This article examines how China’s central political inspections indirectly enhance municipal provision of invisible public goods. Such goods (e.g., underground pipelines, drainage systems) eludes reliable public assessment through daily observation. Drawing on Mani and Mukand, we emphasize their two defining attributes: (1) conditional evaluation (public judgment requires specific triggers like extreme weather), and (2) temporal accountability lag (delayed quality assessment). Unlike technical business inspections, political inspections prioritize provincial leaders’ political loyalty, generating cascading deterrent effects on municipal officials. Confronting heightened career risks, rational local officials strategically reallocate resources to rectify undersupplied invisible goods. Empirical analysis leveraging the first wave of nationwide inspection data confirms this causal mechanism.
South Asia. Southeast Asia. East Asia, Social Sciences
Machine learning practitioners frequently observe tension between predictive accuracy and group fairness constraints -- yet sometimes fairness interventions appear to improve accuracy. We show that both phenomena can be artifacts of training data that misrepresents subgroup proportions. Under subpopulation shift (stable within-group distributions, shifted group proportions), we establish: (i) full importance-weighted correction is asymptotically unbiased but finite-sample suboptimal; (ii) the optimal finite-sample correction is a shrinkage reweighting that interpolates between target and training mixtures; (iii) apparent "fairness helps accuracy" can arise from comparing fairness methods to an improperly-weighted baseline. We provide an actionable evaluation protocol: fix representation (optimally) before fairness -- compare fairness interventions against a shrinkage-corrected baseline to isolate the true, irreducible price of fairness. Experiments on synthetic and real-world benchmarks (Adult, COMPAS) validate our theoretical predictions and demonstrate that this protocol eliminates spurious tradeoffs, revealing the genuine fairness-utility frontier.
Many differentially private (DP) data release systems either output DP synthetic data and leave analysts to perform inference as usual, which can lead to severe miscalibration, or output a DP point estimate without a principled way to do uncertainty quantification. This paper develops a clean and tractable middle ground for exponential families: release only DP sufficient statistics, then perform noise-calibrated likelihood-based inference and optional parametric synthetic data generation as post-processing. Our contributions are: (1) a general recipe for approximate-DP release of clipped sufficient statistics under the Gaussian mechanism; (2) asymptotic normality, explicit variance inflation, and valid Wald-style confidence intervals for the plug-in DP MLE; (3) a noise-aware likelihood correction that is first-order equivalent to the plug-in but supports bootstrap-based intervals; and (4) a matching minimax lower bound showing the privacy distortion rate is unavoidable. The resulting theory yields concrete design rules and a practical pipeline for releasing DP synthetic data with principled uncertainty quantification, validated on three exponential families and real census data.
Randomized controlled trials (RCTs) are the gold standard for estimating heterogeneous treatment effects, yet they are often underpowered for detecting effect heterogeneity. Large observational studies (OS) can supplement RCTs for conditional average treatment effect (CATE) estimation, but a key barrier is covariate mismatch: the two sources measure different, only partially overlapping, covariates. We propose CALM (Calibrated ALignment under covariate Mismatch), which bypasses imputation by learning embeddings that map each source's features into a common representation space. OS outcome models are transferred to the RCT embedding space and calibrated using trial data, preserving causal identification from randomization. Finite-sample risk bounds decompose into alignment error, outcome-model complexity, and calibration complexity terms, identifying when embedding alignment outperforms imputation. Under the calibration-based linear variant, the framework provides protection against negative transfer; the neural variant can be vulnerable under severe distributional shift. Under sparse linear models, the embedding approach strictly generalizes imputation. Simulations across 51 settings confirm that (i) calibration-based methods are equivalent for linear CATEs, and (ii) the neural embedding variant wins all 22 nonlinear-regime settings with large margins.
Neural networks are hypothesized to implement interpretable causal mechanisms, yet verifying this requires finding a causal abstraction -- a simpler, high-level Structural Causal Model (SCM) faithful to the network under interventions. Discovering such abstractions is hard: it typically demands brute-force interchange interventions or retraining. We reframe the problem by viewing structured pruning as a search over approximate abstractions. Treating a trained network as a deterministic SCM, we derive an Interventional Risk objective whose second-order expansion yields closed-form criteria for replacing units with constants or folding them into neighbors. Under uniform curvature, our score reduces to activation variance, recovering variance-based pruning as a special case while clarifying when it fails. The resulting procedure efficiently extracts sparse, intervention-faithful abstractions from pretrained networks, which we validate via interchange interventions.
