Miracle-dz/UniFAR-FTUs huggingface dataset:
Interpretable Discovery in Large Image Data Sets

Automated detection of new, interesting, unusual, or anomalous images within large data sets has great value for applications from surveillance (e.g., airport security) to science (observations that don't fit a given theory can lead to new discoveries). Many image data analysis systems are turning to convolutional neural networks (CNNs) to represent image content due to their success in achieving high classification accuracy rates. However, CNN representations are notoriously difficult for humans to interpret. We describe a new strategy that combines novelty detection with CNN image features to achieve rapid discovery with interpretable explanations of novel image content. We applied this technique to familiar images from ImageNet as well as to a scientific image collection from planetary science.
Effects of Virtual Reality Immersion in Individuals with Central Nervous System Injury

The use of Virtual Reality (VR) based therapeutic interventions as an adjunct to traditional physical therapy is innovative, yet many questions remain regarding its efficacy and safety. The purpose of this exploratory study is to assess the level of presence, amount of simulator sickness and level of perceived exertion when individuals with central nervous system (CNS) injury exercised with the Sony PlayStation 2 EyeToy, an off-the-shelf, VR-based. A convenience sample of ten participants, 4 with stroke and 6 with spinal cord injury, were recruited from the local community. Participants exercised for 1-2 hours/day for 20 sessions. Assessments used included the Simulator Sickness Questionnaire (SSQ), Presence Questionnaire (PQ) and BORG Rate of Perceived Exertion Scale (RPE). Data were collected after each session (SSQ and BORG RPE) and weekly (PQ). In general the results suggest that, as with individuals with intact nervous systems, these participants reported a decrease in presence with an increase in simulator sickness. They also reported a decrease in RPE earlier in training, suggestive of a training effect. In conclusion, while much more research is needed, we have begun to explore the relationship between presence and simulator sickness in individuals with CNS injuries. Keywords--stroke, spinal cord injury, virtual reality games, presence, simulator sickness, rate of perceived exertion
Sparsity, redundancy and robustness in artificial neural networks for learning and memory. (Parcimonie, redondance et robustesse dans les réseaux de neurones artificiels pour l'apprentissage et la mémoire)

L'objectif de la recherche en Intelligence Artificielle (IA) est de repliquer les capacites cognitives humaines au moyen des ordinateurs modernes. Les resultats de ces dernieres annees semblent annoncer une revolution technologique qui pourrait changer profondement la societe. Nous focalisons notre interet sur deux aspects cognitifs fondamentaux, l'apprentissage et la memoire. Les memoires associatives offrent la possibilite de stocker des elements d'information et de les recuperer a partir d'une partie de leur contenu, et imitent ainsi la memoire cerebrale. L'apprentissage profond permet de passer d'une perception analogique du monde exterieur a une representation parcimonieuse et plus compacte. Dans le chapitre 2, nous presentons une memoire associative inspiree des reseaux de Willshaw, avec une connectivite contrainte. Cela augmente la performance de recuperation des messages et l'efficacite du stockage de l'information.Dans le chapitre 3, une architecture convolutive a ete appliquee sur une tâche de lecture de mots partiellement affiches dans des conditions similaires a une etude de psychologie sur des sujets humains. Cette experimentation montre la similarite de comportement du reseau avec les sujets humains concernant differentes caracteristiques de l'affichage des mots.Le chapitre 4 introduit une methode de representation des categories par des assemblees de neurones dans les reseaux profonds. Pour les problemes a grand nombre de classes, cela permet de reduire significativement les dimensions d'un reseau.Le chapitre 5 decrit une methode d'interfacage des reseaux de neurones profonds non supervises avec les memoires associatives a cliques.
A GPS-GSM predicated vehicle tracking system, monitored in a mobile app based on Google Maps

“Internet of things” — is a subject of great interest for many in today's world. IoT is the future that scholars and researchers anticipated and worked for. IoT tries to bring everything under one umbrella with cross disciplinary collaboration. The unification of everything in the world, making use of a common infrastructure that can not only provide the users with the control but also helps them understand the state of it, is the zenith of IoT. Vehicle tracking is one such application of IoT. This system comprises of a GPS antenna, a GSM modem, Atmega microcontroller and a mobile application that locates the vehicle on a map and also helps the user navigate to it. This system is developed keeping in mind, the trouble of finding one's vehicle when lost.
Retinal Protection and Distribution of Curcumin in Vitro and in Vivo

