Miracle-dz/UniFAR-FTUs huggingface dataset:
When a fluid-structure interaction keeps you awake : a physical approach to Obstructive Sleep Apnea.

The Sleep Apnea Syndrome is known to be related with a partial (hypopnea) or total (apnea) collapse of the upper airway. The patency of the upper airway is dictated by a combination of passive mechanical properties and active neural mechanisms. From a physical point of view, neglecting active neural control mechanisms, the airway collapse can be explained by the interaction of the airo w during respiration (uid) with the surrounding tissues (structure). The characteristic recurrent collapse causes about 3 % of the adult population to suffer from Obstructive Sleep Apnea (OSA). A systematic review of published studies on OSA insists on the necessity of a better understanding of the factors determining the airway obstruction in order to improve modelling, simulation and eventually prediction of the uid-structure interaction at the origin of OSA. Prediction of OSA is in particular important to foresee the outcome of surgical procedures and to estimate its long-term effectiveness. In order to be of practical use a surgical prediction tool demands reliable and accurate simulation results available within a reasonable time delay and exploiting relevant and ‘in-vivo’ accessible physiological data. In order to contribute to the understanding of OSA a physical approach is presented consisting mainly of three stages. At rst, relevant physical quantities are formulated based on physiological ‘in-vivo’ observations in order to dene the problem. Secondly, a simplied theoretical model is proposed based on assumptions derived of the order of magnitudes derived during the rst stage. Thirdly, an experimental validation of the assumptions and of the accuracy of the theoretical model is performed in a suitable experimental setup allowing to control model input parameters and to measure model output parameters.
Large-scale quantum photonic circuits in silicon

Abstract Quantum information science offers inherently more powerful methods for communication, computation, and precision measurement that take advantage of quantum superposition and entanglement. In recent years, theoretical and experimental advances in quantum computing and simulation with photons have spurred great interest in developing large photonic entangled states that challenge today’s classical computers. As experiments have increased in complexity, there has been an increasing need to transition bulk optics experiments to integrated photonics platforms to control more spatial modes with higher fidelity and phase stability. The silicon-on-insulator (SOI) nanophotonics platform offers new possibilities for quantum optics, including the integration of bright, nonclassical light sources, based on the large third-order nonlinearity (χ(3)) of silicon, alongside quantum state manipulation circuits with thousands of optical elements, all on a single phase-stable chip. How large do these photonic systems need to be? Recent theoretical work on Boson Sampling suggests that even the problem of sampling from e30 identical photons, having passed through an interferometer of hundreds of modes, becomes challenging for classical computers. While experiments of this size are still challenging, the SOI platform has the required component density to enable low-loss and programmable interferometers for manipulating hundreds of spatial modes. Here, we discuss the SOI nanophotonics platform for quantum photonic circuits with hundreds-to-thousands of optical elements and the associated challenges. We compare SOI to competing technologies in terms of requirements for quantum optical systems. We review recent results on large-scale quantum state evolution circuits and strategies for realizing high-fidelity heralded gates with imperfect, practical systems. Next, we review recent results on silicon photonics-based photon-pair sources and device architectures, and we discuss a path towards large-scale source integration. Finally, we review monolithic integration strategies for single-photon detectors and their essential role in on-chip feed forward operations.
Pro-oncogenic role of SerpinB3 in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most relevant sanitary problems for its prevalence and poor prognosis. This tumor is characterized by highly heterogeneous features, both at clinical and molecular level. SerpinB3 (squamous cell carcinoma antigen-1 or SCCA1) is a serine-protease inhibitor that protects cells from oxidative stress conditions, but in chronic liver damage it may lead to HCC through different strategies, including inhibition of apoptosis, induction of epithelial to mesenchymal transition, cell proliferation and invasiveness. Mechanisms of tumor growth promotion induced by SerpinB3 encompass the inhibition of intratumor infiltration of natural killer cells and the up-regulation of Myc oncogene. Recently this serpin has also been identified as a Ras-responsive factor and modulator of metabolic pathways. In the liver SerpinB3 is undetectable in normal hepatocytes, but its expression progressively increases in chronic liver diseases, dysplastic nodules and hepatocellular carcinoma, especially in those with poor prognosis, in which it could also exert immunomodulatory effects. In serum SerpinB3/4 isoforms (or SCCA) circulate bound to IgMs (SCCA-IgM) in patients with HCC, and in patients with cirrhosis their levels have been found correlated to the risk of HCC development. Preliminary findings in patients with HCC revealed that SCCA-IgM levels are predictive of HCC prognosis.
Archaeal and bacterial communities in geochemically diverse hot springs of Yellowstone National Park, USA

