Watermarking schemes for large language models (LLMs) have been proposed to identify the source of the generated text, mitigating the potential threats emerged from model theft. However, current watermarking solutions hardly resolve the trust issue: the non-public watermark detection cannot prove itself faithfully conducting the detection. We observe that it is attributed to the secret key mostly used in the watermark detection -- it cannot be public, or the adversary may launch removal attacks provided the key; nor can it be private, or the watermarking detection is opaque to the public. To resolve the dilemma, we propose PVMark, a plugin based on zero-knowledge proof (ZKP), enabling the watermark detection process to be publicly verifiable by third parties without disclosing any secret key. PVMark hinges upon the proof of `correct execution' of watermark detection on which a set of ZKP constraints are built, including mapping, random number generation, comparison, and summation. We implement multiple variants of PVMark in Python, Rust and Circom, covering combinations of three watermarking schemes, three hash functions, and four ZKP protocols, to show our approach effectively works under a variety of circumstances. By experimental results, PVMark efficiently enables public verifiability on the state-of-the-art LLM watermarking schemes yet without compromising the watermarking performance, promising to be deployed in practice.
Misinformation poses a growing global threat to institutional trust, democratic stability, and public decision-making. While prior research has often portrayed social media as a channel for spreading falsehoods, less is known about the conditions under which it may instead constrain misinformation by enhancing transparency and accountability. Here we show this dual potential in the context of local governments' GDP reporting in China, where data falsifications are widespread. Analyzing official reports from 2011 to 2019, we find that local governments have overstated GDP on average. However, after adopting social media for public communications, the extent of misreporting declines significantly but only in regions where the public scrutiny over political matters is high. In such regions, social media increases the cost of misinformation by facilitating greater information disclosure and bottom-up monitoring. In contrast, in regions with low public scrutiny, adopting social media can exacerbate data manipulation. These findings challenge the prevailing view that social media primarily amplifies misinformation and instead highlight the importance of civic engagement as a moderating force. Our findings show a boundary condition for the spread of misinformation and offer insights for platform design and public policy aimed at promoting accuracy and institutional accountability.
The most effective differentially private machine learning algorithms in practice rely on an additional source of purportedly public data. This paradigm is most interesting when the two sources combine to be more than the sum of their parts. However, there are settings such as mean estimation where we have strong lower bounds, showing that when the two data sources have the same distribution, there is no complementary value to combining the two data sources. In this work we extend the known lower bounds for public-private learning to setting where the two data sources exhibit significant distribution shift. Our results apply to both Gaussian mean estimation where the two distributions have different means, and to Gaussian linear regression where the two distributions exhibit parameter shift. We find that when the shift is small (relative to the desired accuracy), either public or private data must be sufficiently abundant to estimate the private parameter. Conversely, when the shift is large, public data provides no benefit.
Martyna Brzoza, Julia Stawińska-Dudek, Piotr Mikołajczyk
et al.
Introduction and purpose:
Throughout the years xylitol has become a commonly used sugar substitute. Presenting similar level of sweetness to sucrose, it serves as a much healthier alternative. The aim of this article is to expand knowledge about the beneficial impact of xylitol on human health mainly focusing on aspects regarding oral health.
Materials and methods:
A thorough analysis of scientific databases such as PubMed and Google Scholar has been undertaken using the key words chosen based on their relevance to the matter in subject. Studies since the year 2017 have been analyzed in order to obtain the most up to date information.
The state of knowledge:
Xylitol, being the sweetest of all polyols, has been prevalently used as a sugar substitute due to its various favorable effects on both oral and general health. It may be incorporated into daily oral care regimen as a preventive measure counteracting caries development both in adults and in children. According to the investigated studies, it also acts as a prebiotic, presents low caloric value as well as low glycemic and insulinemic indices.
Conclusions:
Xylitol is characterized by its facile availability in various forms such as for example chewing gums, pastilles, toothpastes, wipes and mouth rinses. It is derived either from natural, mainly plant based sources, or it may also be extracted synthetically. Due to those reasons and its favorable properties, it may serve as a prevalent sugar substitute. Used in appropriate doses it is safe regardless of age and presents multiple advantageous effects on various aspects of human health.