Diabetic retinopathy (DR), a secondary complication of diabetes, is a leading cause of irreversible blindness accounting for 5% of world blindness cases in working age. Oxidative stress and inflammation are considered causes of DR. Curcumin, a product with anti-oxidant and anti-inflammatory properties, is currently proposed as oral supplementation therapy for retinal degenerative diseases, including DR. In this study we predicted the pharmacodynamic profile of curcumin through an in silico approach. Furthermore, we tested the anti-oxidant and anti-inflammatory activity of curcumin on human retinal pigmented epithelial cells exposed to oxidative stress, human retinal endothelial and human retinal pericytes (HRPCs) cultured with high glucose. Because currently marketed curcumin nutraceutical products have not been so far evaluated for their ocular bioavailability; we assessed retinal distribution of curcumin, following oral administration, in rabbit eye. Curcumin (10 μM) decreased significantly (p < 0.01) ROS concentration and TNF-α release in retinal pigmented epithelial cells and retinal endothelial cells, respectively. The same curcumin concentration significantly (p < 0.01) protected retinal pericytes from high glucose damage as assessed by cell viability and LDH release. Among the tested formulations, only that containing a hydrophilic carrier provided therapeutic levels of curcumin in rabbit retina. In conclusion, our data suggest that curcumin, when properly formulated, may be of value in clinical practice to manage retinal diseases.
Deconstructing Blockchains: Concepts, Systems, and Insights

Popularly known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchains is seen as a disruptive technology capable of impacting a wide variety of domains, ranging from finance to governance, by offering superior security, reliability, and transparency in a decentralized manner. In this tutorial presentation, we first study the original Bitcoin design, as well as Ethereum and Hyperledger, and reflect on their design from an academic perspective. We provide an overview of potential applications and associated research challenges, as well as a survey of ongoing research projects. We mention opportunities blockchain creates for event-based systems. Finally, we conclude with a walkthrough showing the process of developing a decentralized application (ĐSApp), using a popular Smart Contract language (Solidity) for the blockchain platform of Ethereum.
Diel patterns in coastal‐stream nitrate concentrations linked to evapotranspiration in the riparian zone of a low‐relief, agricultural catchment

Evapotranspiration (ET) can cause diel fluctuations in the elevation of the water table and the stage in adjacent streams. The diel fluctuations of water levels change head gradients throughout the day, causing specific discharge through near‐stream sediment to fluctuate at the same time scale. In a previous study, we showed that specific discharge controls the residence time of groundwater in streambed sediment that, in turn, exerted the primary control on NO3− removal from groundwater passing through the streambed. In this study, we examine the magnitude of diel specific discharge patterns through the streambed driven by ET in the riparian zone with a transient numerical saturated–unsaturated groundwater flow model. On the basis of a first‐order kinetic model for NO3− removal, we predicted diel fluctuations in stream NO3− concentrations. Model results indicated that ET drove a diel pattern in specific discharge through the streambed and riparian zone (the NO3− removal zones). Because specific discharge is inversely proportional to groundwater travel time through the NO3− removal zones and travel time determines the extent of NO3− removal, diel changes in ET can result in a diel pattern in NO3− concentration in the stream. The model predictions generally matched observations made during summertime base‐flow conditions in a small coastal plain stream in Virginia. A more complicated pattern was observed following a seasonal drawdown period, where source components to the stream changed during the receding limb of the hydrograph and resulted in diel fluctuations being superimposed over a multi‐day trend in NO3− concentrations. Copyright © 2013 John Wiley & Sons, Ltd.
On the Robustness of Interpretability Methods

We argue that robustness of explanations---i.e., that similar inputs should give rise to similar explanations---is a key desideratum for interpretability. We introduce metrics to quantify robustness and demonstrate that current methods do not perform well according to these metrics. Finally, we propose ways that robustness can be enforced on existing interpretability approaches.
Implementing deduplication technique for RDF files with enhanced security using multi cloud servers

Rapid growth of multi clouds in providing file storage and various other cloud facilities increased, to provide enhanced security through file partition into multi clouds and increase efficiency by eliminating deduplication from uploaded files, Current DiploCloud is an efficient and scalable system for managing RDF data in the cloud using intra-operator parallelism and data collocation by considering recurring, fine-grained physiological RDF partitions. Current system using cryptographic techniques for providing security to loaded files, this technique usually increases the computational cost in upload and downloads files. Current RDF does not provide removal of redundant data which increases the cloud storage usage. Enhance the current system with Efficient RDF data processing system through Multi Cloud Server Security and adopting data duplicate removal technique which restricts data duplication from multi clouds. The main objective is developing DiploCloud in several directions: New hybrid storage model that efficiently and effectively partitions an RDF graph and physically finds related data. Security portioned for RDF files using Multi Cloud Servers Elimination of Duplicate data from RDF in clouds
Strong Convexity and Smoothness of Solutions to Geometric Optics Problems via Dynamic Programming

