Scientific evidence gathered over the last couple of decades suggests that climatic conditions are changing rapidly. This trend is likely to continue, and even accelerate in future (IPCC 2007; Moss et al., 2010). These anticipated changes in climate baseline, variability, and extremes will have far-reaching consequences on agricultural production, posing additional challenges to meeting the food security for a growing world population (Lobell et al., 2008; Roudier et al., 2011). It is therefore pertinent to work out the impact of climate change on agricultural production, and develop, both mitigation and adaptation strategies. Although various methods have been proposed for the purpose but climate analogues offer a simple alternative. Reason being that relying on “analogue locations” that have today the climatic characteristics that are expected tomorrow in a target production zone can help predict the effect of changing climate on crops (Haussmann et al., 2012). Moreover, such stud...

Potato tuber yield were simulated at Jorhat, Assam under various Representative Concentration Pathways (RCPs) scenarios for 2020, 2050 and 2080 using DSSAT SUBSTOR-Potato model. The model was calibrated and validated for three potato cultivars, viz., Kufri Jyoti, Kufri Pokhraj and Kufri Himalini with the experimental data collected during 2014-15 and 2015-16. Results revealed that if planting is delayed beyond November, all these cultivars are likely to record drastic reduction in tuber yield. Cultivar Kufri Himalini may incur tuber yield loss of 64 per cent in 2020 to 75 per cent in 2080, followed by Kufri Jyoti (57.6% in 2020 to 71.5% in 2080) and Kufri Pokhraj (45.2% in 2020 to 56.2% in 2080). Among the cultivars, Kufri Pokhraj may remain a viable cultivar up to 2050, but Kufri Himalini may lose its sustainability by 2020 itself. Hence, adjustment of planting time and development of improved adaptive potato cultivarsonly will ascertai n future potato production in this region.

The study was carried out to assess the impact of climate change on potato productivity to develop adaptation strategies in Punjab, using crop growth simulation models for future climate scenarios (2030, 2050 and 2080) under representative concentration pathways (RCPs) 4.5 and 6.0. Three potato cultivars belonging to distinct maturity groups, late (Kufri Badshah), medium (Kufri Jyoti) and early (Kufri Pukhraj), were used. Simulation results showed that under RCP 4.5, increase in CO2 concentration is expected to bring an increase in productivity of Kufri Badshah, Kufri Jyoti and Kufri Pukhraj by 6.7, 7.2 and 7.1% in 2030; 10.8, 11.6 and 11.4% in 2050; and 14.0, 15.0 and 14.8% in 2080. However, the corresponding increase in temperature is likely to decline the mean productivity by 2.6, 3.8 and 3.8% in 2030; 6.5, 8.7 and 9.3% in 2050; and 14.4, 17.6 and 18.4% in 2080, for Kufri Badshah, Kufri Jyoti and Kufri Pukhraj. But, when combined influence of temperature and CO2 was considered, the productivity of potato will not be affected in 2030 and 2050 over the baseline scenario but is expected to decline in 2080 (Kufri Badshah − 1.9%, Kufri Jyoti − 4.1% and Kufri Pukhraj − 5.2%). Similarly, for RCP 6.0, increased CO2 concentration is expected to increase the mean productivity by 6.5% in 2030, 10.5% in 2050 and 19.4% in 2080. However, yield increase due to CO2 is negated by increased temperature with respective values of 2.2, 4.4 and 14.2%. However, under combined effect for RCP 6.0, productivity of potato cultivars is not likely to be affected over the baseline scenarios for 2030, 2050 and 2080. Results further revealed that by changing the dates of planting or selection of suitable cultivars, yield can increase in 2030 by 7.4% in Kufri Badshah and 7.8 and 1.5% in Kufri Pukhraj in 2050 and 2080, under RCP 4.5. Similarly, adaptation may increase mean yield up to 9.1% for Kufri Pukhraj in 2030, 9.8% for Kufri Badshah in 2050 and 8.2% for Kufri Badshah and Kufri Jyoti in 2080 under RCP 6.0. Further, with proper irrigation and nitrogen management practices, yield can be increased.

