Miracle-dz/UniFAR-FTUs huggingface dataset:
POLARIMETRY WITH THE GEMINI PLANET IMAGER: METHODS, PERFORMANCE AT FIRST LIGHT, AND THE CIRCUMSTELLAR RING AROUND HR 4796A

We present the first results from the polarimetry mode of the Gemini Planet Imager (GPI), which uses a new integral field polarimetry architecture to provide high contrast linear polarimetry with minimal systematic biases between the orthogonal polarizations. We describe the design, data reduction methods, and performance of polarimetry with GPI. Point-spread function (PSF) subtraction via differential polarimetry suppresses unpolarized starlight by a factor of over 100, and provides sensitivity to circumstellar dust reaching the photon noise limit for these observations. In the case of the circumstellar disk around HR 4796A, GPI's advanced adaptive optics system reveals the disk clearly even prior to PSF subtraction. In polarized light, the disk is seen all the way in to its semi-minor axis for the first time. The disk exhibits surprisingly strong asymmetry in polarized intensity, with the west side ≳ 9 times brighter than the east side despite the fact that the east side is slightly brighter in total intensity. Based on a synthesis of the total and polarized intensities, we now believe that the west side is closer to us, contrary to most prior interpretations. Forward scattering by relatively large silicate dust particles leads to the strong polarized intensity on the west side, and the ring must be slightly optically thick in order to explain the lower brightness in total intensity there. These findings suggest that the ring is geometrically narrow and dynamically cold, perhaps shepherded by larger bodies in the same manner as Saturn's F ring.
Susceptibility of Atlantic cod Gadus morhua, halibut Hippoglossus hippoglossus and wrasse (Labridae) to Aeromonas salmonicida subsp. salmonicida and the possibility of transmission of furunculosis from farmed salmon Salmo salar to marine fish

The possibility of transmission of Aeromonas salmonicida subsp. salmonicida from Atlantic salrnon Salmo salar to cod Gadus morhua, halibut Hippoglossus h~ppoglossus, and wrasse (Labridae) was studied in both laboratory cohabitation and injection challenge trials, and in a field situation during an outbreak of furunculosis in Atlantic salmon in 2 sea farms containing both cod and salmon. A. salrnonicida subsp. salrnonicida was isolated from cod, halibut and wrasse, but only occasionally. The injection challenge studies with A. salmonicida subsp. salrnonicida were carried out on cod and halibut. Despite challenge with 4.6 X 103, 4.6 X 104 and 4.6 X 10' CFU (colony-forming units) of the bacterium, only 1 halibut died, whereas no mortality occurred in the cod groups. In cohabitation challenge trials in which cod, halibut and wrasse were kept together with infected salmon, 1 cod and 1 halibut died, with subsequent isolat~on of A salmonicida subsp. salmonicida from their kidneys In a group of salmon challenged in the same way with infected salmon cohabitants, all the salmon died In the field study, there were high mortalities of salmon due to furunculosis. However, A. salmonicida subsp. salrnonicida was isolated from only 1 of the wrasse used as 'cleaner fish' for the salmon. A. sahonicida was not isolated from cod during the field study. The results suggest that A. salrnonicida subsp. salmonicida can be transmitted from salmon and cause disease in cod, halibut and wrasse, but that this is a relatively rare event.
Learning Mid-level Attributes for Scene Understanding on Web-images

Understanding various kinds of real-world scenes from web-image data is challenging for many practical applications like web-image tagging, object or concept detection. Existing approaches use manually designed lowlevel representations of scenes (such as color, shape, and texture) which are not reliable on real-world web-images because of their unpredictable content type (a wide range of image type, size, structure, scale, transformations, and so on). This paper addresses scene analysis on webimages by mid-level attribute learning without any visual knowledge about the scenes that may be encountered. We take an advantage of a two-dimensional Long Short-Term Memory recurrent neural networks (2D LSTM networks) architecture which globally trains mid-level attributes only with raw pixel values as input. The first experiment — image classification on semantic attribute oriented images — shows the effectiveness of our approach. Using the learnt model, fully automatic natural scene analysis is demonstrated on a variety of web-based scene images. All of the experiments use web-image data randomly collected from Google’s image search, which include diversity and difficulty of real-world scene images. We also show our approach can improve the retrieval system by automatic web-image tagging owing to its semantics of scenes.
GENOME-WIDE DNA METHYLATION CHANGES DURING BREAST TUMORIGENESIS

