Miracle-dz/UniFAR-FTUs huggingface dataset:
Time Integrated Detection and Applications of Femtosecond Laser Pulses Scattered by Small Particles

In this thesis the time integrated detection of scattered femtosecond laser pulses, and illumination from a continuous wave semiconductor laser source with optical feedback and adaptable coherence length, is investigated for small particles. In this context the scattering function for small particles is numerically advanced. The angular distribution of local maxima of the scattering function is presented for small particles under ultrashort pulse illumination. The position of local maxima relating to scattering angle, particle size and refractive index is calculated with Fourier-Lorenz-Mie theory. Moreover, an estimate of the sensitivity of the scattering function to non-sphericity is presented, utilizing general Lorenz-Mie theory. For ultrashort pulse illumination the maxima of the supernumerary bows of the primary rainbow, which hold information on particle size and refractive index, are freed from disturbing interferences with reflection order and higher refractive order contributions. The presented results indicate the feasibility of precise in-situ measurements with Rainbow refractometry for highly spherical small particles with compact and cost-efficient sources of illumination and quantify the pulse duration or coherence length for the desired lower size range, which is essential information for future experimental studies. Moreover, a substantial reduction of morphology dependent resonances for microscopic water droplets is successfully demonstrated. For the first time, an electrodynamic Paul trap with novel geometry is applied to successfully observe the scattering of femtosecond laser pulses on small water droplets not only during a short period of milliseconds as in a droplet stream, but also over the temporal evolution of an evaporating droplet. Beyond Rainbow refractometry, the acquired results indicate the feasibility of new measurement techniques and the significant enhancement of existing methods. Under the aspect of the separation of scattering orders, interferometric particle imaging (IPI) is enhanceable by fitting the coherence length to the angle of detection. Illumination of small particles with femtosecond laser pulses is shown to facilitate direct size measurement from focused images of a thin spray by measurement of the intensity ratio of specific glare points on individual particles. Moreover, the smoothing of the diameter-intensity function for small particles allows for more precise determination of the Sauter mean diameter in the named size range. Due to the introduction of coherence length as a variable parameter for small particle characterization, the advantages of time integrated detection of femtosecond laser pulses scattered by small particles are underscored by the outlook of utilizing spatially compact and cost-efficient semiconductor laser devices with the important benefit of adjustable coherence length.
Genome-Wide Functional Profiling Reveals Genes Required for Tolerance to Benzene Metabolites in Yeast

Benzene is a ubiquitous environmental contaminant and is widely used in industry. Exposure to benzene causes a number of serious health problems, including blood disorders and leukemia. Benzene undergoes complex metabolism in humans, making mechanistic determination of benzene toxicity difficult. We used a functional genomics approach to identify the genes that modulate the cellular toxicity of three of the phenolic metabolites of benzene, hydroquinone (HQ), catechol (CAT) and 1,2,4-benzenetriol (BT), in the model eukaryote Saccharomyces cerevisiae. Benzene metabolites generate oxidative and cytoskeletal stress, and tolerance requires correct regulation of iron homeostasis and the vacuolar ATPase. We have identified a conserved bZIP transcription factor, Yap3p, as important for a HQ-specific response pathway, as well as two genes that encode putative NAD(P)H:quinone oxidoreductases, PST2 and YCP4. Many of the yeast genes identified have human orthologs that may modulate human benzene toxicity in a similar manner and could play a role in benzene exposure-related disease.
Characterisation of orange peel on highly polished steel surfaces

The surface quality of high gloss polished steel sheets with respect to ‘orange peel’ is studied. This is motivated by the fact that workpieces are ranked solely on the visual appearance of finished surfaces according to the observed degree of orange peel. Here, to quantify the degree of orange peel, surface topographies of industrial samples are acquired by means of phase shifting interferometry, from which various surface roughness parameters are calculated. These parameters are related to qualitative aspects of the surface using the Spearman's rank correlation coefficient. Two surface roughness parameters were identified as necessary for the evaluation of orange peel, suggesting that traditional methods can be replaced with suitable parameters that improve quality control procedures at the industry.
Compressed sensing undersampled MRI reconstruction using iterative shrinkage thresholding based on NSST

