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Lavender is a highly valuable medicinal and aromatic perennial shrub lacking superior and stable varieties for varied environments in the western Himalayas. In the present experiment, estimates of genotypic effects and their interaction with the environment under various conditions of Himachal Pradesh were investigated to identify superior and stable genotypes. For that, seven selections with a check were evaluated at four different locations in randomized block design with three replications during 2020 and 2021. The pooled analysis of variance showed that genotypic and environmental main effects were highly significant for all the traits under study while, G×E interaction was significant (p=0.05) for plant height, spike length and spike yield. The highest mean performance for all the traits revealed that location-4 has favourable conditions for lavender cultivation, and LOH15141 followed by LOH15040 were the best performers over all the locations. These high-performing genotypes were clustered together with the check in a major cluster. The stability parameters of the Eberhart and Russell model showed that LOH15141 is stable and superior for both spike yield and essential oil content, further confirmed by GGE biplot analysis. GGE biplot analysis revealed that all the tested locations formed a single mega-environment. The strong positive yield contribution described through Pearson's correlation coefficients and genotypic path diagram states that plant height, number of spikes and spike length were significant contributors to the spike yield and could be used as selection criteria to improve spike yield due to their high heritability and genetic advance. [ABSTRACT FROM AUTHOR]

Emergencies and disasters place an exceptional demand on the managerial skills of the humanitarian aid community. Most of the developing countries lack in such kind of resilience and effective humanitarian supply chain. Therefore, the purpose of this paper is to identify and analyse the factors to develop the resilience in the humanitarian supply chain. Based on the literature review, total 12 factors related to resilient humanitarian supply chain have been identified. Some of these factors are process oriented and some are result oriented. Interpretive structural modelling with Fuzzy MICMAC analysis is used to develop structural relationships among these factors and to find the driving and the dependence power of these factors. Government support, strategy and capacity planning; and continuous assessment of project progress have emerged as the major drivers for the development of resilient humanitarian supply chain. By managing these driving factors, humanitarian aid programme can be made resilient and agile. The findings will be useful for the humanitarian aid agencies to develop effective and sustainable aid relief programme. [ABSTRACT FROM AUTHOR]

Knowledge is an intangible asset that can increase employees' and organisation's effectiveness. Limited research has been done to upgrade existing knowledge management systems in the Industry 4.0 environment. Hence, this study identifies thirteen critical factors for developing a knowledge management system in Industry 4.0 environment. Interpretive Structural Modelling (ISM) is utilised to develop the structural relationships among these factors. Finally, fuzzy MICAMC is used to categorise the factors based on driving-dependence value. The results reveal the direct and indirect effects of these factors in developing a KM system in the digital age. Findings suggest that top management support, development of knowledge management strategy, knowledge friendly culture, creation and maintenance of digital infrastructure, and employees training are the major drivers for developing a KM system in Industry 4.0 environment. Organizations can use the proposed framework to prioritise their actions to develop a KM system in the Industry 4.0 environment. [ABSTRACT FROM AUTHOR]

The relationship between ideology and learning remains insufficiently theorized and sparsely investigated in the learning sciences. Drawing on Stuart Hall’s theorization of ideology, Judith Butler’s notion of the (un)grievability of lives, and Sara Ahmed’s construct of stickiness, we illustrate how insights from critical social theory are indispensable to understanding processes of learning and how perspectives from the learning sciences can enrich critical social theory. Through the analysis of a classroom discussion on the use of militarized drones in an undergraduate engineering ethics course, we show how ideological convergence among participants constructed locally significant categories of “civilian,” “terrorist,” and (un)grievability, which narrowed the possible trajectories for students’ disciplinary learning in engineering and engineering ethics. Our analysis also shows that fleeting moments of ideological expansion offered opportunities for new learning; however, most of these instances of possibility were not sustained through the classroom discussion. We explicate how ideological convergences and expansions, as interactional achievements, profoundly matter for disciplinary learning and students’ identities. In conclusion, we explore the implications of our findings for broader contexts of learning and for the field of the learning sciences. [ABSTRACT FROM AUTHOR]