Neoplastic reprogramming generates cancerous cells from normal derivatives, enabling researchers to create a model of the early stages of oncogenesis and analyze molecular changes in real-time. Aberrations in DNA methylation are considered a major mechanism contributing to the acquisition and maintenance of a cancerous phenotype; however, little research exists regarding gene-specific changes in DNA methylation during the transition from a normal to neoplastic cell. Human mammary epithelial cells (HMECs) underwent neoplastic transformation through the addition of three defined genetic elements to generate one line of semi-transformed, pre-malignant cells (SHMECs) and two separate lines of fully transformed, malignant cells (THMECs). We used an Illumina Infinium HumanMethylation27 BeadChip to interrogate 27,578 CpG loci and identify genes that exhibited differential methylation over three consecutive time points during breast tumorigenesis. We found 805 CpG loci exhibiting a single DNA methylation change from SHMEC to THMECs at 40 days (THMEC-40d). These genes were enriched for biological functions associated with cellular growth and proliferation. In contrast, 196 CpG sites were differentially methylated between THMEC-40d and THMEC-80d and were associated with major developmental processes. The data
FD-RBF for Partial Integro-Differential Equations with a Weakly Singular Kernel

Finite Difference Method and Radial Basis Functions are applied to solve partial integro-differential equations with a weakly singular kernel. The product trapezoidal method is used to compute singular integrals that appear in the discretization process. Different RBFs are implemented and satisfactory results are shown the ability and the usefulness of the proposed method.
Effects of couples' anxiety and avoidance on physical health symptoms

ii List of Tables . iv List of Illustrations . v Introduction . 1 Literature Review . 2 Adult Attachment Quality . 3 Attachment Quality and Health . 5 Gender Differences . 11 Inter-partner Health Effects . 13 Couples in Therapy . 14 Couple Configuration . 15 Method . 17 Results . 20 Discussion . 23 Conclusion . 29 References . 31 Appendix . 40
Lipids and its Metabolism

Cholesterol is designated as 3-betahydroxy-5, 6-cholestene. Cholesterol is widely distributed in all the cells of the body, particularly abundant in nervous tissues. Higher concentration of cholesterol is found in brain, liver, kidney, adipose tissue and suprarenal glands in both free and esterified forms. In plasma, esterified form comprises 65-75% and in tissues, free form dominates [1]. Liver appears to be chief source of endogenous cholesterol but it is also synthesized in adrenals, intestinal mucosa and brain. Dietary sources of cholesterol are mainly from food of animal origin.
Deriving numerical techniques with zero phase-lag and derivatives for initial value problems of second order

In the present we investigate the advantages of the phase lag analysis for the derivation of phase-fitted techniques on several numerical schemes. Relying on the main characteristics of the phase lag we evaluate the parameters needed firstly for Runge-Kutta methods and secondly for high order variational integration methods, so that the phase lag and its derivatives are zero. The proposed methods are tested for the solution of initial value problems on ordinary differential equations of second order, like the Henon-Heiles model.
Direct-DRRT*: A RRT Improvement Proposal

The present work aims at the development of a new heuristic approach named Direct-DRRT *. This new algorithm is an improvement of the DRRT* method, which is the fusion between RRT * and DRRT. This improvement aims at the mobile robot autonomous planning considering less memory and computational time for a route design. The results show the efficiency of our approach compared to the other methods, presenting less processing time and a signification reduced number of nodes and paths.
Confusion background from compact binaries