James F Thrasher, Tara L Queen, Jennifer Cornacchione Ross
et al.
Background People who smoke cigars often have misperceptions about the associated risks, contributing to rises in smoking rates. This study investigates the perceived warning effectiveness (PWE) of health warning labels (HWLs) on cigar packages. We tested the impact of warning type and warning size in the HWLs on PWE and other health outcomes.Data and methods In a between-subjects experimental design, participants (n=809) who used little cigars or cigarillos in the past 30 days were randomly assigned to one of four conditions: text-only at 30% size, pictorial+text warning at 30% size, text-only at 50% size and pictorial+text warning at 50% size. In each condition, participants rated six cigarillo HWLs on PWE, self-reported learning, thinking about risks, new knowledge, perceived enjoyment and negative affect. Reactance to the labels was also measured. Data were analysed with mixed-effects models.Results Pictorial+text cigarillo HWLs were deemed more effective than text-only HWLs in PWE (b=0.34, SE=0.08, p<0.001), self-reported learning (b=0.20, SE=0.08, p=0.01), thinking about risks (b=0.18, SE=0.08, p=0.03) and new knowledge (b=0.34, SE=0.12, p<0.01). They also elicited more negative affect than text-only warnings (b=0.39, SE=0.08, p<0.001). Warning size did not impact outcomes, and neither warning type nor size predicted perceived enjoyment of smoking cigarillos or reactance to the warnings.Conclusion Including images with text warning statements for cigarillos can increase PWE. Our findings provide important insights for the US Food and Drug Administration and international regulatory agencies in designing new HWLs for cigars that can more effectively communicate smoking risks, address misinformation and potentially reduce cigar smoking.
The study analyses the legislative changes made by the Act of 7 July 2023 amending the Act – the Code of Civil Procedure, the Act – the Law on the System of Common Courts, the Act – the Code of Criminal Procedure and some other acts, relating to the institution of subsidiary prosecution, concerning the discontinuation of criminal proceedings due to the lack of a complaint of an authorised accuser by a decision issued at a session or a main hearing. They were related to the introduction of the provisions of Article 339 § 3b and Article 368a to the Code of Criminal Procedure. The aim of the analysis undertaken was to assess the legitimacy of the changes made. The research carried out by the dogmatic-legal method led to the conclusion that the two new articles are inconsistent with each other, and that the changes introduced are unlikely to improve the quality of criminal proceedings conducted following the filing of a subsidiary indictment.
Law, Political institutions and public administration (General)
Public discourse about technological accidents is dominated by the popular explanation through the "human factor". It makes the essential assertion that a human, by definition, is prone to error, but a machine is not. In the field of autonomous vehicles, it emerged as a result of first the US media- and subsequently, stakeholders-demodalizing the results of a 2008 US National Highway Safety Administration study that claimed drivers were the critical cause of 94% of all road traffic accidents. In this article, we want to show what theoretical and socio-political problems exist with an explanation through the "human factor”. To this end, we consider an alternative in the form of the concept of a technological system as a conflicting set of rules that follow the contextualizing practices proposed by the British sociologist Brian Wynne. We compare this interpretation with Robert Merton's explanation of deviant behavior in the 1930 s. Criticizing the utilitarians, Merton shows that deviations are caused by contradictions in the socio-cultural structure of society. In both conceptual schemes, failures are presented as the result of relational effects of tension and contradiction between the elements of the systems. For a different and more realistic alternative of dealing with accidents, we highlight the ideas of Annemarie Mol and John Law. The latter, analysing accidents, identified four modes of determining the good within disputes after accidents: mobile utopia, absolutism, managerialism, and practical manipulation. We show that both the explanations through the human factor, Merton's theory of deviation-and, to some extent, STS-lean towards utopian regimes (the first three), while the latter regime, based on an ontological turn, proposes a radical project of changing the modes of explanation and accusations of accidents: this makes it possible to articulate different relationships between the ontologies of accidents, to make non-utopian versions of technologies more real and public.
