Miracle-dz/UniFAR-FTUs huggingface dataset:
Biofilm Lifestyle in Recurrent Urinary Tract Infections

Urinary tract infections (UTIs) represent one of the most common infections that are frequently encountered in health care facilities. One of the main mechanisms used by bacteria that allows them to survive hostile environments is biofilm formation. Biofilms are closed bacterial communities that offer protection and safe hiding, allowing bacteria to evade host defenses and hide from the reach of antibiotics. Inside biofilm communities, bacteria show an increased rate of horizontal gene transfer and exchange of resistance and virulence genes. Additionally, bacterial communication within the biofilm allows them to orchestrate the expression of virulence genes, which further cements the infestation and increases the invasiveness of the infection. These facts stress the necessity of continuously updating our information and understanding of the etiology, pathogenesis, and eradication methods of this growing public health concern. This review seeks to understand the role of biofilm formation in recurrent urinary tact infections by outlining the mechanisms underlying biofilm formation in different uropathogens, in addition to shedding light on some biofilm eradication strategies.
Observing Biomass Concentration in a Fixed-Bed Bioreactor

Abstract The growth of microorganisms in a biofilm was monitored, based on available substrate measurements and first principle modeling. The biofilter was described by a set of partial differential equations obtained from species mass balance. Using two interior collocation points, the model was reduced to a set of ordinary differential equations, with sufficient accuracy to describe the growth of biomass along the reactor bed. An extended Kalman filter was designed at three measurement locations, which resulted in an accurate estimation of the process. Simulation results, provided in MathematicaR and MatlabR environments, showed a significant decrease in the biomass error covariance: 0.0065 to 2.50E-05 and 0.0065 to 1.73E-06 for two different measurement noise levels using a normalized bioreactor length of 0.21. Similar results were obtained at the remaining collocation points. The proposed procedure may have applications for water pollution control.
Fatigue failure in thin-film polycrystalline silicon is due to subcritical cracking within the oxide layer

It has been established that microelectromechanical systems created from polycrystalline silicon thin films are subject to cyclic fatigue. Prior work by the authors has suggested that although bulk silicon is not susceptible to fatigue failure in ambient air, fatigue in micron-scale silicon is a result of a “reaction-layer” process, whereby high stresses induce a thickening of the post-release oxide at stress concentrations such as notches, which subsequently undergoing moisture-assisted cracking. However, there exists some controversy regarding the post-release oxide thickness of the samples used in the prior study. In this letter, we present data from devices from a more recent fabrication run that confirm our prior observations. Additionally, new data from tests in high vacuum show that these devices do not fatigue when oxidation and moisture are suppressed. Each of these observations lends credence to the “reaction-layer” mechanism.
Nano-bio quantum technology for device-specific materials

NASA Langley Research Center has developed several breakthrough materials technologies using bio and nanotechnology specifically for device applications. With their expertise and strength in device-specific materials technologies, Langley researchers have identified innovative methods and newly designed materials, such as rhombohedral single crystal silicon-germanium, twin-lattice structures of silicon-germanium for thermoelectric applications, smart optical materials, and size-controlled metallic nanoparticles. These new materials have offered new opportunities to develop devices and power systems, such as micro spectrometers, quantum-apertures, wireless power transmission systems, smart optics, bionanobatteries, and biofuel cells. An overview of these technologies will be given at the meeting.
Morava K-theories and localisation

Introduction Basic definitions $E$ theory $K$-injective spectra Generalised Moore spectra Bousfield classes The $E(n)$-local category General properties of the $K(n)$-local category Smallness and duality Homology and cohomology functors Brown-Comenetz duality The natural topology Dualisable spectra $K$-nilpotent spectra Grading over the Picard group Examples Questions and conjectures Completion Small objects in other categories References Index.
Robust Interferometric ISAR Imaging With UAMP-Based Joint Sparse Signal Recovery