Double neutron stars are one of the most promizing sources for terrestrial gravitational wave interferometers. For actual interferometers and their planned upgrades, the probability of having a signal present in the data is small, but as the sensitivity improves, the detection rate increases and the waveforms may start to overlap, creating a confusion background, ultimately limiting the capabilities of future detectors. The third generation Einstein Telescope, with an horizon of z > 1 and very low frequency seismic wall may be affected by such confusion noise. At a minimum, careful data analysis will be require to separate signals which will appear confused. This result should be borne in mind when designing highly advanced future instruments.
Cell Wall Thickness and Tangential and Radial Cell Diameter of Fertilized and Irrigated Norway Spruce

Two Norway spruce nutrient trials were used to evaluate the effects of fertilization and irrigation on transverse tracheid dimensions. Three different treatments and a control (C) were used; daily irrigation (I), daily liquid fertilization (IL) and an annual solid fertilization (F). The nutrient optimisation was based on foliage analysis and both liquid and solid fertilization essentially comprised the same amount of nutrients but the latter was applied annually in solid form. The cell measurements; cell wall thickness, radial and tangential cell widths, were obtained using image analysis (SilviScan at CSIRO, Melbourne, Australia). Mean annual cell wall thickness was decreased by fertilization (F and IL) on both sites whereas no effect of the irrigation on wall thickness could be detected. Radial cell width was increased by treatment at Flakaliden but at Asa the effect of irrigation and fertilization was reversed when the data structure i.e. development from pith and out and annual ring width was taken into account. Tangential cell width was not significantly affected by treatment at Flakaliden. At Asa fertilization caused a small increase on tangential cell width. Ring width was positively affected by treatment and is an important factor explaining the effects on primarily cell wall thickness and radial cell width.
The study of effect aromatherapy on the anxiety rate and cortisol plasma change on hemodialysis patients

The annual costs for health caring patients with renal disease is more than 21.3 billion dollars and the hemodialysis ,is the most common ,and the most expensive method for curing it ,that is introduced on the world. For this , this research has done , to study the effects of aromatherapy , on anxiety rate . of hemodialysis patients . Based on cortisol plasma viscosity changes . In this study , that is of single blind clinical trial , we used of target sampling , and census on hemodialysis patients in Ganjavina Hospital of Dezful , related to Dezful medicine university.For whom that ,use lavender essence on 3 odd days ,the essence was put on a cloth (1 drop each time ) and stick it to their cloth collar ,the patient were asked to breath normally ,and continue breathing for 15 minute . After the end of each week, the blood sample were gotten and were delivered to laboratory . The gathering tools for dates including : patient , s selection from the letter of satisfaction , demographic , characteristic from , Spielberger anxiety questionnaire and blood sample ,for masuring cortisol rate in blood . average numbers of cortisol serum rate of hemodialysis patients in control and intervention group before aromatherapy isn’t somach different (18.88 against 20.12 ) . Also there isn’t somuch difference . between the average numbers of first and second cortisol after aromatherapy than the average numbers ,before aromatherapy. (19.06 against 21.07 ) and (20.12 against 19.37 ) but on average numbers , of third cortisol after intervention of these 2 groups ,there isn’t clearly difference . (20.60 against 16.44 ) that is difference is useful for intervention group to decrease third cortisol numbers than the control group after aromatherapy .
Characterization of functional domains in the human coronavirus HCV 229 E receptor

Human aminopeptidase N (hAPN or CD13) and porcine aminopeptidase N (pAPN) are functional receptors for human coronavirus (HCV) 229E and porcine transmissible gastroenteritis virus (TGEV), respectively. However, hAPN cannot function as a receptor for TGEV and pAPN cannot function as a receptor for HCV 229E. In this study, we constructed a series of chimeric hAPN/pAPN genes and expressed the corresponding proteins in transfected cells. Subsequently, we identified the chimeric proteins that can function as a receptor for HCV 229E. The results show that replacement of a small region of pAPN sequence (pAPN amino acids 2 5 5 3 4 8 ) with the corresponding hAPN sequence (hAPN amino acids 260 -353 ) converts pAPN into a functional receptor for HCV 229E. The region of hAPN that we have defined in this way does not correspond to the region of pAPN that has been identified as essential for the TGEV-receptor interaction. We conclude that although both viruses use a homologous receptor protein, different regions of the protein are required to mediate susceptibility to infection with HCV 229E and TGEV.
Personalized Monitoring of Calcium Flux Direction during Haemodialysis

