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Robust assessment of the institutionalist account of comparative development is hampered by problems of omitted variable bias and reverse causation, since institutional quality is not randomly assigned with respect to geographic and human capital endowments. A recent series of papers has applied spatial regression discontinuity designs to estimate the impact of institutions on incomes at international borders, drawing inference from the abrupt discontinuity in governance at borders, whereas other determinants of income vary smoothly across borders. I extend this literature by assessing the importance of sub-national variation in institutional quality at provincial borders in China. Employing nighttime lights emissions as a proxy for income, across multiple specifications I find no evidence in favour of an institutionalist account of the comparative development of Chinese provinces.
Astronomy, often perceived as a distant or luxury science, holds immense potential as a driver for sustainable local socio-economic development. This paper explores how astronomy can create tangible benefits for communities through education, tourism, technology transfer, and capacity building. Using case studies from South Africa, Chile, Indonesia, and India, we demonstrate how astronomical facilities and initiatives have stimulated local economies, generated employment, supported small enterprises, and enhanced STEM participation, while simultaneously inspiring a sense of shared global heritage. The analysis identifies both successes and challenges, including unequal benefit distribution, limited local ownership, and sustainability gaps once external funding ends. Building on these lessons, we propose a practical framework/guidelines for designing, implementing, and evaluating astronomy-based community initiatives, rooted in participatory engagement and aligned with the UN Sustainable Development Goals (SDGs). This paper positions astronomy as a catalyst for inclusive growth, demonstrating that investment in the cosmos can translate into grounded, measurable benefits for people a
Empirical studies form an integral part of visualization research. Not only can they facilitate the evaluation of various designs, techniques, systems, and practices in visualization, but they can also enable the discovery of the causalities explaining why and how visualization works. This state-of-the-art report focuses on controlled and semi-controlled empirical studies conducted in laboratories and crowd-sourcing environments. In particular, the survey provides a taxonomic analysis of over 129 empirical studies in the visualization literature. It juxtaposes these studies with topic developments between 1978 and 2017 in psychology, where controlled empirical studies have played a predominant role in research. To help appreciate this broad context, the paper provides two case studies in detail, where specific visualization-related topics were examined in the discipline of psychology as well as the field of visualization. Following a brief discussion on some latest developments in psychology, it outlines challenges and opportunities in making new discoveries about visualization through empirical studies.
The goal of this research is to uncover the channels through which research and development (R&D) impacts economic growth in developing countries. The study employed nine variables from three broader categories in the World Economic Forum database, each covering 32 countries from the lower-middle-income group for the year 2019. The theoretical framework is based on the R&D ecosystem, which includes components such as Institutions, Human capital, Capital market, R&D, and Innovation. Each of these components can contribute to the economic development of the country. Using Structural Equation Modelling (SEM), we build a path diagram to visualize and confirm a potential relationship between the components. R&D features had a positive impact on innovation (regression weight estimate: +0.34, p = 0.001), as did capital market institutions (regression weight estimate: +0.12, p = 0.007), but neither had a significant impact on growth. According to the Schumpeterian institutional interpretation, R&D and innovation efforts may not lead to sustained growth in middle-income countries. We find no significant connection between innovation performance and economic growth. This
Every year many scholars are funded by the China Scholarship Council (CSC). The CSC is a funding agency established by the Chinese government with the main initiative of training Chinese scholars to conduct research abroad and to promote international collaboration. In this study, we identified these CSC-funded scholars sponsored by the China Scholarship Council based on the acknowledgments text indexed by the Web of Science. Bibliometric data of their publications were collected to track their scientific mobility in different fields, and to evaluate the performance of the CSC scholarship in promoting international collaboration by sponsoring the mobility of scholars. Papers funded by the China Scholarship Council are mainly from the fields of natural sciences and engineering sciences. There are few CSC-funded papers in the field of social sciences and humanities. CSC-funded scholars from mainland China have the United States, Australia, Canada, and some European countries, such as Germany, the UK, and the Netherlands, as their preferential mobility destinations across all fields of science. CSC-funded scholars published most of their papers with international collaboration during