Sparse Bayesian learning (SBL) has found successful applications in interferometric inverse synthetic aperture radar (InISAR) imaging, especially in the presence of limited number of pulses or when using sparse apertures. SBL-based InISAR algorithms have been proven to be significantly superior to Fourier transform-based ones. However, the existing SBL-based algorithms are slow due to their high computational complexity. Moreover, there is also much room to improve in terms of imaging performance. In this article, leveraging the approximate message passing with unitary transformation (UAMP), we propose an InISAR imaging algorithm named UAMP joint sparse recovery (JSR), which is much faster and delivers notably higher imaging accuracy than the existing SBL-based algorithms. Specifically, we develop a type-2 joint sparse model for InISAR imaging and formulate it as a two-layer multiple measurement vectors joint sparse problem. Based on a factor graph representation, the message passing techniques are used to efficiently solve this problem, which leads to the UAMP-JSR algorithm. Results based on extensive simulations and experiments based on the real data collected by the Pisa Radar demonstrate the effectiveness and superiority of the proposed algorithm compared to existing algorithms.
The Role of CTNNA1 in Malignancies: An Updated Review

Catenin alpha 1 (CTNNA1), encoding α-catenin, is involved in several physiological activities, such as adherens junction synthesis and signal transduction. Recent studies have suggested additional functions for CTNNA1 malignancies. This review systematically summarizes the varying functions of CTNNA1 in different tumors and briefly describes the diverse pathways and mechanisms involved in different types of tumors. CTNNA1 is abnormally expressed in leukemia and solid tumor such as cancers of digestive system, genitourinary system and breast, and it's related to the occurrence, development, and prognosis of tumors. In addition, the possible physiological processes involving CTNNA1, such as methylation, miRNA interference, or regulatory axes, similar to those of CDH1, SETD2, and hsa-miR-30d-5p/GJA1 are also summarized here. The precise mechanism of CTNNA1 in most cancers remains uncertain; hence, additional pre-clinical studies of CTNNA1 are warranted for potential early tumor diagnosis, prognosis, and treatment.
Introduction to Statistical Time Series.

Moving Average and Autoregressive Processes. Introduction to Fourier Analysis. Spectral Theory and Filtering. Some Large Sample Theory. Estimation of the Mean and Autocorrelations. The Periodogram, Estimated Spectrum. Parameter Estimation. Regression, Trend, and Seasonality. Unit Root and Explosive Time Series. Bibliography. Index.
Association between Malnutrition Risk Factors and Physical Function in Community-Dwelling Adults ≥80 Years

Malnutrition is associated with accelerated loss of physical function in old adults, but the assessment of malnutrition in primary prevention is challenging. This study aimed to investigate if malnutrition risk factors; poor appetite, dysphagia, and poor dental state, were associated with reduced physical function in community-dwelling adults ≥80 years. The study is based on data from two cross-sectional studies. Physical function was assessed by the Short Physical Performance Battery (score ≤ 9 indicate reduced physical function) and poor appetite, dysphagia and poor dental status was assessed by single questions. A total of 900 participants were included (age 85.1 ± 3.7 years; 60.9% females; 62.8% had reduced physical function). Participants with reduced physical function were older, had a higher BMI, more polypharmacy, more falls, and lower quality of life. Poor appetite was reported by 10.8% and associated with reduced physical function (adjusted-OR 1.93, 95%CI 1.18–3.15). No association was identified between dysphagia, poor dental state and reduced physical function (adjusted-OR 0.96, 95%CI 0.53–1.75 and adjusted-OR 0.99, 95%CI 0.41–2.35, respectively). The assessment of appetite during primary preventive strategies was feasible and may offer an opportunity for identification of very old community-dwelling adults at risk of reduced physical function.
An improved implicit predictor–corrector scheme for boundary layer vertical diffusion