The impact of climate change on potato productivity in Madhya Pradesh was analysed using WOFOST crop growth simulation model. The potato cultivars of three maturity groups viz., Kufri Badshah (late), Kufri Jyoti (medium) and Kufri Pukhraj (short) were selected. The study was carried out for 38 representative locations of the state. The study was done for baseline scenario (2000) and for futureclimate scenarios for the years 2020 and 2055 using A1FI scenario of temperature (SRES A1FI pathway) and atmospheric CO2 (based on the Bern-CC model for A1FI scenario). Simulation revealed that although the increase in temperature is likely to reduce the yield by 10 to 11.4 per cent in 2020 and 22.9 to 27 per cent in 2055, a corresponding increase in CO2 may increase the yields by 4.6 to 4.9 per cent in 2020 and 19.6 to 21 per cent in 2055. However, the combined effect of CO2 and temperature will lead to a decline in productivity of Kufri Pukhraj by 7.6 per cent, followed by 7.3 per cent in Kuf...

One significant impact of climate change is the effect upon agriculture. As many evidences indicated that some remarkable changes could happen in climate scenario, the present work is mainly directed to discuss sensitivity of climate change upon the potato production in Egypt. The selection of potato product is mainly dependent upon that potato represent strategic crop cultivated in Egypt. The SUBSTOR potato model was employed to simulate physiological processes and yield of potato production. SUBSTOR model is a mechanistic, process-oriented model for tuber yield includes crop development. The present work introduces two possible cases of climate changes for the sake of climate crop production relationship. The actual measurements for potato production characteristics were used in the comparison with present and predicted. The climate change data is used from two general circulation models (CSIRO and HadCM3) for A1 greenhouse gases Scenario during 2050. The results of the work indicated that the potato yield decrease from 11 to 13% under climate change and the climate change data output from HadCM3 model gave the highest value of potato yield comparing with CSIRO model. And Valor cultivar gave the highest potato yield compared to Dezareah cultivar when the irrigation treatment taken place under current and future climate.

In the competitive project business sector, certifications like PMP are key for vendors, serving as a testament to their expertise and commitment to excellence. In procurement, they subtly impact the vendor selection and prove essential in winning business.

Breve relato sobre a família de Karl Marx. As ideias não estão isentas moralmente de suas experiências pessoais.

