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Nonlinear Distortion Correlation Aware Power Allocation for Massive MIMO Systems
No full textThis article provides a comprehensive analysis aimed at addressing the impact of power amplifier nonlinearities on massive multiple-input multiple-output (MIMO) communication systems. Specifically, we derive a closed-form expression for the received distortion power, a critical aspect that has not been explored in literature. Our derived expression takes into account the combined influence of spatial diversity and frequency-selectivity on received distortion, with a particular emphasis on the slowly varying parameters, primarily the locations of users and delay spread. In the context of massive MIMO systems, characterized by an exceptionally large number of antennas, our work highlights the crucial role of distortion correlation among antennas. Neglecting distortion correlation can result in significant inaccuracies in system evaluation and algorithmic design. Utilizing the analytical framework we have developed, we formulate a power allocation problem that explicitly exploits the distortion correlation. The proposed solution outperforms methods that neglect the spatial distortion correlation, particularly in terms of spectral efficiency (SE). This superior performance is crucial in optimizing the overall system performance and ensuring desirable power allocation decisions
Microstructural Anisotropy, Mechanical Properties, and Fatigue Crack Growth Behavior of AA2050-T84 Alloy
No full textThis study focuses on characterizing the microstructure and mechanical properties of AA2050-T84 alloy produced in two different thicknesses, 20 and 130 mm. A comparative analysis between the two thicknesses aims to understand how the rolling operation for achieving thin plates influences the alloy's microstructure and overall mechanical performance. Microstructural analyses showed a highly anisotropic grain structure and preferred crystallographic orientation in the 20-mm-thick plate, causing anisotropic tensile properties. Also, a significant fatigue crack deviation was observed for the 20-mm-thick plate during fatigue crack growth tests due to its microstructure. This result was attributed to the microcrack formations perpendicular to the crack growth direction and slip bands at the intermediate ΔK, when the loading was parallel to the rolling direction. The findings from this study offer critical insights into how the rolling operation for achieving thin plates influences the microstructure and overall performance of the alloy
The ideological contestation over the Istanbul Convention in Türkiye: Anti-gender movements and feminist struggle
No full textPracticum lesson study: insights from a design-based research in English language teaching practicum
No full textPurpose: This study investigates the implementation of the Practicum Lesson Study (PLS) model, which is designed to be used by preservice teachers (PSTs), mentor teachers and advisors during school practicum. Design/methodology/approach: Employing a design-based research (DBR) framework and a multiple case study design, the research in this study evaluated the PLS model through eight distinct cases across two phases of research. In both phases, the qualitative research explored the nature of the stages and steps followed in each case, providing detailed descriptions of the procedural arrangements, teaching sessions and discussion meetings. Views of the participants regarding their satisfaction levels towards the PLS model, its benefits and challenges were collected through semi-structured interviews and a questionnaire. Findings: The results of the research highlighted significant benefits of the PLS model, such as self-reflection, peer reflection and collaborative practices. These processes notably enhanced PSTs’ abilities to dynamically adjust teaching strategies based on real-time observations and feedback, effectively integrating suggestions from meetings with practical classroom experiences. However, the study also identified several challenges, such as managing diverse opinions and coping with information overload. Research limitations/implications: Based on the comprehensive exploration of the PLS model, the study offers several implications for practitioners and suggestions for future research such as a closer examination of changes in beliefs and identity over time during PLS. Originality/value: The study carries the significance of employing a DBR in the context of implementing LS during ELT school practicum
Empowering Dialogic Feedback in FLW with LLM
No full textThis doctoral study aims to address significant challenges in foreign/second language (L2) writing (FLW/SLW) instruction by leveraging artificial intelligence. The central problem this study addresses is the lack of active learner engagement and the resource-intensive nature of traditional feedback methods, which can lead to teacher burnout and ineffective student learning outcomes. Existing feedback practices often fall short in providing detailed, timely, and comprehensible feedback, which hinders students' ability to critically analyze and act upon it. The study proposes a shift from monologic to dialogic feedback, facilitated by large-language models (LLMs), to promote continuous iterations of editing and rewriting, thus enhancing linguistic and cognitive development. The goal is to reveal the potential of LLMs in facilitating effective dialogic feedback approaches in L2 writing. To achieve this, the study aims to develop a theoretical framework and design principles for AI-enabled dialogic feedback systems, create an AI-writing tool based on this framework, and test its effectiveness through experimental sessions. Ultimately, the study seeks to understand the impact of AI-enhanced feedback on L2 learners' writing progress, their perceptions and experiences, and the emerging interaction patterns during the feedback process. This research holds the potential to transform feedback practices in language learning, contributing to more effective and engaging L2 writing instruction