In this letter, a formulation of Fermat’s principle as an optimization problem over a finite number of stages is used to prove strong convexity and smoothness of the solutions to certain geometric optics problems. The class of problems considered in this letter consists in the determination of the trajectory followed by a ray between a light source and a final fixed point, separated by a finite number of layered homogeneous media, characterized by their refractive indices. To obtain the theoretical results, a dynamic programming argument is used in the analysis. Then, strong convexity and smoothness are exploited to get an error bound valid when an exact solution is replaced by an approximate solution. Numerical results are provided to validate the theoretical achievements.
Population Genomics Provide Insights into the Evolution and Adaptation of the Eastern Honey Bee (Apis cerana)

Abstract The mechanisms by which organisms adapt to variable environments are a fundamental question in evolutionary biology and are important to protect important species in response to a changing climate. An interesting candidate to study this question is the honey bee Apis cerana, a keystone pollinator with a wide distribution throughout a large variety of climates, that exhibits rapid dispersal. Here, we resequenced the genome of 180 A. cerana individuals from 18 populations throughout China. Using a population genomics approach, we observed considerable genetic variation in A. cerana. Patterns of genetic differentiation indicate high divergence at the subspecies level, and physical barriers rather than distance are the driving force for population divergence. Estimations of divergence time suggested that the main branches diverged between 300 and 500 Ka. Analyses of the population history revealed a substantial influence of the Earth’s climate on the effective population size of A. cerana, as increased population sizes were observed during warmer periods. Further analyses identified candidate genes under natural selection that are potentially related to honey bee cognition, temperature adaptation, and olfactory. Based on our results, A. cerana may have great potential in response to climate change. Our study provides fundamental knowledge of the evolution and adaptation of A. cerana.
Parental proportions maximizing the mean value of a parameter in a panmictic population can be useful in plant breeding

La determination des proportions parentales qui maximisent la valeur moyenne d'un parametre dans une population panmictique peut etre utile en amelioration des plantes. De nombreux travaux de selection portent sur la valeur moyenne d'un parametre dans un ensemble de genotypes (ou d'echantillons). Ce parametre peut caracteriser les genotypes eux-memes (distances entre genotypes, diversite genetique de l'ensemble, resistance d'un melange de lignees a un ensemble de pathogenes) ou la descendance de ces genotypes par panmixie (rendement d'une variete synthetique, heterosis moyen). La plupart du temps, la valeur moyenne est calculee avec des frequences egales des genotypes. Le present article propose de determiner les proportions des genotypes qui maximisent la valeur moyenne dans le melange panmictique de facon a augmenter l'efficacite des methodes de selection. L'interet de cette procedure est illustre par une application en gestion des ressources genetiques et par des simulations en selection recurrente assistee par marqueurs. La procedure a permis de supprimer toute redondance dans une collection restreinte (core collection) en augmentant la diversite moyenne de 81 % et de reduire de 38 % le temps et l'argent requis dans une selection recurrente conventionnelle assistee par marqueurs. Elle invite a formuler de nombreux problemes de selection en termes de maximisation de formes quadratiques.
A novel implementation technique for genetic algorithm based auto-tuning PID controller

The auto-tuning proportional-integral-derivative (PID) controllers based on genetic algorithms have many limitations in their implementation. For example, some chromosomes of the tuned genetic algorithms may cause closed-loop system instability, and some chromosomes tuned for an operating condition may cause instability for other operating conditions. This article provides the possible solutions for these problems. An implementation technique of a genetic algorithm is proposed based on these solutions. Numerical simulations are given to evaluate the proposed method applied to a system with variable parameters. Moreover, this technique is also used for controlling a brushless servo motor.
Toward Thermoplastic Lignin Polymers; Part II: Thermal & Polymer Characteristics of Kraft Lignin & Derivatives

This work focused on providing a molecular understanding of the way the polymeric properties of kraft lignin and its derivatives are affected by various thermal treatments. This information was then correlated with the polymeric properties of the materials (glass transition temperature (Tg), molecular weight characteristics, and thermal stability) for a series of selectively and progressively derivatized softwood kraft lignin samples. Softwood kraft lignin was highly susceptible to thermally induced reactions that caused its molecular characteristics to be severely altered with the concomitant formation of irreversible cross-linking. However, by fully methylating the phenolic OH groups from within the structure of softwood kraft lignin, the thermal stability of these materials was dramatically enhanced and their Tg reduced. While optimum thermal stability and melt re-cycling was observed with the fully methylated derivatives, fully oxypropylated phenolic substitution did not offer the same possibilities. The accumulated data is aimed at providing the foundations for a rational design of single component, lignin-based thermoplastic materials with reproducible polymeric properties when thermally processed in a number of manufacturing cycles.
The HB Narrowband Comet Filters: Standard Stars and Calibrations

