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"Drought investments could save 10 times more than predicted 35% cost increase by 2035"
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Drought investments could save 10 times more than predicted 35% cost increase by 2035
The economic costs of drought could rise by more than one-third in the next 10 years without urgent reforms to water policies and irrigation systems, especially in resource-limited countries, according to new analysis.

Deterministic and Stochastic Study of the X-ray Emission from the TeV Blazar Mrk~421
Radim P\'anis (Research Centre for Theoretical Physics and Astrophysics, Institute of Physics in Opava, Silesian University in Opava, Czech Republic), Gopal Bhatta (Janusz Gil Institute of Astronomy, University of Zielona G\'ora, Zielona G\'ora, Poland), Tek P. Adhikari (CAS Key Laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science and Technology …

Deterministic and Stochastic Study of the X-ray Emission from the TeV Blazar Mrk~421
We present a comprehensive timing analysis of X-ray data from the {\it XMM-Newton} satellite, examining 50 light curves covering 17 years of observations of the blazar Mrk~421. This work uses classical deterministic and stochastic methods in a novel way, enabling the distinction of temporal scales and offering essential insights through correlations among parameters. Deterministic behaviors are primarily explored through recurrence quantification analysis (RQA), used innovatively by varying the…

This https://arxiv.org/abs/2504.19832 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Identifying the Frontier Structural Function and Bounding Mean Deviations
This paper analyzes a model in which an outcome variable equals a frontier function of inputs less a nonnegative unobserved deviation. If zero lies in the support of the deviation given inputs, then the frontier function is identified by the supremum outcome at those inputs. This obviates the need for instrumental variables. Implementation requires allowing for the distribution of deviations to depend on inputs, thus not ruling out endogeneity. Including random errors yields a stochastic fronti…

Deep Research Agents: A Systematic Examination And Roadmap
Yuxuan Huang, Yihang Chen, Haozheng Zhang, Kang Li, Meng Fang, Linyi Yang, Xiaoguang Li, Lifeng Shang, Songcen Xu, Jianye Hao, Kun Shao, Jun Wang
https://arxiv.org/abs/2506.18096

Deep Research Agents: A Systematic Examination And Roadmap
The rapid progress of Large Language Models (LLMs) has given rise to a new category of autonomous AI systems, referred to as Deep Research (DR) agents. These agents are designed to tackle complex, multi-turn informational research tasks by leveraging a combination of dynamic reasoning, adaptive long-horizon planning, multi-hop information retrieval, iterative tool use, and the generation of structured analytical reports. In this paper, we conduct a detailed analysis of the foundational technolo…

Analyzing the Impact of Strategic Bidding on the Reserve Capacity via a Bi-Level Model
Yun Xu, Yunxiao Bai, Yunyong Zhang, Peng Wang, Xuelin Wang, Jiqun Guo, Kaijun Xie, Rusheng Zhao
https://arxiv.org/abs/2506.20493

Analyzing the Impact of Strategic Bidding on the Reserve Capacity via a Bi-Level Model
The growing integration of renewable energy sources necessitates adequate reserve capacity to maintain power balance. However, in market clearing, power companies with flexible resources may submit strategic bids to maximize profits, potentially compromising system reserves. This paper examines the effects of such strategic behavior by modeling the market as a bi-level problem. The upper level represents a strategic company aiming to maximize profit, while the lower level simulates the system o…

This https://arxiv.org/abs/2302.00469 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Regression Adjustment, Cross-Fitting, and Randomized Experiments with Many Controls
This paper studies estimation and inference for average treatment effects in randomized experiments with many covariates, under a design-based framework with a deterministic number of treated units. We show that a simple yet powerful cross-fitted regression adjustment achieves bias-correction and leads to sharper asymptotic properties than existing alternatives. Specifically, we derive higher-order stochastic expansions, analyze associated inference procedures, and propose a modified HC3 varian…

The Impact of the Russia-Ukraine Conflict on the Cloud Computing Risk Landscape
Malikussaid, Sutiyo
https://arxiv.org/abs/2506.20104 https://

The Impact of the Russia-Ukraine Conflict on the Cloud Computing Risk Landscape
The Russian invasion of Ukraine has fundamentally altered the information technology (IT) risk landscape, particularly in cloud computing environments. This paper examines how this geopolitical conflict has accelerated data sovereignty concerns, transformed cybersecurity paradigms, and reshaped cloud infrastructure strategies worldwide. Through an analysis of documented cyber operations, regulatory responses, and organizational adaptations between 2022 and early 2025, this research demonstrates…

This https://arxiv.org/abs/2311.06891 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Design-based Estimation Theory for Complex Experiments
This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units. We develop a design-based estimation theory for arbitrary experimental designs. Our theory facilitates the analysis of many design-estimator pairs that researchers commonly employ in practice and provide procedures to consistently estimate asymptotic variance bounds. We propose new classes of estimators with favorable asymptotic p…

The Compositional Architecture of Regret in Large Language Models
Xiangxiang Cui, Shu Yang, Tianjin Huang, Wanyu Lin, Lijie Hu, Di Wang
https://arxiv.org/abs/2506.15617

The Compositional Architecture of Regret in Large Language Models
Regret in Large Language Models refers to their explicit regret expression when presented with evidence contradicting their previously generated misinformation. Studying the regret mechanism is crucial for enhancing model reliability and helps in revealing how cognition is coded in neural networks. To understand this mechanism, we need to first identify regret expressions in model outputs, then analyze their internal representation. This analysis requires examining the model's hidden states, wh…

The Persistent Effects of Peru's Mining MITA: Double Machine Learning Approach
Alper Deniz Karakas
https://arxiv.org/abs/2506.18947 https://

The Persistent Effects of Peru's Mining MITA: Double Machine Learning Approach
This study examines the long-term economic impact of the colonial Mita system in Peru, building on Melissa Dell's foundational work on the enduring effects of forced labor institutions. The Mita, imposed by the Spanish colonial authorities from 1573 to 1812, required indigenous communities within a designated boundary to supply labor to mines, primarily near Potosi. Dell's original regression discontinuity design (RDD) analysis, leveraging the Mita boundary to estimate the Mita's legacy on mode…