We initiate the study of locally differentially private (LDP) learning with public features. We define semi-feature LDP, where some features are publicly available while the remaining ones, along with the label, require protection under local differential privacy. Under semi-feature LDP, we demonstrate that the mini-max convergence rate for non-parametric regression is significantly reduced compared to that of classical LDP. Then we propose HistOfTree, an estimator that fully leverages the information contained in both public and private features. Theoretically, HistOfTree reaches the mini-max optimal convergence rate. Empirically, HistOfTree achieves superior performance on both synthetic and real data. We also explore scenarios where users have the flexibility to select features for protection manually. In such cases, we propose an estimator and a data-driven parameter tuning strategy, leading to analogous theoretical and empirical results.
A tool to improve the effectiveness and the efficiency of public spending is proposed here. In the 19th century banknotes had a serial number. However, in modern days the use of digital transactions that do not use physical currency has opened the possibility to digitally track almost each cent of the economy. In this article a serial number or tracking number for each cent, pence or any other monetary unit of the economy is proposed. Then, almost all cents can be tracked by recording the transactions in a public distributed ledger, rather than recording the amount of the transaction, the information recorded in the block of the transaction is the actual serial number or tracking number for each cent that changes ownership. In order to keep the privacy of the transaction, only generic identification of private companies and individuals are recorded along with generic information about the concept of transaction, the region and the date/time. A secondary public distributed ledger whose blocks are identified by a hash reference that is recorded in the bank statement available to the payer and the payee allows for checking the accuracy of the first public distributed ledger by comparing the transactions made in one day, one region and one type of concept. However, the transactions made or received by the government are recorded with a much higher level of detail in the first ledger and a higher level of disclosure in the second ledger. The result is a tool that is able to accurately track public spending, to keep privacy of individuals and companies and to make statistical analysis and experiments or real tests in the economy of a country. This tool has the potential to assist public policymakers in demonstrating the societal benefits resulting from their policies, thereby enabling more informed decision-making for future policy endeavours.
Abordam-se aspectos da decisão da Corte Interamericana de Direitos Humanos, no caso Moradores de La Oroya contra o Peru, publicada em março de 2024, afirmando a justiciabilidade do direito ao meio ambiente como um direito difuso e reconhecendo a responsabilidade internacional do Peru (Estado parte) pela omissão em relação às medidas de prevenção e na prestação de informações à população exposta. Trata-se de precedente de relevância emitido pela Corte Internacional para a defesa do meio ambiente e dos direitos humanos, abrindo alvissareiras possibilidades de um novo e efetivo espaço para a afirmação de princípios caros ao Direito Sanitário e a preservação da vida.
Submissão: 09/05/24| Revisão: 10/05/24| Aprovação: 10/05/24
Pablo Valverde, Jaime Fernandez, Edwin Buenaño
et al.
We investigate an agent-based model for the emergence of corruption in public contracts. There are two types of agents: business people and public servants. Both business people and public servants can adopt two strategies: corrupt or honest behavior. Interactions between business people and public servants take place through defined payoff rules. Either type of agent can switch between corrupt or honest strategies by comparing their payoffs after interacting. We measure the level of corruption in the system by the fractions of corrupt and honest agents for asymptotic times. We study the effects of the group size of the interacting agents, the dispersion with respect to the average salary of the public servants, and a parameter representing the institutional control of corruption. We characterize the fractions of honest and corrupt agents as functions of these variables. We construct phase diagrams for the level of corruption in the system in terms of these variables, where three collective states can be distinguished: i) a phase where corruption dominates; ii) a phase where corruption remains in less than $50\%$ of the agents; and iii) a phase where corruption disappear. Our results indicate that a combination of large group sizes of interacting servants and business people and small dispersion of the salaries of public servants, contributes to the decrease of systemic corruption in public contracts.