Time integration of the parametrized boundary layer vertical diffusion in models of the atmosphere, used in numerical weather prediction (NWP) and climate modelling, can produce noise which appears as two‐time‐step oscillations in boundary layer tendencies. The origin of this noise was considered by Kalnay and Kanamitsu who analysed a number of schemes, two of which were based on a predictor–corrector approach. Here, a generalization of these two schemes is presented which results in unconditional stability for practical NWP vertical diffusion problems. The proposed generalization improves the stability of the original schemes. Asymptotic error analysis shows that this improvement is achieved without loss of accuracy, and that a small reduction in the leading error term is possible. Second‐order accuracy is feasible but in this case unconditional stability can be achieved only for linear or mildly nonlinear problems. Numerical experiments and model simulations support the analysis presented in this paper. The limitations and strengths of the scheme are exposed and suggestions for a practical implementation are made. This scheme is ideally suited as a component of a more general predictor–corrector algorithm for the problem of physics–dynamics coupling, for example that of Cullen and Salmond. © Crown copyright, 2006.
Optical coupling at a distance between detuned spherical cavities

Using numerical modeling, we observe surprisingly high coupling efficiencies (up to 0.1) between spatially separated spherical cavities with strongly detuned whispering gallery modes. We show that the coupling arises from resonance between a discrete energy eigenstate in the sphere containing the source of light and a continuum of “quasi”-whispering gallery modes with noncircular shape and reduced quality factors in the sphere receiving the electromagnetic energy. Such coupling effects may make possible broad spectral transmission effects in coupled resonator optical waveguides, previously thought to be excluded in a real system with significant size disorder.
Venus' center of figure-center of mass offset

Abstract Magellan altimetry data reveal that the center of figure (CF) of Venus is displaced approximately 280 m from its center of mass (CM) toward 4.4°S, 135.8°E, a location in Aphrodite Terra. This offset is smaller than those of other terrestrial planets but larger than the estimated error, which is no more than a few tens of meters. We examine the possibility that the CF-CM offset is related to specific geologic provinces on Venus by deriving three simple models for the offset: a thick-crust model, a hotspot model, and a thick-lithosphere model. The offset caused by a region of thick crust depends upon the region's extent, the crust-mantle density contrast, and the thickness of excess crust. A hotspot-related offset depends on the extent of the thermally anomalous region and the magnitude of the thermal anomaly. Offset due to a region of thick lithosphere depends upon the extent of the region, the average temperature contrast across the lithosphere, and the amount of excess lithosphere. We apply the three models to Venus plateau-shaped highlands, volcanic rises, and lowlands, respectively, in an attempt to match the observed CF-CM offset location and magnitude. The influence of most volcanic rises and of Ishtar Terra on the CF-CM offset must be quite small if we are to explain the direction of the observed offset. The lack of influence of volcanic rises can be explained if the related thermal anomalies are limited to a few hundred degrees or less and are plume-shaped (i.e., characterized by a flattened sublithospheric "head" with a narrow, cylindrical feeder "tail"). The unimportance of Ishtar Terra is most easily explained if it lies atop a significant mantle downwelling.
Hermitian hat wavelet design for singularity detection in the Paraguay river-level data analyses

The direct differentiation of a noisy signal ds/dt is known to be inaccurate. Differentiation can be improved by employing the Dirac (delta) -function introduced into a convolution product denoted by (direct product) and then integrated by parts: ds/dt equals ds/dt (direct product) (delta) equals - s (direct product) d(delta) /dt. The Schwartz Gaussian representation of the delta function is then explicitly used in the differentiation. It turns out that such a convolution approach to the first and the second derivatives produces a pair of mother wavelets the combination of which is the complex generalization of the Mexican hat called a Hermitian hat wavelet. It is shown that the Hermitian filter is a single oscillation wavelet having much lower frequency bandwidth than the Mortlet or Gabor wavelet. As a result of Nyquist theorem, a fewer number of grid points would be needed for the discrete convolution operation. Therefore, the singularity characteristic will not be overly smeared and the noise can be smoothed away. The phase plot of the Hermitian wavelet transform in terms of the time scale and frequency domains reveal a bifurcation discontinuity of a noisy cusp singularity at the precise location of the singularity as well as the scale nature of the underlying dynamics. This phase plot is defined as (theta) (t/a) equals tan-1 [(ds/dt)/(-d2s/dt2] equals tan-1 [((d(delta) (t/a)dt) (direct product) s)/((d2(delta) (t/a)/dt2) (direct product) s)] applied to a real world data of the Paraguay river levels.
The Stochastic Maximum Principle for Linear, Convex Optimal Control with Random Coefficients

