Hasil untuk "Public law"

William Law

The rapid advancement of creating Zero-Knowledge (ZK) programs has led to the development of numerous tools designed to support developers. Popular options include being able to write in general-purpose programming languages like Rust from Risc Zero. Other languages exist like Circom, Lib-snark, and Cairo. However, developers entering the ZK space are faced with many different ZK backends to choose from, leading to a steep learning curve and a fragmented developer experience across different platforms. As a result, many developers tend to select a single ZK backend and remain tied to it. This thesis introduces zkSDK, a modular framework that streamlines ZK application development by abstracting the backend complexities. At the core of zkSDK is Presto, a custom Python-like programming language that enables the profiling and analysis of a program to assess its computational workload intensity. Combined with user-defined criteria, zkSDK employs a dynamic selection algorithm to automatically choose the optimal ZK-proving backend. Through an in-depth analysis and evaluation of real-world workloads, we demonstrate that zkSDK effectively selects the best-suited backend from a set of supported ZK backends, delivering a seamless and user-friendly development experience.

Noelle Law, Yuki Miura

Natural disasters are increasing in frequency and severity, causing hundreds of billions of dollars in damage annually and posing growing threats to infrastructure and human livelihoods. Accurate data on roofing materials is critical for modeling building vulnerability to natural hazards such as earthquakes, floods, wildfires, and hurricanes, yet such data remain unavailable. To address this gap, we introduce RoofNet, the largest and most geographically diverse novel multimodal dataset to date, comprising over 51,500 samples from 184 geographically diverse sites pairing high-resolution Earth Observation (EO) imagery with curated text annotations for global roof material classification. RoofNet includes geographically diverse satellite imagery labeled with 14 key roofing types -- such as asphalt shingles, clay tiles, and metal sheets -- and is designed to enhance the fidelity of global exposure datasets through vision-language modeling (VLM). We sample EO tiles from climatically and architecturally distinct regions to construct a representative dataset. A subset of 6,000 images was annotated in collaboration with domain experts to fine-tune a VLM. We used geographic- and material-aware prompt tuning to enhance class separability. The fine-tuned model was then applied to the remaining EO tiles, with predictions refined through rule-based and human-in-the-loop verification. In addition to material labels, RoofNet provides rich metadata including roof shape, footprint area, solar panel presence, and indicators of mixed roofing materials (e.g., HVAC systems). RoofNet supports scalable, AI-driven risk assessment and serves as a downstream benchmark for evaluating model generalization across regions -- offering actionable insights for insurance underwriting, disaster preparedness, and infrastructure policy planning.

Yanka dos Santos Pinto

Este artigo analisou a presença da violência policial nas periferias brasileiras, everificou a importância do hip hop, especificamente o rap, como meio de manifestação e oposição contra os atos abusivos e negligentes do Estado. O método utilizado foi de revisão de literatura, por meio da técnica de pesquisa de documentação indireta, aplicando a abordagem dedutiva, partindo de uma regra geral para um caso concreto. Discutiu-se a seletividade penal e as ações lesivas do Estado, bem como o desenvolvimento do hip hop no Brasil. Examinaram-se cinco faixas do álbum “Convoque o seu Buda”, do rapper Criolo, que retratam a realidade de pessoas marginalizadas socialmente. Concluiu-se que o rap funciona como um instrumento de luta e denúncia às injustiças e violências presentes nos espaços periféricos.

Lilian Gressthy Florencya Apituley, Wishnu Agung Baroto, Valentino Dinatra Soplantila

Introduction: This article will outline how the application of restorative justice in the civil law system, the common law system, and the Indonesian legal system compares. Purposes of the Research: This study aims to provide a comprehensive comparison of the regulation and implementation of restorative justice across three legal systems - civil law, common law, and Indonesia’s hybrid legal system - and to identify best practices and challenges that can inform the development of restorative justice in diverse legal contexts. Methods of the Research: The study uses a normative legal method, combining a legal concept approach to examine the philosophical and ethical foundations of restorative justice with a statutory approach to analyze formal legal mechanisms. This methodology links legal theory with practice while highlighting the integration of normative principles within Indonesia’s socio-cultural context, including Pancasila and customary law. Results of the Research: This study compares restorative justice implementation in civil law, common law, and Indonesia’s legal system. Civil law is rigid and procedural, while common law allows flexible mechanisms such as victim–offender mediation. In Indonesia, despite Supreme Court Rule Number 1 of 2024, challenges include limited understanding among law enforcement, inconsistent application, and insufficient institutional support. Strengthening implementation requires harmonized regulations, professional training, community-based mechanisms rooted in local wisdom and customary law, and public awareness. Indonesia’s model highlights a transformative approach that integrates restorative principles with national values of humanity, justice, and social harmony.

