Towards Developing Uniform Lexicon Based Sorting Algorithm for Three Prominent Indo-Aryan Languages

Three different Indic/Indo-Aryan languages - Bengali, Hindi and Nepali have been explored here in character level to find out similarities and dissimilarities. Having shared the same root, the Sanskrit, Indic languages bear common characteristics. That is why computer and language scientists can take the opportunity to develop common Natural Language Processing (NLP) techniques or algorithms. Bearing the concept in mind, we compare and analyze these three languages character by character. As an application of the hypothesis, we also developed a uniform sorting algorithm in two steps, first for the Bengali and Nepali languages only and then extended it for Hindi in the second step. Our thorough investigation with more than 30,000 words from each language suggests that, the algorithm maintains total accuracy as set by the local language authorities of the respective languages and good efficiency.

The historical relics in Chongqing Natural History Museum: An annotated checklist of original materials for 37 names of Chinese seed plants

A catalogue of type specimens deposited at the herbarium of Chongqing Natural History Museum (CQNM) is carried out. A total of 62 specimens belonging to 56 gatherings concerning 37 valid published names in 23 families of Chinese seed plants are documented as original materials. They include seven isotypes, 21 syntypes, of which 16 of them are isolectotypes and 34 paratypes. A checklist of the 37 names is presented with annotations on the typification, authorship citation, type localities and other taxonomic issues. Eight names were lectotypified, and one name’s second-step lectotype is proposed. Additionally, Distylium lanceolatum Chun, which is invalid pending for further study, and which has long been treated as a synonym of D. dunnianum H.Lév., is listed after the 37 names.

Substitution of Synthetic Fibers by Bio-Based Fibers in a Structural Mortar

The use of bio-based material is now widespread in insulation concrete, for example hemp concrete. The bio-based materials in concrete provide many advantages: lightness, sound and thermal insulation, hydrothermal regulation while contributing to a reduction in the environmental impact due to the carbon capture during the plant growth. The development of materials incorporating plant is therefore an important objective for the construction. The next step will be to introduce bio-based materials in structural mortars and concretes. The project FIBRABETON proposes to substitute synthetic or metallic fibers by natural fibers in screed and slab. After a selection of biomass on the resources availability, separation and fractionation are the key step in processing to obtain technical natural fibers. Bulk fiber shaping and packaging methods for easy handling and transportation are tested. Then, functionalization of technical natural fibers by physical & chemical treatments to improve the durability with cement paste is carried out. The second step concerns the introduction of treated or not treated fibers in mortar and concrete formulations. The variation of the nature of the biomass, fibers shape and dosage in concrete are studied. The workability, the compressive strength and withdrawal resistance are measured in order to obtain the best formulation parameters. The evolution of properties over time is also evaluated. The project FIBRABETON is carried out with ESTP, FRD and Vicat and is subsidized by ADEME, Grand Est region and FEDER.

Pilot Study to Reduce Added Salt on a University Canteen through the Use of an Innovative Dosage Equipment

Background: This study aims to demonstrate the practical application of an innovative easy-to-use equipment to dosage cooking salt, and evaluate the effectiveness in reducing 30% of the added salt in meals and the impact on consumer’s satisfaction and food waste. Methods: Two canteens from one public university where randomized in one control arm and one intervention arm. The first step was to evaluate the salt added to food through atomic emission spectrophotometry in both canteens, and the second step was to perform gradual reductions of up to 30% of cooking salt in the intervention canteen using the Salt Control-C (SC-C) equipment. Consumer acceptability was assessed through satisfaction questionnaires and food waste was evaluated by weighing. Results: The intervention canteen achieved to a reduction of more than 30% of added salt in soup (−34.3% per 100 g), fish dish (−41.1% per 100 g) and meat dish (−48.0% per 100 g), except for the vegetarian dish (6.1% per 100 g). There was no decrease in consumer satisfaction, with a significant satisfaction increase of 15.7% (p = 0.044) regarding the flavor of the main dish. Also, no significant differences were found in food waste. Conclusions: SC-C seems to be effective in reducing 30% of added salt levels in canteen meals, and may be a good strategy to control and reach adequate levels of added salt in meals served outside-the-home, promoting benefits to the individual’s health.

Neural Network Embedding of Functional Microconnectome.

Our brain works as a vast and complex network system. We need to compress the networks to extract simple principles of network patterns and interpret these paradigms to better comprehend their complexities. This study treats this simplification process using a two-step analysis of topological patterns of functional connectivities that were produced from electrical activities of ~1000 neurons from acute slices of mouse brains [Kajiwara et al. 2021] As the first step, we trained an artificial neural network system called neural network embedding (NNE) and automatically compressed the functional connectivities. As the second step, we widely compared the compressed features with 15 representative network metrics, having clear interpretations, including not only common metrics, such as centralities clusters and modules but also newly developed network metrics. The result demonstrates not only the fact that the newly developed network metrics could complementarily explain the features of what was compressed by the NNE method but was previously relatively hard to explain using common metrics such as hubs, clusters and communities. This NNE method surpasses the limitations of commonly used human-made metrics but also provides the possibility that recognizing our own limitations drives us to extend interpretable targets by developing new network metrics.

