Restructured eigenfilter matching for novelty detection in random textures

A new eigenfilter-based novelty detection approach to find abnormalities in random textures is presented. The proposed algorithm reconstructs a given texture twice using a subset of its own eigenfilter bank and a subset of a reference (template) eigenfilter bank, and measures the reconstruction error as the level of novelty. We then present an improved reconstruction generated by structurally matched eigenfilters through rotation, negation, and mirroring. We apply the method to the detection of defects in textured ceramic tiles. The method is over 90 % accurate, and is fast and amenable to implementation on a production line.

Effect of Non-Rubber Constituents on Guayule and Hevea Rubber Intrinsic Properties

To meet the increasing demand for natural rubber (NR), currently sourced from the tropical rubber tree Hevea brasiliensis, and address price volatility and steadily increasing labor costs, alternate rubber-producing species are in commercial development. One of these, guayule (Parthenium argentatum), has emerged on the market as a commercial source of high quality rubber. Non-rubber constituents play an important role in the physical properties of NR products. The intrinsic composition of the two NR materials differs and these differences may be a principal cause of the performance differences between them.We have compared the effect of non-rubber constituents, such as protein, lipids, resin and rubber particle membranes. Firstly, a film casting method was developed to obtain rubber films with a uniform thickness. Secondly, the glass transition temperature of different rubbers was determined by dynamic mechanical analysis, and tensile properties were tested for uncompounded materials. Guayule natural rubber (GNR), from which most of the membranes were removed while in latex form (MRGNR) was found to have higher intrinsic strength than GNR or gel-free NR (FNR). An acetone extraction was performed to quantify the resin and free lipids in the rubber samples

Multimodal Mental Health Analysis in Social Media

Depression is a major public health concern in the U.S. and globally. While successful early identification and treatment can lead to many positive health and behavioral outcomes, depression, remains undiagnosed, untreated or undertreated due to several reasons, including denial of the illness as well as cultural and social stigma. With the ubiquity of social media platforms, millions of people are now sharing their online persona by expressing their thoughts, moods, emotions, and even their daily struggles with mental health on social media. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of depressive symptoms from tweets obtained, unobtrusively. Particularly, we examine and exploit multimodal big (social) data to discern depressive behaviors using a wide variety of features including individual-level demographics. By developing a multimodal framework and employing statistical techniques to fuse heterogeneous sets of features obtained through the processing of visual, textual, and user interaction data, we significantly enhance the current state-of-the-art approaches for identifying depressed individuals on Twitter (improving the average F1-Score by 5 percent) as well as facilitate demographic inferences from social media. Besides providing insights into the relationship between demographics and mental health, our research assists in the design of a new breed of demographic-aware health interventions

Humic Substances Enhance Chlorothalonil Phototransformation via Photoreduction and Energy Transfer

ABSTRACT: The photodegradation of chlorothalonil, a polychlorinated aromatic fungicide widely used in agriculture, was investigated under ultraviolet–visible irradiation in the presence and absence of different humic substances that significantly enhance the chlorothalonil phototransformation. On the basis of a kinetic model, an analytical study, the effect of scavengers, the chlorothalonil phosphorescence measurement, and varying irradiation conditions, it was possible to demonstrate that this accelerating effect is due to their capacity to reduce the chlorothalonil triplet state via H-donor reaction and to energy transfer from the triplet humic to ground state chlorothalonil. Energy transfer occurs at wavelengths below 450 nm and accounts for up to 30% of the reaction in deoxygenated medium upon irradiation with polychromatic light (300–450 nm). This process is more important with Elliott humic and fulvic acids and with humic acids extracted from natural carbonaceous material than with Nordic NOM and Pahokee peat humic acids. The obtained results are of high relevance to understanding the processes involved in chlorothalonil phototransformation and the photoreactivity of humic substances. Chlorothalonil is one of the rare molecules shown to react by energy transfer from excited humic substances

Recherche sur la matérialisation de l'énergie des rayons β

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Recherches sur la matérialisation de l'énergie des rayons β

Expériences sur la matérialisation de l'énergie des rayons β effectuées en concentrant les électrons par la méthode de la trochoïde. Les résultats sur la matérialisation de l'énergie des rayons β, ainsi que la section efficace de la matérialisation sont en accord avec ceux obtenus par Skobelzyn et Stepanowa et par Da Silva. D'autre part il a été constaté qu'à masse superficielle égale. le rendement pour la création de paires est du même ordre de grandeur dans le cuivre que dans l'aluminium; la probabilité de matérialisation serait donc proportionnelle à Z et non à Z2 comme prévoit la théorie. Pour le rapport du nombre de positons naturels au nombre de négatons émis par des corps radioactifs, nous avons trouvé 2 à 3. 10-3 pour RaBr2 est 3 à 4. 10-3 pour Th (B + C)