The role of NADH in Apoptosis (Programmed Cell Death). 11 1.5 – NON-REDOX ROLES OF NADH IN EUKARYOTES. 12 1.5. 1 – NADH in Protein Synthesis . 12 1.5. 2 – The role of Nuclear NADH in ADP ribosylation . 12 1.5. 3 – Nuclear NADH in Transcription . 13 1.6 – HOMEOSTASIS OF NUCLEAR NADH VIA THE DE NOVO AND SCAVENGER PATHWAYS. 15 1.7 – METHODOLOGIES FOR VISUALISING FLUORESCENCE USING BASIC FLUORESCENCE MICROSCOPY TECHNIQUES . 16 1.7. 1 – Confocal Laser Scanning Microscopy . 17 1.7. 2 – Multiphoton Microscopy . 19 1.8 – ADVANCED MICROSCOPY TECHNIQUES FOR VISUALISING NADH FLUORESCENCE . 21 1.8. 1 – Enzyme Dependent Fluorescence Recovery after Photobleaching . 21 1.8. 2 – Förster Resonance Energy Transfer . 22 1.8. 3 – Fluorescence Lifetime Imaging Microscopy . 23 1.8. 3.1 – Time Domain FLIM . 25 1.8. 3.2 – Frequency Domain FLIM . 27 1.8. 3.3 – Data Analysis of TD FLIM and FD FLIM . 27 1.8. 4 – Spectral Fluorescence Imaging Microscopy and Analysis . 28 CHAPTER 2 PHASOR-FLIM ANALYSIS OF ENDOGENOUS AUTOFLUORESCENCE IN THE DEVELOPING MUSCULAR TISSUE OF ZEBRAFISH EMBRYOS. 30 2.1 – INTRODUCTION . 30
Constraint-based Tree Pattern Mining

A lot of recent applications dealing with complex data require sophis- ticated data structures (trees or graphs) for their specification. Recently, several techniques for tree and graph mining have been proposed in the literature. In this paper, we focus on constraint-based tree mining. We propose to use tree au- tomata as a mechanism to specify user constraints over tree patterns. We present the algorithm CobMiner which allows user constraints specified by a tree au- tomata to be incorporated in the mining process. An extensive set of experiments executed over synthetic and real data allow us to conclude that incorporating constraints during the mining process is far better effective than filtering the frequent and interesting patterns after the mining process.
Model for charging/discharging dynamics of cells in redox flow battery with transport delay

A redox flow battery (RFB) is an energy storage capable of contributing to grid balancing under the fluctuation of renewable power sources and loads. An RFB consists of reaction cells and tanks containing electrolytes that are pumped to the cells. Modeling of the charging/discharging dynamics is necessary for controlling the flows of the electrolytes and the current. The previous researches have assumed that the transport delay is small and negligible. However, when the transport delay appears, it affects the performance of the control systems. This paper aims to propose a model for considering charging/discharging dynamics with transport delay. The delay appears in the voltages of the cells in the tested system, and a model is introduced to simulate the delay. The model is represented by delay differential equations (DDEs) of the ion concentration in the cells with the Nernst relationship. The DDEs are derived from the mass balance equation including the transport delay translated to the time delay. The simulation result excellently agrees well with the experiment at results. In other words, the model can predict the dynamics governed by the transport delay accurately.
Scanning Files for Signatures with a MapReduce System on Cloud Computing

Because malicious code gradually endangers people's life and verifying the harmlessness of a file usually costs many resources, the MapReduce System for Online File Scanning (MRSOFS) is proposed as a solution for combing the online file scanning service and a MapReduce system on cloud computing. In this paper, MRSOFS is introduced, implemented, and evaluated with experiments. In experiments, MRSOFS outperforms the standard case of using a single computer to scan a file for a specific signature in a signature database. MRSOFS is proved to get performance benefits by using a MapReduce system to scan a file for a specific signature, and can be utilized by an online file scanning service against malicious code.
Three very old men's experiences of mobility device use over time

Abstract Aim: The aim of this study was to explore experiences of mobility device (MD) use among very old single-living Swedish men. Methods: A multiple case study of three men, involving quantitative and qualitative data, was used in an embedded mixed methods design and presented in three narrative stories. To capture differences and similarities in the use of MDs a cross-case analysis was conducted. Results: The findings show that the devices were important for retaining independence in everyday life and for participation in social activities. Use of MDs impacted on everyday activities by enabling, restricting, or changing the performance. Planning and careful thinking were new strategies developed for managing everyday life. The devices were purchased, received from relatives, or prescribed by professionals at a time point when there was a need. The function and form of the devices and a supportive environment were considered important for optimal use. Conclusions: These narrative stories nurture our understanding of complex and multifaceted aspects impacting on MD use in everyday life for very old men. To support active ageing, occupational therapists and other health professionals need to seek information on personal needs and expectations, in order to understand individual perspectives on MD use.
Investigation of the Mechanical Faults Classification Using Support Vector Machine Approach