Optimal liquidation with conditions on minimum price
No full textThe classical optimal trading problem is the closure of an initial position in a financial asset over a fixed time interval; the trader tries to maximize an expected utility under the constraint that the position is fully closed by terminal time. Given that the asset price is stochastic, the liquidation constraint may be too restrictive; the trader may want to relax the full liquidation constraint or slow down/stop trading depending on price behavior. We consider two additional parameters that serve these purposes within the Almgren-Chriss liquidation framework: a binary valued process I that prescribes when trading takes place and a measurable set S that prescribes when full liquidation is required. We give four examples for S and I which are all based on a lower bound specified for the price process. The terminal cost of the stochastic optimal control problem is ∞ over S; this represents the liquidation constraint. The permanent price impact defines the negative part of the terminal cost over the complement of S. The I parameter enters the stochastic optimal control problem as a multiplier of the running cost. Except for quadratic liquidation costs the problem turns out to be non-convex. A terminal cost that can take negative values implies 1) the backward stochastic differential equation (BSDE) associated with the value function of the control problem can explode to −∞ backward in time and 2) the existence results on minimal supersolutions of BSDE with singular terminal values and monotone drivers are not directly applicable. To tackle these we introduce an assumption that balances the market volume process and the permanent price impact in the model over the trading horizon. In the quadratic case, assuming only that the noise driving the asset price is a martingale, we show that the minimal supersolution of the BSDE gives both the value function and the optimal control of the stochastic optimal control problem. For the non-quadratic case, we assume a Brownian motion driven stochastic volatility model and focus on choices of I and S that are either Markovian or can be broken into Markovian pieces. These assumptions allow us to represent the value functions as solutions of PDE or PDE systems. The PDE arguments are based on the smoothness of the value functions and do not require convexity. We quantify the financial performance of the resulting liquidation algorithms by the percentage difference between the initial stock price and the average price at which the position is (partially) closed in the time interval [0, T]. We note that this difference can be divided into three pieces: one corresponding to permanent price impact (A1), one corresponding to random fluctuations in the price (A2) and one corresponding to transaction/bid-ask spread costs (A3). We provide a numerical study of the distribution of the closed portion under the assumption that the price process is Brownian for I = 1 and an S corresponding to a lower bound on terminal price
Chitosan Increases the Sensitivity of Soybean Under Iron Deficiency by Impairing the Antioxidant Mechanisms and Nutrient Balance
No full textIron (Fe) deficiency is a common problem, especially in alkaline soils, and large yield losses are experienced in sensitive plants such as soybean (Glycine max L.) when they are grown on alkaline soils. Natural and organic products can be used as fertilizer alternatives to complex with a small amount of Fe in the soil and make it available for the plant roots for effective uptake. For this reason, the effectiveness of chitosan application in different doses was studied in two soybean cultivars (tolerant—Arısoy and sensitive—Atakişi) under Fe deficiency. Plants were grown in hydroponic media containing 60-µM (Fe-sufficient) or 6-µM (Fe-deficient) Fe-EDTA supplemented with chitosan in different concentrations (0.5, 1, 1.5, and 2%) until the V2 stage. An increase in Fe deficiency symptoms was observed in plants due to the increased chitosan concentration. Iron deficiency-related genes were induced after chitosan application. Fe, Mn, Zn, and Mg concentrations were altered significantly in the sensitive cultivar after chitosan application. Therefore, chitosan application cannot rescue Fe deficiency; on the contrary, it impacts the availability of other divalent metals to plants. These alterations resulted in increased H2O2 and MDA, and decreased proline levels. All these changes were more drastic in IDC-sensitive soybean cultivar. Antioxidant enzyme activities varied between cultivars, with Arısoy relying on catalase and superoxide dismutase, while Atakişi favored ascorbate peroxidase. Overall, chitosan application from the roots leads to oxidative stress due to the altered nutrient balance under Fe deficiency
