Comparison of growth and conversion efficiency of the freshwater prawn Macrobrachium malcolmsonii (H. Milne Edwards) juveniles fed with formulated and commercial feeds

A nutritional study was carried out to know the feasibility of formulated and commercial feeds on the growth of juveniles of the freshwater prawn Macrobrachium malcolmsonii. Best relative growth rate was observed for feed 1 followed by feeds 2 and 3. Animals fed with feed 1 showed higher production than the other feeds. Higher assimilation efficiency was noticed in the animals provided with feeds 5 and 4. Higher gross and net growth efficiencies were observed in the animals offered feed 1. Among the commercial feeds, feed 3 may considered to be suitable alternative to feed 1

Investigation of inversion, accumulation and junctionless mode bulk Germanium FinFETs

The characteristic performance of n-type and p-type inversion (IM) mode, accumulation (AC) mode and junctionless (JL) mode, bulk Germanium FinFET device with 3-nm gate length (LG) are demonstrated by using 3-D quantum transport device simulation. The simulated bulk Ge FinFET device exhibits favorable short channel characteristics, including drain-induced barrier lowering (DIBL<10mV/V), sub threshold slope (SS∼64mV/dec.). Electron density distributions in ON-state and OFF-state also show that the simulated devices have large ION/IOFF ratios. Homogenous source/drain doping is maintained and only the channel doping is varied among different operating modes. Also, a constant threshold voltage |VTH|∼0.31V is maintained. Moreover, the calculated quantum capacitance (CQ) values of the Ge nanowire emphasizes the importance of quantum confinement effects (QCE) on the performance of the ultra-scaled devices

Mobile Commerce Application Development and Implementation

The relationship with technology has totally changed because of mobile applications, which give solid and versatile apparatuses to improve communication, diversion, and efficiency. In this study report, the assessment takes a gander at the best practices from top to base for creating and carrying out mobile apps. This study plans to reveal insight into the generally acknowledged techniques presently being used and investigate the difficulties related with creating mobile applications, which vary from creating customary venture applications. Accordingly, an internet-based overview from the mobile imaginative workspace was finished. The survey questions enveloped the whole lifecycle of fostering a mobile application, from prerequisites for social events to posting a completed item for public deal. Through the investigation of genuine issues experienced and the investigation of best practices that can be really applied to overview, assess, and support the appropriateness of the association, this study adds to how we might interpret the mobile application development process. These outcomes could likewise be seen as an anticipated field of examination delineating the broadness of the field. This' article will probably give specialists and accomplices associated with mobile app development with helpful guidance by consolidating pieces of data from insightful examination with industry best practices. Eventually, our examination progresses the comprehension of the subject and gives shrewd data that will direct further exploration and headways in the plan and utilization of mobile applications

A Comprehensive Insight into Cloud Robotics, Digital Transformation, Automation, and Technological Innovation

Cloud robotics is the integration of cloud computing technology and robotics. Digital transformation is defined as the process of implementing technology in various fields of industry and automation is defined as the process of automating a task using technology. Technological innovation defines the improvements in technology that can be used in industries and other aspects of life. From the study, it can be seen that all these concepts are associated closely and their implementation will help in the development of various industries and fields. The aim of the study is to provide a comprehensive overview of cloud robotics, digital transformation automation and technological innovation which can serve as a repository to researchers. For this study, the systematic literature review methodology was adopted to gather the necessary studies from the years 2015 to 2021. Using this study, researchers can gather various details without having to search the vast collection of studies, books, journals etc. The study also provides additional information like advantages, challenges, applications, etc associated with the topics

EVALUATION OF LITHIUM BASED DEICING CHEMICALS FOR MITIGATING ASR IN CONCRETE PAVEMENT

Deicing and anti-icing chemicals such as alkali-acetate and alkali-formate based formulations are increasingly being used on airfield pavements. Among these new deicers, potassium acetate-based formulations are widely used due to their environmentally friendly nature and effectiveness in melting and undercutting ice at low temperatures. Recent research on premature deterioration of airfield pavements due to alkali-silica reaction (ASR) has indicated that alkali-acetate and alkali-formate deicers such as potassium acetate and sodium formate may have been responsible for the observed distress. In an effort to develop a deicing chemical that is benign to concrete from an ASR standpoint, a new deicing formulation based on lithium compounds is being explored. This research study presents the findings from a laboratory-based investigation on developing a lithium-acetate based deicing chemical to specifically address ASR concern in concrete. In these studies, mortar bars and concrete prism specimens were prepared with aggregates of known reactivity and exposed to solutions of pure lithium acetate and pure potassium acetate at different concentrations. In addition, parallel tests were conducted on mortar bars and concrete prisms in which test specimens were exposed to solution blends of lithium acetate and potassium acetate at different Li/K molar ratios (Li/K molar ratios=0.2, 0.4, 0.6, 0.8). Also, in order to evaluate the effect of these deicing chemicals on scaling resistance of concrete, modified ASTM C 672 tests were conducted. In order to understand the extent of externally applied damage in concrete, the K+ ion and Li+ ion profiles were established using Inductively Coupled Plasma (ICP) and X-Ray Fluorescence spectrometer (XRF) techniques. Also, tests were conducted to determine the effectiveness of lithium nitrate, when applied as a pre-treatment before exposing to potassium acetate to find its effect in mitigating ASR. Results from this study showed that specimens containing reactive aggregates and soaked in blends of lithium acetate and potassium acetate showed little or no expansion due to alkali-silica reactivity. It is also observed that potassium acetate deicer at concentration levels of 3 and 6.4 plays a significant role in the expansion of mortar bars and concrete prisms. No scaling was observed in concrete slabs made with both reactive and non-reactive aggregate exposed to 3 and 6.4 molar KAc solutions. From the penetration test, the gradient from top to bottom showed the influence of K in concrete samples. Mortar bars which were pre-treated with LiNO3 showed significantly lesser expansion compared to bars which were not treated, upon exposure to potassium acetate deicers. In general, specimens made with high-alkali cement expanded more, compared to specimen made with low-alkali cement. It is recommended that lithium blended deicers with at least Li/K ratio of 0.2 be used for mitigating ASR. Also, low-alkali cements should be preferred when exposure to deicers is anticipated