Support Vector Machine (SVM) is a machine learning algorithm based on the Statistical Learning Theory (SLT), which can get good classification effects with a few learning samples. SVM represents a new approach to pattern classification and has been shown to be particularly successful in many fields such as image identification and face recognition. It also provides us with a new method to develop intelligent fault diagnosis. This paper presents a SVM based approach for fault diagnosis of rolling bearings. Experimentation with vibration signals of bearing was conducted. The vibration signals acquired from the bearings were directly used in the calculating without the preprocessing of extracting its features. Compared with the Artificial Neural Network (ANN) based method, the SVM based method has desirable advantages. Also a multi-faults SVM classifier based on binary classifiers is constructed for gear faults in this paper. Other experiments with gear fault samples showed that the multi-fault SVM classifier has good classification ability and high efficiency, and suitable for on line diagnosis for mechanical system.
Effective Interference Cancellation Scheme for Device-to-Device Communication Underlaying Cellular Networks

It is expected that Device-to-Device (D2D) communication is allowed to underlay future cellular networks such as IMT-Advanced for spectrum efficiency. However, by reusing the uplink spectrums with the cellular system, the interference to D2D users has to be addressed to maximize the overall system performance. In this paper, a novel method to deal with the resource allocation and interference avoidance issues by utilizing the network peculiarity of a hybrid network to share the uplink resource is proposed and the implementation details are described in a real cellular system. Simulation results prove that satisfying performance can be achieved by using the proposed mechanism.
Estimation of KL divergence between large-alphabet distributions

The problem of estimating the KL divergence between two unknown distributions is studied. The alphabet size k of the distributions can scale to infinity. The estimation is based on m and n independent samples respectively drawn from the two distributions. It is first shown that there does not exist any consistent estimator to guarantee asymptotic small worst-case quadratic risk over the set of all pairs of distributions. A restricted set that contains pairs of distributions with bounded ratio f(k) is further considered. An augmented plug-in estimator is proposed, and is shown to be consistent if and only if m = ω(k ⋁ log2(f(k)) and n = ω(k f(k)). Furthermore, if f(k) ≥ log2k and log2(f(k)) = o(k), it is shown that any consistent estimator must satisfy the necessary conditions: m = ω( k/log k ⋁ log2(f(k)) and n = ω( k f(k)/log k).
Max Bergmann lecture Protein epitope mimetics in the age of structural vaccinology

This review highlights the growing importance of protein epitope mimetics in the discovery of new biologically active molecules and their potential applications in drug and vaccine research. The focus is on folded β‐hairpin mimetics, which are designed to mimic β‐hairpin motifs in biologically important peptides and proteins. An ever‐growing number of protein crystal structures reveal how β‐hairpin motifs often play key roles in protein–protein and protein–nucleic acid interactions. This review illustrates how using protein structures as a starting point for small‐molecule mimetic design can provide novel ligands as protein–protein interaction inhibitors, as protease inhibitors, and as ligands for chemokine receptors and folded RNA targets, as well as novel antibiotics to combat the growing health threat posed by the emergence of antibiotic‐resistant bacteria. The β‐hairpin antibiotics are shown to target a β‐barrel outer membrane protein (LptD) in Pseudomonas sp. , which is essential for the biogenesis of the outer cell membrane. Another exciting prospect is that protein epitope mimetics will be of increasing importance in synthetic vaccine design, in the emerging field of structural vaccinology. Crystal structures of protective antibodies bound to their pathogen‐derived epitopes provide an ideal starting point for the design of synthetic epitope mimetics. The mimetics can be delivered to the immune system in a highly immunogenic format on the surface of synthetic virus‐like particles. The scientific challenges in molecular design remain great, but the potential significance of success in this area is even greater. Copyright © 2013 European Peptide Society and John Wiley & Sons, Ltd.
THE FIRST DATA RELEASE OF THE KODIAQ SURVEY