Adverse effects related to calcium depletion and calcium excess is and will remain common in patients on hemodialysis HD as long as practical and validated tools to monitor calcium redistribution during HD are not available. Maintaining zero calcium mass balance CaMB is generally believed to prevent calcium related complications [1]. However, CaMB management is extremely complex and its assessment represents a major challenge because of the many variables that are involved [2,3]. Food calcium content, fractional calcium absorption, type of phosphate binders, vitamin D status and calcium exchange during HD will all affect calcium balance [2,4]. An exact quantification of all these effects on a personal level is virtually impossible to achieve, and with current methods it is not feasible in daily practice. We hypothesize that such a detailed approach may not be necessary and propose to explore a more simple method that is focused on assessment of calcium flux direction instead of an exact quantification of CaMB in mass units. As calcium exchange during HD is a major factor of overall CaMB, knowledge of calcium flux direction and a qualitative estimate of the degree of calcium exchange during HD may contribute to improve treatment. Knowing whether there is calcium influx or efflux during HD, and an indication whether the exchange is large or small may provide the guidance needed to choose the most appropriate dialysate calcium concentration DCa in individual patients.
Nutritional importance of benthic bacteria for deep‐sea nematodes from the Arctic ice margin: Results of an isotope tracer experiment

A stable isotope (13C)‐labeling experiment was performed to quantify the importance of bacterial carbon as a food source for an Arctic deep‐sea nematode community. Bacterial functional groups were isotopically enriched with 13C‐glucose, 13C‐acetate, 13C‐bicarbonate, and 13C‐amino acids injected into sediments collected from 1280 m depth at 79°N, 6°E, west of Svalbard. Incorporation of the 13C label into bacterial phospholipid‐derived fatty acids (PLFAs) and nematodes in the top 5 cm of the sediment was monitored over a 7‐d period. The 13C dynamics of nematodes was fitted with a simple isotope turnover model to derive the importance of the different bacterial functional groups as carbon sources for the nematodes. The different substrates clearly labeled different bacterial groups as evidenced by differential labeling of the PLFA patterns. The deep‐sea nematode community incorporated a very limited amount of the label, and the isotope turnover model showed that the dynamics of the isotope transfer could not be attributed to bacterivory. The low enrichment of nematodes suggests a limited passive uptake of injected 13C‐labeled substrates. The lack of accumulation suggests that the injected 13C‐labeled dissolved organic carbon compounds are not important as carbon sources for deep‐sea nematodes. Since earlier studies with isotopically enriched algae also found limited uptake by nematodes, the food sources of deep‐sea nematodes remain unclear.
Smart Audio Sensors in the Internet of Things Edge for Anomaly Detection

Everyday objects are becoming smart enough to directly connect to other nearby and remote objects and systems. These objects increasingly interact with machine learning applications that perform feature extraction and model inference in the cloud. However, this approach poses several challenges due to latency, privacy, and dependency on network connectivity between data producers and consumers. To alleviate these limitations, computation should be moved as much as possible towards the IoT edge, that is on gateways, if not directly on data producers. In this paper, we propose a design framework for smart audio sensors able to record and pre-process raw audio streams, before wirelessly transmitting the computed audio features to a modular IoT gateway. In this paper, an anomaly detection algorithm executed as a micro-service is capable of analyzing the received features, hence detecting audio anomalies in real-time. First, to assess the effectiveness of the proposed solution, we deployed a real smart environment showcase. More in detail, we adopted two different anomaly detection algorithms, namely Elliptic Envelope and Isolation Forest, that were purposely trained and deployed on an affordable IoT gateway to detect anomalous sound events happening in an office environment. Then, we numerically compared both the deployments, in terms of end-to-end latency and gateway CPU load, also deriving some ideal capacity bounds.
How to make someone speak a language that they don ’ t know