Microbiological and geochemical surveys were conducted at three hot springs (Obsidian Pool, Sylvan Spring, and ‘Bison Pool’) in Yellowstone National Park (Wyoming, USA). Microbial community structure was investigated by polymerase chain reaction (PCR) amplification of 16S rRNA gene sequences from DNA extracted from sediments of each hot spring, followed by molecular cloning. Both bacterial and archaeal DNA was retrieved from all samples. No Euryarchaea were found, but diverse Crenarchaea exist in all three pools, particularly affiliating with deep‐branching, but uncultivated organisms. In addition, cloned DNA affiliating with the Desulphurococcales and Thermoproteales was identified, but the distribution of taxa differs in each hot spring. The bacterial community at all three locations is dominated by members of the Aquificales and Thermodesulfobacteriales, indicating that the ‘knallgas’ reaction (aerobic hydrogen oxidation) may be a central metabolism in these ecosystems. To provide geochemical context for the microbial community structures, energy‐yields for a number of chemolithoautotrophic reactions are provided for >80 sampling sites in Yellowstone, including Obsidian Pool, Sylvan Spring, and ‘Bison Pool’. This energy profile shows that the knallgas reaction is just one of many exergonic reactions in the Yellowstone hot springs, that energy‐yields for certain reactions can vary substantially from one site to the next, and that few of the demonstrated exergonic reactions are known to support microbial metabolism.
The Importance of Haem vs Non-Haem Iron in the Survival and Pathogenesis of Brucella abortus

The genus Brucella belongs to the alpha-group of proteobacteria, along with plant pathogens as Agrobacterium and symbionts as Rhizobium and Bradyrhizobium. Several Brucella species, highly related at the genetic level, have been identified as the etiological agents of brucellosis. Each one has shown a preferred host although they can infect other animals. Animal brucellosis is usually endemic in developing countries and its main impact is economic. Human brucellosis is difficult to diagnose because symptoms are extremely variable. Few live vaccines are available for animals only, not for humans. The main problems with this pathogen are the lack of virulence factors commonly identified in other bacteria and the ability to establish a niche inside eukaryotic cells, where they replicate and survive evading the immune response and the action of other antibacterial molecules.
A High-Throughput Method for Targeted Metabolomics Analysis of Different Tissue Samples using the Absolute IDQ TM Kit

In recent years technology improvements have greatly enhanced the field of metabolomics and nowadays hundreds of endogenous metabolites can be quantified in body fluids like plasma and serum in a high-throughput manner using targeted metabolomics approaches [1-3]. Accurate and reproducible determination of metabolite concentrations in tissue samples are of high importance to characterize animal models and to identify metabolic changes that occur in different tissue types in specific diseases. However, the extraction of metabolites from tissue is often one of the most labor intensive steps for metabolomics studies. Here we report the development of a high-throughput method allowing the rapid extraction of metabolites from multiple tissue samples. The method involves a beadbased homogenizer in combination with a simple extraction protocol and the use of the AbsoluteIDQTM Kit. The AbsoluteIDQ kit was originally validated for plasma and can simultaneously identify and quantify a large number of endogenous metabolites [4]. The metabolite panel of the kit includes acylcarnitines, amino acids, hexose, glycerophospholipids, and sphingolipids metabolites with significant different lipophilic and hydrophilic properties. Therefore, different extraction solvents were tested, and both reproducibility as well as suppression effects were evaluated for a range of different animal tissue types including liver, kidney, muscle, brain, and fat tissue.
In Vitro Study of Iron Doped Hydroxyapatite

The effect of iron substitution on the bioactivity of hydroxyapatite (HAp) under the physiological conditions was investigated. Five samples of iron doped hydroxyapatite (FeHAp) with different iron concentrations (0, 0.05, 0.1, 0.2, and 0.3 mol%) were synthesized by wet chemical method. The formation of bone-like apatite layer on the surface of the samples was detected using X-ray diffraction (XRD), Fourier transforms infrared (FTIR) and scanning electron microscope techniques. The changes of the pH of SBF medium were measured at pre-determined time intervals using a pH meter. The dissolution of calcium, phosphorus and iron ions in SBF medium was determined by single beam scanning spectrophotometer. XRD and FTIR results exhibit the formation of carbonate apatite layer on the surface of the immersed samples, which increase with the increase of iron content. SEM results showed agglomeration of small crystals on the surface of the immersed samples. The solubility and dissolution tests revealed that iron doped HAp samples had a higher solubility and dissolution rate than pure sample, which indicated that iron increased the bioactivity of HAp in vitro.
Thermodynamics with Continuous Information Flow