The strengthening of the zonal sea surface temperature (SST) gradient observed in the tropical Pacific in recent decades is a regional climate change signal that may be outside the range of historical simulations with comprehensive climate models. Given the important role that this change has on other aspects of climate, a series of idealized surface energy balance calculations with imposed parameters is performed to build a baseline understanding of the sensitivities that govern these changes. I quantify the requisite magnitudes of five perturbations that reach a new equilibrium with a mean-SST warming of about $0.5 \, \mathrm{K}$ and about $0.4 \, \mathrm{K}$ more west Pacific warming than east Pacific warming, based approximately on observed trends. A characteristic magnitude of zonal asymmetry in a surface energy tendency that can bring changes in line with observed trends is $\approx 3 \, \mathrm{W \, m^{-2}}$. Strengthened zonal SST gradients can arise from a more zonally asymmetric ocean heat flux that increases by $\approx 20\% \, \mathrm{K}^{-1}$ using that implied by ERA5's surface fluxes, a spatially varying radiative forcing with a west--east contrast of $\approx 3.3 \, \mathrm{W \, m^{-2}}$, a more amplifying surface radiative feedback in the west than the east with a contrast of $\approx 4 \, \mathrm{W \, m^{-2} \, K^{-1}}$, a surface-air relative humidity (RH) contrast that increases RH in the west and decreases it in the east by $\approx 0.5 \% \, \mathrm{K^{-1}}$, or a more zonally asymmetric wind speed that increases by $\approx 16 \% \, \mathrm{K^{-1}}$. The ``storylines'' of forced surface energy budget change identified here are valuable in determining the plausibility of mechanisms that may be absent or underestimated in coupled climate model simulations.
Itay Dreyfuss, Antonio Abu Nassar, Samuel Ackerman
et al.
Large Language Model (LLM)-based code assistants have emerged as a powerful application of generative AI, demonstrating impressive capabilities in code generation and comprehension. A key requirement for these systems is their ability to accurately follow user instructions. We present Precise Automatically Checked Instruction Following In Code (PACIFIC), a novel framework designed to automatically generate benchmarks that rigorously assess sequential instruction-following and code dry-running capabilities in LLMs, while allowing control over benchmark difficulty. PACIFIC produces benchmark variants with clearly defined expected outputs, enabling straightforward and reliable evaluation through simple output comparisons. In contrast to existing approaches that often rely on tool usage or agentic behavior, our work isolates and evaluates the LLM's intrinsic ability to reason through code behavior step-by-step without execution (dry running) and to follow instructions. Furthermore, our framework mitigates training data contamination by facilitating effortless generation of novel benchmark variations. We validate our framework by generating a suite of benchmarks spanning a range of difficulty levels and evaluating multiple state-of-the-art LLMs. Our results demonstrate that PACIFIC can produce increasingly challenging benchmarks that effectively differentiate instruction-following and dry running capabilities, even among advanced models. Overall, our framework offers a scalable, contamination-resilient methodology for assessing core competencies of LLMs in code-related tasks.
This study examines the determinants of financial and digital inclusion in West and Central Africa using the World Bank Findex 2021 data. Unlike prior works that rely solely on traditional logit and probit models, we combine country-by-country analysis with robustness checks including K-fold cross-validation and Vuong test. Three samples were considered : a full sample combin- ing both regions and two separate subsamples for West and Central Africa. The results indicate that gender, educational attainment, income level, and place of residence are significant factors influencing both financial and digital inclusion in the full sample and the West African subsam- ple. In the Central African subsample, gender is not significant; however, age, education, income, and rural residence emerge as key determinants of financial and digital inclusion. Overall, Ghana stands out as the most financially inclusive country, although it trails Senegal in terms of credit access and digital payment use. Nigeria leads in formal account ownership and formal savings but falls considerably behind Ghana in mobile money account ownership and digital payments. Central African countries generally report lower levels of inclusion compared to West Africa, with Cameroon performing comparatively better.
The review introduces the collection of the archival documents covering cultural ties between the USSR and PRC from 1949 to 1960. The published materials are stored in seven Russian and two Chinese archives. The major part of the documents is published for the first time, which confirms the
particular value of this publication as a result of the joint effort of the Russian and Chinese experts. The book addresses the history of the formation of relations between the USSR and China in the 1950s by means of cultural diplomacy. The archival materials display the mechanisms and results of the exchanges of Soviet and Chinese delegations of writers, artists, musicians, athletes, actors and scientists. The publication is aimed at researchers, students, academics and all those interested in Russian history, history of international relations, Oriental studies and Sinology. The review argues that the materials introduced in the volume provide new sources for the in-depth study of cultural diplomacy as a part of Russian-Chinese relations, as well as the cultural history of the PRC in the early period.
