Green solvents for the dissolution and processing of biopolymers

Dissolution and processing of biopolymers perhaps is one of the oldest chemical processes in the world, and there are several breakthrough inventions took place in this area. How- ever, with the advent of technological interventions, the number of improvements in the processing technologies of the bio- polymers has been made to address the efficiency and tech- noeconomics of the developed processes. Application of alternate solvent systems is one of the strategies being popularly used in many such cases. The search of alternative solvent systems to solubilise and process biopolymers is always challenging from sustainability point of view. Bio- polymers are conventionally solubilised in aqueous systems and processed using multistep tedious protocols. Ionic liquids, deep eutectic solvents and bio-derived solvents are emerging as alternative solvents for biomass pretreatment and extraction of natural polymers from the resources. Application of bio- derived and green solvents in various industrial processes can be envisaged in near future, and hence, studies on such sol- vents to critically assess their potential towards industrial ap- plications should be performed. Considering these points, the present review article compiles various recent literature and reports pertaining to the sustainable processing of natural polymers using green solvents for practical applications.publishe

Software-based Solution for Analysis and Decoding of FSK-2 Modulated, Baudot-coded Signals

In the present-day scenario, digital communication has become predominant choice overanalog communication worldwide. Digital modulation schemes form the main block of the digitalcommunication. Among these, frequency shift keying (FSK-2) is a widely used technique employedfor Baudot-coded english text transmission. A Baudot-coded-FSK-2 modulated signal wassimulated corresponding to an english text file. A technique has been developed for its analysisand decoding in the MATLAB environment. This technique does the signal analysis, its parameterextraction, and then digital demodulation, to retrieve its corresponding composite bit-stream. Anefficient method for edge detection using the number of zero-crossings has been devised andimplemented successfully. From the composite bit-stream, overhead bits were removed anddecoding was performed to get back the text output

Comparative study of hypoglycemic effects of oral vildagliptin and voglibose on fasting blood sugar level in albino rats

Background: Diabetes mellitus is a metabolic disorder in which there is increased blood sugar level, glycosuria, dyslipidemia and sometimes ketonemia occurs. Increased blood sugar level leads to characteristic symptoms such as polydipsia, polyurea, blurring of vision, polyphagia and weight loss.Methods: Healthy male Wister rats weighing between 150-250 gm were taken. Total 2 groups A and B were prepared and each group contains 6 animals. Group A was administered voglibose as 0.6 mg/70 kg body weight. Group B was administered vildagliptin as 100 mg/70 kg body weight. Diabetes was induced in group A and B by administration of 120 mg/kg body weight of nicotinamide and 60 mg/kg body weight of streptozocin intraperitoneally. Streptozocin was administered after 15-20 minutes of administration of nicotinamide. After 72 hours of streptozotocin injection, fasting blood glucose level was determined and induction of diabetes was confirmed. The fasting blood samples were collected from all the groups on further days 7, 14, 21 and 28 day to determine the glucose level by glucometer. Results: The decline in fasting blood sugar level by voglibose was 36.4% on day 7, 40.2% on day 14, 43.94% on day 21 and 46.4% on day 28. The reduction in Fasting blood sugar level by vildagliptin was 49% on day 7, 52.25% on day 14 and 54% on day 21 and 28. Thus in group B rats, decline was maximal on day 7 and little fall was recorded on subsequent days. It suggests good efficacy as vildagliptin normalized the blood glucose level effectively.  Conclusions: Vildagliptin was found significantly more effective in lowering fasting blood glucose level than voglibose

FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING APPROACH FOR SOLVING PROBLEM OF FOOD INDUSTRY

Enterprises and industrial centers need current decision for making products in fast changing market. Uncertainty and yield defined goals make decision making more difficult. In this situation fuzzy logic is used for coping surrounding environment. This paper deals with a fuzzy linear programming model for a problem of food industry. The different types of achievement function such as compensatory and weighted compensatory form&nbsp

Comparison of Nitroglycerin versus Lignocaine Spray to Attenuate Haemodynamic Changes in Elective Surgical Patients Undergoing Direct Laryngoscopy and Endotracheal Intubation: A prospective randomised study

Objectives: This study aimed to compare the effects of nitroglycerin (NTG) versus lignocaine spray in blunting the pressor response during direct laryngoscopy and endotracheal intubation. Methods: This study was conducted between January and June 2018 in the Department of Anesthesiology, Teerthankar Mahaveer Medical College, Moradabad, India. A total of 90 elective surgical patients of American Society of Anesthesiologists physical status grades I or II were divided into three groups, comprising two treatment groups and one control group. Patients in the treatment groups received either one puff (1.5 mg/kg) of lignocaine 10% spray or one puff (400 μg) of NTG spray in the oropharynx one minute prior to the induction of anaesthesia. Haemodynamic variables and mean rate pressure product at baseline and one, two, three, four and five minutes post-induction were compared. Results: There was a significant reduction in mean heart rate at 3–5 minutes in both treatment groups compared to the control group (P <0.050), as well as lower increases in mean arterial pressure at 1–3 minutes (P <0.050). However, at 2–4 minutes, there was a significantly greater decrease in mean systolic blood pressure in the NTG group compared to both the lignocaine and control groups (P <0.050). Moreover, a greater decrease in mean rate pressure product response at 1–5 minutes was observed in the NTG group compared to the lignocaine and control groups (P = 0.001). Conclusion: The NTG spray was more effective than lignocaine in attenuating blood pressure increases and rate pressure product during elective laryngoscopy and intubation.Keywords: Endotracheal Anesthesia; Intubation; Laryngoscopy; Lignocaine; Nitroglycerin; Comparative Effectiveness Research; India

SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation

This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations. We accomplish this goal by a simple yet effective self-supervised approach coupled with the U-Net based discriminator. The proposed method extends the ability of the standard discriminators to learn not only the global data representations via classification (real/fake) but also learn semantic and structural information through pseudo labels created using the self-supervised task. The proposed method empowers the generator to create meaningful masks by forcing it to learn informative per-pixel as well as global image feedback from the discriminator. Our experiments demonstrate that our proposed method significantly outperforms the state-of-the-art methods on the standard benchmark datasets

DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)

Influence Maximization is the task of selecting optimal nodes maximising the influence spread in social networks. This study proposes a Discretized Quantum-based Salp Swarm Algorithm (DQSSA) for optimizing influence diffusion in social networks. By discretizing meta-heuristic algorithms and infusing them with quantum-inspired enhancements, we address issues like premature convergence and low efficacy. The proposed method, guided by quantum principles, offers a promising solution for Influence Maximisation. Experiments on four real-world datasets reveal DQSSA's superior performance as compared to established cutting-edge algorithms.Comment: AAAI Conference on Artificial Intelligence 202

Factors Influencing Artificial Intelligence Conversational Agents Usage in the E-commerce Field: A Systematic Literature Review

Artificial intelligence conversational agents have become an important strategy for business, both as an online shopping application and as a customer support solution, where they provide interactive communication for online customers. To ensure the effective usage and successful implementation of the conversational agents, the factors influencing customers\u27 attitudes and acceptance towards conversational agents need to be explored. This paper presents a systematic literature review of conversational agents in the field of e-commerce to identify the variables that influence conversational agents\u27 usage and to present the state-of-the-art in this research area. Twenty-four relevant papers are reviewed, and many significant factors are identified that positively influence customers\u27 acceptance, satisfaction, and trust towards conversational agents’ technology

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