An experimental and computational IR and hybrid DFT-D3 study of the conformations of L-lactic and acrylic acid: new insight to the dehydration mechanism of lactic acid to acrylic acid

We have studied with hybrid Density Functional Theory (DFT) with an aug-cc-pVTZ basis set and D3 dispersion corrections the intra-molecular hydrogen bond of L-lactic acid and L-lactic-acid analogs with the hydroxyl group on the alpha carbon atom substituted by α -XH (where X = S, Se, Te) as well as the conformations of acrylic acid. The results show there are three types of intramolecular hydrogen bonds that can form only when α-OH is present, whereas other less electronegative functional groups such as -SH, -SeH and -TeH do not exhibit the formation of an intramolecular H-bond. We show that the intra-molecular H-bond formed between the alpha-OH hydrogen and the COOH carbonyl oxygen would enhance the rate of the nucleophilic subsitution of alpha-OH to the K+ sites for the previously suggested dehydration mechanism of L-lactic to acrylic acids. We find that a temperature range between 190-210 °C would be optimum to maximise the rate of the nuleophilic substitution of the alpha-OH group onto the potassium sites during the dehydration mechanism of L-lactic acid to acrylic acid. Additionally, our hybrid-DFT simulation of the infrared spectrum of the various conformers shows that the lowest energy conformer can be identified by a single vibrational band at 3734 cm-1 whereas the other conformers this vibrational band is split with Δν that ranges between 6 cm-1 - 176 cm-1. We also find that the various conformers of acrylic acid can be identified by a double peak for the C=O and O-H vibrations which have Δν' of Δν'' 24 and 42 cm-1, respectively. This computational study is useful for spectroscopic experimental efforts that try to identify the various conformers of L-lactic acid and acrylic acid and to gain mechanistic insight into the dehydration mechanism over K substituted NaY Zeolites

Impact of systemic juvenile idiopathic arthritis/Still’s disease on adolescents as evidenced through social media posts

Renee F Modica,1 Kathleen G Lomax,2 Pamela Batzel,3 Armelle Cassanas3 1Department of Pediatrics, University of Florida, Gainesville, FL, USA; 2Immunology, Hepatology and Dermatology Medical Affairs, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 3Treato, Princeton, NJ, USA Purpose: To understand the experience of adolescent systemic juvenile idiopathic arthritis (SJIA) patients and those of their parents based on their social media posts.Methods: English language posts related to SJIA, Still’s disease, or juvenile arthritis were collected and analyzed.Results: In total, 71 posts created between 2009 and 2015 on 15 websites were identified in November 2015. Of the 32 unique authors, 17 were SJIA patients aged 13–20 years (40 posts), 7 were mothers of SJIA patients (12 posts), and 8 patients had unspecified forms of juvenile arthritis (19 posts). Many patients posted about similar diagnostic experiences marked by 5 phases: 1) early prediagnosis: pain and fatigue overlooked until crisis occurred, 2) first misdiagnosis: doctors talked about “growing pains” and psychosocial problems (“fake pains” to avoid school), 3) second misdiagnosis: severity acknowledged, but diagnosed as leukemia or another cancer, 4) tests: tests leading to diagnosis and treatment conducted, and 5) cognitive identity: patient accepted the diagnosis and its implications. Many adolescent patients, looking back at disease onset in their childhood, described themselves as a “sleeping child” rather than the typical active child. Several patients tried to hide their illness from friends, but expressed concerns openly online. Many patients described SJIA as a powerful external enemy, using terms like “bulldozer,” “dragon,” and “monster.” Many posts from patients and their mothers used superhero language/imagery to help “fight” SJIA. Some patients also posted about the risk of death.Conclusion: Although most adolescent SJIA patients openly posted about the difficulties of their disease online, they made efforts to hide their disease in the real world. They frequently used superhero words and images in describing their fight for better health. Physicians can use these insights when counseling SJIA patients to provide a narrative that meshes with the patients’ worldview and perhaps to improve physician–patient communication to increase treatment adherence. Keywords: adolescents, juvenile arthritis, SJIA, social media, Still’s disease, superheroe

"Eaux d'alimentation en zone rurale ivoirienne : approche de la qualité chimique"

Pour une première évaluation de la qualité chimique des eaux souterraines ivoiriennes, 11 paramètres "toxiques et indésirables" ont été dosés dans plus de 200 forages sélectionnés selon des critères géologiques. Il semble possible de conclure que les eaux souterraines sont généralement de qualité acceptable du point de vue de ces paramètres. Il apparaît localement des taux excessifs de fluor, qui sont liés apparemment à des zones faillées particulières. La présence fréquente de teneurs excessives en fer provient de l'inadéquation de certains matériels de pompage aux caractéristiques des eaux souterraines ivoiriennes, toutes agressives

Classifying Words: A Syllables-Based Model

Abstract—Text classification has been extensively studied by linguists and computer scientists. However, there are very few works on classification of words into classes or concepts (e.g. thesaurus). In this paper, we consider this topic, especially in the context of the classification of names like brand names or neologisms. The challenge is thus to provide automated tools to analyze new names by classifying them into concepts. Then, for example, a naming company customer can be informed about which concept a new name is closest to. As we argue that a word can belong to several concepts, we propose to consider the top-k classification approach. Moreover, we rely on syllables to build the classification model. The word corpus is collected from French thesaurus. All labeled-words are separated into syllables. Feature selection techniques are used to select discriminative syllables. We use a syllables frequency (SF) and mutual information (MI) performing with Naive Bayes classifier and K-nearest neighbor (KNN). Instead of selecting only one class, the model select top-k classes ranking them by a classifier score. The result shows the top-k classification model helps to analyze a new word by showing that it can be related to more than one concept. Moreover, the set of discriminative syllables can be used to explain the classification results which makes the results more meaningful