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Abstract Background Longitudinal ordinal data are commonly analyzed using a marginal proportional odds model for relating ordinal outcomes to covariates in the biomedical and health sciences. The generalized estimating equation (GEE) consistently estimates the regression parameters of marginal models even if the working covariance structure is misspecified. For small-sample longitudinal binary data, recent studies have shown that the bias of regression parameters may result from the GEE and have addressed the issue by applying Firth’s adjustment for the likelihood score equation to the GEE as if generalized estimating functions were likelihood score functions. In this manuscript, for the proportional odds model for longitudinal ordinal data, the small-sample properties of the GEE were investigated, and a bias-reduced GEE (BR-GEE) was derived. Methods By applying the adjusted function originally derived for the likelihood score function of the proportional odds model to the GEE, we produced the BR-GEE. We investigated the small-sample properties of both GEE and BR-GEE through simulation and applied them to a clinical study dataset. Results In simulation studies, the BR-GEE had a bias closer to zero, smaller root mean square error than the GEE with coverage probability of confidence interval near or above the nominal level. The simulation also showed that BR-GEE maintained a type I error rate near or below the nominal level. Conclusions For the analysis of longitudinal ordinal data involving a small number of subjects, the BR-GEE is advantageous for obtaining estimates of the regression parameters of marginal proportional odds models.

The rapid digital transformation of crime determines the high importance of criminal law regulation, which, according to some scholars, requires modernization to ensure a stricter state censure of persons encroaching on security in the information and communication space. Critically assessing this proposal, whose implementation will entail numerous norms that are constructively inconsistent with the requirements of non-characteristic property of a qualifying feature for acts, which threatens to artificially increase the danger of crime, the author proposes to amend the law, ensuring a unified definition of the relevant objective feature. The totality and multivariability of the use of information and telecommunication networks for criminal purposes actualizes the issue of determining the boundaries within which the involvement of communication reserves of the relevant technologies will form a mechanism for a criminal act, the significance of which has increased due to the broad interpretation by the Plenum of the Supreme Court of the Russian Federation of the relevant objective feature in relation to the composition paragraph "b" part 2 Article 228.1 of the Criminal Code of the Russian Federation. The systematic implementation of the law may serve as a basis for a broad definition of this feature also within the framework of other compositions, posing a threat of judicial penalization of acts. The repressive nature of criminal law regulation precludes hasty reforming of the law, devoid of criminological substantiation. The decision to expand the differentiating meaning of the analyzed objective feature may be dictated by the emergence in society of social relations that are not regulated by law, giving rise to acts that pose danger, or to ensure a unified normative definition of related criminal acts. The methodological basis is made up of general scientific (analysis and synthesis, dialectics) and private scientific research methods (criminal-statistical, systemic structural, formal legal).

Topology optimization has become a popular tool for designing optimal shapes while meeting specific objectives and restrictions. However, the resulting shape from the optimization process may not be easy to manufacture using typical methods like machining and may require interpretation and validation. Additionally, the final shape depends on chosen parameters. In this study, we conduct a sensitivity analysis of the main parameters involved in 3D topology optimization—penalization and filter radius—focusing on the density-based method. We analyze the features and characteristics of the results, concluding that a machinable and low interpretable part is not an attainable result in by-default topology optimization. Therefore, we propose a new method for obtaining more manufacturable and easily interpretable parts. The main goal is to assist designers in choosing appropriate parameters and understanding what to consider when seeking optimized shapes, giving them a new plug-and-play tool for manufacturable designs. We chose the density-based topology optimization method due to its popularity in commercial packages, and the conclusions may directly influence designers’ work. Finally, we verify the study results through different cases to ensure the validity of the conclusions.

We investigate the obstacle problem for a class of nonlinear and noncoercive parabolic variational inequalities whose model is a Leray–Lions type operator having singularities in the coefficients of the lower order terms. We prove the existence of a solution to the obstacle problem satisfying a Lewy-Stampacchia type inequality.

An important challenge in statistical modeling is to balance how well our model explains the phenomenon under investigation with the parsimony of this explanation. In structural equation modeling (SEM), penalization approaches that add a penalty term to the estimation procedure have been proposed to achieve this balance. An alternative to the classical penalization approach is Bayesian regularized SEM in which the prior distribution serves as the penalty function. Many different shrinkage priors exist, enabling great flexibility in terms of shrinkage behavior. As a result, different types of shrinkage priors have been proposed for use in a wide variety of SEMs. However, the lack of a general framework and the technical details of these shrinkage methods can make it difficult for researchers outside the field of (Bayesian) regularized SEM to understand and apply these methods in their own work. Therefore, the aim of this paper is to provide an overview of Bayesian regularized SEM, with a focus on the types of SEMs in which Bayesian regularization has been applied as well as available software implementations. Through an empirical example, various open-source software packages for (Bayesian) regularized SEM are illustrated and all code is made available online to aid researchers in applying these methods. Finally, reviewing the current capabilities and constraints of Bayesian regularized SEM identifies several directions for future research.