On the reliability of a modification of the fluid model of a glow discharge incorporating the calculation of the local EEDF at each point in space
No full textAn analysis of the approach named “Space-Dependent Electron Energy Distribution Function (EEDF) Modeling” in the COMSOL Multiphysics's Plasma Module is carried out. This modeling approach allows a wide range of users to determine profiles of glow discharge parameters, including the EEDF, in the entire discharge volume. Comparison of computed results for a short (without a positive column) glow discharge, obtained from this model and from kinetic simulations, displays not only significant quantitative but also qualitative differences in the EEDFs. The analysis showed that in this model, as well as in the previous models provided by the COMSOL Multiphysics's Plasma Module, the derivation of the main equations is based on the factorization of the EEDF, which implies the use of a local approximation when solving the Boltzmann kinetic equation. However, as has been repeatedly shown in the literature, this approximation is fulfilled under rather harsh conditions, namely, when the scale of plasma inhomogeneity is small compared to the electron energy relaxation length, and the ambipolar field is small compared to the external electric field heating the electrons. These restrictions significantly limit the applicability range of the analyzed model and make it impossible to use it in the near-electrode and near-wall regions of any gas discharges. Comparison with the corresponding data from the kinetic simulation and the subsequent analysis reveals the existence of fundamental disagreement and internal contradiction within this model that cast doubt on the reliability of the results obtained using this approach, which we address to the “computational plasma community"
Machine learning approach to stock price crash risk
No full textIn this study, we propose a novel machine-learning-based measure for stock price crash risk, utilizing the minimum covariance determinant methodology. Employing this newly introduced dependent variable, we predict stock price crash risk through cross-sectional regression analysis. The findings confirm that the proposed method effectively captures stock price crash risk, with the model demonstrating strong performance in terms of both statistical significance and economic relevance. Furthermore, leveraging a newly developed firm-specific investor sentiment index, the analysis identifies a positive correlation between stock price crash risk and firm-specific investor sentiment. Specifically, higher levels of sentiment are associated with an increased likelihood of stock price crash risk. This relationship remains robust across different firm sizes and when using the detoned version of the firm-specific investor sentiment index, further validating the reliability of the proposed approach
Board Game as a Participatory Design Technique for Urban Spaces: A Ludological Analysis
No full textBackground: The contemporary city has transformed into an ever-changing and multi-actorial entity, necessitating more transformative and communicative understanding. This has resulted in the development of participatory methods emphasizing collaboration and negotiation among multiple actors over the future of urban spaces. Board games have gained popularity as a participatory technique in this respect, as they allow multiple players to engage, negotiate, and present their perspectives within a structured environment while exploring potentials and alternatives in an emancipating atmosphere enmeshed with the fun experience. Despite the growing literature on the applied examples of participatory board games in architecture and planning, there is a lack of a comprehensive understanding of the elements of board games concerning participatory interactions. In light of this, the study aims to provide a ludological analysis of participatory board games to understand their instrumentalization for engaging practices in architecture and planning. Methods: The study applies a ludological analysis to understand the fundamental aspects of a selected sample of ten participatory board games based on their constitutive elements. It evaluates how diverse approaches impact the forms and processes of participation. Results: It is seen that most participatory board games utilize abstract board environments for collective materialization through modular pieces and tiles representing buildings in various scales. While there is no dominant approach in determining the rules, spatial placement mechanics are incorporated in most games, followed by economy and discussion-based ones. Unlike modern board games, many analyzed participatory games lack defined scoring and win conditions, leaving the gameplay more vague and open to player alterations, which might hinder practices’ learning and research qualities. Conclusion: The study showed that despite the increasing practices in participatory board games, there are still potential areas of knowledge in both spatial studies and modern board game design that can merge and enhance practices toward new paths and forms of participation