This paper considers a stochastic control problem with linear dynamics, convex cost criterion, and convex state constraint, in which the control enters both the drift and diffusion coefficients. These coefficients are allowed to be random, and no $L^{p}$-bounds are imposed on the control. An explicit solution for the adjoint equation and a global stochastic maximum principle are obtained for this model. This is evidently the first version of the stochastic maximum principle that covers the consumption-investment problem. The mathematical tools are those of stochastic calculus and convex analysis. When it is assumed, as in other versions of the stochastic maximum principle, that the admissible controls are square-integrable, not only a necessary but also a sufficient condition for optimality is obtained. It is then shown that this particular case of the general model may be applied to solve a variety of problems in stochastic control, including the linear-regulator, predicted-miss, and Benes problems.
Fast orthogonal search method for modeling nonlinear hemodynamic response in fMRI

This study presents a fast orthogonal search (FOS) method for modeling fMRI time series. Based on the system identification theory, an orthogonalization procedure to model the fMRI time series is described. FOS method does not require equally space data, and can resolve sinusoidal frequencies much more closely than Fourier transform method. After the time series are modeled by means of the FOS, F-test is employed to detect the activation regions. Eight volunteers' data were collected to validate the proposed method. The results demonstrate the feasibility of the proposed method.
Physical mechanism of comet outbursts - An experimental result

Abstract During experimental impacts into regoliths in vacuo at NASA Ames Research Center, an explosive eruption of gas-charged powder was observed and photographed. Analysis gives four main results applicable to comets: (1) Loose regoliths can retain interstitial gas pressure, supporting recent comet mantle theories. (2) The observed eruption could have produced a dust coma around a comet nucleus larger than a few kilometers. (3) The eruption involved discrete jets emitted by one primary vent (site of the initial disturbance) rather than a uniform spray from the vent or uniform dust/gas flow from the entire regolith surface. This behavior may clarify the discrete jets from P/Halley and other nuclei, but it is not well described in recent mathematical models of comet "mantles. " (4) As discussed earlier by the author and colleagues, the mechanism for sporadic eruptions on comets probably involves gas pressure buildup in the porespace of regoliths having a slight effective tensile strength; outbursts occur spontaneously when pressure exceeds tensile strength. This model explains the recharge mechanism required by intermittent outbursts on P/Schwassmann-Wachmann 1, 2060 Chiron, and other bodies—a mechanism not well described by some mathematical models. This work is generally consistent with a 1990 comet regolith model by H. Rickman, J. Fernandez, and B. Gustafson ( Astron. Astrophys. 237, 524-535) and supports 1992 observations by A.D. Storrs, A. L. Cochran, and E. S. Barker ( Icarus 98, 163-178), who interpret their data as requiring "a porous … mantle of nonnegligible tensile strength. " Such experiments may lead to improved theoretical modeling of comet mantle behavior.
Detection of Black and Grey Hole Attacks Using Hybrid Cat with PSO-Based Deep Learning Algorithm in MANET

