Suggesting Deletion of Blurry Photos

Generally, the present disclosure is directed to identifying and suggesting deletion of blurry photos. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a blurriness characteristic of an image based on image data. For example, the blurriness characteristic can describe a percentage of the image that is blurry

PHOTO ANALYZER AND AUTO HASHTAG TAGGER

A photo identification application involving photo analysis and automatic hashtag generation is disclosed. The application analyzes the content of the uploaded photo and applies automatic hashtags corresponding to the themes identified in the analysis to the photo for identification purposes. Thus the application allows search for images corresponding to one or more themes and makes them more accessible

Markovian master equations for quantum thermal machines: local vs global approach

The study of quantum thermal machines, and more generally of open quantum systems, often relies on master equations. Two approaches are mainly followed. On the one hand, there is the widely used, but often criticized, local approach, where machine sub-systems locally couple to thermal baths. On the other hand, in the more established global approach, thermal baths couple to global degrees of freedom of the machine. There has been debate as to which of these two conceptually different approaches should be used in situations out of thermal equilibrium. Here we compare the local and global approaches against an exact solution for a particular class of thermal machines. We consider thermodynamically relevant observables, such as heat currents, as well as the quantum state of the machine. Our results show that the use of a local master equation is generally well justified. In particular, for weak inter-system coupling, the local approach agrees with the exact solution, whereas the global approach fails for non-equilibrium situations. For intermediate coupling, the local and the global approach both agree with the exact solution and for strong coupling, the global approach is preferable. These results are backed by detailed derivations of the regimes of validity for the respective approaches.Comment: Published version. See also the related work by J. Onam Gonzalez et al. arXiv:1707.0922

Torque wiggles -- a robust feature of the global disc-planet interaction

Gravitational coupling between planets and protoplanetary discs is responsible for many important phenomena such as planet migration and gap formation. The key quantitative characteristics of this coupling is the excitation torque density -- the torque (per unit radius) imparted on the disc by planetary gravity. Recent global simulations and linear calculations found an intricate pattern of low-amplitude, quasi-periodic oscillations in the global radial distribution of torque density in the outer disc, which we call torque wiggles. Here we show that torque wiggles are a robust outcome of global disc-planet interaction and exist despite the variation of disc parameters and thermodynamic assumptions (including $\beta$-cooling). They result from coupling of the planetary potential to the planet-driven density wave freely propagating in the disc. We developed analytical theory of this phenomenon based on approximate self-similarity of the planet-driven density waves in the outer disc. We used it, together with linear calculations and simulations, to show that (a) the radial periodicity of the wiggles is determined by the global shape of the planet-driven density wave (its wrapping in the disc) and (b) the sharp features in the torque density distribution result from constructive interference of different azimuthal (Fourier) torque contributions at radii where the planetary wake crosses the star-planet line. In the linear regime the torque wiggles represent a weak effect, affecting the total (integrated) torque by only a few per cent. However, their significance should increase in the non-linear regime, when a gap (or a cavity) forms around the perturber's orbit.Comment: 19 pages, 15 figures, submitted to MNRA

Heterogeneous data reduction in WSN: Application to Smart Grids

International audienceThe transformation of existing power grids into Smart Grids (SGs) aims to facilitate grid energy automation for a better quality of service by providing fault tolerance and integrating renewable energy resources in the power market. This evolution towards a smarter electricity grid requires the ability to transmit in real time a maximum of data on the network usage. A Wireless Sensor Network (WSN) distributed across the power grid is a promising solution, given the reduced cost and ease of deployment of such networks. These advantages come up against the unstable radio links and limited resources of WSN. In order to reduce the amount of data sent over the network, and thus reduce energy consumption, data prediction is a potent solution of data reduction. It consists on predicting the values sensed by sensor nodes within certain error threshold, and resides both at the sensors and at the sink. The raw data is sent only if the desired accuracy is not satisfied, thereby reducing data transmission. We focus on time series estimation with Least Mean Square (LMS) for data prediction in WSN, in a Smart Grid context, where several applications with different data types and Quality of Service (QoS) requirements will exist on the same network. LMS proved its simplicity and robustness for a wide variety of applications, but the parameters selection (step size and filter length) can directly affect its global performance, choosing the right ones is then crucial. Having no clear and robust method on how to optimize these parameters for a variety of applications, we propose a modification of the original LMS that consists of training the filter for a certain time with the data itself in order to customize the aforementioned parameters. We consider different types of real data traces for the photo voltaic cells monitoring. Our simulation results provide a better data prediction while minimizing the mean square error compared to an existing solution in literatur

Campaña de marketing digital para las redes sociales de Kametsa EIRL

El presente proyecto profesional es una campaña de marketing para la empresa Kametsa E.I.R.L que buscará la reactivación de la marca junto a sus submarcas, puesto que, por la pandemia, durante el año 2021, estuvieron en pausa y se ha retornado en brindar nuevamente sus servicios desde mediados de febrero del 2022. Para lograr reposicionar a Kametsa como uno de los principales destinos turísticos nocturnos se integrarán diversas herramientas del marketing digital como otros recursos de apoyo en los medios ATL. Desde lo tradicional, se hará uso de volantes y banners localizados en puntos clave donde serán expuestos al público objetivo; mientras que, en el espacio digital, se utilizará marketing de contenidos mediante los formatos de publicaciones cuadradas, historias y reels para lograr la difusión de información.This professional project will design a communication campaign for the return to operations of Kametsa E.I.R.L. It was closed due to the global pandemic caused by COVID-19 for the entirety of 2021 and reopened in March 2022. In addition to positioning Kametsa as one of the main nighttime tourist destinations in Junín, Perú; various traditional marketing tools and techniques will be integrated such as digital marketing too. From traditional marketing instruments, the campaign relied on the use of flyers and banners that were located at key points where they were exposed to the target audience. In terms of digital space, content marketing will be used through social media standards, which are square or 1:1 post and vertical or 9:16 stories and reels to achieve the spread of content and information