We provide a unified thermodynamic formalism describing information transfers in autonomous as well as nonautonomous systems described by stochastic thermodynamics. We demonstrate how information is continuously generated in an auxiliary system and then transferred to a relevant system that can utilize it to fuel otherwise impossible processes. Indeed, while the joint system satisfies the second law, the entropy balance for the relevant system is modified by an information term related to the mutual information rate between the two systems. We show that many important results previously derived for nonautonomous Maxwell demons can be recovered from our formalism and use a cycle decomposition to analyze the continuous information flow in autonomous systems operating at steady-state. A model system is used to illustrate our findings.
Factors Influencing Exercise Engagement When Using Activity Trackers: Nonrandomized Pilot Study

Background It is well reported that tracking physical activity can lead to sustained exercise routines, which can decrease disease risk. However, most stop using trackers within a couple months of initial use. The reasons people stop using activity trackers can be varied and personal. Understanding the reasons for discontinued use could lead to greater acceptance of tracking and more regular exercise engagement. Objective The aim of this study was to determine the individualistic reasons for nonengagement with activity trackers. Methods Overweight and obese participants (n=30) were enrolled and allowed to choose an activity tracker of their choice to use for 9 weeks. Questionnaires were administered at the beginning and end of the study to collect data on their technology use, as well as social, physiological, and psychological attributes that may influence tracker use. Closeout interviews were also conducted to further identify individual influencers and attributes. In addition, daily steps were collected from the activity tracker. Results The results of the study indicate that participants typically valued the knowledge of their activity level the activity tracker provided, but it was not a sufficient motivator to overcome personal barriers to maintain or increase exercise engagement. Participants identified as extrinsically motivated were more influenced by wearing an activity tracker than those who were intrinsically motivated. During the study, participants who reported either owning multiple technology devices or knowing someone who used multiple devices were more likely to remain engaged with their activity tracker. Conclusions This study lays the foundation for developing a smart app that could promote individual engagement with activity trackers.
High-resolution surface plasmon imaging of gold nanoparticles by energy-filtered transmission electron microscopy

We demonstrate the imaging capabilities of energy-filtered transmission electron microscopy at high-energy resolution in the low-energy-loss region, reporting the direct image of a surface plasmon of an elongated gold nanoparticle at energies around 1 eV. Using complimentary model calculations performed within the boundary element method approach we can assign the observed results to the plasmon eigenmodes of the metallic nanoparticle.
NONLINEAR DEMOGRAPHIC DYNAMICS: MATHEMATICAL MODELS, STATISTICAL METHODS, AND BIOLOGICAL EXPERIMENTS'

Our approach to testing nonlinear population theory is to connect rigorously mathematical models with data by means of statistical methods for nonlinear time series. We begin by deriving a biologically based demographic model. The mathematical analysis identifies boundaries in parameter space where stable equilibria bifurcate to periodic 2-cy- cles and aperiodic motion on invariant loops. The statistical analysis, based on a stochastic version of the demographic model, provides procedures for parameter estimation, hypothesis testing, and model evaluation. Experiments using the flour beetle Tribolium yield the time series data. A three-dimensional map of larval, pupal, and adult numbers forecasts four possible population behaviors: extinction, equilibria, periodicities, and aperiodic motion including chaos. This study documents the nonlinear prediction of periodic 2-cycles in laboratory cultures of Tribolium and represents a new interdisciplinary approach to un- derstanding nonlinear ecological dynamics.
Intensity of interaction in supply of business advice and client impact: a comparison of consultancy, business associations and government support initiatives for SMEs

This paper assesses the supply of business advice using new empirical evidence from a large scale survey of SMEs. The chief focus of the paper is on a comparison of suppliers that operate in different environments of regulation, contract and reputation. The paper argues that interaction intensity varies with the level of information asymmetry of these different environments, between different types of service supplier and their clients. Interaction intensity between suppliers also varies as a result of the level of trust they enjoy: for example, the low trust enjoyed by consultants appears to encourage higher intensity of interaction which improves the tailoring of the service to the client's needs and enhances impact. The paper assesses interaction intensity using the existence of site visits and/or a written brief/contract as indicators. Although these measures have limitations, the paper demonstrates clear and significant differences between suppliers in terms of interaction intensity, use of contracts and impact in three broad categories: private sector consultancy (low trust, high intensity, high impact), business associations (high trust, low intensity, moderate impact) and government support agencies (moderate trust, moderate to high intensity, moderate or low impact). Multivariate estimation methods demonstrate that significant differences in interaction intensity, use of contracts and impact by client type are much less important than differences in supplier type. This indicates that suppliers generally develop more into niche service fields or groups of services rather than niches related to types of firm.
Stability Analysis of Converter Control Modes in Low-Inertia Power Systems