Domestic and foreign scholars have already done much research on regional disparity and its evolution in China, but there is a big difference in conclusions. What is the reason for this? We think it is mainly due to different analytic approaches, perspectives, spatial units, statistical indicators and different periods for studies. On the basis of previous analyses and findings, we have done some further quantitative computation and empirical study, and revealed the inter-provincial disparity and regional disparity of economic development and their evolution trends from 1952-2000. The results shows that (a) Regional disparity in economic development in China, including the inter-provincial disparity, inter-regional disparity and intra-regional disparity, has existed for years; (b) Gini coefficient and Theil coefficient have revealed a similar dynamic trend for comparative disparity in economic development between provinces in China. From 1952 to 1978, except for the "Great Leap Forward" period, comparative disparity basically assumes a upward trend and it assumed a slowly downward trend from 1979 to1990. Afterwards from 1991 to 2000 the disparity assumed a slowly upward trend again
Large language models (LLMs) achieve strong performance across many natural language processing tasks, yet their decision processes remain difficult to interpret. This lack of transparency creates challenges for trust, debugging, and deployment in real-world systems. This paper presents an applied comparative study of three explainability techniques: Integrated Gradients, Attention Rollout, and SHAP, on a fine-tuned DistilBERT model for SST-2 sentiment classification. Rather than proposing new methods, the focus is on evaluating the practical behavior of existing approaches under a consistent and reproducible setup. The results show that gradient-based attribution provides more stable and intuitive explanations, while attention-based methods are computationally efficient but less aligned with prediction-relevant features. Model-agnostic approaches offer flexibility but introduce higher computational cost and variability. This work highlights key trade-offs between explainability methods and emphasizes their role as diagnostic tools rather than definitive explanations. The findings provide practical insights for researchers and engineers working with transformer-based NLP systems. T
AI revolutionizes transportation through autonomous vehicles (AVs) but introduces complex criminal liability issues regarding infractions. This study employs a comparative legal analysis of primary statutes, real-world liability claims, and academic literature across the US, Germany, UK, China, and India; jurisdictions selected for their technological advancement and contrasting regulatory approaches. The research examines the attribution of human error, AI moral agency, and the identification of primary offenders in AV incidents. Findings reveal fragmented regulatory landscapes: India and the US rely on loose networks of state laws, whereas the UK enacted the pioneering Automated and Electric Vehicles Act 2018. Germany enforces strict safety standards, distinguishing liability based on the vehicle's operating mode, while China similarly aims for a stringent liability regime. The study concludes that globally harmonized legal standards are essential to foster technological innovation while ensuring minimum risk and clear liability attribution.
The pre-training paradigm plays a key role in the success of Large Language Models (LLMs), which have been recognized as one of the most significant advancements of AI recently. Building on these breakthroughs, code LLMs with advanced coding capabilities bring huge impacts on software engineering, showing the tendency to become an essential part of developers' daily routines. However, the current code LLMs still face serious challenges related to trustworthiness, as they can generate incorrect, insecure, or unreliable code. Recent exploratory studies find that it can be promising to detect such risky outputs by analyzing LLMs' internal states, akin to how the human brain unconsciously recognizes its own mistakes. Yet, most of these approaches are limited to narrow sub-domains of LLM operations and fall short of achieving industry-level scalability and practicability. To address these challenges, in this paper, we propose PtTrust, a two-stage risk assessment framework for code LLM based on internal state pre-training, designed to integrate seamlessly with the existing infrastructure of software companies. The core idea is that the risk assessment framework could also undergo a pre-t
Sustainable development is a framework for achieving human development goals. It provides natural systems' ability to deliver natural resources and ecosystem services. Sustainable development is crucial for the economy and society. Artificial intelligence (AI) has attracted increasing attention in recent years, with the potential to have a positive influence across many domains. AI is a commonly employed component in the quest for long-term sustainability. In this study, we explore the impact of AI on three pillars of sustainable development: society, environment, and economy, as well as numerous case studies from which we may deduce the impact of AI in a variety of areas, i.e., agriculture, classifying waste, smart water management, and Heating, Ventilation, and Air Conditioning (HVAC) systems. Furthermore, we present AI-based strategies for achieving Sustainable Development Goals (SDGs) which are effective for developing countries like Bangladesh. The framework that we propose may reduce the negative impact of AI and promote the proactiveness of this technology.