Abstract We present results concerning the development and calibration of a new set of narrowband comet filters, designated the HB filter set, which was designed and manufactured to replace aging IHW filters. Information is also presented about the design and manufacturing of the filters, including the reasoning that was used for deciding the final wavelengths and bandpasses. The new filters are designed to measure five different gas species (OH, NH, CN, C2, C3), two ions (CO+, H2O+), and four continuum points. An improved understanding of extended wings from emission bands in comet spectra, gained since the development of the IHW filters, was incorporated into the new design, so that contamination from undesired species is significantly reduced compared to previous filters. In addition, advances in manufacturing techniques lead to squarer transmission profiles, higher peak transmission and UV filters with longer lifetimes. We performed the necessary calibrations so that data obtained with the filters can be converted to absolute fluxes, allowing for, among other things, accurate subtraction of the continuum from the gas species. Flux standards and solar analogs were selected and observed, and the data were used to establish a magnitude system for the HB filters. The star measurements were also used to evaluate which solar analogs were best representatives of the Sun and to explore how the flux standards differed in the UV with respect to their spectral type. New procedures were developed to account for the non-linear extinction in the OH filter, so that proper extrapolations to zero airmass can be performed, and a new formalism, which can account for mutual contaminations in two (or more) filters, was developed for reducing comet observations. The relevant equations and reduction coefficients are given, along with detailed instructions on how to apply them. We also performed a series of tests involving factors that can affect either the filter transmission profiles or the distribution of the emission lines in the gas species to determine how these effects propagate through to the calibration coefficients. The results indicate that there are only two factors that are a concern at a level of more than a few percent: f-ratios smaller than f/4, and a few individual filters whose transmission profiles are significantly different from the filters used in the calibrations.
Design of heart disease diagnosis system using fuzzy logic

In most of the cases, heart disease results in death. Medical diagnosis is a difficult task and most of the time done by experts in domain. The aim of this work is to develop a fuzzy expert system to identify heart disease risk in the patients. There are several factors to analyze the heart disease in the patient and it is not an easier task, which makes the physician's job difficult. However, the experts want an accurate tool which considers and identifies the risk factors on the basis of provided information. This paper uses fuzzy expert system for diagnosis of the heart disease. The proposed fuzzy expert system consists of three major steps i.e. fuzzification, rule base and defuzzification. Centroid technique is used for defuzzification. This system has 13 input parameters and 1 output parameter. MATLAB software is used as a development tool. The database is taken from V.A. Medical Center, Long Beach and Cleveland Clinic Foundation.
2D/3D buccal epithelial cell self-assembling as a tool for cell phenotype maintenance and fabrication of multilayered epithelial linings in vitro

Maintaining the epithelial status of cells in vitro and fabrication of a multilayered epithelial lining is one of the key problems in the therapy using cell technologies. When cultured in a monolayer, epithelial cells change their phenotype from epithelial to epithelial-mesenchymal or mesenchymal that makes it difficult to obtain a sufficient number of cells in a 2D culture and to use them in tissue engineering. Here, using buccal epithelial cells from the oral mucosa, we developed a novel approach to recover and maintain the stable cell phenotype and form a multilayered epithelial lining in vitro via the 2D/3D cell self-assembling. Transitioning the cells from the monolayer to non-adhesive 3D culture conditions led to formation of self-assembling spheroids, with restoration of their epithelial characteristics after epithelial-mesenchymal transition. In 7 days, the cells within spheroids restored the apical-basal polarity, and the formation of both tight (ZO1) and adherent (E-cadherin) intercellular junctions was shown. Thus, culturing buccal epithelial cells in a 3D system allowed us to recover and durably maintain the morphological and functional characteristics of epithelial cells. The multilayered epithelial lining formation was achieved after placing spheroids for 7 days onto a hybrid matrix, which consisted of collagen layers and reinforcing poly (lactide-co-glycolide) fibers and was proven promising for replacement of the urothelium. Thus, we offer an effective technique of forming multilayered epithelial linings on carrier-matrices using cell spheroids that was not previously described elsewhere and can find a wide range of applications in tissue engineering, replacement surgery, and regenerative medicine.
Phase Identification With Incomplete Data

Phase identification is a process to determine which of the three phases a particular house is connected to. The state-of-the-art identification methods usually exploit smart metering data. However, the data sets are not always available and the major challenge is hence to identify phases with incomplete data set. This paper proposes a novel spectral and saliency analysis identification method to overcome this hurdle. Spectral analysis is first performed to extract the high-frequency features from the incomplete data. Saliency analysis is then adopted to extract salient features from the variations of high-frequency loads in the time domain. Correlation analysis between customer features and the phase features is used to determine customers’ phase connectivity. The method is executed iteratively until all customers with smart meters have been allocated to a specific phase or no salient features can be found. It is validated against real data from over 6000 smart meters in Ireland and achieves an accuracy of over 93% with only 10% smart meter penetration ratio in a 100-household network.