A comparison of the reactivity of different synthetic calcium carbonate minerals with arsenic oxyanions

This study was conducted to determine how the structure and surface chemistry of bulk CaCO3 differs from that of nanometer-sized CaCO3 and then to determine rate, extent and mechanisms of As adsorption on various synthetic CaCO3 materials. Additionally, we sought to devise a chemical CaCO3 precipitate that approximates biogenic CaCO3. The bulk CaCO3 precipitation was performed by using a solution that was highly oversaturated so that large CaCO3 precipitates rapidly form. Two different methods were employed for the synthesis of nanometer size CaCO3 i) an in situ deposition technique and ii) an interfacial reaction (water in oil emulsion). Mineral characterization of all CaCO3 precipitates was done with Nitrogen Porosimetry (Brunauer Emmett Teller method), particle size analysis, X-ray diffraction and Fourier Transform Infrared/ Fourier Transform Raman spectroscopy. The principal objective of the research was to assess the overall reactivity of As(III) and As(V) with different synthetic CaCO3 minerals. This was accomplished by i) running adsorption isotherms (varying As concentration), ii) measuring pH envelopes (varying pH at a fixed concentration) and iii) kinetic experiments (varying reaction time). Also, electrophoretic mobility experiments were performed in the presence of As(III) and As(V), and these studies revealed that As(III) forms stronger inner-sphere complexes with CaCO3 than As(V). Also, it was found that nanometer-sized CaCO3 prepared via deposition formed stronger inner-sphere complexes with As oxyanions (q = 5.26 µmol/m2) compared to either nano-sized CaCO3 from interfacial reactions (q = 4.51 µmol/m2) or bulk CaCO3 (q = 4.39 µmol/m2). The PEG-based nano CaCO3 prepared by an in-situ deposition technique presents a novel and readily available synthesis route that can be used as proxy for the biogenic CaCO3 known to be present in many different environmental conditions. The results of this study suggest that CaCO3 can be used as a sorbent for As in groundwater

On Lie algebroid over algebraic spaces

We consider Lie algebroids over algebraic spaces (in short we call it as $a$-spaces) by considering the sheaf of Lie-Rinehart algebras. We discuss about properties of universal enveloping algebroid $\mathscr{U}(\mathcal{O}_X,\mathcal{L})$ of a Lie algebroid $\mathcal{L}$ over an $a$-space $(X, \mathcal{O}_X)$. This is done by sheafification of the presheaf of universal enveloping algebras of Lie-Rinehart algebras. We review the extent to which the structure of the universal enveloping algebroid of Lie algebroids (over special $a$-spaces) resembles a bialgebroid structure, and present a version of Poincare-Birkhoff-Witt theorem and Cartier-Milnor-Moore theorem for this type of structure.Comment: Some minor changes done. Mainly, we shorten it and kept main idea

Retrospect, resurgence and prospects of micelles

Recent studies on micellar systems were systematically overviewed, paying special attention to Gemini surfactants, mixed micelles, clouding phenomena and microemulsions. Gemini surfactants are surfactants that have two hydrophilic groups and two hydrophobic groups per amphiphilic molecule, rather than the single hydrophilic and single hydrophobic group of conventional surfactants. The greater efficiency and effectiveness of geminis over comparable conventional surfactants make them more cost effective as well as environmentally desirable. Mixed micelles have received wide attention for several decades, both in theoretical studies and in practical applications, because of their distinctive behaviour in comparison with normal micellar systems. Clouding (cloud point, CP) is a well known phenomenon observed in non-ionic surfactants. For charged micelles (i.e., ionic surfactants), the phenomenon rarely occurs, however, under special conditions, the CP in ionic surfactant solutions is observed. Some amphiphilic drugs, like ionic surfactants, also undergo pH-, concentration-, and temperature- dependent phase separation. It was observed that their CP can vary with additives. Due to their unique properties, namely, thermodynamic stability, ultralow interfacial tension, large interfacial area and the ability to solubilize otherwise immiscible liquids, microemulsions have attained increasing significance both in basic research and in industry. The uses and applications of microemulsions have been numerous. Several reviews on micellar systems and their applications have been published. However, this topic is developing quite rapidly and it is hoped that this review will help newcomers in the field as well as those already involved in this field

Biased Attention: Do Vision Transformers Amplify Gender Bias More than Convolutional Neural Networks?

Deep neural networks used in computer vision have been shown to exhibit many social biases such as gender bias. Vision Transformers (ViTs) have become increasingly popular in computer vision applications, outperforming Convolutional Neural Networks (CNNs) in many tasks such as image classification. However, given that research on mitigating bias in computer vision has primarily focused on CNNs, it is important to evaluate the effect of a different network architecture on the potential for bias amplification. In this paper we therefore introduce a novel metric to measure bias in architectures, Accuracy Difference. We examine bias amplification when models belonging to these two architectures are used as a part of large multimodal models, evaluating the different image encoders of Contrastive Language Image Pretraining which is an important model used in many generative models such as DALL-E and Stable Diffusion. Our experiments demonstrate that architecture can play a role in amplifying social biases due to the different techniques employed by the models for feature extraction and embedding as well as their different learning properties. This research found that ViTs amplified gender bias to a greater extent than CNN

Gender Bias in Multimodal Models: A Transnational Feminist Approach Considering Geographical Region and Culture

Deep learning based visual-linguistic multimodal models such as Contrastive Language Image Pre-training (CLIP) have become increasingly popular recently and are used within text-to-image generative models such as DALL-E and Stable Diffusion. However, gender and other social biases have been uncovered in these models, and this has the potential to be amplified and perpetuated through AI systems. In this paper, we present a methodology for auditing multimodal models that consider gender, informed by concepts from transnational feminism, including regional and cultural dimensions. Focusing on CLIP, we found evidence of significant gender bias with varying patterns across global regions. Harmful stereotypical associations were also uncovered related to visual cultural cues and labels such as terrorism. Levels of gender bias uncovered within CLIP for different regions aligned with global indices of societal gender equality, with those from the Global South reflecting the highest levels of gender bias.Comment: Selected for publication at the Aequitas 2023: Workshop on Fairness and Bias in AI | co-located with ECAI 2023, Krak\'ow, Polan

Observational constraints and some toy models in f(Q)f(Q) gravity with bulk viscous fluid

The standard formulation of general relativity fails to describe some recent interests in the universe. It impels us to go beyond the standard formulation of gravity. The $f(Q)$ gravity theory is an interesting modified theory of gravity, where the gravitational interaction is driven by the nonmetricity $Q$. This study aims to examine the cosmological models with the presence of bulk viscosity effect in the cosmological fluid within the framework of $f(Q)$ gravity. We construct three bulk viscous fluid models, i.e. (i) for the first model, we assuming the Lagrangian $f(Q)$ as linear dependence on $Q$, (ii) for the second model the Lagrangian $f(Q)$ as a polynomial functional form, and (iii) the Lagrangian $f(Q)$ as a logarithmic dependence on $Q$. Furthermore, we use 57 points of Hubble data and 1048 Pantheon dataset to constraint the model parameters. Then, we discuss all the energy conditions for each model, which helps us to test the self-consistency of our models. Finally, we present the profiles of the equation of state parameters to test the models' present status.Comment: 13 pages,9 figures. Comments are Welcom