Interactions of short chain phenylalkanoic acids within ionic surfactant micelles in aqueous media

% SDS KR nema Solubilization and interactions of phenylalkanoic acids induced by cationic surfactant, cetyltrimethylammonium bromide (CTAB) and an anionic surfactant, sodium dodecyl sulfate (SDS) was investigated spectrophotometrically at 25.0°C. The UV spectra of the additives (acids) were measured with and without surfactant above and below critical micelle concentration (cmc) of the surfactant. The presence of alkyl chain in phenylalkanoic acids is responsible for hydrophobic interaction resulting in shift of the spectra towards longer wavelength (red shift). The value of partition coefficient (Kx) between the bulk water and surfactant micelles and in turn standard free energy change of solubilization (ΔGpº) were also estimated by measuring the differential absorbance (ΔA) of the additives in micellar solutions

Investigation of 1-alkanols in organised solutions

Conductometric behaviour of 1-alkanols (C5-C10) in organised solutions of sodium dodecylbenzenesulfonate (SDBS) is investigated. Interaction of each alkanol with anionic surfactant is reflected in terms of association constants, Kc. It is observed that self-assembly of SDBS is induced by the alkanol addition. The depression in critical micelle concentration (CMC) of SDBS caused by each alkanol is translated to partition coefficient, Kc by using interaction coefficient. The dimensionless partition coefficient, Kx is utilized to highlight the energy efficiency of the solubilization process. The results indicate that even longer chain alkanols prefer interfacial area for their residence. The relative solubility of each alkanol is enhanced with increasing SDBS concentration. Such basic information could be vital for development of nano-scale assemblies for specific delivery of water soluble drugs.KEY WORDS: SDBS, Alcohols, Partition coefficient, Relative solubility, Conductometry Bull. Chem. Soc. Ethiop. 2011, 25(3), 469-474

A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models

Word representation has always been an important research area in the history of natural language processing (NLP). Understanding such complex text data is imperative, given that it is rich in information and can be used widely across various applications. In this survey, we explore different word representation models and its power of expression, from the classical to modern-day state-of-the-art word representation language models (LMS). We describe a variety of text representation methods, and model designs have blossomed in the context of NLP, including SOTA LMs. These models can transform large volumes of text into effective vector representations capturing the same semantic information. Further, such representations can be utilized by various machine learning (ML) algorithms for a variety of NLP related tasks. In the end, this survey briefly discusses the commonly used ML and DL based classifiers, evaluation metrics and the applications of these word embeddings in different NLP tasks

Growth and production of Nile tilapia (Oreochromis niloticus Lin.) in irrigated Boro rice under floodplain environment

The experiment was conducted at BRRI Regional Station, Habiganj during 1994-95 to evaluate the growth and economic performance of Nile tilapia, Oreochromis niloticus, fish reared in the field of irrigated boro rice with different fertilizer levels. Grain yield of rice was not affected by fish culture. It was observed that 50% of recommended fertilizer was enough to produce increased rice yield (8-10 t/ha) at floodplain environment and additional yield was obtained with the increasing fertilizer rates. Results further indicated that O. niloticus could successfully be reared in the field of irrigated boro rice with recommended fertilizer level. Larger size of fingerlings at release had improved recovery percent, body weight gain and higher fish yield. Results also revealed that rice + fish production system produced higher net return than the system with rice alone

A Multi-Modal Dataset for Hate Speech Detection on Social Media: Case-study of Russia-Ukraine Conflict

Hate speech consists of types of content (e.g. text, audio, image) that express derogatory sentiments and hate against certain people or groups of individuals. The internet, particularly social media and microblogging sites, have become an increasingly popular platform for expressing ideas and opinions. Hate speech is prevalent in both offline and online media. A substantial proportion of this kind of content is presented in different modalities (e.g. text, image, video). Taking into account that hate speech spreads quickly during political events, we present a novel multimodal dataset composed of 5680 text-image pairs of tweets data related to the Russia-Ukraine war and annotated with a binary class:”hate” or”no-hate” The baseline results show that multimodal resources are relevant to leverage the hateful information from different types of data. The baselines and dataset provided in this paper may boost researchers in direction of multimodal hate speech, mainly during serious conflicts such as war contexts

