Limit Laws Research Articles

Health, safety, and socioeconomic impacts of cannabis liberalization laws: An evidence and gap map.

Globally, cannabis laws and regulations are rapidly changing. Countries are increasingly permitting access to cannabis under various decriminalization, medicalization, and legalization laws. With strong economic, public health, and social justice incentives driving these domestic cannabis policy reforms, liberalization trends are bound to continue. However, despite a large and growing body of interdisciplinary research addressing the policy-relevant health, safety, and socioeconomic consequences of cannabis liberalization, there is a lack of robust primary and systematic research that comprehensively investigates the consequences of these reforms. This evidence and gap map (EGM) summarizes the empirical evidence on cannabis liberalization policies. Primary objectives were to develop a conceptual framework linking cannabis liberalization policies to relevant outcomes, descriptively summarize the empirical evidence, and identify areas of evidence concentration and gaps. We comprehensively searched for eligible English-language empirical studies published across 23 academic databases and 11 gray literature sources through August 2020. Additions to the pool of potentially eligible studies from supplemental sources were made through November 2020. The conceptual framework for this EGM draws upon a legal epidemiological perspective highlighting the causal effects of law and policy on population-level outcomes. Eligible interventions include policies that create or expand access to a legal or decriminalized supply of cannabis: comprehensive medical cannabis laws (MCLs), limited medical cannabidiol laws (CBDLs), recreational cannabis laws (RCLs), industrial hemp laws (IHLs), and decriminalization of cultivations laws (DCLs). Eligible outcomes include intermediate responses (i.e., attitudes/behaviors and markets/environments) and longer-term consequences (health, safety, and socioeconomic outcomes) of these laws. Both dual screening and dual data extraction were performed with third person deconfliction. Primary studies were appraised using the Maryland Scientific Methods Scale and systematic reviews were assessed using AMSTAR 2. The EGM includes 447 studies, comprising 438 primary studies and nine systematic reviews. Most research derives from the United States, with little research from other countries. By far, most cannabis liberalization research focuses on the effects of MCLs and RCLs. Studies targeting other laws-including CBDLs, IHLs, and DCLs-are relatively rare. Of the 113 distinct outcomes we documented, cannabis use was the single most frequently investigated. More than half these outcomes were addressed by three or fewer studies, highlighting substantial evidence gaps in the literature. The systematic evidence base is relatively small, comprising just seven completed reviews on cannabis use (3), opioid-related harms (3), and alcohol-related outcomes (1). Moreover, we have limited confidence in the reviews, as five were appraised as minimal quality and two as low quality. More primary and systematic research is needed to better understand the effects of cannabis liberalization laws on longer-term-and arguably more salient-health, safety, and socioeconomic outcomes. Since most research concerns MCLs and RCLs, there is a critical need for research on the societal impacts of industrial hemp production, medical CBD products, and decriminalized cannabis cultivation. Future research should also prioritize understanding the heterogeneous effects of these laws given differences in specific provisions and implementation across jurisdictions.

Physics-Guided Deep Learning for Prediction of Energy Production from Geothermal Reservoirs

Predictive models are traditionally used for the development and management of geothermal reservoirs. While field operation optimization based on physics-based simulations offers dependable strategies, simulation models require detailed descriptions of reservoir conditions and properties and entail extensive computational efforts. As efficient alternatives to traditional physics-based simulation, data-driven predictive models such as deep learning-based models can provide fast predictions to facilitate complex iterative tasks that otherwise entail high computation time. However, purely data-driven models that are trained using limited data often provide physically inconsistent predictions and fail to generalize beyond the training data. This has important consequences in optimization applications where, during optimization, the well control strategies are likely to fall beyond the training data. These limitations undermine the suitability and strength of data-driven models in scientific and engineering applications, where the amount of data is typically limited but physical laws are well-established and frequently used. To address the above challenges, we propose a novel physics-guided machine learning model by incorporating the general structure of the physics-based equations into deep learning models. A typical approach for incorporating physics is adding physics-based constraints in the loss function to regularize the trainable parameters. However, this approach does not exploit or adapt the architecture of the neural network. In this work, the architecture of the proposed recurrent neural networks (RNN) is designed to represent the differential equations of the subsurface flow system. We present the physics-guided RNN models in detail and demonstrate their connection to the underlying differential equations describing the fluid flow physics. We investigate the prediction performance of the proposed models by first applying them to controlled example to evaluate their extrapolation power, before using them with simulated and field datasets.