South Asia. Southeast Asia. East Asia, Bibliography. Library science. Information resources
The article examines the content of “state overseas interests”, which is an important Chinese diplomatic concept, and studies the role those interests play in the country's foreign policy strategy. The work analyzes a relatively wide range of Chinese research literature, conceptual and regulatory documents related to the PRC’s policy to protect its overseas interests. The author concludes that the Chinese leadership adheres to a narrow materialistic interpretation of overseas interests and does not regard their protection as an existential need as compared to the “core interests” of the country. At present, Beijing's pursuit of its overseas interests exhibits protective nature and is aimed at promoting country’s economic development, implementing foreign economic initiatives, improving international image and deepening its relations with other states. This situation is unlikely to change in the foreseeable future, but the emergence of more serious threats to China's overseas interests may bring about new changes in the country's foreign policy strategy.
South Asia. Southeast Asia. East Asia, Bibliography. Library science. Information resources
The relevance of this article is due to the changes in Russian-Chinese relations that are taking place under the influence of the military crisis in Ukraine and Western sanctions applied against Russia and China. The purpose of this study is to analyze the problems and prospects of cooperation between Moscow and Beijing in the political, trade, economic and humanitarian spheres. The author used the following research methods: generalization, structural synthesis, deductive and comparative analyses. Their application allowed us to come to the following conclusions. In the context of the ongoing crisis in Ukraine, Russian-Chinese r elations are being tested for strength, as they are subject to comprehensive sanctions pressure from the “collective West”. Despite this pressure, relations between Russia and China demonstrate the growth of political interaction in the international arena. In the field of trade and economic relations, Moscow is trying to compensate for its economic and financial weakness by actively attracting Chinese investments and products. However, Russia is a less significant partner for Beijing compared to the European Union and the United States. To eliminate these problems, governments, economists and scientists from Russia and China are working together to activate the development of economic cooperation between the countries. Along with political and economic cooperation, humanitarian interaction between Moscow and Beijing is extremely important. It is aimed at confronting Western ideology and strengthening mutual understanding between the peoples of the Russian Federation and the People’s Republic of China, as well as strengthening cooperation within the framework of the EAEU, SCO and BRICS.
South Asia. Southeast Asia. East Asia, Bibliography. Library science. Information resources
South Africa is currently facing a critical situation in its power generation landscape, which is plagued by frequent power outages and the need to move from fossil fuels to renewable energy sources. This period emphasizes the importance of having firm-dispatchable power to balance out the intermittent nature of wind and solar energy sources. The paper proposes to repurpose old coal-fired power plants to generate firm-dispatchable energy in line with the principles of a Just Transition. Eskom's coal plants are approaching the end of their economic life, and their declining energy availability factor is becoming a challenge in meeting the country's energy needs. The study suggests that a comprehensive strategy that integrates wind, solar, and firm-dispatchable power can be cost-effective and reliable compared to the traditional coal-based approach or the nuclear alternative. The study emphasizes the necessity of a 25-year plan that would invest in flexible and modular dispatchable generation. It also highlights the strategic location of this generating capacity, including repurposing decommissioned coal plant sites. The proposed model integrates private investment, adheres to established best practices, and emphasizes adaptability to changing demand dynamics. The study provides a roadmap for enabling firm-dispatchable capacity for South Africa's energy transition, emphasizing economic prudence, environmental sustainability, and alignment with the principles of the Just Transition program.
Athul Rasheeda Satheesh, Peter Knippertz, Andreas H. Fink
Numerical weather prediction (NWP) models often underperform compared to simpler climatology-based precipitation forecasts in northern tropical Africa, even after statistical postprocessing. AI-based forecasting models show promise but have avoided precipitation due to its complexity. Synoptic-scale forcings like African easterly waves and other tropical waves (TWs) are important for predictability in tropical Africa, yet their value for predicting daily rainfall remains unexplored. This study uses two machine-learning models--gamma regression and a convolutional neural network (CNN)--trained on TW predictors from satellite-based GPM IMERG data to predict daily rainfall during the July-September monsoon season. Predictor variables are derived from the local amplitude and phase information of seven TW from the target and up-and-downstream neighboring grids at 1-degree spatial resolution. The ML models are combined with Easy Uncertainty Quantification (EasyUQ) to generate calibrated probabilistic forecasts and are compared with three benchmarks: Extended Probabilistic Climatology (EPC15), ECMWF operational ensemble forecast (ENS), and a probabilistic forecast from the ENS control member using EasyUQ (CTRL EasyUQ). The study finds that downstream predictor variables offer the highest predictability, with downstream tropical depression (TD)-type wave-based predictors being most important. Other waves like mixed-Rossby gravity (MRG), Kelvin, and inertio-gravity waves also contribute significantly but show regional preferences. ENS forecasts exhibit poor skill due to miscalibration. CTRL EasyUQ shows improvement over ENS and marginal enhancement over EPC15. Both gamma regression and CNN forecasts significantly outperform benchmarks in tropical Africa. This study highlights the potential of ML models trained on TW-based predictors to improve daily precipitation forecasts in tropical Africa.