This paper proposes a generalised framework for density estimation in large networks with measurable spatiotemporal variance in edge weights. We solve the stochastic shortest path problem for a large network by estimating the density of the edge weights in the network and analytically finding the distribution of a path. In this study, we employ Gaussian Processes to model the edge weights. This approach not only reduces the analytical complexity associated with computing the stochastic shortest path but also yields satisfactory performance. We also provide an online version of the model that yields a 30 times speedup in the algorithm's runtime while retaining equivalent performance. As an application of the model, we design a real-time trip planning system to find the stochastic shortest path between locations in the public transit network of Delhi. Our observations show that different paths have different likelihoods of being the shortest path at any given time in a public transit network. We demonstrate that choosing the stochastic shortest path over a deterministic shortest path leads to savings in travel time of up to 40\%. Thus, our model takes a significant step towards creating a reliable trip planner and increase the confidence of the general public in developing countries to take up public transit as a primary mode of transportation.
Paolo Ciancarini, Raffaele Giancarlo, Gennaro Grimaudo
Digital Transformation (DT) is the process of integrating digital technologies and solutions into the activities of an organization, whether public or private. This paper focuses on the DT of public sector organizations, where the targets of innovative digital solutions are either the citizens or the administrative bodies or both. This paper is a guided tour for Computer Scientists, as the digital transformation of the public sector involves more than just the use of technology. While technological innovation is a crucial component of any digital transformation, it is not sufficient on its own. Instead, DT requires a cultural, organizational, and technological shift in the way public sector organizations operate and relate to their users, creating the capabilities within the organization to take full advantage of any opportunity in the fastest, best, and most innovative manner in the ways they operate and relate to the citizens. Our tutorial is based on the results of a survey that we performed as an analysis of scientific literature available in some digital libraries well known to Computer Scientists. Such tutorial let us to identify four key pillars that sustain a successful DT: (open) data, ICT technologies, digital skills of citizens and public administrators, and agile processes for developing new digital services and products. The tutorial discusses the interaction of these pillars and highlights the importance of data as the first and foremost pillar of any DT. We have developed a conceptual map in the form of a graph model to show some basic relationships among these pillars. We discuss the relationships among the four pillars aiming at avoiding the potential negative bias that may arise from a rendering of DT restricted to technology only. We also provide illustrative examples and highlight relevant trends emerging from the current state of the art.
Penelitian ini bertujuan untuk mengetahui diskripsi kasus dan bagaimana pertimbangan hakim dalam Penetapan Pengadilan Agama Bogor dengan perkara Nomor 54/Pdt.P/2021/PA.Bgr. Adapun pertanyaan penelitian 1) Bagaimana duduk perkara dispensasi kawin di Pengadilan Agama Bogor. 2) Bagaiaman analisis pertimbangan hakim dalam penetapan dispensasi kawin dari segi aspek Filosofis, Yuridis, dan Sosiologis. Penelitian ini menggunkan metode kualitatif deskriptif analisis. Sumber data menggunakan primer dan skunder. Teknik pengumpulan data dengan wawancara, observasi, dan dokumentasi. Penelitian ini menggunakan kajian teori pertimbangan hakim dalam Penetapan pengadilan agama, yang mana sudah menentukan bahwa Penetapan hakim harus mempertimbangkan sebagai aspek filosofis, yurisis, dan sosiologis, sehingga keadilan yang ingin dicapai, diwujudkan, dan dipertanggungjawabkan dalam Penetapan hakim. Hasil penelitian menunjukkan bahwa: Pertama, pertimbangan hakim dalam memberikan dispensasi kawin sebagaimana Undang-Undang Nomor 16 Tahun 2019 tentang perubahan atas Undang-Undang Nomor 1 Tahun 1974 Tentang Perkawinan, di mana umur pria dan wanita harus mencapai usia 19 (sembilan belas) tahun. Maka melangsukan perkawinannya para mohon harus mendapatkan izin dispensasi kawin dari pengadilan sesuai ketentuan pasal 7 ayat (2) Undang-Undang Perkawinan. Kedua, Pengadilan Agama Bogor memberikan izin dipensasi kawin karena Para pemohon sudah memiliki hubungan yang sangat erat, supaya menjaga agar tidak terjadi hal-hal yang dilarang oleh Agama dan peraturan perundang-undangan.