THE EFFECTIVENESS OF CORRUPTION CRIME INVESTIGATIONS IN THE SECTOR OF PROCUREMENT OF GOVERNMENT GOODS AND SERVICES (Case Study at Poso Police)

This study aims to: 1) find out and analyze and evaluate the effectiveness of the investigation into corruption in the field of procurement of government goods and services in the jurisdiction of the Poso Police and 2) To find out and analyze and evaluate the factors that influence the implementation of the investigation of corruption in the procurement of government goods and services in the jurisdiction of the Poso Police. This study uses a juridical-empirical type of research because the emphasis is on examining the effectiveness of investigations into criminal acts of corruption in the procurement of government goods and services in the jurisdiction of the Poso Police. So, the data needed in this study are primary and secondary. The data collection technique is by conducting interviews to obtain valid data. The results of the study show that: 1) The effectiveness of the Investigation of Corruption Crimes in the Procurement of Government Goods and Services in the jurisdiction of the Poso Police is less effective because of several obstacles such as limited investigator resources, limited laws, limited facilities and infrastructure, and limited information from the community; and 2) Factors influencing corruption law enforcement by investigators from the Poso Police Tipikor Unit in handling corruption cases, namely human resource factors and legal structures, internal and external constraints, while internal constraints are quantity, quality and facilities and infrastructure factors, while external constraints namely Intervention Factors (political) and public support or public trust is still lacking.

Rusty Weapons in a Digital Battlespace

This article explores the evolving landscape of foreign interference in domestic affairs, particularly in the context of ‘information operations’ facilitated by the internet. The primary focus of the article is on the lawful authority to respond to external information operations, and how this authority may be shaped by international law. Specifically, the article explores the royal prerogative in two manifestations — the war prerogative, and external affairs prerogative — as a potential source of authority. In doing so, the article employs an analytical framework by Winterton, distinguishing between the ‘breadth’ and ‘depth’ of constitutional executive power. The article acknowledges the limited case law and debates surrounding these prerogatives’ scope and triggers, and slight nuances between British and Australian jurisprudence. It discusses the relationship between the war prerogative and the existence of armed conflict and touches on how international law can support the exercise of the war prerogative through the ‘public policy test’. Drawing from international legal perspectives, the article references United Nations resolutions from 1976 and 1981 that emphasise the importance of domestic legal remedies against information operations. It stresses the duty of states to combat the dissemination of false or distorted news that interferes with other states’ internal affairs. In sum, the article concludes that, while countering IOs is a matter requiring domestic legal authority, international law can likely extend the ambit of the royal prerogative and should also, as a matter of public policy, apply to such campaigns.

Mixture Representations for Generalized Burr, Snedecor–Fisher and Generalized Student Distributions with Related Results

In this paper, the representability of the generalized Student’s distribution as uniform and normal-scale mixtures is considered. It is also shown that the generalized Burr and the Snedecor–Fisher distributions can be represented as the scale mixtures of uniform, folded normal, exponential, Weibull or Fréchet distributions. New multiplication-type theorems are proven for these and related distributions. The relation between the generalized Student and generalized Burr distribution is studied. It is shown that the Snedecor–Fisher distribution is a special case of the generalized Burr distribution. Based on these mixture representations, some limit theorems are proven for random sums in which the symmetric and asymmetric generalized Student or symmetric and asymmetric two-sided generalized Burr distributions are limit laws. Also, limit theorems are proven for maximum and minimum random sums and absolute values of random sums in which the generalized Burr distributions are limit laws.