Amblyopia, the primary cause of one-sided vision impairment among children globally, occurs at a rate of 3.7%. It stems from early visual deprivation or inadequate focusing in one eye, creating an unevenness in visual information sent to the brain’s visual cortex. Consequently, vision diminishes in the affected eye, impacting the coordination between both eyes. When signals from one eye are unclear, the brain inhibits input from that eye, disrupting the visual pathway. Apart from impacting visual coordination, amblyopia can influence tasks like eye-hand coordination, reading, and an individual’s self-perception. Several therapies have emerged for treating amblyopia in both children and adults. Traditional treatments mainly penalized the stronger eye through patching or medicinal penalization. Yet, these methods have limitations concerning their effectiveness and patient comfort, affecting individuals and their families. Recent studies indicate that people with amblyopia retain binocular cortical mechanisms responsive to varying visual stimuli levels. As a result, a more practical approach might involve simultaneously stimulating both eyes to enhance vision in the weaker eye, diminish suppression, and bolster binocular vision.

The interaction between a plasma and a solid surface is studied in a (1D-1V) kinetic approach using immersed boundary conditions and penalization to model the wall. Two solutions for the penalized wall region are investigated that either allow currents to flow within the material boundary or not. Essential kinetic aspects of sheath physics are recovered in both cases and their parametric dependencies investigated. Importantly, we show how the two approaches can be reconciled when accounting for relevant kinetic effects. Non-Maxwellian features of the ion and electron distribution functions are essential to capture the value of the potential drop in the sheath. These features lead to a sheath heat transmission factor for ions 60% larger than usually predicted and 35% for electrons. The role of collisions is discussed and means of incorporating minimally-relevant kinetic sheath physics in the gyrokinetic framework are discussed.

By reflecting on social relations, the footprints of power will be revealed, and in other words, power has a fluid presence in all matters of human life. Human societies have accepted the power of Mehr by establishing a political system for the order of affairs, and by establishing various institutions, they have tried to manage their affairs. By accepting the principle of separation of powers in a society or sovereign territory, the legislative, executive and judicial institutions will work together in harmony, and it is obvious that these institutions will also be affected by the ruling political context. The institution of criminal legislation in every society will explain the legislative policies and determine the normative boundaries and protect the value models of the citizens, and without a doubt, the determination of this value territory is also a function of power considerations, the foundations of which are established in the general policy of the country. The fluid power in the public policy of a country will determine the direction of the criminalization and punishment processes in the context of legislative criminal policy and with this description, the influence of power on the criminalization and punishment processes will be revealed. Power has manifested itself in different forms and on this basis, the degree of influence on various categories in the administration of a society will also be different. Political power, military power, royal power or religious power, media power and other examples, depending on the type and nature of the ruling regime of a society, can affect the legislative framework and the regime of crimes and punishments against illegal behaviors. Therefore, it is reasonable to maintin that the legislative system will be affected by the context of the ruling power. Realizing that power, whether obtained through legitimate means or through force and domination over subordinates, ultimately affects the legislative system and the processes of criminalization and determining punishments, and this issue will be the beginning of a way to another research: how this affects the institutions responsible for determining crimes and punishments will be determined. On this basis, in terms of revealing the new discourse of influence of power in the hidden layers of the legislative policy of the countries, which in the future and in the hands of the governments, will become a power in the direction of controlling and restraining the subjects that make up the discourse of power, the present article has been written in order to present an answer to the important question of "How does power influence the processes of criminalization and punishment?" Undoubtedly, today, with the ever-increasing development of the "government" institution in its many forms, it has made people see more clearly the influence of economic, military powers at the national and international levels. In some cases, the influence of political power in the approval or non-approval of punitive laws is so obvious that the role of expediency can be clearly seen. Expediency in supporting and protecting the interests of a limited number of people or belonging to a specific group causes the approval of laws that are completely contrary to the criterion of "public interest" and makes the color and shape of some laws so clear that other than protection. It does not serve any purpose of special group interests. It should not be forgotten that in such cases, the law is passed in the name of protecting the interests of the general public of a society. In many cases, it can be seen that in authoritarian government systems, the people are not at all aware of the mass of approved laws, and the people's representatives are also under the direct influence of economic, military, and media power, etc.The question of "How does power affect the processes of criminalization and punishment?" is a question that needs to be analyzed due to the lack of research writings in the scientific bases of the country, and we have tried to understand its hidden layers with an analytical-descriptive method and using theoretical sources. In this regard, uncovering the role of power in the process of criminalization and that the system of crimes and punishments determined for them is itself a function of the foundations of the ruling power, is considered the achievement of the article, because it puts a seal of approval on the fact that; the type and even the amount of crimes are based on the ruling powers and their beliefs, and therefore, it is not always the case that the interest of the individual is the basis of criminalization, and the appeal to the concept of protection of the "public good" is itself a sign of the superiority of political power and its obvious influence in determining the system of crimes and punishments. In other words, in many cases, the political governments of countries act through the system of criminalization-punishment to maintain their power and in this way keep the citizens in the center of power.