Modelling the resilience of start-ups during COVID-19 pandemic

PurposeResilience, the ability of start-ups to deal with anticipated instabilities and probable disruptions, is becoming an important success element during coronavirus disease 2019 (Covid-19). To survive in this pandemic situation, resilience is an important concept for start-ups. The present paper aims to “identify”, “analyse” and “categorize” the resilience factors for start-ups during the Covid-19 pandemic using total interpretive structural modelling (TISM).Design/methodology/approachThe resilience elements of start-ups during Covid-19 were identified and shortlisted during the first phase, which included literature analysis and extensive interaction with experts. TISM was used in the second phase to investigate or to determine how the factors interplayed between the resilience factors of start-ups during Covid-19. The Matrice d'impacts Croises Multiplication Appliquee a un Classment (MICMAC) method is used to rank and categorize the factors. Closed-ended questionnaire with the scheduled interview was conducted to collect the data.FindingsThe first part of the study found ten resilience elements in total. The TISM digraph was constructed in the second step to show why one resilience component led to another. The MICMAC analysis divided these factors into four groups: autonomous, linkage, dependent and independent. These groups represented resilience variables based on their driving and dependent power, which assist executives and managers in proactively addressing them while using the TISM digraph as a guide.Research limitations/implicationsDuring the Covid-19 epidemic, this study focused primarily on resilience characteristics for Indian start-ups.Practical implicationsThis study will help key stakeholders and scholars to better understand the elements that contribute to start-up's resilience.Originality/valueThe TISM method for start-up's resilience is suggested in this paper, which is a novel attempt in the field of resilience in this industry.

Survey on Technique and User Profiling in Unsupervised Machine Learning Method

In order to generate precise behavioural patterns or user segmentation, organisations often struggle with pulling information from data and choosing suitable Machine Learning (ML) techniques. Furthermore, many marketing teams are unfamiliar with data-driven classification methods. The goal of this research is to provide a framework that outlines the Unsupervised Machine Learning (UML) methods for User-Profiling (UP) based on essential data attributes. A thorough literature study was undertaken on the most popular UML techniques and their dataset attributes needs. For UP, a structure is developed that outlines several UML techniques. In terms of data size and dimensions, it offers two-stage clustering algorithms for category, quantitative, and mixed types of datasets. The clusters are determined in the first step using a multilevel or model-based classification method. Cluster refining is done in the second step using a non-hierarchical clustering technique. Academics and professionals may use the framework to figure out which UML techniques are best for creating strong profiles or data-driven user segmentation.

Hydrolysis of S. platensis Using Sulfuric Acid for Ethanol Production

S. platensis is a microalga that contains carbohydrate composition of 30.21% which makes it potential to be used as raw material for ethanol production. Hydrolysis of S. platensis is the first step for converting its carbohydrates into monosaccharides. The second step is fermentation of monosaccharides into ethanol. This research aims to study the effect of temperature and microalgae concentration on the hydrolysis of S. platensis using sulfuric acid as catalyst. This research was conducted using 300 mL sulfuric acid of 2 mol/L, hydrolysis temperatures of 70, 80 and 90 °C, and microalgae concentrations of 20, 26.7, and 33.3 g/L. The effect of temperature is significant in the hydrolysis of S. platensis using sulfuric acid. At microalgae concentration of 20 g/L and hydrolysis time of 35 minutes, the higher the temperatures (70, 80, and 90 °C), the more the glucose yields would be (8.9, 13.5, and 22.9%). This temperature effect got stronger when the hydrolysis was running for 15 minutes. Every time the hydrolysis temperature increased by 10 °C, the glucose yield increased by 13.0% at microalgae concentration of 33.3 g/L. At temperature of 90 °C and time of 35 minutes, the higher the microalgae concentrations (20, 26.7, and 33.3 g/L), the higher the glucose yields would be (25.5, 27.7, and 28.2%). The highest glucose concentration obtained was 2.82 g/L at microalgae concentration of 33.3 g/L, temperature of 90 °C, and time of 35 minutes.

Empathizing and Sympathizing With Robots: Implications for Moral Standing

This paper discusses the ethical nature of empathetic and sympathetic engagement with social robots, ultimately arguing that an entity which is engaged with through empathy or sympathy is engaged with as an “experiencing Other” and is as such due at least “minimal” moral consideration. Additionally, it is argued that extant HRI research often fails to recognize the complexity of empathy and sympathy, such that the two concepts are frequently treated as synonymous. The arguments for these claims occur in two steps. First, it is argued that there are at least three understandings of empathy, such that particular care is needed when researching “empathy” in human-robot interactions. The phenomenological approach to empathy—perhaps the least utilized of the three discussed understandings—is the approach with the most direct implications for moral standing. Furthermore, because “empathy” and “sympathy” are often conflated, a novel account of sympathy which makes clear the difference between the two concepts is presented, and the importance for these distinctions is argued for. In the second step, the phenomenological insights presented before regarding the nature of empathy are applied to the problem of robot moral standing to argue that empathetic and sympathetic engagement with an entity constitute an ethical engagement with it. The paper concludes by offering several potential research questions that result from the phenomenological analysis of empathy in human-robot interactions.

Smart Grid Implementation of the Industrial Sector

In the development of smart grid solutions, the contribution of industrial consumers is prime essential to ensure the energy system transformation. The present article introduces a covenant with the implementation of an economic dispatch (ED) in the electrical framework with the smart grid. The proposed ED strategy is comprised of two steps; the first step includes the swarm optimization technique of energy ED with the net loss of the power system and the second step consists of an ED that considers the cutoff points of system security. The prime goal of the second step is to minimize the net loss and the foundation development of the generator cost function. The test framework is comprised of four generators with one battery storage apparatus that considers the energy demand. The ED will perform for 24 hours. The test results show that the two-step ED technique not only reduces system losses but also the fuel consumption of the system as well. This article gives ideas to the industrial consumers to implement a smart grid in the industrial sector.