Compressed sensing (CS) has great potential for use in reducing data acquisition time in MRI. Generally sparsity is used as a prior knowledge to improve the quality of reconstructed image. In this paper, we propose an effective compressed sensing rapid MR imaging method incorporating Non-Subsampled Shearlet transform (NSST) sparsity prior information for MR image reconstruction from highly undersampled k-space data. In particular, we have implemented the more flexible decomposition with 2n directional subbands at each scale using NSST to obtain the prominent sparser representation for MR images. In addition, the mixed L1-L2 norm of the coefficients from the prior component and residual component is used to enforce joint sparsity. Numerical experiments demonstrate that the proposed method can significantly increase signal sparsity and improve the ill-conditioning of MR imaging system using NSST sparsity regularization. The evaluations on a T2-weighted brain image and a MR phantom experiment demonstrate superior performance of the proposed method in terms of reconstruction error reduction, detail preservation and aliasing, Gibbs ringing artifacts suppression compared to state-of-the-art technique. Its performance in objective evaluation indices outperforms conventional CS-MRI methods prominently.
Silicon neuron design based on phase reduction analysis

In this paper, we propose a dynamical system design approach for silicon neurons (SiNs) based on the phase reduction theory. The design approaches for SiNs can be classified as three: the phenomenological design, the conductance-based design, and the dynamical systems design. As a part of the third approach, we propose the phase response curve (PRC)-based design for SiNs to enhance synchronization in an ensembles of SiNs. We consider the key criteria to optimize SiN design in terms of phase response properties by analyzing various circuit models of previous SiNs. Furthermore, as a case study, we demonstrate how to tune circuit parameters to obtain a desirable PRC of a resonate-and-fire neuron (RFN) circuit. Finally, we discuss the possibility of extending our approach to design a class of the generalized integrate-and-fire neuron (GIFN) circuits including the Izhikevich type SiNs.
Effects of Mowing on Methane Uptake in a Semiarid Grassland in Northern China

Background Mowing is a widely adopted management practice for the semiarid steppe in China and affects CH4 exchange. However, the magnitude and the underlying mechanisms for CH4 uptake in response to mowing remain uncertain. Methodology/Principal Findings In two consecutive growing seasons, we measured the effect of mowing on CH4 uptake in a steppe community. Vegetation was mowed to 2 cm (M2), 5 cm (M5), 10 cm (M10), 15 cm (M15) above soil surface, respectively, and control was set as non-mowing (NM). Compared with control, CH4 uptake was substantially enhanced at almost all the mowing treatments except for M15 plots of 2009. CH4 uptake was significantly correlated with soil microbial biomass carbon, microbial biomass nitrogen, and soil moisture. Mowing affects CH4 uptake primarily through its effect on some biotic factors, such as net primary productivity, soil microbial C\N supply and soil microbial activities, while soil temperature and moisture were less important. Conclusions/Significance This study found that mowing affects the fluxes of CH4 in the semiarid temperate steppe of north China.
Nafion Nanofiber Membranes

A new type of proton conducting fuel cell membrane has been fabricated and evaluated via preliminary physical property determinations. The membrane is composed of a 3-D interconnected network of Nafion (perfluorosulfonic acid) nanofibers that have been embedded in an uncharged and inert polymer matrix. Nafion was successfully electrospun into fibers by adding to the spinning solution a low concentration (1 wt% relative to Nafion) of high molecular weight poly(ethylene oxide). Membranes were made with an average fiber diameter in the range of 161-730 nm, where the nanofiber mat occupied 60-80% of the membrane volume. The inert matrix polymer was UV-crosslinked Norland Optical Adhesive 63. The resulting membranes exhibited a high proton conductivity (0.06-0.08 S/cm at 25oC in water), low water swelling (12-23 wt% at 25oC), and improved mechanical properties, as compared to a recast homogeneous Nafion film.
Microstructural investigation and mechanical properties of dissimilar friction stir welded magnesium alloys

Dissimilar joints of magnesium alloys were obtained by friction stir welding. Detailed microstructure and texture examinations were performed on the joints. Significant difference in microtexture distribution and microstructural features is observed between crown and stir zones in the dissimilar joints. However, an overall effect of these factors on mechanical properties of layered joints is not obvious as both the up and middle samples present quite similar yield strength and strain hardening behaviour. Moreover, both samples fracture in the Mg–3Al–1Zn alloy side. The fracture of the middle sample starts at the boundary of transition and stir zones, while the up sample starts in the crown zone side.
Analysis of a Robust Reputation System for Self-Organized Networks Analysis of Reputation System

Self-organized networks require some mechanism to ensure cooperation and fairness. A promising approach is the use of decentralized reputation systems. However, their vulnerability to liars has not yet been analyzed in detail. In this paper, we provide a first step to the robustness analysis of a reputation system based on a deviation test. Users accept second hand information only if this does not differ too much from their reputation values. We simplify the original system in order to obtain a one-dimensional formulation and show that it exhibits a phase transition. In the subcritical regime, the reputation system is robust. In the supercritical regime, lying has an impact. We obtain the critical values via a meanfield approach and verify the results by explicit computation. Thus, we provide conditions for the deviation test to make the reputation system robust as well as quantitative results on what goes wrong in the supercritical regime.
The disruptive effects of pain on n-back task performance in a large general population sample

