Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Face Recognition System by using a Principle Component Analysis and Fully Convolutional Network

Face recognition has gained a significant position among most commonly used applications of image processing. With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. Partial face images are produced in an unconstrained environment. A face may be occluded by sunglasses, a hat and a scarf, captured in various poses, positioned partially out of cameras ﬁeld of view . Human face plays an important role in our social interaction, conveying people’s identity but it is a dynamic object and has a high degree of variability in its appearances. The problem of recognizing an arbitrary patch of a face image remains largely unsolved. This study proposes a new partial face recognition approach, called Dynamic Feature Matching, which combines Fully Convolutional Networks, Principle Component Analysis and Sparse Representation Classiﬁcation to address partial face recognition problem regardless of various face sizes. DFM does not require prior position information of partial faces against a holistic face.
Kidney cell mechanotransduction in response to sustained hydrostatic pressure

Several kidney pathologies result in elevated pressures within the renal interstitial fluid, affecting cell function and gene expression. The long-term objective of this research was, therefore, to elucidate the signaling cascades involved in kidney cell responses to hydrostatic (physiological and/or pathological) pressures. Initial in vitro studies were performed on two kidney cell lines (tubular and medullary) to determine changes in cell proliferation, cytoskeletal (specifically, microfilament and microtubule) arrangement, and mRNA expression (of cell signaling genes such as G/sub /spl alpha//, G/sub /spl beta//, c-jun, and c-fos) following exposure to pathological (60 cmH/sub 2/O) pressures. Proliferation studies provided evidence that exposure to pressures of 60 cmH/sub 2/O resulted in increased renal cell proliferation (compared to controls cells under 0.3 cmH/sub 2/O) after 7 days. In addition to increased cell proliferation, time-dependent changes in individual microfilament structures took place in response to the pressure stimulus. These results prove that hydrostatic pressure alters the function of tubular and medullary cells; more importantly, microfilaments were involved in the signaling mechanism of this response. Additionally, preliminary results suggest that G/sub /spl alpha//, G/sub /spl beta//, c-jun, and c-fos are up-regulated in renal cells following exposure to 60 cmH/sub 2/O pressure. Uncovering this signaling cascade in renal cells may aid in the design of novel, targeted drug therapies for kidney pathologies.
Silicon content of five marine plankton diatom species measured with a rapid filter method1

The silicon content of five species of marine planktonic diatoms grown in laboratory culture was measured by a method involving soda hydrolysis of cells collected on polycarbonate filters. An increase in the temperature or light intensity during growth resulted in an increase in the Si content in some species and a decrease in others. The magnitude of these changes depended on whether the results were expressed as pg Siacell-r, pg Si*prnd2 cell surface area, or pg Si per pg C.
A unified first-order hyperbolic model for nonlinear dynamic rupture processes in diffuse fracture zones

Earthquake fault zones are more complex, both geometrically and rheologically, than an idealized infinitely thin plane embedded in linear elastic material. To incorporate nonlinear material behaviour, natural complexities and multi-physics coupling within and outside of fault zones, here we present a first-order hyperbolic and thermodynamically compatible mathematical model for a continuum in a gravitational field which provides a unified description of nonlinear elasto-plasticity, material damage and of viscous Newtonian flows with phase transition between solid and liquid phases. The fault geometry and secondary cracks are described via a scalar function ξ ∈ [0, 1] that indicates the local level of material damage. The model also permits the representation of arbitrarily complex geometries via a diffuse interface approach based on the solid volume fraction function α ∈ [0, 1]. Neither of the two scalar fields ξ and α needs to be mesh-aligned, allowing thus faults and cracks with complex topology and the use of adaptive Cartesian meshes (AMR). The model shares common features with phase-field approaches, but substantially extends them. We show a wide range of numerical applications that are relevant for dynamic earthquake rupture in fault zones, including the co-seismic generation of secondary off-fault shear cracks, tensile rock fracture in the Brazilian disc test, as well as a natural convection problem in molten rock-like material. This article is part of the theme issue ‘Fracture dynamics of solid materials: from particles to the globe’.
Nonanalytic nonequilibrium field theory: Stochastic reheating of the Ising model

Many-body non-equilibrium steady states can still be described by a Landau-Ginzburg theory if one allows non-analytic terms in the potential. We substantiate this claim by working out the case of the Ising magnet in contact with a thermal bath and undergoing stochastic reheating: it is reset to a paramagnet at random times. By a combination of stochastic field theory and Monte Carlo simulations, we unveil how the usual $\varphi^4$ potential is deformed by non-analytic operators of intrinsic non-equilibrium nature. We demonstrate their infrared relevance at low temperatures by a renormalization-group analysis of the non-equilibrium steady state. The equilibrium ferromagnetic fixed point is thus destabilized by stochastic reheating, and we identify the new non-equilibrium fixed point.
Twitter, human mobility, and COVID-19