We present and make publicly available the first data release (DR1) of the Keck Observatory Database of Ionized Absorption toward Quasars (KODIAQ) survey. The KODIAQ survey is aimed at studying galactic and circumgalactic gas in absorption at high redshift, with a focus on highly ionized gas traced by O vi, using the HIRES spectrograph on the Keck I telescope. KODIAQ DR1 consists of a fully reduced sample of 170 quasars at 0.29 < z em < 5.29 ? > observed with HIRES at high resolution (36,000 ≤ R ≤ 103,000) between 2004 and 2012. DR1 contains 247 spectra available in continuum normalized form, representing a sum total exposure time of ∼1.6 megaseconds. These coadded spectra arise from a total of 567 individual exposures of quasars taken from the Keck Observatory Archive (KOA) in raw form and uniformly processed using a publicly available HIRES data reduction package. DR1 is publicly available to the community, housed as a higher level science product at the KOA. We will provide future data releases that make available additional quasars, including those with pre-2004 observations taken with the previous-generation HIRES detectors.
Stability Margins in Adaptive Mixing Control Via a Lyapunov-Based Switching Criterion

This paper proposes a Lyapunov-based switching logic within the framework of adaptive mixing control (AMC), where a weighted combination of a family of candidate controllers can be inserted in the loop to regulate the output of an uncertain plant. The proposed AMC scheme employs a bank of parallel estimators, or multiple estimators, together with a switching logic that orchestrates which estimate should be evaluated by the mixer. The switching logic is driven by input/output data and uses Lyapunov-based criteria to assess the best estimate among the bank of parallel estimates. The resulting scheme guarantees convergence of the switching signal in finite time to a controller that satisfies a Lyapunov inequality implying a prescribed stability margin. The problem of convergence to the desired controller is addressed both analytically and numerically. In contrast, most classes of continuous tuning adaptive control or switching adaptive control schemes do not guarantee that after the switching stops or the adaptation is switched off the resulting closed loop linear time-invariant (LTI) system is stable, unless there is sufficient plant excitation that guarantees convergence to the desired fixed parameter controller. The proposed scheme guarantees that if the desired controller is switched on, it will never be switched off thereafter. Furthermore, simulations demonstrate that while alternative adaptation methods can converge to an LTI unstable feedback loop, the proposed scheme consistently converges to the desired controller.
Kullback–Leibler Divergence Frequency Warping Scale for Acoustic Scene Classification Using Convolutional Neural Network

Most of current best performing Acoustic Scene Classification (ASC) systems utilize Mel scale spectrograms with Convolutional Neural Networks (CNNs). Mel scale is a common way to suit frequency warping of human ears, with strict decreasing frequency resolution on low to high frequency range. However, we find that significant frequency bins are located at mid to high frequency range for some acoustic scenes, such as travelling by bus, tram or train. In this paper, we show that a better frequency warping scale for ASC can be automatically learned from raw spectrograms, using Kullback-Leibler (KL) divergence scale. Our KL scale spectrograms with CNN method is evaluated on two public ASC datasets. The results show that we outperform the Mel scale method on both datasets. In addition, we also employ a Conditional Generative Adversarial Nets (Conditional-GAN) model for data augmentation, to prevent overfitting problem and allow further improvements on ASC.
Distributed Power and Admission Control for Cognitive Radio Networks Using Antenna Arrays

We consider a system where two networks, namely the primary and secondary network operate by sharing a common radio spectrum that is licensed to the primary network. The secondary network uses cognitive radio technology to serve a number of secondary users, by making opportunistic access of the radio spectrum. For this system scenario, we present a distributed power and admission control algorithm with beamforming that minimizes the total transmitted power of the system such that the primary users as well as all secondary users who are permitted to be active in the system are guaranteed with their signal to interference plus noise ratio (SINR) requirements. Simulation results are provided to see the performance of the algorithm.
An Adaptive Variable Window Algorithm for Transformer Differential Protection Relay

The large-scale transformer protection is one of the most important devices in the protection system of substation and the requiring operating time is limited to 20ms or even less, i. e. A short data window orthogonal filter design method was presented through solving linear matrix equation after analyzing the physical concepts of sampling value phasor in fault signal. It could filter integer or fractional harmonic and guarantee cosine and sine filter possess the same amplitude versus frequency response characteristics. Then the design principle was put forward after analyzing the relationship between frequency property and data window transient responding performance. As an example, the design method was used as the adaptive digital filters for the transformer differential digital transformer differential protection device. The simulation of the algorithm was put forward in the MATLAB software platform. The dynamic test result of the algorithm shows the design method has the good ability for the transformer differential protection especial in transient performance. If it has appropriate settings, it won't be mal-operation on the condition of TA saturation or energizing inrush. The digital transformer differential protection will be improved greatly if this digital filter is used.
New Developments in Music Information Retrieval