The Role of Green Accounting and Corporate Social Responsibilities in Tourism Industries in Indonesia: The Travel Cost Method

The low quality of local tourist destinations is often seen from the need for more infrastructure, unprofessional management, limited management of human resources, and others. For this reason, attention is needed from not only the government but also the role of the private sector to improve the quality of local tourist destinations. This study aimed to describe the implementation of green accounting through corporate social responsibility (CSR) in improving the quality of the tourism industry in Indonesia with a study in Manado City, North Sulawesi Province. Our study examines the economic value of a tourist destination as one of the requirements for the valuation of CSR as part of green accounting records. Data analysis used the travel cost method (TCM). The total of participants in this study was 112 tourists. Data were collected with collection used a survey. The results of this study provide valuable information to the tourism industry in North Sulawesi, especially in Manado City, regarding the need for CSR funds to develop the tourism industry to improve the quality of the tourism industry and the environment. In conclusion, the business and industrial world in North Sulawesi, including companies that wish to implement corporate social responsibility (CSR) based on the limited liability company law number 40 of 2007, can obtain information for the implementation of this CSR in the tourism industry in North Sulawesi, especially in improving the quality of the tourism industry as well as the environment.

Tinjauan Yuridis Pendirian Perseroan Terbatas Perorangan Oleh Usaha Mikro Kecil Berdasarkan Undang-Undang No 11 Tahun 2020 Tentang Cipta Kerja

Small Enterprises are growing rapidly in Indonesia, and play an important role in economic development in Indonesia. The emergence of Law Number 11 of 2020 concerning Job Creation has contributed to the ease of establishing a limited liability company for Small Enterprises. It supports the development of Small Enterprises, with the Job Creation Law the establishment of a company no longer requires a notary deed but can be registered easily on the official website of the Directorate General of Administration Of General Laws. The author wants to see how the establishment of a limited liability company by Small Enterprises is based on the Job Creation Law and see the differences in the procedure for independent establishment and establishment using a notarial deed. The benefit of this research is that to contributes to legal thinking and becomes a reference that related to the topic. The research method used is normative juridical, with a conceptual and statutory approach, secondary data collection, qualitative data types, with library study data collection techniques to be analyzed using descriptive analysis techniques. The results of the author's research on establishment by Small Enterprises are carried out on the website of the Directorate General of Administration Of General Laws and can be established by one person aged at least 17 years and fulfills the requirements in the form, which later if received will get a legal entity establishment certificate. The difference between those established with a notary is that the process of establishment with a notary deed is longer and has a deed of establishment, ownership by Small Enterprises as sole ownership, the legal basis on which Small Enterprises is based refers to the Job Creation Law while with a notary deed it is more Limited Liability Company Law.

Degrees in random m-ary hooking networks

The theme in this paper is a composition of random graphs and Pólya urns. The random graphs are generated through a small structure called the seed. Via Pólya urns, we study the asymptotic degree structure in a random m-ary hooking network and identify strong laws. We further upgrade the result to second-order asymptotics in the form of multivariate Gaussian limit laws. We give a few concrete examples and explore some properties with a full representation of the Gaussian limit in each case. The asymptotic covariance matrix associated with the Pólya urn is obtained by a new method that originated in this paper and is reported in \cite{Mahmoud2022}.

Limit theorems for patterns in ranked tree‐child networks

AbstractWe prove limit laws for the number of occurrences of a pattern on the fringe of a ranked tree‐child network which is picked uniformly at random. Our results extend the limit law for cherries proved by Bienvenu et al. (Random Struct. Algoritm. 60 (2022), no. 4, 653–689). For patterns of height 1 and 2, we show that they either occur frequently (mean is asymptotically linear and limit law is normal) or sporadically (mean is asymptotically constant and limit law is Poisson) or not all (mean tends to 0 and limit law is degenerate). We expect that these are the only possible limit laws for any fringe pattern.