This Electronic Monograph (E-Monpgraph) is interested to present different models using artificial intelligence (AI) to evaluate different economic issues such as financial and pure economic respectively using Econographicology (Ruiz Estrada, 2017) as the main analytical and theoretical framework to support the construction of all these models. This E-Monograph is divided into twelve chapters. The second chapter evaluates the past, present, and future of economic modeling from both qualitative and quantitive perspectives. We do this through an extensive review of chapters published in the Journal of Economic Modeling (JEM) between 1979 and 2017. The third chapter is interested to evaluate how artificial intelligence (AI) can help in the economic modeling. The chapter fourth is interested to present “The Autonomous Economic Decision Maker Simulator (AEDM-Simulator).” This research introduces the AEDM-Simulator theoretical framework and a few examples of how to use the AEDM-Simulator to solve any economic issue(s). The purpose of chapter fifth is to suggest the uses of an alternative Simulator. It is called “The Economic Cubic Warp Effect Simulator (ECWE-Simulator)”. The main objective of the ECWE-Simulator is to evaluate how strong or weak can be an economy in case of a financial crisis, war, natural disasters, and pandemic an economy under the uses of a large number of exogenous variables and endogenous variables that interacting together in the same graphical space framework. Hence, our final target is to observe HOW any crisis be natural or social can economy tolerate under certain circumstances and environments through the visualization of a cube that keep in constant movement and warp stage all the time. The sixth chapter is interested to evaluate how artificial intelligence (AI) can change the way to do it finance modeling. The seventh chapter introduces a novel theoretical and graphical model designed to scrutinize the interplay between marginal revenue (R’) (Hawkins, 1970) and marginal production cost (C’) (Bulow and Pfleiderer, 1983), and its impact on overall profit maximization (Pmax) performance. Additionally, we put forward the concepts of the Maximum Critical Optimum Inflection Point (MCOI-Point), the firm's border limit, and the zero point as pivotal indicators within this framework. Termed as "The Return to the Zero Point of the Firm", this model offers a comprehensive perspective on firm behaviour. We conduct simulations under three distinct scenarios: (i) Scenario 1: Halting the decline of marginal revenue (R’) while maintaining lower marginal production costs (C’) in the long run to prevent reaching zero (potential bankruptcy). This scenario, labelled as Full Firm Surviving Sustainability, aims to sustain profits, thereby averting final collapse; (ii) The scenario 2: Keeping firm marginal revenue (R’) constant from the MCOI-Point, alongside maintaining consistently low marginal production costs (C’). This approach fosters the steady accumulation of profits in the long run, referred to as Long Constant Profit Sustainability.; (iii) The scenario 3: Generating a substantial surge in marginal revenue -R’- (exponentially), coupled with a thorough minimization of marginal production costs (C’) in the short term. This scenario is aimed at rapid financial growth. All three scenarios commence from the MCOI-Point, necessitating a series of systematic strategies to ensure the success of any firm and its ability to weather market crises. These strategies encompass coordinated efforts across various departments including Human Capital, Research and Development, Sales and Marketing, Finance, and Production. Through this synchronized approach, firms can achieve sustainable profit maximization and chart a clear path for their business operations. The eight chapter is interested to propose an alternative Multi-Dimensional (MD) graphical computational system to observe or simulate different macroeconomic scenarios simultaneously in real-time or live. It is called “The Macroeconomic Interactive Mega-Surface Model (MIMS-Model)”. Therefore, the construction of this Multi-Dimensional graphical computational system is based on the application of Econographicology (Ruiz, 2017) and Database analysis. In chapter ninth shows the rationale behind the Cryptodata Multi-Level Analytical Intelligence System (Cryptodata MCAI-System) lies in the effectiveness of multi-level mega-data analysis frameworks, combined with the utilization of multidimensional graphs as a powerful tool for artificial intelligence learning. This approach enables a comprehensive understanding and resolution of economic, financial, and business challenges. The primary goal in developing the Cryptodata MCAI-System is to provide a new artificial intelligence learning tool capable of efficiently evaluating dynamic and complex economic, financial, and business issues, thereby facilitating a wide range of potential solutions. As such, the Cryptodata MCAI-System seeks to present academics, researchers, and policymakers with an alternative artificial intelligence approach. It introduces a suite of different types of multidimensional artificial intelligence learning tools, including the mega-dynamic disks coordinate space (vertical and horizontal position) learning machine tool, and the mega-disks networks mapping (MDN-Mapping) learning machine tool. The tenth chapter introduces a groundbreaking system, the Auto-Sustainable Artificial Intelligence Generator System (ASAIG-System), which exhibits the capability to autonomously collect, process, and provide feedback, ultimately culminating in full autonomy. This system enables the acquisition of data with unprecedented precision, facilitating rapid and rational decision-making in short timeframes. The ASAIG-System offers a novel theoretical framework for the development of self-sustaining learning machines, poised to eventually supplant human involvement in complex decision-making processes with enhanced long-term precision. Finally, his research chapter introduces the Auto-Sustainable Artificial Intelligence Generator System (ASAIG-System), highlighting its potential to revolutionize decision-making processes through autonomous data collection, processing, and feedback mechanisms. The study underscores the system's auto-sustainability and its implications for a wide range of industries and applications. Additionally, pure technical considerations and human-machine interaction are addressed to ensure responsible deployment of the ASAIG-System. The chapter eleventh introduces a novel evaluation model called the "Economic Research Open Access Repository Performance Index (EROARP-Index)" to assess the performance of these repositories from various perspectives, including form and content. The evaluation takes into account factors such as accessibility (Armstrong, 2015), dissemination, impact, and user engagement. The research aims to offer valuable insights for researchers, policymakers, and institutions in selecting platforms that align with their objectives. Additionally, the chapter emphasizes the importance of technical considerations and data security in the use of open-access repositories. Overall, it appears to be a comprehensive study that provides a thorough evaluation of these repositories, along with tailored recommendations for improvement. The introduction of the EROARP-Index adds a unique framework to the assessment process, ensuring a rigorous and multi-dimensional evaluation. We applied the EROARP-Index to evaluate SSRN, ResearchGate, and Academia, respectively. The chapter twelfth delves into the transformative impact of ChatGPT-4 and Google Scholar on the landscape of socio-economic research and problem-solving. The evolution of search engines, driven by advancements in artificial intelligence (AI), sophisticated algorithms, and robust programming tools, has significantly enhanced precision and expanded databases. This paradigm shift opens up unprecedented opportunities for analysing and addressing dynamic and intricate socio-economic challenges. The chapter twelfth introduces a novel evaluation model, termed the "Economic Solutions Searcher Evaluation Model (ESSE-Model)," designed to gauge the effectiveness of ChatGPT-4 and Google Scholar. An experimental study is also conducted to compare their performance in finding solutions to a specific socio-economic problem, exemplified by unemployment control.