Sentiment Analytics and Financial Markets

From major news outlets to social media and the general public, it is common to find mentions of the existence of relationships between narratives and economic outcomes. By definition, those narratives are forms of soft information, which until recently have been difficult to quantify and are often propagated through natural language and text in particular. This thesis seeks to leverage this soft information and harness one key dimension of text in particular: Sentiment. In the context of this thesis, sentiment is defined as the disposition of an entity toward another entity, expressed via a specific medium. In the first three chapters of this thesis, the medium of interest is “News”, specifically news stories published in the financial press. The first paper uses firm-specific news sentiment to understand why market anomalies earn a premium on earnings announcement days. News sentiment shows that this premium for value firms is concentrated on bad news events, which permits us to propose new avenues to understand this market anomaly. The second and third chapters investigate more generally how news can help understand drivers of market anomalies. Market anomalies have played a central role in asset pricing research over the past decades, and numerous competing theories seek to accommodate empirical observations that deviate from the classical model. Chapter two proposes a framework based on cash-flow and discount rate news, allowing us to capture the driving forces behind anomaly returns and disentangle competing explanations for anomalies. The third chapter investigates drivers of anomaly returns and characterizes news of momentum and value stocks, in particular, highlighting the strong negative correlation between the two. It is also the first to link cash-flow news, discount rate news, and news sentiment. The economic outcome of interest in the fourth chapter is to understand how changes in company ownership, especially following leveraged buy-outs, affect employee welfare. We gather millions of online reviews of employees about their employers and investigate the underlying text data to characterize the impact private equity firms have on those narratives. Overall, employees’ satisfaction drops sharper following leverage buy-outs than in other types of ownership changes and we can trace those problems back to specific issues related to lack of management care and fear of cost-cutting and layoffs

The Polerovirus Silencing Suppressor P0 Targets ARGONAUTE Proteins for Degradation

SummaryPlant and animal viruses encode suppressor proteins of an adaptive immunity mechanism [1] in which viral double-stranded RNA is processed into 21–25 nt short interfering (si)RNAs. The siRNAs guide ARGONAUTE (AGO) proteins so that they target viral RNA. Most viral suppressors bind long dsRNA or siRNAs [2–11] and thereby prevent production of siRNA or binding of siRNA to AGO. The one exception is the 2b suppressor of Cucumoviruses that binds to and inhibits AGO1 [12]. Here we describe a novel suppressor mechanism in which a Polerovirus-encoded F box protein (P0) [13] targets the PAZ motif and its adjacent upstream sequence in AGO1 and mediates its degradation. F box proteins are components of E3 ubiquitin ligase complexes that add polyubiquitin tracts on selected lysine residues and thereby mark a protein for proteasome-mediated degradation [14]. With P0, however, the targeted degradation of AGO is insensitive to inhibition of the proteasome, indicating that the proteasome is not involved. We also show that P0 does not block a mobile signal of silencing, indicating that the signal molecule does not have AGO protein components. The ability of P0 to block silencing without affecting signal movement may contribute to the phloem restriction of viruses in the Polerovirus group

Intensive care unit admission in chronic obstructive pulmonary disease: patient information and the physician’s decision-making process

International audienceIntroduction: ICU admission is required in more than 25% of patients with chronic obstructive pulmonary disease (COPD) at some time during the course of the disease. However, only limited information is available on how physicians communicate with COPD patients about ICU admission. Methods: COPD patients and relatives from 19 French ICUs were interviewed at ICU discharge about their knowledge of COPD. French pulmonologists self-reported their practices for informing and discussing intensive care treatment preferences with COPD patients. Finally, pulmonologists and ICU physicians reported barriers and facilitators for transfer of COPD patients to the ICU and to propose invasive mechanical ventilation. Results: Self-report questionnaires were filled in by 126 COPD patients and 102 relatives, and 173 pulmonologists and 135 ICU physicians were interviewed. For 41% (n = 39) of patients and 54% (n = 51) of relatives, ICU admission had never been expected prior to admission. One half of patients were not routinely informed by their pulmonologist about possible ICU admission at some time during the course of COPD. Moreover, treatment options (that is, non-invasive ventilation, intubation and mechanical ventilation or tracheotomy) were not explained to COPD patients during regular pulmonologist visits. Pulmonologists and ICU physician have different perceptions of the decision-making process pertaining to ICU admission and intubation. Conclusions: The information provided by pulmonologists to patients and families concerning the prognosis of COPD, the risks of ICU admission and specific care could be improved in order to deliver ICU care in accordance with the patient's personal values and preferences. Given the discrepancies in the decision-making process between pulmonologists and intensivists, a more collaborative approach should probably be discussed