Counting and boundary limit theorems for representations of Gromov‐hyperbolic groups

AbstractGiven a Gromov‐hyperbolic group endowed with a finite symmetric generating set, we study the statistics of counting measures on the spheres of the associated Cayley graph under linear representations of . More generally, we obtain a weak law of large numbers for subadditive functions, echoing the classical Fekete lemma. For strongly irreducible and proximal representations, we prove a counting central limit theorem with a Berry–Esseen type error rate and exponential large deviation estimates. Moreover, in the same setting, we show convergence of interpolated normalized matrix norms along geodesic rays to Brownian motion and a functional law of iterated logarithm, paralleling the analogous results in the theory of random matrix products. Our counting large deviation estimates address a question of Kaimanovich–Kapovich–Schupp. In most cases, our counting limit theorems will be obtained from stronger almost sure limit laws for Patterson–Sullivan measures on the boundary of the group.

Managing risk in corporate groups: Limited liability, asset partitioning, and risk compartmentalization

AbstractResearch SummaryLimited liability enables corporate parents to avoid financial responsibility of their subsidiaries. However, courts can disregard separate legal personality, “pierce the corporate veil,” and impose the debts of a subsidiary on its parent—an exception referred to as “enterprise liability.” We argue that in countries with weak enterprise liability, groups can better compartmentalize risks by incorporating more of their units as legally independent subsidiaries. Weaker enterprise liability may also induce headquarters to delegate more decision‐making authority to their subsidiaries, invest more, and expand faster, although failure rates could rise. Using data from 16 countries across the Americas, Asia, and Europe, we provide evidence supporting these predictions. This paper highlights two channels—risk compartmentalization and subsidiary autonomy—through which limited liability laws affect organizational outcomes.Managerial SummaryLimited liability is a key attribute of the corporate form. However, when the owner of a corporation is another corporation (as in corporate groups), a key justification for limited liability—to protect small, passive investors from unlimited losses—is severely weakened. We examine how variation in parent limited liability protections for subsidiaries across countries affect firm boundaries, internal organization, and performance. In countries with strong limited liability protections, groups partition their assets more finely into legally independent subsidiaries and grant their subsidiaries more autonomy. They also invest more and grow faster, although they experience higher rates of significant revenue declines. Our findings suggest that limited liability laws play a central role in shaping organizational structure and performance.

Analytic and Asymptotic Properties of the Generalized Student and Generalized Lomax Distributions

Analytic and asymptotic properties of the generalized Student and generalized Lomax distributions are discussed, with the main focus on the representation of these distributions as scale mixtures of the laws that appear as limit distributions in classical limit theorems of probability theory, such as the normal, folded normal, exponential, Weibull, and Fréchet distributions. These representations result in the possibility of proving some limit theorems for statistics constructed from samples with random sizes in which the generalized Student and generalized Lomax distributions are limit laws. An overview of known properties of the generalized Student distribution is given, and some simple bounds for its tail probabilities are presented. An analog of the ‘multiplication theorem’ is proved, and the identifiability of scale mixtures of generalized Student distributions is considered. The normal scale mixture representation for the generalized Student distribution is discussed, and the properties of the mixing distribution in this representation are studied. Some simple general inequalities are proved that relate the tails of the scale mixture with that of the mixing distribution. It is proved that for some values of the parameters, the generalized Student distribution is infinitely divisible and admits a representation as a scale mixture of Laplace distributions. Necessary and sufficient conditions are presented that provide the convergence of the distributions of sums of a random number of independent random variables with finite variances and other statistics constructed from samples with random sizes to the generalized Student distribution. As an example, the convergence of the distributions of sample quantiles in samples with random sizes is considered. The generalized Lomax distribution is defined as the distribution of the absolute value of the random variable with the generalized Student distribution. It is shown that the generalized Lomax distribution can be represented as a scale mixture of folded normal distributions. The convergence of the distributions of maximum and minimum random sums to the generalized Lomax distribution is considered. It is demonstrated that the generalized Lomax distribution can be represented as a scale mixture of Weibull distributions or that of Fréchet distributions. As a consequence, it is demonstrated that the generalized Lomax distribution can be limiting for extreme statistics in samples with random size. The convergence of the distributions of mixed geometric random sums to the generalized Lomax distribution is considered, and the corresponding extension of the famous Rényi theorem is proved. The law of large numbers for mixed Poisson random sums is presented, in which the limit random variable has a generalized Lomax distribution.

