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This chapter is about the theories explaining the transition from foraging to farming. It aims to establish which links exist between the traditional theories – based on push/pull models – and the micro-founded approaches developed since the 1980s. More precisely, it asks how the latter may contribute, as the former did, to defining a macro-narrative of the transition to farming.

While they were providing a global narrative of the Neolithic revolution, the push and pull models have been progressively dismissed. Recent research is diverse, but it is all based upon human behaviour or micro-founded. We critically examine three of these approaches which focus either on foraging behaviour, or on the initial domestication of plants and animals, or on the evolution of social institutions related to ownership.

We demonstrate that these recent micro-founded approaches only provide a partial vision of the transition to farming. Despite this limit, they conciliate push and pull explanations in a single framework. Moreover, they confirm a conclusion held by tenants of pull models: the transition to farming is more likely to have occurred in a resource-rich environment such as the one associated with complex hunter-gatherers. Some archaeological evidence from the Levant is provided to support our claim.

This research chapter provides a useful overview of the differing approaches to the behavioural, environmental and economic factors that led to the shift to farming from foraging. Its value lies in the way it presents and evaluates differing positions derived from differing scales of analysis and types of evidence.

Commonly studied hunter-gatherer traits, such as grouping and sharing, may require special attention when self-selection introduces bias into typical analyses. We therefore re-examine forager sociality by asking a series of nested questions: (1) To what extent are foraging groups random samples from the larger population? (2) What social and economic factors might explain the composition of foraging groups? (3) If certain groups of individuals preferentially forage together, do these same groups also preferentially share with each other when resident at their permanent settlement? (4) To what extent can we understand behavior in the foraging context without consideration of other contexts in which individuals live and work, and vice versa? Among the Ache of Paraguay, we show that foraging treks are not representative of the larger population, individuals vary in the kinds of treks in which they participate, and those who tend to share together at the reservation are more likely to forage together on trek.

Parallels between subsistence foraging and scholarly information seeking are described in the context of the World‐Wide Web. It is suggested that the prevailing information retrieval paradigm lacks requisite variety to capture the complex of behaviours and stimuli that drives scholars' quests for new ideas and insights. The authors outline a variety of research questions suggested by extended use of the optimal foraging metaphor in relation to distributed multimedia information resources.

This essay provides evidence that the invention of agriculture was not a dramatic technological advance in the history of humankind and that agriculture was quite consistent with nomadic hunting and gathering. The available clues also suggest that exact origins of agriculture do not seem important. Rather, the crucial question is why certain societies dramatically increased their dependency on agriculture for subsistence two to ten millennia ago. Unfortunately, most of the major theories purporting to explain the neolithic revolution – either the origins or the spread of agriculture – are either untestable or inconsistent with the available evidence. What is at stake for economic historians is to rethink the process of the adoption of agriculture using a multi-causal approach.

Purpose of this paper are Real power loss reduction, voltage stability enhancement and minimization of Voltage deviation.

In HLG approach as per Henry gas law sum of gas dissolved in the liquid is directly proportional to the partial pressure on above the liquid. Gas dissolving in the liquid which based on Henry gas law is main concept to formulate the proposed algorithm. Populations are divided into groups and all the groups possess the similar Henry constant value. Exploration and exploitation has been balanced effectively. Ranking and position of the worst agents is done in order to avoid the local optima. Then in this work Mobula alfredi optimization (MAO) algorithm is projected to solve optimal reactive power problem. Foraging actions of Mobula alfredi has been imitated to design the algorithm. String foraging, twister foraging and backward roll foraging are mathematically formulated to solve the problem. In the entire exploration space the Mobula alfredi has been forced to discover new regions by assigning capricious position. Through this approach, exploration competence of the algorithm has been improved. In all iterations, the position of the Mobula alfredi has been updated and replaced with the most excellent solution found so far. Exploration and exploitation capabilities have been maintained sequentially. Then in this work balanced condition algorithm (BCA) is projected to solve optimal reactive power problem. Proposed BCA approach based on the conception in physics- on the subject of the mass; incoming, exit and producing in the control volume. Preliminary population has been created based on the dimensions and number of particles and it initialized capriciously in the exploration space with minimum and maximum concentration. Production control parameter and Production probability utilized to control the exploration and exploitation.