Miguel Fuentes, Brett Mullins, Ryan McKenna et al.

Mechanisms for generating differentially private synthetic data based on marginals and graphical models have been successful in a wide range of settings. However, one limitation of these methods is their inability to incorporate public data. Initializing a data generating model by pre-training on public data has shown to improve the quality of synthetic data, but this technique is not applicable when model structure is not determined a priori. We develop the mechanism jam-pgm, which expands the adaptive measurements framework to jointly select between measuring public data and private data. This technique allows for public data to be included in a graphical-model-based mechanism. We show that jam-pgm is able to outperform both publicly assisted and non publicly assisted synthetic data generation mechanisms even when the public data distribution is biased.

Aviral Damle, Thomas Law

This paper presents a speculative model exploring the behavior of quantum information for particles entering closed timelike curves (CTCs) in Kerr-Newman spacetime. We apply Gavassino's restoration principle to derive a theoretical framework for cyclic information dynamics within these extreme gravitational environments. Our model focuses specifically on particles that enter CTCs near the inner horizon of a Kerr-Newman black hole, examining how such curves might affect quantum state evolution, entanglement preservation, and information retention.

Jonathan Bright, Florence E. Enock, Saba Esnaashari et al.

Generative AI has the potential to transform how public services are delivered by enhancing productivity and reducing time spent on bureaucracy. Furthermore, unlike other types of artificial intelligence, it is a technology that has quickly become widely available for bottom-up adoption: essentially anyone can decide to make use of it in their day to day work. But to what extent is generative AI already in use in the public sector? Our survey of 938 public service professionals within the UK (covering education, health, social work and emergency services) seeks to answer this question. We find that use of generative AI systems is already widespread: 45% of respondents were aware of generative AI usage within their area of work, while 22% actively use a generative AI system. Public sector professionals were positive about both current use of the technology and its potential to enhance their efficiency and reduce bureaucratic workload in the future. For example, those working in the NHS thought that time spent on bureaucracy could drop from 50% to 30% if generative AI was properly exploited, an equivalent of one day per week (an enormous potential impact). Our survey also found a high amount of trust (61%) around generative AI outputs, and a low fear of replacement (16%). While respondents were optimistic overall, areas of concern included feeling like the UK is missing out on opportunities to use AI to improve public services (76%), and only a minority of respondents (32%) felt like there was clear guidance on generative AI usage in their workplaces. In other words, it is clear that generative AI is already transforming the public sector, but uptake is happening in a disorganised fashion without clear guidelines. The UK's public sector urgently needs to develop more systematic methods for taking advantage of the technology.

Jasmina Karabegovic

This paper introduces an explicit algorithm for computing perfect public equilibrium (PPE) payoffs in repeated games with imperfect public monitoring, public randomization, and discounting. The method adapts the established framework by Abreu, Pearce, and Stacchetti (1990) into a practical tool that balances theoretical accuracy with computational efficiency. The algorithm simplifies the complex task of identifying PPE payoff sets for any given discount factor δ. A stand-alone implementation of the algorithm can be accessed at: https://github.com/jasmina-karabegovic/IRGames.git.

M. M. Makarenko

The article describes the place of the State Bureau of Investigation in the system of state bodies of Ukraine, in particular, the content of the categories “state bodies” and “public authorities” is defined, the system of state bodies is outlined, and the specifics of law enforcement agencies are clarified. It is noted that state bodies (public authorities) are characterised by their own specific features, among which the following are distinguished: a set of state bodies form the apparatus of the State, and therefore each of them is one of the elements of the integral system of the State apparatus; they are created and operate on the basis of relevant regulations, in the person of one person (citizen) or a group of citizens; each structural unit (state body) is endowed with unique powers of state power; they are created with the aim of performing tasks and It is also emphasised that the State Bureau of Investigation is a law enforcement agency. Therefore, the place of the State Bureau of Investigation in the system of state bodies is determined by its legal status as a central executive body, as evidenced by the specifics of its activities, since it was established for the special purpose of preventing and combating crimes committed by special categories of subjects, as well as war crimes, which is consistent with the law enforcement function of the state and has nothing to do with either legislative or judicial activities; as a law enforcement agency in view of the fact that its main and, in fact, the only task is to counteract criminal offences within its competence; as a state body with a special status, as evidenced by its tasks, powers and the fact that it carries out its activities independently and independently of other executive authorities in the organisational and functional aspect.

