Punishment of Public Corruption in China and the United States

Corruption is pervasive in many countries. However, the most effective punishment to deter corruption remains unknown. Some have suggested that the death penalty is required to reduce corruption and ensure clean government. However, research shows that the likelihood of punishment is the strongest factor, not the severity of the punishment. It requires large social costs, such as expenditure on policemen, court personnel, and specialized monitoring equipment, to improve the probability of punishment. Can elevation of the severity of punishment be a good substitute? The empirical results from this dissertation suggest that the probability of punishing corruption, i.e., how likely a corrupt public official is to be detected, investigated, apprehended, convicted, and ultimately sentenced, matters a great deal. This dissertation finds that if the probability of punishing corruption is low, even the most severe punishment cannot effectively deter corruption. Instead, a high probability, even of mild punishment, appears to work effectively. This dissertation examines corruption punishment in China, a country that relies heavily on the most severe form of punishment, as well as the United States, a country that implements milder forms of punishment to deter corruption. I conducted the comparison with individual-level corruption case data in both countries. It is inherently difficult to obtain data on the probability of corruption punishment. Thus, I created a novel inverted measurement for the probability of corruption punishment-- the duration of corruption. This measurement instrument enables comparisons between probabilities of corruption punishment. Using this novel measurement, I find that the probability of punishing corruption is substantially smaller in China than in the United States. Within each country, I also find evidence of institutional designs for compensating for the low probability of punishment with raised severity. The probability of punishment differs between subcategories of public officials within a country; however, the severity of punishment varies. I also find that implementation consistency plays a role. The graphed relationship between the total corruption amount and the severity of punishment is that of a concave parabola in China and linear in the United States. Although large amounts of missing data for individual cases may cause bias, our results show that, in contrast to relying on severity for deterrence, improving the probability of punishment consistently relates to the effectiveness of anti-corruption activity. Additionally, the case details show that public servants think rationally and respond to these probability differences

Przedsiębiorczość i ślad węglowy w Afryce Subsaharyjskiej

This study examines the impact of entrepreneurship on carbon footprints in sub-Saharan Africa (SSA). The study applied the generalised method of moments on the data sourced from the World Development indicators (WDI) and World Governance Indicators (WGI). Result shows that entrepreneurship has a negative but not statistically significant impact on carbon footprints in SSA. Furthermore, across SSA subregions, entrepreneurship has a positive and statistically significant impact on carbon footprints in Central Africa (0.052%) and Southern Africa (0.1914%), while entrepreneurship has a negative and statistically significant impact on carbon footprints in Eastern Africa (0.064%) and Western Africa (0.0273%). Based on findings, the study concludes that entrepreneurs can develop and promote clean technologies, renewable energy projects, circular economy initiatives, sustainable agriculture practices, green transport solutions, and educational programs to lower carbon footprints. This calls for collaboration between stakeholders to create an enabling environment for sustainable entrepreneurship and accelerate Africa's transition towards a low-carbon future. The findings of the study contribute to the policy dialogue for the actualisation of sustainable development goals of good health and wellbeing (SDG 3), clean water and sanitation (SDG 6), promotion of development-oriented policies that support productive activities, decent job creation and entrepreneurship (SDG 8.3); sustainable cities and communities (SDG 11), climate action (SGD 13), life below water (SDG14) and life on land (SDG 15), respectively.W niniejszym artykule zbadano wpływ przedsiębiorczości na ślad węglowy w Afryce Subsaharyjskiej (SSA). Wykorzystano dane pochodzące ze wskaźników rozwoju świata (World Development indicators, WDI) i wskaźników zarządzania światowego (World Governance indicators, WGI). Wykazano, że przedsiębiorczość ma negatywny, ale nieistotny statystycznie wpływ na ślad węglowy w Afryce Południowej. Ponadto przedsiębiorczość ma pozytywny i statystycznie istotny wpływ na ślad węglowy w Afryce Środkowej (0,052%) i Afryce Południowej (0,1914%), natomiast ma negatywny i statystycznie istotny wpływ na ślad węglowy w Afryce Wschodniej (0,064% ) i Afryce Zachodniej (0,0273%). Stwierdzono, że przedsiębiorcy mogą opracowywać i promować czyste technologie, projekty w zakresie energii odnawialnej, inicjatywy dotyczące gospodarki o obiegu zamkniętym, praktyki zrównoważonego rolnictwa, ekologiczne rozwiązania transportowe i programy edukacyjne mające na celu zmniejszenie śladu węglowego. Wymaga to współpracy między zainteresowanymi stronami w celu stworzenia sprzyjającego środowiska dla zrównoważonej przedsiębiorczości i przyspieszenia przejścia Afryki w kierunku niskoemisyjności. Wyniki przyczyniają się do dialogu politycznego na rzecz realizacji Celów zrównoważonego rozwoju, takich jak dobre zdrowie i dobre samopoczucie (SDG 3), czysta woda i warunki sanitarne (SDG 6), promowanie polityk zorientowanych na rozwój, które wspierają działalność produkcyjną, tworzenie miejsc pracy i przedsiębiorczość (cel zrównoważonego rozwoju 8.3); zrównoważone miasta i społeczności (SDG 11), działania w dziedzinie klimatu (SDG 13), życie pod wodą (SDG 14) i życie na lądzie (SDG 15)