– The newest example of wireless networks, known as mobile ad hoc networks (MANETs), offers some qualities, including a topology that can change dynamically, a baseless network, a range of transmission, a routing procedure, and reliability. In a black hole attack on a computer network, packets are deleted as opposed to being forwarded through a router. This often happens when a router has been corrupted by several circumstances. A routing attack called a "black hole" has the power to bring down an entire network. One of the most common types of assaults on MANETs is the Grey Hole Attack, in which a hostile node allows routing but prevents data transmission. MANET security is a top priority because they are far more susceptible to assaults than wired infrastructure. This study focused on detecting black and grey-hole attacks in MANET by using deep learning techniques. The forwarding ratio metric is used in the individual attack detection phase to distinguish between the defective and normal nodes. The encounter records are manipulated by malicious nodes in the collusion attack detection phase for escaping the detection process. The attacks are detected by using different deep learning techniques like Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. The parameter tuning operation is carried out by using the Hybrid Cat-Particle Swarm Optimization (HCPSO). The simulation results shown in our proposed system detect with better accuracy.
Multi-Relations Aware Network for In-the-Wild Facial Expression Recognition

Facial expression recognition (FER) becomes more challenging in the wild due to unconstrained conditions, such as the different illumination, pose changes, and occlusion of the face. Current FER methods deploy the attention mechanism in deep neural networks to improve the performance. However, these models only capture the limited attention features and relationships. Thus this paper proposes a novel FER framework called multi-relations aware network (MRAN), which can focus on global and local attention features and learn the multi-level relationships among local regions, between global-local features and among different samples, to obtain efficient emotional features. Specifically, our method first imposes the spatial attention on both the whole face and local regions to simultaneously learn the global and local salient features. After that, a region relation transformer is deployed to capture the internal structure among local facial regions, and a global-local relation transformer is designed to learn the fusion relations between global features and local features for different facial expressions. Subsequently, a sample relation transformer is deployed to focus on intrinsic similarity relationship among training samples, which promotes invariant feature learning for each expression. Finally, a joint optimization strategy is designed to efficiently optimize the model. The conducted experimental results on in-the-wild databases show that our method obtains the superior performance compared to some state-of-the-art models.
Real-Time Optical Localization and Tracking of UAV Using Ellipse Detection

A real-time 3-D spatial localization system to track an unmanned aerial vehicle (UAV) using a single off-board conventional camera and an onboard circle-shaped colored light-emitting diode (LED) marker is presented. The image from the camera is color-segmented and then morphologically closed before being sent to the ellipse detector. The location of the drone is then estimated with geometric/optical calculations using the pixel coordinates provided by the real-time ellipse detector. The location data generated by this system was validated by a motion-capture system (MCS) that was simultaneously tracking the system in real time. The average position error was of 6 cm, while the processing speed achieved 15 locations/s, which are comparable with recent research references. The usage of a low-cost camera makes this method promising for most mobile UAV tracking applications.
Super-resolution imaging of dielectric objects using a slab of left-handed material

The Born iterative method has been presented to study two-dimensional inverse scattering problems for dielectric objects with the aid of left-handed material (LHM). Super-resolution imaging can be achieved since the LHM slab could amplify evanescent waves emitted from transmitters, which are interacted with the dielectric objects and then captured by receivers. The evanescent waves contain high-frequency spectra of dielectric objects, leading to significant improvement of resolution in imaging. Simulation results are presented to verify the super-resolution imaging.
Enhanced spin relaxation in an ultrathin metal film by the Rashba-type surface

Nobuhiro Miyata,1 Hisashi Narita,2 Manami Ogawa,2 Ayumi Harasawa,2 Rei Hobara,1 Toru Hirahara,1 P. Moras,3 D. Topwal,4 C. Carbone,3 Shuji Hasegawa,1 and Iwao Matsuda2,* 1School of Science, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan 2The Institute for Solid State Physics, the University of Tokyo, 5-1-5 Kashiwanoha, Chiba 277-8581, Japan 3Istituto di Struttura della Materia, Consiglio Nazionale delle Ricerche, Trieste, Italy 4International Centre for Theoretical Physics (ICTP), Strada Costiera 11, I-34100 Trieste, Italy (Received 25 October 2010; revised manuscript received 28 March 2011; published 6 May 2011)