Object detection in remotely sensed satellite pictures is fundamental in many fields such as biophysical, and environmental monitoring. While deep learning algorithms are constantly evolving, they have been mostly implemented and tested on popular ground-based taken photos. This paper critically evaluates and compares a suite of advanced object detection algorithms customized for the task of identifying aircraft within satellite imagery. Using the large HRPlanesV2 dataset, together with a rigorous validation with the GDIT dataset, this research encompasses an array of methodologies including YOLO versions 5 and 8, Faster RCNN, CenterNet, RetinaNet, RTMDet, and DETR, all trained from scratch. This exhaustive training and validation study reveal YOLOv5 as the preeminent model for the specific case of identifying airplanes from remote sensing data, showcasing high precision and adaptability across diverse imaging conditions. This research highlight the nuanced performance landscapes of these algorithms, with YOLOv5 emerging as a robust solution for aerial object detection, underlining its importance through superior mean average precision, Recall, and Intersection over Union scores. T
This empirical study investigates the impact of the Hofstede cultural dimensions (HCD) on the Global Innovation Index (GII) scores in four different years (2007, 2009, 2019 and 2021) to compare the impacts during the pre- and post-crisis (financial and COVID-19) period by employing ordinary least square (OLS) and robust least square (Robust) analyses. The purpose of this study is to identify the impact of cultural factors on the innovation development for different income groups during the pre- and post-crisis period. We found that, in general, the same cultural properties were required for countries to enhance innovation inputs and outputs regardless of pre- and post-crisis periods and time variances. The significant cultural factors (driving forces) of the innovation performance do not change over time. However, our empirical results revealed that not the crisis itself but the income group (either developed or developing) is the factor that influences the relationship between cultural properties and innovation. It is also worth noting that cultural properties have lost much of their impact on innovation, particularly in developing countries, during recent periods. It is highly li
Astrotourism has emerged as a powerful cross sectoral tool to promote science education, sustainable economic development, and cultural exchange. Recognising its potential, the International Astronomical Union's Office of Astronomy for Development (IAU OAD) has developed a suite of openly accessible resources to support individuals and institutions interested in implementing astrotourism initiatives globally. These resources also encourage individuals and existing businesses to broaden their offerings to include activities that use the night sky as a backdrop, such as food experiences, wellness practices, and cultural exploration. This paper offers a comprehensive summary of these resources, available on the OAD's Astrotourism Portal, and situates them within the broader context of astronomy for development work. The paper is targeted at educators, policymakers, tourism operators, grassroots organisers, and entrepreneurs, providing guidance on how they can foster inclusive, locally grounded, and sustainable astrotourism efforts, particularly in underresourced or emerging contexts.
Agile methods have transformed the way software is developed, emphasizing active end-user involvement, tolerance to change, and evolutionary delivery of products. The first special issue on agile development described the methods as focusing on "feedback and change". These methods have led to major changes in how software is developed. Scrum is now the most common framework for development in most countries, and other methods like extreme programming (XP) and elements of lean software development and Kanban are widely used. What started as a bottom-up movement amongst software practitioners and consultants has been taken up by major international consulting companies who prescribe agile development, particularly for contexts where learning and innovation are key. Agile development methods have attracted interest primarily in software engineering, but also in a number of other disciplines including information systems and project management. The agile software development methods were originally targeted towards small, co-located development teams, but are increasingly applied in other contexts. They were initially used to develop Web systems and internal IT systems, but are now use
This publication presents a relation computation or calculus for international relations using a mathematical modeling. It examined trust for international relations and its calculus, which related to Bayesian inference, Dempster-Shafer theory and subjective logic. Based on an observation in the literature, we found no literature discussing the calculus method for the international relations. To bridge this research gap, we propose a relation algebra method for international relations computation. The proposed method will allow a relation computation which is previously subjective and incomputable. We also present three international relations as case studies to demonstrate the proposed method is a real-world scenario. The method will deliver the relation computation for the international relations that to support decision makers in a government such as foreign ministry, defense ministry, presidential or prime minister office. The Department of Defense (DoD) may use our method to determine a nation that can be identified as a friendly, neutral or hostile nation.