Ali Reza Nasrollahi, Mostafa Mansourian

Introduction The concept of public rights is commonly understood as the rights of the general public. However, when scrutinized more closely, this notion becomes somewhat ambiguous, leading to questions and disagreements among legal doctrines and jurists. This ambiguity revolves around the precise definition of the term, its instances, and its scope, such as whether it pertains solely to criminal law or extends to non-criminal law. Examining the scope of public rights reveals numerous and sometimes conflicting interpretations. Legal and judicial opinions on the scope of public rights generally fall into two general yet conflicting approaches, namely narrow and broad. Given the divergent viewpoints, it is crucial to adopt a valid interpretive approach within the legal system to establish a systematic framework aimed at reaching an understanding. Objective consequentialism, as a normative-based interpretive method, serves as a valuable theoretical tool for evaluating these approaches. In this line, the present study sought to address the following research question: Which of the two approaches, narrow or broad, to the scope of public rights is deemed acceptable from the perspective of objective consequentialism? Literature Review Legal and judicial opinions concerning public rights can generally be categorized into two competing approaches. On one hand, there are viewpoints advocating for a narrow interpretation, which suggests limiting the scope of public rights in times of uncertainty. On the other hand, there are perspectives that advocate for a broader understanding of public rights, incorporating a wider range of interpretations and instances. Although there is no coherent and methodical discussion on this matter in legal literature thus far, various schools of legal interpretation have debated different methods, such as objective consequentialism. In objective consequentialism, the focus lies on discerning the purpose of the law, so the interpreter, whether a judge or a lawyer, seeks to deduce the purpose of the law from the text itself and other relevant sources. Subsequently, they interpret provisions of the law in light of the general purpose. In this method, justification for interpretation is grounded on the objective purpose behind establishing the rule. The purpose of the law can be inferred from the very text of the law, including its title, preamble, or relevant chapters. Furthermore, the purpose may be predestined or assumed, with implications being inferred through logical or judicious readings of the text of the law—based on the premise that the legislator is judicious. Therefore, it is assumed that the legislator has intended for legal provisions to have meaningful effects rather than being rendered null or futile. Objective consequentialism seeks to uncover the underlying purpose behind a given law or provision.     Materials and Methods The present study relied on objective consequentialism, which is an interpretive method based on the normative ground, in order to evaluate the two approaches concerning the scope of pubic rights. The study aimed to address the following research question: Which of the two approaches, narrow or broad, to the scope of public rights is deemed acceptable from the perspective of objective consequentialism? Results and Discussion According to objective consequentialism, fostering a broad understanding of the concept of public rights while maintaining a systematic view of functions of the judiciary body can result in an appropriately balanced understanding aimed at claiming public rights. The present study synthesized the opinions sharing a common essence and overarching direction, discussing the existing legal approaches regarding the scope of public rights. Additionally, considering the principles of the Constitution, a hypothesis (called the conceptual approach derived from purposiveness) was formulated and tested about the distinction between the scope of public rights—as outlined in the Constitution—and the restoration of public rights. The scope of public rights can be either narrowed or expanded, considering the purpose of the law and of justice outlined in each instance, as well as the implications derived from a judicious interpretation of the law. Conclusion Public rights can be re-evaluated with an eye to the purpose of the law, hence interpreted as rights and interests arising from the objective goal of the law. In this light, the scope of public rights becomes meaningful considering the purpose of the law, the justice it guarantees in each instance, and the implications stemming from the judicious interpretation of the law. Therefore, there two central points here: rights (the conceptual standpoint) and the negation of oppression and injustice (the functional standpoint). From the conceptual standpoint, public rights extend to legal rights. Yet the functional standpoint would include those instances of rights that have been or are about to be unjustly taken away from their rightful owners, making it impossible for the beneficiaries (whether individuals or groups) to reclaim them.