Abstract Pain captures attention, displaces current concerns, and prioritises escape and repair. This attentional capture can be measured by its effects on general cognition. Studies on induced pain, naturally occurring acute pain, and chronic pain all demonstrate a detrimental effect on specific tasks of attention, especially those that involve working memory. However, studies to date have relied on relatively small samples and/or one type of pain, thus restricting our ability to generalise to wider populations. We investigated the effect of pain on an n-back task in a large heterogeneous sample of 1318 adults. Participants were recruited from the general population and tested through the internet. Despite the heterogeneity of pain conditions, participant characteristics, and testing environments, we found a performance decrement on the n-back task for those with pain, compared with those without pain; there were significantly more false alarms on nontarget trials. Furthermore, we also found an effect of pain intensity; performance was poorer in participants with higher intensity compared with that in those with lower intensity pain. We suggest that the effects of pain on attention found in the laboratory occur in more naturalistic settings. Pain is common in the general population, and such interruption may have important, as yet uninvestigated, consequences for tasks of everyday cognition that involve working memory, such as concentration, reasoning, motor planning, and prospective memory.
Proactive Policy Management using TBVH Mechanism in Heterogeneous Networks

In order to achieve seamless interoperability in heterogeneous networking, it is vital to improve the context-awareness of the mobile node (MN) so that it is able to predict future network conditions with sufficient accuracy. In this paper, we introduce a predictive mathematical model for calculating the estimated Time Before Vertical Handover (TBVH) component from available network parameters. The model is practically implemented in OPNET and our simulation results confirm the validity of the concept. We then demonstrate how the knowledge of TBVH along with other network parameters can be applied by downward Quality of Service management policies which bundle multi-class traffic streams on to available network channels based on application QoS, device mobility patterns and prevailing channel conditions.
An Energy-Efficient Positioning Scheme for Location-Based Services in a Smartphone

As Location-Based Services (LBSs) are widely used in smartphone applications, Global Positioning System (GPS) becomes one of the main sources of a smartphone's energy consumption. This paper presents an energy-efficient positioning scheme for smartphones called EEPS (Energy-Efficient Positioning Scheme). EEPS adaptively performs the positioning of a smartphone considering the interesting regions of a user, accuracy requirement of each application executed within the smartphone, and the battery level. Simulations with various real applications and scenarios show that EEPS reduces 50.1% of energy consumption compared to GPS. Nevertheless, it satisfies the accuracy requirement of each application.
Answering the demands of digital genomics

The continuing revolution in DNA sequencing and biological sensor technologies is driving a digital transformation to our approaches for observation, experimentation, and interpretation that form the foundation of modern biology and genomics. Whereas classical experiments were limited to thousands of hand‐collected observations, today's improved sensors allow billions of digital observations and are improving at an exponential rate that exceeds Moore's law. These improvements have made it possible to monitor the dynamics of biological processes on an unprecedented scale, but have proportionally greater quantitative and computational requirements.
Immune Response to Lipoproteins in Atherosclerosis

Atherosclerosis, the underlying cause of cardiovascular disease, is characterized by chronic inflammation and altered immune response. Cholesterol is a well-known risk factor associated with the development of cardiovascular diseases. Elevated serum cholesterol is unique because it can lead to development of atherosclerosis in animals and humans even in the absence of other risk factors. Modifications of low-density lipoproteins mediated by oxidation, enzymatic degradation, and aggregation result in changes in their function and activate both innate and adaptive immune system. Oxidized low-density lipoprotein (LDL) has been identified as one of the most important autoantigens in atherosclerosis. This escape from self-tolerance is dependent on the formation of oxidized phospholipids. The emerging understanding of the importance of immune responses against oxidized LDL in atherosclerosis has focused attention on the possibility of development of novel therapy for atherosclerosis. This review provides an overview of immune response to lipoproteins and the fascinating possibility of developing an immunomodulatory therapy for atherosclerosis.
Research on secure interaction of Distribution Network data assets under Privacy Protection Framework

This paper discusses the research on the secure interaction of distribution network data assets under the framework of privacy protection. The intermediary introduces the classification and classification of data assets, and puts forward a scheme to determine the weight of distribution network data assets by using Analytic hierarchy process (AHP), which can further subdivide the classification of data assets, so that sensitive information can be protected more accurately. In addition, according to the existing problems in the process of data exchange in distribution network, a data interaction protection scheme based on Merkle tree is proposed. combined with Hash algorithm, a multi-level Merkle tree is constructed to ensure the security of data exchange, and the effectiveness of the scheme is illustrated by the conclusion, which puts forward a new idea for the research on secure interaction of distribution network data assets under the framework of privacy protection.
Model for self-polarization and motility of keratocyte fragments