We present a simple idea that allows to record a speaker in a given language and 1 synthesize their voice in other languages that they may not even know. These 2 techniques open a wide range of potential applications such as cross-language 3 communication, language learning or automatic video dubbing. We call this 4 general problem multi-language speaker-conditioned speech synthesis and we 5 present a simple but strong baseline for it. 6 Our model architecture is similar to the encoder-decoder Char2Wav model [Sotelo 7 et al., 2017] or Tacotron [Shen et al., 2017]. The main difference is that, instead 8 of conditioning on characters or phonemes that are specific to a given language, 9 we condition on a shared phonetic representation that is universal to all languages 10 [Meier, 2016]. This cross-language phonetic representation of text allows to 11 synthesize speech in any language while preserving the vocal characteristics of the 12 original speaker. Furthermore, we show that fine-tuning the weights of our model 13 allows us to extend our results to speakers outside of the training dataset. 14
Bounds on the capacity and power of quantum batteries

Quantum batteries, composed of quantum cells, are expected to outperform their classical analogs. The origin of such advantages lies in the role of quantum correlations, which may arise during the charging and discharging processes performed on the battery. In this theoretical work, we introduce a systematic characterization of the relevant quantities of quantum batteries, i.e., the capacity and the power, in relation to such correlations. For these quantities, we derive upper bounds for batteries that are a collection of noninteracting quantum cells with fixed Hamiltonians. The capacity, that is, a bound on the stored or extractable energy, is derived with the help of the energy-entropy diagram, and this bound is respected as long as the charging and discharging processes are entropy preserving. While studying power, we consider a geometric approach for the evolution of the battery state in the energy eigenspace of the battery Hamiltonian. Then, an upper bound for power is derived for arbitrary charging process, in terms of the Fisher information and the energy variance of the battery. The former quantifies the speed of evolution, and the latter encodes the nonlocal character of the battery state. Indeed, due to the fact that the energy variance is bounded by the multipartite entanglement properties of batteries composed of qubits, we establish a fundamental bound on power imposed by quantum entanglement. We also discuss paradigmatic models for batteries that saturate the bounds both for the stored energy and power. Several experimentally realizable quantum batteries, based on integrable spin chains, the Lipkin-Meshkov-Glick and the Dicke models, are also studied in the light of these newly introduced bounds.
Scaling limits for the threshold window: When does a monotone Boolean function flip its outcome?

Consider a monotone Boolean function f:{0,1}^n \to {0,1} and the canonical monotone coupling {eta_p:p in [0,1]} of an element in {0,1}^n chosen according to product measure with intensity p in [0,1]. The random point p in [0,1] where f(eta_p) flips from 0 to 1 is often concentrated near a particular point, thus exhibiting a threshold phenomenon. For a sequence of such Boolean functions, we peer closely into this threshold window and consider, for large n, the limiting distribution (properly normalized to be nondegenerate) of this random point where the Boolean function switches from being 0 to 1. We determine this distribution for a number of the Boolean functions which are typically studied and pay particular attention to the functions corresponding to iterated majorityand percolation crossings. It turns out that these limiting distributions have quite varying behavior. In fact, we show that any nondegenerate probability measure on R arises in this way for some sequence of Boolean functions.
Deep Learning Approach in Computer-Aided Detection System for Lung Cancer

Lung cancer is one of the most aggressive type of cancer and the possibility to detect it at early stage can save lot of the patient life worldwide. This article considers approaches to build automated diagnose system based on the lung cancer diagnose task. Mainly, 3D convolution and recurrent neural networks are considered based on the latest research works. Finally, we compare the overall accuracy of these networks on lung cancer detection problem.