Energy is an abstract science concept, so the ways that we think and talk about energy rely heavily on ontological metaphors: metaphors for what kind of thing energy is. Two commonly used ontological metaphors for energy are energy as a substance and energy as a vertical location. Our previous work has demonstrated that students and experts can productively use both the substance and location ontologies for energy. In this paper, we use Fauconnier and Turner's conceptual blending framework to demonstrate that experts and novices can successfully blend the substance and location ontologies into a coherent mental model in order to reason about energy. Our data come from classroom recordings of a physics professor teaching a physics course for the life sciences, and from an interview with an undergraduate student in that course. We analyze these data using predicate analysis and gesture analysis, looking at verbal utterances, gestures, and the interaction between them. This analysis yields evidence that the speakers are blending the substance and location ontologies into a single blended mental space. [ABSTRACT FROM PUBLISHER]

Researchers have argued against deficit-based explanations of students’ difficulties with mathematical sense-making, pointing instead to factors such as epistemology. Students’ beliefs about knowledge and learning can hinder the activation and integration of productive knowledge they have. Such explanations, however, risk falling into a ‘deficit trap’—substituting a concepts/skills deficit with an epistemological one. Our interview-based case study of a freshman engineering major, ‘Jim,’ explains his difficulty solving a physics problem (on hydrostatic pressure) in terms of his epistemology, but avoids a deficit trap by modeling the dynamics of his epistemological stabilities and shifts in terms of fine-grained cognitive elements that include the seeds of epistemological expertise. Specifically, during a problem-solving episode in the interview, Jim reaches and sticks with an incorrect answer that violates common sense. We show that Jim has all the mathematical skills and physics knowledge he would need to resolve the contradiction. We argue that his difficulty doing so stems in part from his epistemological views that (i) physics equations are much more trustworthy than everyday reasoning, and (ii) physics equations do not express meaning that tractably connects to common sense. For these reasons, he does not view reconciling between common sense and formalism as either necessary or plausible to accomplish. But Jim’s in-the-moment shift to a more sophisticated epistemological stance highlights the seeds of epistemological expertise that were present all along: he does see common sense as connected to formalism (though not always tractably so), and in some circumstances, this connection is both salient and valued. [ABSTRACT FROM PUBLISHER]

The authors respond to a comment by professor J. D. Slotta in response to their critique on static and dynamic intuitive ontologies. The authors believe that Slotta has misinterpreted aspects of their position. The authors offer an explanation on their use of static ontologies and how their dynamic view could account for evidence of stabilities.

In a series of well-known papers, Chi and Slotta (M. T. H. Chi, 1992, 2005; M. T. H. Chi & J. D. Slotta, 1993; M. T. H. Chi, J. D. Slotta, & N. de Leeuw, 1994; J. Slotta & M. T. H. Chi, 2006; J. D. Slotta, M. T. H. Chi, & E. Joram, 1995) have contended that a reason for students' difficulties in learning physics is that students think about concepts as things rather than as processes and that there is a significant barrier between these 2 ontological categories. We contest this view, arguing that expert and novice reasoning often and productively traverses ontological categories. We cite examples from everyday, classroom, and professional contexts to illustrate this. We agree with Chi and Slotta that instruction should attend to learners' ontologies, but we find that these ontologies are better understood as dynamic and context dependent rather than as static constraints. To promote 1 ontological description in physics instruction, as suggested by Slotta and Chi, could undermine novices' access to productive cognitive resources that they bring to their studies and inhibit their transition to the dynamic ontological flexibility required of experts. [ABSTRACT FROM AUTHOR]

Energy crisis is affecting the world badly. While the production in developed countries stabilizes, in the developing world it continues to expand. This results in higher energy use, thereby releasing higher CO2. Thus, a pilot experiment was conducted to check and subsequently take corrective measures to reduce the energy consumption of manufacturing industry. Here, the emphasis is laid particularly on the turning operation for the cutting parameters, and effort has been made to optimize them, using Design Expert, with regard to the energy consumed. Also the optimized values, from the, for the different parameters under study have been checked and compared by those being generally used. For experimental studies, the machining was first carried on mild steel and then after aluminum and brass were also considered for study. All the values show an appreciable reduction in the energy consumption, thus reducing the carbon emission, for all the materials. [ABSTRACT FROM AUTHOR]