The article is dedicated to the new stage of the policy of the Japanese authorities and companies, aimed at the accelerated development of the sector for production of advanced semiconductors (chips) and making the country one of the world leaders in this field. The author considers the current state, structure and features of the production of chips in Japan and the main directions for the development of this sector in the coming years. The influence of the geopolitical situation in East Asia and the decision of the country's authorities to pursue the accelerated development with the help of the new Rapidus holding, designed to become one of the key elements in moving towards the intended goal, are analyzed. The article also considers features and prospects of Japan's cooperation with the United States, China and its closest neighbors. In conclusion, the author states that Japan's progress towards the intended goal within the declared time frame will take place in the face of increased competition from the main chip manufacturers. However, the main concern against the backdrop of growing economic difficulties will be the lack of funds for the implementation of large projects, which may lead to a slowdown in implementation and adjustment of the outlined plans.
South Asia. Southeast Asia. East Asia, Bibliography. Library science. Information resources
In the quest for solutions to its persistent instability and the economic and social crisis, the Democratic Republic of Congo (DR Congo) is engaged in a regional integration process that challenges the idea of the African Economic Community. After joining the East African Community (EAC), the country is now part of four regional economic communities and several other regional trade agreements. Its geographical proximity to the EAC countries, their common historical links as well as the significant economic dependence of its eastern part on the EAC countries fuel its ambition to integrate it in order to benefit from its common market. While this integration is desired by all EAC member countries, experts still question its viability as it could disclose the economic fragility of a resource rich but unstable and poorly industrialized country. This paper seeks not only to highlight the particularities of the EAC and the rationale for the integration of the DR Congo, but also to outline some preconditions for the latter’s successful integration.
Asia and Eurasia, Africa, Pacific Area, and Antarctica
The article explores the influence of the economic policy uncertainty on investment decisions in China and Russia. Both countries are important actors in the global economy and attract significant amounts of foreign investment. However, uncertainty in the economic policy can influence the decision of investors. The author explores various factors that can create uncertainty in the economic policies of both countries, including changes in tax regulation, monetary policy, legal system and trade relations. The article also analyzes the impact of such uncertainty on investment, including reduced investor confidence, increased risks and difficulties in long-term planning. The author highlights the features of China and Russia’s economic policy, assesses the level of uncertainty faced by investors, and analyzes the response of the investment community to such uncertainty. The role of government in removing or reducing economic policy uncertainty and stimulating investment is also considered. The study is based on an analysis of economic data, statistical indicators and previous studies in this field. The article's findings and conclusions provide practical suggestions and recommendations for improving the investment climate in China and Russia, including measures aimed at reducing uncertainty and increasing attractiveness to foreign investors.
South Asia. Southeast Asia. East Asia, Bibliography. Library science. Information resources
The article focuses on the processes of presenting contemporary Japanese photography in Russia from the early 1990s to the early 2020s. The end of the Soviet period, in which Japanese photography had its own expositional peculiarities, brought new opportunities and significantly expanded the geography of exhibition, as well as increased the number of cultural initiatives aimed at presenting Japanese art, including photography. The article outlines and analyzes the dynamics of Japanese photography exhibition in Russia and provides a brief overview of the largest and most significant exhibition projects in Moscow and St. Petersburg. The specifics and trajectory of Japanese photographers' shows in different regions of Russia, including touring projects, are also noted. In addition, the author gives information about the participation of Japanese photographers in international art fairs in Moscow and considers the role of magazines in popularizing photography from Japan. The appendix to the article contains the most complete list of exhibitions of Japanese photographers in Russia from 1993 to 2023.
South Asia. Southeast Asia. East Asia, Bibliography. Library science. Information resources
Xinyi Wen, Mehrnaz Anvari, Leonardo Rydin Gorjao
et al.
The power-grid frequency reflects the balance between electricity supply and demand. Measuring the frequency and its variations allows monitoring of the power balance in the system and, thus, the grid stability. In addition, gaining insight into the characteristics of frequency variations and defining precise evaluation metrics for these variations enables accurate assessment of the performance of forecasts and synthetic models of the power-grid frequency. Previous work was limited to a few geographical regions and did not quantify the observed effects. In this contribution, we analyze and quantify the statistical and stochastic properties of self-recorded power-grid frequency data from various synchronous areas in Asia, Australia, and Europe at a resolution of one second. Revealing non-standard statistics of both empirical and synthetic frequency data, we effectively constrain the space of possible (stochastic) power-grid frequency models and share a range of analysis tools to benchmark any model or characterize empirical data. Furthermore, we emphasize the need to analyze data from a large range of synchronous areas to obtain generally applicable models.