The digital revolution has brought about a massive increase in the availability and distribution of musicrelated documents of various modalities comprising textual, audio, as well as visual material. Therefore, the development of techniques and tools for organizing, structuring, retrieving, navigating, and presenting music-related data has become a major strand of research—the field is often referred to as Music Information Retrieval (MIR). Major challenges arise because of the richness and diversity of music in form and content leading to novel and exciting research problems. In this article, we give an overview of new developments in the MIR field with a focus on content-based music analysis tasks including audio retrieval, music synchronization, structure analysis, and performance analysis.
Physiological consequences of an altered flow regime on Alabama bass (Micropterus henshalli)

The field of physiological ecology has expanded over the last several decades to incorporate concerns regarding the effects of anthro‐ pogenic disturbances on animals, including the endocrine response (Romero, 2004). When animals become stressed, their physiology and behaviour are often altered. Typically, this response is adaptive, but with more intense or prolonged stressors, the response can be‐ come maladaptive and possibly even physiologically dysfunctional (Barton, 2002; Wendelaar Bonga, 1997). The acute type of stress is experienced for brief periods, causing a temporary disturbance in homeostasis (Van Weerd & Komen, 1998). Chronic stress is associ‐ ated with prolonged challenges where there is a continued loss of homeostasis and adaptation is either not possible or is only achieved after a long time (Schreck, 1981, cited in Van Weerd & Komen, 1998). Chronic stress has been observed to affect growth, physiological condition, immune function, feeding behavior, competitive ability, and swimming performance of fishes (Barton, Schreck, & Barton, 1987; Gregory & Wood, 1999; Van Weerd & Komen, 1998). The stress response in teleosts is similar to other vertebrates that are ex‐ posed to environmental challenges (Baker, Gobush, & Vynne, 2013) with glucocorticoids often used as indicators of stress (Dantzer, Fletcher, Boonstra, & Sheriff, 2014). Altered flows resulting from hydropeaking operation from power‐generating dams have been found to have profound effects on aquatic ecosystems (Ligon, Dietrich, & Trush, 1995). Peaking oper‐ ation usually results in rapid changes in the quantity, quality, and lo‐ cation of different habitats (Garcia, Jorde, Habit, Caamano, & Parra, 2011). Bain, Finn, and Booke (1988) documented that highly variable and unpredictable flow modifications can cause a disturbance to fish Received: 9 October 2018 | Revised: 28 February 2019 | Accepted: 5 March 2019 DOI: 10.1111/jai.13906
Real time human face detection and tracking

This paper describes the technique for real time human face detection and tracking using a modified version of the algorithm suggested by Paul viola and Michael Jones. The paper starts with the introduction to human face detection and tracking, followed by apprehension of the Vila Jones algorithm and then discussing about the implementation in real video applications. Viola jones algorithm was based on object detection by extracting some specific features from the image. We used the same approach for real time human face detection and tracking. Simulation results of this developed algorithm shows the Real time human face detection and tracking supporting up to 50 human faces. This algorithm computes data and produce results in just a mere fraction of seconds.
Three-dimensional preservation of cellular and subcellular structures suggests 1.6 billion-year-old crown-group red algae

The ~1.6 Ga Tirohan Dolomite of the Lower Vindhyan in central India contains phosphatized stromatolitic microbialites. We report from there uniquely well-preserved fossils interpreted as probable crown-group rhodophytes (red algae). The filamentous form Rafatazmia chitrakootensis n. gen, n. sp. has uniserial rows of large cells and grows through diffusely distributed septation. Each cell has a centrally suspended, conspicuous rhomboidal disk interpreted as a pyrenoid. The septa between the cells have central structures that may represent pit connections and pit plugs. Another filamentous form, Denaricion mendax n. gen., n. sp. , has coin-like cells reminiscent of those in large sulfur-oxidizing bacteria but much more recalcitrant than the liquid-vacuole-filled cells of the latter. There are also resemblances with oscillatoriacean cyanobacteria, although cell volumes in the latter are much smaller. The wider affinities of Denaricion are uncertain. Ramathallus lobatus n. gen., n. sp. is a lobate sessile alga with pseudoparenchymatous thallus, “cell fountains,” and apical growth, suggesting florideophycean affinity. If these inferences are correct, Rafatazmia and Ramathallus represent crown-group multicellular rhodophytes, antedating the oldest previously accepted red alga in the fossil record by about 400 million years.
A Markov random field based multi-band model

An extension of the multi-band model including inter-band control of time asynchrony is described. It is based on the framework of Markov random fields. The law of the speech process is given by a parametric Gibbs distribution and a maximum likelihood parameter estimation algorithm is developed. This random field model is applied to isolated word recognition. It is shown that similar performances are obtained with the new model and with standard HMM techniques in the mono-band case. In the multi-band case, it is shown that the recognition rate decreases when the number of bands is increased but that modeling inter-band synchrony limits the performance decrease.