Jurisprudence. Philosophy and theory of law, Islamic law
Kétévi Adiklè Assamagan, Mateus Carneiro, Sarah Demers
et al.
This Snowmass21 Contributed Paper addresses the structural changes that need to occur in the many groups and organizations that intersect with the US particle physics community to enable impactful public engagement to flourish. The impetus for these changes should come from the particle physics community, which should acknowledge the importance of public engagement and act on the recommendations in this Snowmass contributed paper. Scientists have expressed frustration at the barriers, penalties and lack of support that discourage them from participating in public engagement. In this paper, we provide many ways to create a supportive, enabling atmosphere for public engagement among physicists.
Nik Khadijah Nik Aznan, John Brennan, Daniel Bell
et al.
Social distancing in public spaces has become an essential aspect in helping to reduce the impact of the COVID-19 pandemic. Exploiting recent advances in machine learning, there have been many studies in the literature implementing social distancing via object detection through the use of surveillance cameras in public spaces. However, to date, there has been no study of social distance measurement on public transport. The public transport setting has some unique challenges, including some low-resolution images and camera locations that can lead to the partial occlusion of passengers, which make it challenging to perform accurate detection. Thus, in this paper, we investigate the challenges of performing accurate social distance measurement on public transportation. We benchmark several state-of-the-art object detection algorithms using real-world footage taken from the London Underground and bus network. The work highlights the complexity of performing social distancing measurement on images from current public transportation onboard cameras. Further, exploiting domain knowledge of expected passenger behaviour, we attempt to improve the quality of the detections using various strategies and show improvement over using vanilla object detection alone.
BackgroundThe aging population conundrum and the gradual weakening of older adults' health and ability to obtain resources as they age have drawn attention to this population's health. Older adults' health relates not only to their own quality of life, but also to the development of families/society.MethodsWe analyzed micro data from the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study Follow-up Questionnaire, using the probit model, ordinary least squares model, and other methods.Results and ConclusionsBoth formal and informal social support significantly impacted the physical and mental health of Chinese older adults, and the community environment moderated this relationship. To build a reasonable and effective social support system for older adults and improve their health, we suggest that stakeholders should continue to strengthen the formal and informal social support provided to older adults; they should also build a community-based care system, which will allow for the moderating role of community environment on the relationship between social support and older adults' health. Family and social support factors are important for older adults' health. We should enable the moderating role of community environment on the relationship between social support and health to be fully exerted, as well as build a community-based pension system.
Sivakumar Vishnuvardhan Mambakkam, Saadia Nasir, Wilder Acuna
et al.
The discovery of topological insulators (TIs) and their unique electronic properties has motivated research into a variety of applications, including quantum computing. It has been proposed that TI surface states will be energetically discretized in a quantum dot nanoparticle. These discretized states could then be used as basis states for a qubit that is more resistant to decoherence. In this work, prototypical TI Bi2Se3 nanoparticles are grown on GaAs (001) using the droplet epitaxy technique, and we demonstrate the control of nanoparticle height, area, and density by changing the duration of bismuth deposition and substrate temperature. Within the growth window studied, nanoparticles ranged from 5-15 nm tall with an 8-18nm equivalent circular radius, and the density could be relatively well controlled by changing the substrate temperature and bismuth deposition time.
The Internet contains a wealth of public opinion on food safety, including views on food adulteration, food-borne diseases, agricultural pollution, irregular food distribution, and food production issues. In order to systematically collect and analyse public opinion on food safety, we developed IFoodCloud, a platform for the real-time sentiment analysis of public opinion on food safety in China. It collects data from more than 3,100 public sources that can be used to explore public opinion trends, public sentiment, and regional attention differences of food safety incidents. At the same time, we constructed a sentiment classification model using multiple lexicon-based and deep learning-based algorithms integrated with IFoodCloud that provide an unprecedented rapid means of understanding the public sentiment toward specific food safety incidents. Our best model's F1-score achieved 0.9737. Further, three real-world cases are presented to demonstrate the application and robustness. IFoodCloud could be considered a valuable tool for promote scientisation of food safety supervision and risk communication.