The outbreak of COVID-19 highlights the need for a more harmonized, less privacy-concerning, easily accessible approach to monitoring the human mobility that has been proved to be associated with the viral transmission. In this study, we analyzed 587 million tweets worldwide to see how global collaborative efforts in reducing human mobility are reflected from the user-generated information at the global, country, and the U.S. state scale. Considering the multifaceted nature of mobility, we propose two types of distance: the single-day distance and the cross-day distance. To quantify the responsiveness in certain geographical regions, we further propose a mobility-based responsive index (MRI) that captures the overall degree of mobility changes within a time window. The results suggest that mobility patterns obtained from Twitter data are amendable to quantitatively reflect the mobility dynamics. Globally, the proposed two distances had greatly deviated from their baselines after March 11, 2020, when WHO declared COVID-19 as a pandemic. The considerably less periodicity after the declaration suggests that the protection measures have obviously affected people's travel routines. The country scale comparisons reveal the discrepancies in responsiveness, evidenced by the contrasting mobility patterns in different epidemic phases. We find that the triggers of mobility changes correspond well with the national announcements of mitigation measures. In the U.S., the influence of the COVID-19 pandemic on mobility is distinct. However, the impacts varied substantially among states. The strong mobility recovering momentum is further fueled by the Black Lives Matter protests, potentially fostering the second wave of infections in the U.S.
Guidance of Agents in Cyclic Pursuit

This report studies the emergent behavior of systems of agents performing cyclic pursuit controlled by an external broadcast signal detected by a random set of the agents. Two types of cyclic pursuit are analyzed: 1)linear cyclic pursuit, where each agent senses the relative position of its target or leading agent 2)non-linear cyclic pursuit, where the agents can sense only bearing to their leading agent and colliding agents merge and continue on the path of the pursued agent (a so-called "bugs" model). Cyclic pursuit is, in both cases, a gathering algorithm, which has been previously analyzed. The novelty of our work is the derivation of emergent behaviours, in both linear and non-linear cyclic pursuit, in the presence of an exogenous broadcast control detected by a random subset of agents. We show that the emergent behavior of the swarm depends on the type of cyclic pursuit. In the linear case, the agents asymptotically align in the desired direction and move with a common speed which is a proportional to the ratio of the number of agents detecting the broadcast control to the total number of agents in the swarm, for any magnitude of input (velocity) signal. In the non-linear case, the agents gather and move with a shared velocity, which equals the input velocity signal, independently of the number of agents detecting the broadcast signal.
Detection of HPV DNA in Cervical Carcinomas after Treatment in India

Abstract Objective of this study was to evaluate the effect of treatment in eradicating HPV infection. We investigated presence of HPV DNAs in exfoliated cervical cells from cervical cancer patients before and after treatment. HPV DNA was detected by PCR using HPV consensus primers. HPV 16/18 were identified by PCR using type specific primers. HPV eradication was investigated after 3-8 months of treatment. Out of the 24 patients 4 were surgically treated and the rest by radiotherapy. HPV DNA was detected in 83.3% (20/24) of the patients before treatment. HPV types 16, 18, 16 plus 18 and HPV types other than 16/18 were demonstrated in 30%, 5%, 35%, and 30% of the patients. Following treatment 37.5% (9/24) of the patients were HPV positive. Results indicate that treatment may eradicate cervical HPV infection (p<0.001).
The relationship between lameness and reproductive performance in dairy cows raised in small holder farms, Thailand

The aim of this study was to investigate the relationship between lameness and reproductive performance in dairy cows. A retrospective case-control study was conducted at 20 farms in 326 cows with high prevalence (>30%) and at 20 farms in 331 cows with low prevalence (<10%) of lameness. Cows having a locomotion score ≥3 were classified as lame. Reproductive data were collected and analyzed. Calving to calving interval, calving to first service interval, services per conception, and pregnancy rate in lame cows were poorer than non-lame cows (P<0.05). The severity of reproductive consequences was greater in high prevalence farms than in low prevalence farms. Cows classified as lame were 3.5 times more likely to be non-pregnant compared with non-lame cows (P=0.0001). Attributable proportion analysis indicated that non-pregnancy in lame cows could have been reduced by 70% if lameness had been prevented.
Fluctuation-dissipation relation for open quantum systems in a nonequilibrium steady state