Local limit laws for symbol statistics in bicomponent rational models

We study the local limit distribution of the number of occurrences of a symbol in words of length n generated at random in a regular language according to a rational stochastic model. We present an analysis of the main local limits when the finite state automaton defining the stochastic model consists of two primitive components. The limit distributions depend on several parameters and conditions, such as the main constants of mean value and variance of our statistics associated with the two components, and the existence of communications from the first to the second component. The convergence rate of these results is always of order O(n−1/2). For the same statistics we also prove an analogous O(n−1/2) convergence rate of the Gaussian local limit law whenever the stochastic model consists of one primitive component.

Cycles in Mallows random permutations

AbstractWe study cycle counts in permutations of drawn at random according to the Mallows distribution. Under this distribution, each permutation is selected with probability proportional to , where is a parameter and denotes the number of inversions of . For fixed, we study the vector where denotes the number of cycles of length in and is sampled according to the Mallows distribution. When the Mallows distribution simply samples a permutation of uniformly at random. A classical result going back to Kolchin and Goncharoff states that in this case, the vector of cycle counts tends in distribution to a vector of independent Poisson random variables, with means . Here we show that if is fixed and then there are positive constants such that each has mean and the vector of cycle counts can be suitably rescaled to tend to a joint Gaussian distribution. Our results also show that when there is a striking difference between the behavior of the even and the odd cycles. The even cycle counts still have linear means, and when properly rescaled tend to a multivariate Gaussian distribution. For the odd cycle counts on the other hand, the limiting behavior depends on the parity of when . Both and have discrete limiting distributions—they do not need to be renormalized—but the two limiting distributions are distinct for all . We describe these limiting distributions in terms of Gnedin and Olshanski's bi‐infinite extension of the Mallows model. We investigate these limiting distributions further, and study the behavior of the constants involved in the Gaussian limit laws. We for example show that as the expected number of 1‐cycles tends to —which, curiously, differs from the value corresponding to . In addition we exhibit an interesting “oscillating” behavior in the limiting probability measures for and odd versus even.

Gumbel Laws in the Symmetric Exclusion Process

We consider the symmetric exclusion particle system on $\mathbb{Z}$ starting from an infinite particle step configuration in which there are no particles to the right of a maximal one. We show that the scaled position $X_t/(\sigma b_t) - a_t$ of the right-most particle at time $t$ converges to a Gumbel limit law, where $b_t = \sqrt{t/\log t}$, $a_t = \log(t/(\sqrt{2\pi}\log t))$, and $\sigma$ is the standard deviation of the random walk jump probabilities. This work solves a problem left open in Arratia (1983). Moreover, to investigate the influence of the mass of particles behind the leading one, we consider initial profiles consisting of a block of $L$ particles, where $L \to \infty$ as $t \to \infty$. Gumbel limit laws, under appropriate scaling, are obtained for $X_t$ when $L$ diverges in $t$. In particular, there is a transition when $L$ is of order $b_t$, above which the displacement of $X_t$ is similar to that under a infinite particle step profile, and below which it is of order $\sqrt{t\log L}$. Proofs are based on recently developed negative dependence properties of the symmetric exclusion system. Remarks are also made on the behavior of the right-most particle starting from a step profile in asymmetric nearest-neighbor exclusion, which complement known results.

Limit cycle enumeration in random vector fields

We study the number and distribution of the limit cycles of a planar vector field whose component functions are random polynomials. We prove a lower bound on the average number of limit cycles when the random polynomials are sampled from the Kostlan-Shub-Smale ensemble. Investigating a problem introduced by Brudnyi [Ann. of Math. (2) 154 (2001), pp. 227–243] we also consider a special local setting of counting limit cycles near a randomly perturbed center focus, and when the perturbation has i.i.d. coefficients, we prove a limit law showing that the number of limit cycles situated within a disk of radius less than unity converges almost surely to the number of real zeros of a logarithmically-correlated random univariate power series. We also consider infinitesimal perturbations where we obtain precise asymptotics on the global average count of limit cycles for a family of models. The proofs of these results use novel combinations of techniques from dynamical systems and random analytic functions.