Luis Jiro Suzuri Hernández, Alexa Villavicencio Queijeiro, Valeria Alexandra Alonzo Matamoros

En virtud de la importancia que, para la comunidad forense, tiene la perspectiva de las ciencias forenses planteada en el artículo publicado por Roux y Col. 2022, la Editora de la RCFH, considero importante traducir al español este trabajo y ponerlo a disposición de nuestros lectores. Este artículo es la traducción al español del documento original en inglés, titulado: “The Sydney Declaration – Revisiting the essence of forensic science through its fundamental principles”, escrito por Claude Roux, Rebecca Bucht, Frank Crispino, Peter De Forest, Chris Lennard, Pierre Margot, Michelle D. Miranda, Niamh NicDaeid, Olivier Ribaux, Alastair Ross y Sheila Willis, y publicado en la revista Forensic Science International, volumen 332, año 2022, cuyo original está disponible en: https://doi.org/10.1016/j.forsciint.2022.111182 La traducción fue realizada en marzo del 2024 por Luis Jiro Suzuri Hernández y Alexa Villavicencio Queijeiro, de la Escuela Nacional de Ciencias Forenses de la Universidad Nacional Autónoma de México, y fue revisado, editado y corregido por la Licda. Valeria Alexandra Alonzo Matamoros egresada de la carrera de lenguas extranjeras, de la Universidad Nacional Autónoma de Honduras. Se agradece a Claude Roux, por brindarnos su autorización para publicar la traducción al español en nuestra revista.

Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld et al.

Irregularities in public health data streams (like COVID-19 Cases) hamper data-driven decision-making for public health stakeholders. A real-time, computer-generated list of the most important, outlying data points from thousands of daily-updated public health data streams could assist an expert reviewer in identifying these irregularities. However, existing outlier detection frameworks perform poorly on this task because they do not account for the data volume or for the statistical properties of public health streams. Accordingly, we developed FlaSH (Flagging Streams in public Health), a practical outlier detection framework for public health data users that uses simple, scalable models to capture these statistical properties explicitly. In an experiment where human experts evaluate FlaSH and existing methods (including deep learning approaches), FlaSH scales to the data volume of this task, matches or exceeds these other methods in mean accuracy, and identifies the outlier points that users empirically rate as more helpful. Based on these results, FlaSH has been deployed on data streams used by public health stakeholders.

Matan Gilboa

We complete the characterization of the computational complexity of equilibrium in public goods games on graphs. In this model, each vertex represents an agent deciding whether to produce a public good, with utility defined by a "best-response pattern" determining the best response to any number of productive neighbors. We prove that the equilibrium problem is NP-complete for every finite non-monotone best-response pattern. This answers the open problem of [Gilboa and Nisan, 2022], and completes the answer to a question raised by [Papadimitriou and Peng, 2021], for all finite best-response patterns.

Vartika Singh, Veeraruna Kavitha

Celebrities can significantly influence the public towards any desired outcome. In a bid to tackle an infectious disease, a leader (government) exploits such influence towards motivating a fraction of public to get vaccinated, sufficient enough to ensure eradication. The leader also aims to minimize the vaccinated fraction of public (that ensures eradication) and use minimal incentives to motivate the influencers; it also controls vaccine-supply-rates. Towards this, we consider a three-layered Stackelberg game, with the leader at the top. A set of influencers at the middle layer are involved in a stochastic vaccination game driven by incentives. The public at the bottom layer is involved in an evolutionary game with respect to vaccine responses. We prove the disease can always be eradicated once the public is sufficiently sensitive towards the vaccination choices of the influencers -- with a minimal fraction of public vaccinated. This minimal fraction depends only on the disease characteristics and not on other aspects. Interestingly, there are many configurations to achieve eradication, each configuration is specified by a dynamic vaccine-supply-rate and a number -- this number represents the count of the influencers that needs to be vaccinated to achieve the desired influence. Incentive schemes are optimal when this number equals all or just one; the former curbs free-riding among influencers while the latter minimizes the dependency on influencers.

Alexander Spangher, Emilio Ferrara, Ben Welsh et al.