Ahstract- This paper deals with the small-signal stability analysis of converter control modes in low-inertia power systems. For this purpose, a detailed differential-algebraic equation model of the voltage source converter and its control scheme is developed. Both grid-forming and grid-feeding concepts have been considered, as well as different active power controllers based on traditional droop and virtual inertia emulation. An eigenvalue analysis of the linearized state-space system is conducted and the performance of different control configurations is compared. Furthermore, various bifurcation studies have been completed and conclusions on stability margins have been drawn with respect to control sensitivity and robustness.
Temporal Stability of Soil Water Contents: A Review of Data and Analyses

Temporal stability (TS) of soil water content (SWC) has been observed throughout a wide range of spatial and temporal scales. Yet, the evidence with respect to the controlling factors on TS SWC remains contradictory or nonexistent. The objective of this work was to develop the first comprehensive review of methodologies to evaluate TS SWC and to present and analyze an inventory of published data. Statistical analysis of mean relative difference (MRD) data and associated standard deviations (SDRD) from 157 graphs in 37 publications showed a trend for the standard deviation of MRD (SDMRD) to increase with scale, as expected. The MRD followed generally the Gaussian distribution with R2 ranging from 0.841 to 0.998. No relationship between SDMRD and R2 was observed. The smallest R2 values were mostly found for negatively skewed and platykurtic MRD distributions. A new statistical model for temporally stable SWC fields was proposed. The analysis of the published data on seven measurement‐, terrain‐, and climate‐related potentially controlling factors of TS SWC suggested intertwined effects of controlling factors rather than single dominant factors. This calls for a focused research effort on the interactions and effects of measurement design, topography, soil, vegetation and climate on TS SWC. Research avenues are proposed which will lead to a better understanding of the TS phenomenon and ultimately to the identification of the underlying mechanisms.
Metal Induced Growth of Si Thin Films and NiSi Nanowires

Abstract : Thin film silicon has many useful purposes. Among the applications are solar cells and thin film transistors. This project involves a new and potentially lower cost method to produce thin silicon films. The method is called metal induced growth (MIG). A thin catalyst metal layer deposited on a foreign low cost substrate serves as the basis for growth of a nanocrystalline silicon thin film with thickness of 5-10 microns and preferred orientation of (220). The silicon deposition by magnetron sputtering on the heated substrate resulted in columnar structured grains having a diameter up to about 0.5 microns. Schottky barrier solar cells fabricated on these films gave a photocurrent of about 5 mA/sq cm and open circuit voltage of 0.25 volts. A modified process gave NiSi crystalline nanowires with length up to 10 microns and diameter of about 50 nm.
Performance Analysis of Channel Capacity and Throughput of LTE Downlink System

In this paper, we analyzed a numerical evaluation of the performance of MIMO radio systems in the LTE network environment. Downlink physical layer of the OFDM-MIMO based radio interface is considered for system model and a theoretical analysis of the bit error rate of the two space-time codes (SFBC 2×1 and FSTD 4×2 codes are adopted by the LTE norm as a function of the signal to noise ratio. Analytical expressions are given for transmission over a Rayleigh channel without spatial correlation which is then compared with Monte-Carlo simulations. Further evaluated channel capacity and simulation results show throughput almost reaches to the capacity limit.
Differential Evolution Enhanced with Composite Population Information

Differential evolution (DE) is a simple and powerful evolutionary algorithm, which has been successfully used in various scientific and engineering fields. Generally, the base and difference vectors of the mutation operator in most of DE are randomly selected from the current population. Additionally, the population information is not fully exploited in the design of DE. In order to alleviate these drawbacks and enhance the performance of DE, this study presents a DE framework with Composite Population Information based mutation operator (DE-CPI) for global numerical optimization. In DE-CPI, the ring topology is employed to define a neighborhood for each individual and then the direction information with the neighbors is introduced into the mutation operator of DE. By this way, the composite population information, i.e., neighborhood and direction information, can be fully and simultaneously utilized in DE-CPI to guide the search of DE. In order to evaluate the effectiveness of the proposed method, DE-CPI is incorporated into the original DE algorithms, as well as several advanced DE variants. Experimental results clearly show that DE-CPI is able to enhance the performance of most of the DE algorithms studied. Subject Categories and Descriptors I.5. 3 [Clustering]; Algorithms G.1. 6 [Optimization] General Terms: Evolutionary Algorithms, Neighborhood