Continuing our work on the nature and existence of fluctuation-dissipation relations (FDR) in linear and nonlinear open quantum systems [1-3], here we consider such relations when a linear system is in a nonequilibrium steady state (NESS). With the model of two-oscillators (considered as a short harmonic chain with the two ends) each connected to a thermal bath of different temperatures we find that when the chain is fully relaxed due to interaction with the baths, the relation that connects the noise kernel and the imaginary part of the dissipation kernel of the chain in one bath does not assume the conventional form for the FDR in equilibrium cases. There exists an additional term we call the `bias current' that depends on the difference of the bath's initial temperatures and the inter-oscillator coupling strength. We further show that this term is related to the steady heat flow between the two baths when the system is in NESS. The ability to know the real-time development of the inter-heat exchange (between the baths and the end-oscillators) and the intra-heat transfer (within the chain) and their dependence on the parameters in the system offers possibilities for quantifiable control and in the design of quantum heat engines or thermal devices.
Effects of Watersoaking on Response to Xanthomonas vesicatoria in Pepper Leaves

COOK, A. A. , and R. E. STALL. 1977. Effects of watersoaking on response to Xanthomonas vesicatoria in pepper leaves. Phytopathology 67:1101-1103. Detached pepper leaves watersoaked after infiltration with watersoaking was permitted to dissipate from leaves kept Xanthomonas vesicatoria (XV) did not develop a watersoaked for various periods ranging from 0-6 hr after hypersensitive response (HR). Bacterial concentration in the inoculation. Patterns of bacterial multiplication and inoculum and multiplication in vivo during incubation electrolyte leakage in detached leaves kept watersoaked for resulted in bacterial populations in excess of the minimal 72 hr after infiltration inoculation with either of two concentration required to induce HR, but only a small pathotypes of XV were similar to results from susceptible increase in electrolyte leakage was detected after 24-36 hr of leaves left in situ after inoculation. incubation. Typical development of HR began 2-3 hr after
Supporting Real-Time COVID-19 Medical Management Decisions: The Transition Matrix Model Approach

Since the onset of the COVID-19 outbreak in Wuhan, China, numerous forecasting models have been proposed to project the trajectory of coronavirus infection cases. We propose a new discrete-time Markov chain transition matrix model that directly incorporates stochastic behavior and for which parameter estimation is straightforward from available data. Using such data from China's Hubei province (for which Wuhan is the provincial capital city), the model is shown to be flexible, robust, and accurate. As a result, it has been adopted by the first Shanghai assistance medical team in Wuhan's Jinyintan Hospital, which was the first designated hospital to take COVID-19 patients in the world. The forecast has been used for preparing medical staff, intensive care unit (ICU) beds, ventilators, and other critical care medical resources and for supporting real-time medical management decisions. Empirical data from China's first two months (January/February) of fighting COVID-19 was collected and used to enhance the model by embedding NPI efficiency into the model. We applied the model to forecast Italy, South Korea, and Iran on March 9. Later we made forecasts for Spain, Germany, France, US on March 24. Again, the model has performed very well, proven to be flexible, robust, and accurate for most of these countries/regions outside China.
Group invariant solutions of certain partial differential equations

\begin{abstract} Let $M$ be a complete Riemannian manifold and $G$ a Lie subgroup of the isometry group of $M$ acting freely and properly on $M. $ We study the Dirichlet Problem% \[ \left\{ \begin{array} [c]{l}% \operatorname{div}\left( \frac{a\left( \left\Vert \nabla u\right\Vert \right) }{\left\Vert \nabla u\right\Vert }\nabla u\right) =0\text{ in }\Omega\\ u|\partial\Omega=\varphi \end{array} \right. \] where $\Omega$ is a $G-$invariant domain of $C^{2,\alpha}$ class in $M$ and $\varphi\in C^{0}\left( \partial\overline{\Omega}\right) $ a $G-$invariant function. Two classical PDE's are included in this family: the $p-$Laplacian $(a(s)=s^{p-1},$ $p>1)$ and the minimal surface equation $(a(s)=s/\sqrt {1+s^{2}}). $ Our motivation is to present a method in studying $G$-invariant solutions for noncompact Lie groups which allows the reduction of the Dirichlet problem on unbounded domains to one on bounded domains. \end{abstract}
An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time

Multiple digital data streams forecast COVID-19 activity weeks before traditional epidemiological surveillance. Given still-high levels of coronavirus disease 2019 (COVID-19) susceptibility and inconsistent transmission-containing strategies, outbreaks have continued to emerge across the United States. Until effective vaccines are widely deployed, curbing COVID-19 will require carefully timed nonpharmaceutical interventions (NPIs). A COVID-19 early warning system is vital for this. Here, we evaluate digital data streams as early indicators of state-level COVID-19 activity from 1 March to 30 September 2020. We observe that increases in digital data stream activity anticipate increases in confirmed cases and deaths by 2 to 3 weeks. Confirmed cases and deaths also decrease 2 to 4 weeks after NPI implementation, as measured by anonymized, phone-derived human mobility data. We propose a means of harmonizing these data streams to identify future COVID-19 outbreaks. Our results suggest that combining disparate health and behavioral data may help identify disease activity changes weeks before observation using traditional epidemiological monitoring.
A Survey on Plant Disease Detection System