The kriging-based estimation of the different types of atmospheric particulate matter (PM) pollutions defined in the air quality regulation raises some operational problems because the (co)kriging equations are obtained by minimizing a linear combination of the estimation variances subject to unbiasedness constraints. As a consequence, the estimation process can result in total PM10 concentrations that are less than the PM2.5 concentrations which would be physically impossible. In a previous publication, it was shown that a convenient external drift modeling can reduce the number of spatial locations where the inequality constraint is not satisfied, without completely solving the problem. In this work, the formulation of the cokriging system is modified, inspired by previous works focusing on positive kriging. The introduction of additional constraints on the cokriging weights are presented, leading to a unique and optimal solution to the problem of cokriging under inequality constraints between two variables. Some computational and algorithmic details are introduced. An evaluation of the penalized cokriging is provided by using the European PM monitoring sites dataset: some maps and performance scores are given to assess the relevance of our iterative optimization scheme.

Ensemble-based systems are well known to have the capacity to outperform individual approaches if the ensemble members are sufficiently accurate and diverse. This paper investigates how an efficient ensemble of deep convolutional neural networks (CNNs) can be created by forcing them to adjust their parameters during the training process to increase diversity in their decisions. As a new theoretical approach to reach this aim, we join the member neural architectures via a fully connected layer and insert a new correlation penalty term in the loss function to obstruct their similar operation. With this complementary term, we implement the standard guideline of ensemble creation to increase the members’ diversity for CNNs in a more detailed and flexible way than similar existing techniques. As for applicability, we show that our approach can be efficiently used in various classification tasks. More specifically, we demonstrate its performance in challenging medical image analysis and natural image classification problems. Besides the theoretical considerations and foundations, our experimental findings suggest that the proposed technique is competitive. Namely, on the one hand, the classification rate of the ensemble trained in this way outperformed all the individual accuracies of the state-of-the-art member CNNs according to the standard error functions of these application domains. On the other hand, it is also validated that the ensemble members get more diverse and their accuracies are raised by adding the penalization term. Moreover, we performed a full comparative analysis, including other state-of-the-art ensemble-based approaches recommended for the same classification tasks. This comparative study also confirmed the superiority of our method, as it overcame the current solutions.

IntroductionMotor Brain–Computer Interfaces (BCIs) create new communication pathways between the brain and external effectors for patients with severe motor impairments. Control of complex effectors such as robotic arms or exoskeletons is generally based on the real-time decoding of high-resolution neural signals. However, high-dimensional and noisy brain signals pose challenges, such as limitations in the generalization ability of the decoding model and increased computational demands.MethodsThe use of sparse decoders may offer a way to address these challenges. A sparsity-promoting penalization is a common approach to obtaining a sparse solution. BCI features are naturally structured and grouped according to spatial (electrodes), frequency, and temporal dimensions. Applying group-wise sparsity, where the coefficients of a group are set to zero simultaneously, has the potential to decrease computational time and memory usage, as well as simplify data transfer. Additionally, online closed-loop decoder adaptation (CLDA) is known to be an efficient procedure for BCI decoder training, taking into account neuronal feedback. In this study, we propose a new algorithm for online closed-loop training of group-wise sparse multilinear decoders using Lp-Penalized Recursive Exponentially Weighted N-way Partial Least Square (PREW-NPLS). Three types of sparsity-promoting penalization were explored using Lpwith p = 0., 0.5, and 1.ResultsThe algorithms were tested offline in a pseudo-online manner for features grouped by spatial dimension. A comparison study was conducted using an epidural ECoG dataset recorded from a tetraplegic individual during long-term BCI experiments for controlling a virtual avatar (left/right-hand 3D translation). Novel algorithms showed comparable or better decoding performance than conventional REW-NPLS, which was achieved with sparse models. The proposed algorithms are compatible with real-time CLDA.DiscussionThe proposed algorithm demonstrated good performance while drastically reducing the computational load and the memory consumption. However, the current study is limited to offline computation on data recorded with a single patient, with penalization restricted to the spatial domain only.