Effect of Bleaching on Color Change and Surface Topography of Composite Restorations

This study was conducted to determine the effect of 15% carbamide peroxide bleaching agent on color change and surface topography of different composite veneering materials (Filtek Z350 (3M ESPE), Esthet X (Dentsply India), and Admira (Voco, Germany). Methods. 30 samples were fabricated for evaluation of color change using CIELAB color system and Gonioreflectometer (GK 311/M, ZEISS). 45 disc-shaped specimens were made for evaluation of surface topography after bleaching (Nupro White Gold; Dentsply) using SEM. Statistical analysis. One way ANOVA and Multiple comparison tests were used to analyze the data. Statistical significance was declared if the P value was .05 or less. Results and conclusion. All the specimens showed significant discoloration (ΔE > 3.3) after their immersion in solutions representing food and beverages. The total color change after bleaching as compared to baseline color was significant in Filtek Z350 (P = .000) and Esthet X (P = .002), while it was insignificant for Admira (P = .18). Esthet X showed maximum surface roughness followed by Admira and Filtek Z350. Bleaching was effective in reducing the discoloration to a clinically acceptable value in all the three groups (ΔE < 3.3)

Hepatoprotective effect of Cichorium Intybus linn (Kasni) Extracts against Carbon Tetrachloride induced Liver Damage

Background: To assess the effect of aqueous and alcoholic extracts of Cichorium intybus linn , frequently used by Hakims and traditional healers, on liver, against the carbon tetrachloride (CCl4) induced hepatic injury. Methods: In this experimental intervention study, forty rats were subdivided into four sub groups, ten in each group. Group I was kept as standard control. For this study three groups (II, III, IV) were made in which aqueous and alcoholic extract was given prior to hepatic damage by CCl4. Hepatoprotective effect was assessed by measuring serum levels of alanine transaminase(ALT), aspartate transaminase (AST) and alkaline phosphatase (ALP). Results: Very significant hepatoprotective effect (p&lt;0.001) was observed by alcoholic extract while aqueous extract showed no significant effect against CCl4 induced hepatic injury. Conclusion: Alcoholic extract of Cichorium intybus linn exhibits a very significant hepatoprotective effec

IMPACTS OF ATTABAD LAKE (PAKISTAN) AND ITS FUTURE OUTLOOK

Due to geological, hydrological and anthropogenic variations in Northern Areas of Pakistan, the possibility of hazards like earthquake, flash floods, landslide and Glacial Lake Outburst Flood (GLOF) have increased manifolds. The incident of Attabad landslide on 4th January 2010 blocking the Hunza River and resulting in the formation of huge lake as a sequel to Astore earthquake in 2002 and Kashmir earthquake in 2005 is a testimony to the fact hazards turn into disasters causing loss and damage to lives, properties, assets and environment. There are multiple reasons ranging from global warming, deforestation, unplanned settlements, population growth, aggressive farming and host of other man induced activities which have made the Northern Areas of Pakistan hazards prone and are likely to pose continuous threat if requisite preparation and response options are not considered well in advance. In case of Attabad landslide, viewing from the prism of disaster risk management the response of Gilgit-Baltistan and Federal Governments has though not been up to the mark yet mobilization of resources and opinion to manage the disaster leaves a promising environment of hope and capacity which can be further developed to more resilient respondent provided little extra deliberations are done and attention is paid. The solution to Attabad landslide dam crisis lies in reducing the risk by either draining out the lake completely or making a reliable structure with proper design for flow of the water from the lake

Improved Binary Similarity Measures for Software Modularization

Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence and absence of features. Binary similarity measures have also been explored with different clustering approaches (e.g., agglomerative hierarchical clustering) for software modularization to make the software systems understandable and manageable. Each similarity measure has its own strengths and weaknesses that result in improving and deteriorating the clustering results, respectively. This paper highlights the strengths of some well-known existing binary similarity measures for software modularization. Furthermore, based on these existing similarity measures, this paper introduces the improved new binary similarity measures. Proofs of the correctness with illustration and a series of experiments are presented to evaluate the effectiveness of our new binary similarity measures