Software product innovation in large organizations is fundamentally chal-lenging because of restrained freedom and flexibility to conduct experi-ments. As a response, large agile companies form internal startups to initiate employ-driven innovation, inspired by Lean startup. This case study investi-gates how communities of practice support five internal startups in develop-ing new software products within a large organization. We observed six communities of practice meetings, two workshops and conducted ten semi-structured interviews over the course of a year. Our findings show that a community of practice, called the Innovation guild, allowed internal startups to help each other by collectively solving problems, creating shared practic-es, and sharing knowledge. This study confirms that benefits documented in earlier research into CoPs also hold true in the context of software product innovation in large organizations. Henceforth, we suggest that similar innova-tion guilds, as described in this paper, can support large companies in the in-novation race for new software products.
India is the largest democracy in the world and has recently surpassed China to be the highest-populated country, with an estimated 1.425 billion (approximately 18% of the world population). Moreover, India's elderly population is projected to increase to 138 million by 2035. Indian economy is already reeling under the pressure of exorbitant pension liabilities of the government for existing pensioners. As such, India has introduced a National Pension System (NPS), which is a Defined Contribution Scheme for employees joining government service on or after 1st January 2004, bidding adieu to the age-old, tried and tested Old Pension System (OPS) which is a Direct Benefit Scheme, in vogue in India since the British Raj. This is an epoch-making move by the government as it seeks to inculcate Disciplined Saving among the people while significantly reducing the government burden by reducing the Pension Liabilities of the Central and State Governments. This paper aims to analyse various features and intricacies of the NPS and address the claims of various stakeholders like the Central Government, State Government, Employees, Pensioners, etc. In light of the above, and taking cognisance of
Optical clocks have improved their frequency stability and estimated accuracy by more than two orders of magnitude over the best caesium microwave clocks that realise the SI second. Accordingly, an optical redefinition of the second has been widely discussed, prompting a need for the consistency of optical clocks to be verified worldwide. While satellite frequency links are sufficient to compare microwave clocks, a suitable method for comparing high-performance optical clocks over intercontinental distances is missing. Furthermore, remote comparisons over frequency links face fractional uncertainties of a few $10^{-18}$ due to imprecise knowledge of each clock's relativistic redshift, which stems from uncertainty in the geopotential determined at each distant location. Here, we report a landmark campaign towards the era of optical clocks, where, for the first time, state-of-the-art transportable optical clocks from Japan and Europe are brought together to demonstrate international comparisons that require neither a high-performance frequency link nor information on the geopotential difference between remote sites. Conversely, the reproducibility of the clocks after being transporte
To keep up with the pace of innovation, established companies are increasingly relying on internal software startups. However, succeeding with such startups is a challenging task because internal startups need to find a balance between the interests of the company and the interest of the innovator. One approach that is argued to strengthen innovation in existing companies is employee-driven innovation (EDI). This study explores this argument by examining two internal software startups in companies aligned with the principles of EDI and with a strong focus on innovation. The preliminary findings indicate that startups with EDI are characterized by commitment towards innovation, cooperative orientation, and autonomy. The findings suggest that internal software startups may be strengthened when the parent companies practice EDI.
Hydraulic systems have been one of the most used technologies in many industries due to their reliance on incompressible fluids that facilitate energy and power transfer. Within such systems, hydraulic cylinders are prime devices that convert hydraulic energy into mechanical energy. Some of the genuine and very common problems related to hydraulic cylinders are leakages. Leakage in hydraulic systems can cause a drop in pressure, general inefficiency, and even complete failure of such systems. The various ways leakage can occur define the major categorization of leakage: internal and external leakage. External leakage is easily noticeable, while internal leakage, which involves fluid movement between pressure chambers, can be harder to detect and may gradually impact system performance without obvious signs. When leakage surpasses acceptable limits, it is classified as a fault or failure. In such cases, leakage is divided into three categories: no leakage, low leakage, and high leakage. It suggests a fault detection algorithm with the basic responsibility of detecting minimum leakage within the Hydraulic system, and minimizing detection time is the core idea of this paper. In order