Proposed Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA are evaluated in IEEE 30 bus system with L-index (Voltage stability) and also tested in standard IEEE 14, 30, 57, 118, 300 bus test systems without L- index. Real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained.

For the first time Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA is projected to solve the power loss reduction problem.

To examine how reading in electronic formats differs from traditional reading of print.

Concepts about digital print are discussed alongside research studies in fields related to multisensory technologies and electronic means of communication. A model of online reading is proposed integrating aspects of information foraging theory. Pedagogical applications are needed to integrate e-reading theory within classrooms.

With the varied text structures, directionality concerns, and interactive text features, our attention must turn to the theoretical foundations that underpin digital literacy learning today. Online foraging schemes can explain how information is sought and retrieved when reading new information from digital mediums.

Teachers must address the current, digital literacy needs of their students, thus preparing them for challenges in the 21st century. Varying text structures within digital formats as well as providing as-needed facilitation are the scaffolds that students need today. Using technologies such as digital games, tools, and contexts advances the mission of resource-based teaching and learning.

Burden transport is a ubiquitous primate behavior. Modern humans, however, take this primate tendency and extend it to a behavioral repertoire that influences many of our daily activities and almost certainly helped shape our physical and behavioral form. I examine the transportation of food in the context of central place foraging, from the perspective of maximizing energy acquisition. A detailed model of the energetic cost of burden transport is presented and its sensitivity to the variables of body mass, burden mass, terrain, incline and velocity discussed.

Drawing on information foraging theory and the SERVQUAL model, this study built a research model to investigate the roles of middle-aged and elderly short-video creators' online attributes in attracting short-video viewers to be their followers.

Taking Douyin (a famous short-video platform in China) as an example, this study used a sequential triangulation mixed-methods approach (quantitative → qualitative) to examine the proposed model by investigating both creators and viewers.

Viewers who clicked the “like” button for the middle-aged and elderly creators' videos are more likely to follow the creators. Viewers will believe that middle-aged and elderly creators who received more likes are more popular. Thus, middle-aged and elderly creators with more likes usually have more followers. Viewers usually believe that middle-aged and elderly creators who more frequently publish professional and high-quality videos have invested more effort and who have official verification also have a high level of authority and are recognized by the platform. Thus, middle-aged and elderly creators with more professional videos and verification usually have more followers. Moreover, verification, the number of videos and the professionalism of videos can enhance the transformation of viewers who liked middle-aged and elderly creators' videos into their followers, and thus strengthen the positive relationship between the number of likes and the number of followers; however, the number of bio words will have an opposite effect.

These findings have implications for platform managers, middle-aged and elderly creators and the brands aiming to develop a “silver economy” by attracting more followers.

This study researches short-video platforms by using a mixed-methods approach to develop an understanding of viewers' decision-making when following middle-aged and elderly creators based on information foraging theory and the SERVQUAL model from the perspectives of both short-video creators and viewers.

The purpose of this paper is to present the application of an adaptive bacterial foraging (BF) algorithm for the design optimization of an energy efficient induction motor.

The induction motor design problem is formulated as a mixed integer nonlinear optimization problem. A set of nine independent variables is selected, and to make the machine feasible and practically acceptable, six constraints are imposed on the design. Two different objective functions are considered, namely, the annual active material cost, and the sum of the annual active material cost, annual cost of the active power loss of the motor and annual energy cost required to supply such power loss. A new adaptive BF algorithm is used for solving the optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling.

The adaptive BF algorithm is validated for two sample motors and benchmarked with the genetic algorithm, particle swarm optimization, simple BF algorithm, and conventional design methods. The results show that the proposed algorithm outperforms the other methods in both the solution quality and convergence rate. The annual cost of the induction motor is remarkably reduced when designed on the basis of minimizing its annual total cost, instead of minimizing its material cost only.

To the best of the knowledge, none of the existing work has applied the BF algorithms for electrical machine design problems. Therefore, the solution to this problem constitutes the main contribution of the paper. According to the huge number of induction motors operating all over the world, the BF techniques used in their design, on minimum annual cost basis, will lead to a tremendous saving in global energy consumption.