Journalists must find stories in huge amounts of textual data (e.g. leaks, bills, press releases) as part of their jobs: determining when and why text becomes news can help us understand coverage patterns and help us build assistive tools. Yet, this is challenging because very few labelled links exist, language use between corpora is very different, and text may be covered for a variety of reasons. In this work we focus on news coverage of local public policy in the San Francisco Bay Area by the San Francisco Chronicle. First, we gather news articles, public policy documents and meeting recordings and link them using probabilistic relational modeling, which we show is a low-annotation linking methodology that outperforms other retrieval-based baselines. Second, we define a new task: newsworthiness prediction, to predict if a policy item will get covered. We show that different aspects of public policy discussion yield different newsworthiness signals. Finally we perform human evaluation with expert journalists and show our systems identify policies they consider newsworthy with 68% F1 and our coverage recommendations are helpful with an 84% win-rate.

Antonio J. Di Scala, Carlo Sanna

MinRank is an NP-complete problem in linear algebra whose characteristics make it attractive to build post-quantum cryptographic primitives. Several MinRank-based digital signature schemes have been proposed. In particular, two of them, MIRA and MiRitH, have been submitted to the NIST Post-Quantum Cryptography Standardization Process. In this paper, we propose a key-generation algorithm for MinRank-based schemes that reduces the size of the public key to about 50% of the size of the public key generated by the previous best (in terms of public-key size) algorithm. Precisely, the size of the public key generated by our algorithm sits in the range of 328-676 bits for security levels of 128-256 bits. We also prove that our algorithm is as secure as the previous ones.

Yiling Chen, Biaoshuai Tao, Fang-Yi Yu

When can cooperation arise from self-interested decisions in public goods games? And how can we help agents to act cooperatively? We examine these classical questions in a pivotal participation game, a variant of public good games, where heterogeneous agents make binary participation decisions on contributing their endowments, and the public project succeeds when it has enough contributions. We prove it is NP-complete to decide the existence of a cooperative Nash equilibrium such that the project succeeds. We also identify two natural special scenarios where this decision problem is tractable. We then propose two algorithms to help cooperation in the game. Our first algorithm adds an external investment to the public project, and our second algorithm uses matching funds. We show that the cost to induce a cooperative Nash equilibrium is near-optimal for both algorithms. Finally, the cost of matching funds can always be smaller than the cost of adding an external investment. Intuitively, matching funds provide a greater incentive for cooperation than adding an external investment does.

Michael Law, Ya'acov Ritov

We consider a sparse high-dimensional varying coefficients model with random effects, a flexible linear model allowing covariates and coefficients to have a functional dependence with time. For each individual, we observe discretely sampled responses and covariates as a function of time as well as time invariant covariates. Under sampling times that are either fixed and common or random and independent amongst individuals, we propose a projection procedure for the empirical estimation of all varying coefficients. We extend this estimator to construct confidence bands for a fixed number of varying coefficients.

Piotr Gramacki

The role of spatial data in tackling city-related tasks has been growing in recent years. To use them in machine learning models, it is often necessary to transform them into a vector representation, which has led to the development in the field of spatial data representation learning. There is also a growing variety of spatial data types for which representation learning methods are proposed. Public transport timetables have so far not been used in the task of learning representations of regions in a city. In this work, a method is developed to embed public transport availability information into vector space. To conduct experiments on its application, public transport timetables were collected from 48 European cities. Using the H3 spatial indexing method, they were divided into micro-regions. A method was also proposed to identify regions with similar characteristics of public transport offers. On its basis, a multi-level typology of public transport offers in the regions was defined. This thesis shows that the proposed representation method makes it possible to identify micro-regions with similar public transport characteristics between the cities, and can be used to evaluate the quality of public transport available in a city.

Hui Yan, Ping Xiang, Min Shen

Hair analysis has been mainly used to document drug use history in abusers, drug-facilitated crime cases, doping control analysis and postmortem toxicology in the fields of forensic toxicology, clinical toxicology, and doping control. Hair analysis has also gained more attention in the last 30 years in China. Relevant technology has been promoted as more research has appeared concerning hair analysis, and consensus has been sought among forensic toxicologists regarding aspects such as hair decontamination treatment, detection of abused substances in hair, segmental hair analysis and interpretation of analytical results. However, there are still some limitations in the estimation of drug intake time and frequency by segmental hair analysis due to the different growth cycles evident within a bundle of hairs, the drug incorporation mechanism and sampling errors. Microsampling and imaging mass spectrometry (IMS) technology based on a single hair may be a good choice to estimate drug intake time more accurately. Analysis of hair root samples may also be used to document acute poisoning in postmortem toxicology, and the analysis of the hair shaft can document long-term use of drugs depending on the length of the hair being evaluated.