Computational modelling of cell motility on substrates is a formidable challenge; regulatory pathways are intertwined and forces that influence cell motion are not fully quantified. Additional challenges arise from the need to describe a moving deformable cell boundary. Here, we present a simple mathematical model coupling cell shape dynamics, treated by the phase-field approach, to a vector field describing the mean orientation (polarization) of the actin filament network. The model successfully reproduces the primary phenomenology of cell motility: discontinuous onset of motion, diversity of cell shapes and shape oscillations. The results are in qualitative agreement with recent experiments on motility of keratocyte cells and cell fragments. The asymmetry of the shapes is captured to a large extent in this simple model, which may prove useful for the interpretation of experiments.
Terrain adaptive detector selection for visual odometry in natural scenes

Pose estimation is one of the important tasks for mobile robots exploring in outdoor environments. Recently, visual odometry has received a lot of attention since its localization is accurate even with low-cost sensors. Furthermore, the technique is not affected by wheel slips, and it can be performed without external infrastructures and preliminary maps. While existing techniques successfully provide good localization of outdoor vehicles, possible failures are not yet fully examined in untextured terrains where feature tracking occasionally fails. This paper proposes an approach to detect interest points from a wide variety of terrains by adaptively selecting algorithms. Experiments show that the approach provides robust and fast interest point detection even in untextured natural scenes. Graphical Abstract
Mechanisms of Neural Synchrony in the Septohippocampal Pathways Underlying Hippocampal Theta Generation

Using urethane-anesthetized rats, 18 simultaneously recorded septohippocampal cell pairs (36 individual cells), each classified as theta-related according to the criteria of Colom and Bland (1987), were studied during four spontaneously occurring hippocampal field conditions: (1) large amplitude irregular activity (LIA) only; (2) the transition from LIA to theta; (3) theta only; and (4) the transition from theta to LIA. The main objective was to study the temporal relationships and degree of neural synchrony between the discharges of the cell pairs, using both time-averaged and time-dependent joint peristimulus time histogram correlation techniques, during the four conditions, to determine their contribution to the control of oscillation and synchrony (theta) in the hippocampus. The study demonstrated that the transition from the LIA state to the theta field state in the hippocampus required a temporal sequence of changes in theta-related cellular activity occurring on average 500 msec preceding the transition: (1) the medial septum inhibits hippocampal theta-OFF cells; (2) medial septal tonic theta-ON cells provide tonic depolarizing inputs to initiate membrane potential oscillations (MPOs) in hippocampal phasic theta-ON cells, whereas medial septal phasic theta-ON cells synchronize the MPOs of hippocampal phasic theta-ON cells and the discharges of hippocampal tonic theta-ON cells. Much of the time preceding the LIA to theta transition is accounted for by recruitment of these theta-related cell populations. Conversely, “turning off” the theta state occurs abruptly and involves the medial septal disinhibition of hippocampal theta-OFF cells.
Performance improvement of MUSIC algorithm by combined use of Root and Beam-space MUSIC versions

A process using a combination of the spectral MUSIC algorithm with its variations Root-MUSIC, Beamspace MUSIC and Beamspace Root-MUSIC for determination of Direction-of-Arrival of wavefronts impinging on an array is proposed. Simulation results are presented, that illustrate the success of the process to determine the correct angles of signals arriving at the array sensors in a wide range of angles.
PEARL: An interactive visual analytic tool for understanding personal emotion style derived from social media

Hundreds of millions of people leave digital footprints on social media (e.g., Twitter and Facebook). Such data not only disclose a person's demographics and opinions, but also reveal one's emotional style. Emotional style captures a person's patterns of emotions over time, including his overall emotional volatility and resilience. Understanding one's emotional style can provide great benefits for both individuals and businesses alike, including the support of self-reflection and delivery of individualized customer care. We present PEARL, a timeline-based visual analytic tool that allows users to interactively discover and examine a person's emotional style derived from this person's social media text. Compared to other visual text analytic systems, our work offers three unique contributions. First, it supports multi-dimensional emotion analysis from social media text to automatically detect a person's expressed emotions at different time points and summarize those emotions to reveal the person's emotional style. Second, it effectively visualizes complex, multi-dimensional emotion analysis results to create a visual emotional profile of an individual, which helps users browse and interpret one's emotional style. Third, it supports rich visual interactions that allow users to interactively explore and validate emotion analysis results. We have evaluated our work extensively through a series of studies. The results demonstrate the effectiveness of our tool both in emotion analysis from social media and in support of interactive visualization of the emotion analysis results.