Research and prospects of environmental DNA (eDNA) for detection of invasive aquatic species in East Asia

The issue of biological invasions in aquatic ecosystems is becoming increasingly severe in the contemporary world. Due to the lack of monitoring and management systems for aquatic invasive species, the difficulty in identifying aquatic invasive species, and the limited effectiveness of conventional control methods in aquatic environments, biological control in water bodies is comparatively more challenging than other types of interventions. In recent years, environmental DNA (eDNA) survey methods have rapidly developed in various fields, such as biological monitoring, community ecology, paleoenvironmental research, conservation biology, and invasion ecology, due to their unique advantages of being rapid, sensitive, efficient, and non-invasive. Because of these characteristics, this innovative molecular approach has gained wider acceptance and is being increasingly utilized for the detection of biological diversity in aquatic environments. Furthermore, it has emerged as a novel technology to address the pressing and significant issue of aquatic invasive species in the vast freshwater and marine resources of the East Asian region. This paper summarizes a variety of literature sources to summarize the major aquatic invasive species in East Asian countries and the current application status of eDNA technology in their survey processes. Using China as a case study, it expounds on the prospective incorporation of the 4E strategy with eDNA technology for the surveillance of biological invasions. Furthermore, it explores the potential prospects of eDNA technology in species diversity management and policy formulation, offering theoretical guidance for establishing aquatic invasive species monitoring systems. From a technological standpoint, the integration of eDNA technology with the 4E strategy holds significant potential for application, thereby offering a promising reference for the formulation of policies related to the management of aquatic biological invasions and biodiversity

Optimization of structural and operational parameters for the multi-size sinter vertical waste heat recovery with the objective of the income exergy

To be consistent with the actual production, this paper establishes the 2-D steady-state mathematical model of the porous media to numerically analyze influences of structural and operational parameters on the vertical cooling process by applying particle characteristic parameters, and heat transfer and resistance correlations of the multi-size sinter. Considering comprehensive effects of the temperature and pressure drop, the operating and structural parameters are optimized with the objective of the maximum income exergy of the gas. Results show that the numerical model established in this paper can well predict the gas-solid heat transfer process in the sinter bed with the maximum error of 7%. Besides, the income exergy of the gas increases and decreases with the sinter outlet temperature and gas outlet temperature increasing, respectively. The reduction in the equivalent particle diameter is conducive to improving the income exergy. What’s more, the income exergy of the gas first ascends and then descends with the increase of the flow rate ratio of gas to sinter and the height of the sinter layer. Therefore, optimal values of the flow rate ratio of the gas to sinter and the height of the sinter layer are 1,050–1,540 m3·h−1 and 7–11.5 m within the scope of this study, respectively

Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning

We introduce the initial release of our software Robustar, which aims to improve the robustness of vision classification machine learning models through a data-driven perspective. Building upon the recent understanding that the lack of machine learning model's robustness is the tendency of the model's learning of spurious features, we aim to solve this problem from its root at the data perspective by removing the spurious features from the data before training. In particular, we introduce a software that helps the users to better prepare the data for training image classification models by allowing the users to annotate the spurious features at the pixel level of images. To facilitate this process, our software also leverages recent advances to help identify potential images and pixels worthy of attention and to continue the training with newly annotated data. Our software is hosted at the GitHub Repository https://github.com/HaohanWang/Robustar.Comment: This paper introduces the first release of our software. The paper is expected to be updated as we continue to develop the softwar

Few-cycle optical rogue waves: Complex modified Korteweg-de Vries equation

In this paper, we consider the complex modified Korteweg–de Vries (mKdV) equation as a model of few-cycle optical pulses. Using the Lax pair, we construct a generalized Darboux transformation and systematically generate the first-, second-, and third-order rogue wave solutions and analyze the nature of evolution of higher-order rogue waves in detail. Based on detailed numerical and analytical investigations, we classify the higher-order rogue waves with respect to their intrinsic structure, namely, fundamental pattern, triangular pattern, and ring pattern. We also present several new patterns of the rogue wave according to the standard and nonstandard decomposition. The results of this paper explain the generalization of higher-order rogue waves in terms of rational solutions. We apply the contour line method to obtain the analytical formulas of the length and width of the first-order rogue wave of the complex mKdV and the nonlinear Schrödinger equations. In nonlinear optics, the higher-order rogue wave solutions found here will be very useful to generate high-power few-cycle optical pulses which will be applicable in the area of ultrashort pulse technology