: Plant diseases are a major threat to plant growth and crop yield and many researchers have expended substantial efforts on detecting plant diseases. Traditionally, visual examination by experts has been carried out to diagnose plant diseases and biological examination is the second option, if necessary. In recent years, through the development of computer technology, machine learning has been widely utilized to train and detect plant diseases and is a satisfactory alternative for the detection of plant diseases. It is easier to realize higher accuracy by using a deep learning approach that is based on convolution neural networks. In this proposed system a deep learning approach that is based on improved convolution neural networks (CNN) for the real-time detection of apple leaf diseases. The proposed deep-learning based approach can automatically identify the discriminative features of the diseased apple images and detect the types of apple leaf diseases with high accuracy.
The relative importance of disturbance and environmental stress at local and regional scales in French coastal sand dunes

Abstract Questions: 1. Is there a primary role of disturbance at local scale and of environmental stress at regional scale? 2. Does disturbance increase or decrease environmental stress at local scale? Location: The Atlantic coastal dune system of the Aquitaine Region (France). Methods: Species biomass and 16 environmental variables were sampled in 128 quadrats along a local beach-inland gradient and a regional North-South gradient. Environmental data were analysed with ANOVAs and vegetation-environment relationships with Canonical Correspondence Analysis. Results: At the local scale community composition was primarily driven by disturbance due to sand burial, whereas water and nutrient stress better explained regional differences. However, random biogeographical events are very likely to also affect community composition at the largest scale. The main interaction between environmental stress and disturbance was the mitigation of nutrient stress induced by disturbance at a local scale. This was due to a positive direct effect of sand burial and a positive indirect effect of wind (decrease in VPD by ocean spray). Although wind had also a significant effect on soil conductivity and pH, there was no evidence that these factors had any role in community composition. Conclusions: Our results support the hypothesis that disturbance had a primary role at local scale and environmental stress at regional scale but further research is needed to separate the effect of stress from that of dispersal at regional scale. We also demonstrated that environmental stress in primary succession may not always decline with decreasing disturbance. Nomenclature: Flora Europaea (Tutin et al. 1964–1980).
The Aurelian Legacy – British Butterflies and their Collectors

Pioneers, dandies and frauds: 300 years of British butterfly collectors Book titles such as ‘Intrepid Explorers’, ‘Great Inventors’ and ‘Lives of the Presidents [of the USA]’ are a staple of dusty school libraries and spare-bedroom bookshelves, and were written to improve young minds using biographies of exemplary men. Somehow, ‘Great British Bug-collectors’ doesn’t have quite the same ring about it, but this was not always so. As Michael Salmon describes, in the 17th and 18th centuries, men such as James Petiver and John Ray, who were the first to collect and classify British insects, were Fellows of the Royal Society; and associated with the likes of Isaac Newton, Robert Hooke, Christopher Wren and Edmond Halley. Three hundred years later, the laws of biodiversity are only just beginning to be understood, whereas the much simpler physical laws[! ] have long been known. Salmon’s historical analysis shows that our current perception of bug-collecting as dull and slightly eccentric is more likely an example of a periodic downturn in the fashion for entomology and natural history than a real long-term decline in importance. Systematics and the cataloguing of living things was believed to be as vital for an understanding of the ‘Wisdom of God’ as the motion of planets, and the nature of light, heat, electricity and matter. In my view, systematics still has this kind of importance, but the incompleteness of data and greater complexity of biology have made its laws much more difficult to reveal. The taxonomy of British butterflies is today, of course, hardly a scientific frontier. Nevertheless, the detailed knowledge of British species is extraordinary: for example, British butterfly mapping data are foremost in showing the effects of global warming. However, several hundred years ago, the reward for lugging an unwieldy ‘clap-net’ or ‘bat-fowler’ out to your local meadow would be to explore an unknown world. As you pinned your catch, and perhaps stored it inside your stove-pipe top-hat (hopefully, you would not have to salute any ladies on your way home), you might have the satisfaction of knowing that a butterfly collected in the suburbs of London was new to science. John Ray had this enviable experience with insects and plants around Cambridge, and later near his home at Black Notley, Essex. His many publications on flora and fauna were to become an important basis for Linnaeus’ own work.