Reform of the Limited Liability Company Law for the Enforcement of Good Corporate Governance

The presence of majority shareholders who also hold positions as public company executives leads to a conflict of interest due to their dual status. During the general meeting of shareholders, these shareholders have the power to endorse the work plans of the directors and commissioners. As per the limited liability corporation law, shareholders are responsible for appointing and dismissing directors and commissioners. This study aims to investigate the conflict of interest that arises when a majority shareholder serves as a director or commissioner, utilizing normative legal theory. The research focuses on a sample of companies in the financial industry. The findings of this study recommend regulatory reforms to govern the voting rights of majority shareholders at the annual general meeting of shareholders (AGMS). It suggests that the AGMS should exclude the voting rights of shareholders with conflicts of interest. Additionally, any transaction involving a conflict of interest should require the approval of other shareholders, which can be deliberated during a general meeting of shareholders.

Erdős-Rényi laws for exponentially and polynomially mixing dynamical systems

Erdős-Rényi limit laws give the length scale of a time-window over which time-averages in Birkhoff sums have a non-trivial almost-sure limit. We establish Erdős-Rényi type limit laws for Hölder observables on dynamical systems modeled by Young Towers with exponential and polynomial tails. This extends earlier results on Erdős-Rényi limit laws to a broad class of dynamical systems with some degree of hyperbolicity.

Kedudukan Keuangan Negara Dalam Badan Usaha Milik Negara

Introduction: The state separates its finances to be used as capital in state-owned enterprises. However, Law Number 17 of 2003 concerning State Finances still counts the separated capital as state finance, contrary to the principle that separated finance is corporate finance.Purposes of the Research: Analyzing the Position of State Financial Status in State-Owned Enterprises. Methods of the Research: The research method used is normative juridical, with a statutory and conceptual approach. The sources of legal materials used are primary, secondary, and tertiary legal materials. The technique of collecting legal materials carried out in this research is through literature study.Results of the Research: The results of the study show that state finances are all rights attached to the state in the form of money or goods, including equity participation in state-owned enterprises. However, in its management, when the capital has been handed over to a state-owned enterprise, the state's financial status has completely changed to private finance, in this case it is a state-owned enterprise in accordance with Article 4 paragraph (1) UUBUMN which states that the company's capital comes from separated state assets. This capital in the legal context of the company is equity capital. Pursuant to the provisions of Article 1 point 7 of Government Regulation Number 72 of 2016 concerning Procedures for Participation and Administration of State Capital in BUMN and Limited Liability Companies, state capital participation is the separation of State assets from the APBN or determination of company reserves or other sources to serve as BUMN capital and/or other limited liability companies are managed as a corporation. has also been explained in the Constitutional Court Decision No. 77/PUU-IX/2011. The Constitutional Court ruled that a BUMN is a business entity that has separate assets from state assets so that the authority to manage business assets, including the settlement of BUMN debts, is subject to the limited liability company law. This is the point of privatization of state finances which are included in state-owned enterprises where the capital is then managed by the business entity with business principles.

The Impact of Opioid Prescribing Limits on Drug Usage in South Carolina: A Novel Geospatial and Time Series Data Analysis.

The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications in an effort to reduce the number of overdose deaths. This study investigates the impact of South Carolina's prescription limit law (S.C. Code Ann. 44-53-360), which aims to reduce opioid overdose deaths, on opioid prescription rates. The study utilizes South Carolina Reporting and Identification Prescription Tracking System (SCRIPTS) data and proposes a distance classification system to group records based on proximity and evaluates prescription volumes in each distance class. Prescription volumes were found to be highest in classes with pharmacies located further away from the patient. An Interrupted Time Series (ITS) model is utilized to assess the policy impact, with benzodiazepine prescriptions as a control group. The ITS models indicate an overall decrease in prescription volume, but with varying impacts across the different distance classes. While the policy effectively reduced opioid prescription volumes overall, an unintended consequence was observed as prescription volume increased in areas where prescribers were located at far distances from patients, highlighting the limitations of state-level policies on doctors. These findings contribute to the understanding of the effects of prescription limit laws on opioid prescription rates and the importance of considering location and distance in policy design and implementation.