Leveraging Machine Learning for Predictive Analytics in Ecommerce

Predictive analytics is becoming more and more necessary for organizations to use in the quickly changing e-commerce industry in order to predict customer behaviour, optimize marketing campaigns, and improve overall operational efficiency. The goal of this research study is to strengthen predictive analytics in the e-commerce industry by utilizing machine learning approaches.AI is essential for the business analyst's ability to make predictions. AI is a rapidly developing field that is employed in all fields, particularly in data analysis and prediction. In this study, machine learning—a subset of AI—is used for this purpose. The paper's goal is to determine the potential for growth and application of e-commerce in the future. In order to provide a clear explanation, we have used secondary data on the market value of e-commerce as a basis to support the income generated by e-commerce, and online consumers are taken to understand the total contribution of the e-commerce sector in India, then attempted to use Python to determine the forecast for the following years, 2024 to 2026. The current study aims to improve the accuracy of market value projection by using two more factors: the percentage of Indian online shoppers and e-commerce revenue. This paper attempts to offer practical suggestions and best practices for e-commerce practitioners and decision-makers wishing to leverage machine learning for predictive analytics by combining insights from both academic research and industry operations. In the end, the study advances our understanding of e-commerce analytics and establishes the groundwork for more in-depth investigation and creative thinking in this area

Conversational Commerce Blueprint: Strategy, Architecture, and Implementation for the Modern Digital Marketplace

This research & Implementation scrutinizes the strategy and application of conversational commerce along with special emphasis on variables affecting consumer happiness and transactional success. A mixed-methods approach in the study was carried out to find out the effectiveness metrics of user experience, effectiveness of AI tools, various techniques for personalization, and level of interaction with e-commerce websites. Key findings show that, respectively with 85% and 78% of respondents ranking these features as important, simplicity of use and rapid response times are crucial. Hybrid chatbots, combining AI with human interaction, produce the highest rated customer satisfaction ratings. Moreover, product personalization increases user interaction by leaps and bounds, and the completion rates for transactions are higher with full integration of conversational tools with the current systems of e-commerce. This result does make the case for an overall approach that puts a premium on accessible design, effective AI deployment, and tailored experience to succeed in conversational commerce

Influence of affective response at the end of exercise on future exercise choice in low-active, overweight participants

PURPOSE: Approximately 35-50% of individuals who start an exercise program have been reported to drop-out within the first few months (e.g., Dishman & Buckworth, 1997). Suggestions have been made that affective experience of exercise is linked to adherence, but only a limited amount of research has been conducted in this area. Also, none of these studies measured the influence of affective experiences during exercise on future choice. Identifying exercise that results in a positive affective experience may increase adherence. A theory that has found support in other fields is the Peak-End hypothesis (Kahneman et al., 1993). It suggests that individuals\u27 positive affective experience and subsequent decisions about a behavior are derived from the peak affective moment and the final moments while engaged in the behavior. An episode with a pleasurable peak at the end will be remembered as positive even if it is longer than another episode with no pleasurable peak at the end (a concept known as Duration Neglect) Therefore, the purpose of this study was to determine whether adding a positive end to an unpleasant exercise bout will influence the choice to repeat an exercise bout and to test whether exercise duration plays a role in this choice. METHODS: 27 overweight and low-active young adults (14 males, mean age 26 yrs) completed an incremental treadmill exercise test to determine ventilatory threshold (VT). They then completed two counterbalanced exercise sessions: one at 10% above VT for 20 minutes and one at 10% above VT for 20 minutes followed by 2.5 mph, 0% grade for 5 minutes. Given that exercising above VT has been shown to elicit predominantly negative responses and exercising below VT elicits a positive affective response, these workloads were designed to result in a peak negative end affect and a peak positive end affect, respectively. Feeling Scale scores were measured before, during, and after exercise in both the sessions. In a final session, participants were asked to choose to repeat one of the two exercise bouts. RESULTS: Participants were twice as likely to choose to repeat the exercise bout that ended positively over the one that ended negatively, even though it was longer and involved more work overall. CONCLUSION: The results support the Peak-End and Duration neglect hypotheses in an exercise setting. To promote adherence, exercise prescriptions should put emphasis on a pleasurable (i.e. reduced intensity) end to each exercise bout

A Case of Mirizzi Syndrome with Pancreatic Divisum: A rare association

Mirizzi syndrome (MS), a rare complication of gallstones, refers to extrahepatic biliary compression by calculus in the cystic duct or Hartman’s pouch and is usually associated with cystic duct abnormalities. Its association with pancreatic divisum(PD) is infrequent, the most common complication of PD being recurrent pancreatitis. We report a case of 39-year-old female who presented with acute abdominal pain to the department of general surgery, Chennai, Tamil Nadu, India in August 2022. Magnetic resonance cholangiopancreaticography (MRCP) showed calculous cholecystitis with a calculus indenting the cystic duct, causing luminal narrowing of the common hepatic duct (type I), which was associated with type II PD. The association of MS with PD has been rarely described. PD may be one of the factors responsible for bile stasis leading to calculous cholecystitis and its complications. Knowledge of MS and its associations helps in early diagnosis and selection of appropriate treatment management