In this paper, we present a novel validated penalization method for bias reduction to estimate parameters for the logistic model when data are missing at random (MAR). Specific focus was given to address the data missingness problem among categorical model covariates. We penalize a logit log-likelihood with a novel prior distribution based on the family of the LogF(m,m) generalized distribution. The principle of expectation-maximization with weights was employed with the Louis' method to derive an information matrix, while a closed form for the exact bias was derived following the Cox and Snell's equation. A combination of simulation studies and real life data were used to validate the proposed method. Findings from the validation studies show that our model's standard errors are consistently lower than those derived from other bias reduction methods for the missing at random data mechanism. Consequently, we conclude that in most cases, our method's performance in parameter estimation is superior to the other classical methods for bias reduction when data are MAR.

Amblyopia is the most common cause for preventable monocular visual loss in children. Visual system at birth is at a stage of dramatic developmental neural plasticity. Abnormal visual impulses from eyes (e.g., visual deprivation and refractive error) can affect normal anatomical and functional organization of the system. Abnormal cortical changes thus produced can be reversed if proper treatment is instituted during this time. This so-called critical period was thought to extend from birth to 7–8 years. However, now, it is understood that cortical plasticity though reduced may extend up to 6th decade of life and this accounts for increased interest in the management of adult amblyopia. Early detection and instituting treatment on detection are important for achieving better outcomes. Classical amblyopia treatment modalities include optical correction of significant refractive errors, occlusion therapy and penalization. Pharmacologic therapy, binocular therapy, and liquid crystal display eyeglasses are the newer treatment options. This review gives a simplified update of amblyopia including simplified pathophysiological concept in different types of amblyopia which will be useful to the clinician. Recent treatment options available for treatment including that in adult amblyopia are also discussed. Literature search using Google scholar, PubMed with a combination of words appropriate to this article was done and relevant articles were reviewed.

Strabismic amblyopia is characterized by a distorted spatial perception. In this condition, the neurofunctional disorder occurring during first years of life provoke several monocular and binocular anomalies such as crowding, deficits in the accommodative response, contrast sensitivity, and ocular motility abilities. The inhibition of the binocular function of the brain by the misaligned amblyopic eye induces a binocular imbalance leading to interocular suppression and the reduction or lack of stereoacuity. Passive treatments such as occlusion, optical and/or pharmacological penalization, and Bangerter foils has been demonstrated to be potentially useful treatments for strabismic amblyopia. Recent researches have proved new pharmacological options to improve and maintain visual acuity after occlusion treatment in strabismic amblyopia. Likewise, the active vision therapy, in the last years, is becoming a very relevant therapeutic option in combination with passive treatments, especially during and after monocular therapy, in the attempt of recovering the imbalanced binocular vision.

More behaviors are entering criminal responsibility by approval the law on new offenses. In some forms of criminalization and penalization, the use of various types of criminal referral techniques in identifying the crime, determining punishment, and defining the label and title of criminal, citizens and activists of the judicial system are referred to multiple criminal or non-judicial texts. Awareness to people about how to behave and coexist peacefully are legislative goals that will be undermined by the use of criminal labelling without observing the rules, principles and requirements of the legislation. The fair labeling principle is one of the fundamental principles of criminal intervention, which should always be considered by legislators in the process of constitution in order to determine the title and description of the legislator, in order to transferring the functions of the criminal label and the message of the criminal policy makers in a proportionate and realistic way to contacts. In the present study, in addition to the review of criminal referral conceptual scope as one of the most widely used methods in the process of legislation, this technique is evaluated and analyzed in the light of the fair labeling principle.

The main aim of this paper is to extend to the case of a pseudomonotone operator Lewy-Stampacchia’s inequality proposed by F. Donati [7] in the framework of monotone operators. For that, an ad hoc type of perturbation of the operator is proposed.

In paired comparison models, the inclusion of covariates is a tool to account for the heterogeneity of preferences and to investigate which characteristics determine the preferences. Although methods for the selection of variables have been proposed no coherent framework that combines all possible types of covariates is available. There are three different types of covariates that can occur in paired comparisons, the covariates can either vary over the subjects, the objects or both the subjects and the objects of the paired comparisons. This paper gives an overview over all possible types of covariates in paired comparisons and introduces a general framework to include covariate effects into BradleyTerry models. For each type of covariate, appropriate penalty terms that allow for sparser models and, therefore, easier interpretation are proposed. The whole framework is implemented in the R package BTLLasso. The main functionality and the visualization tools of the package are introduced and illustrated by real data sets.

Topology optimization is a modern method for optimizing the material distribution in a given space, automatically searching for the ideal design of the product. The method aims to maximize the design performance of the system regarding given conditions. In engineering practice, a given space is first described using the finite element method and, subsequently, density-based method with solid isotropic material with penalty. Then, the final shape is found using a gradient-based method, such as the optimality criteria algorithm. However, obtaining the ideal shape is highly dependent on the correct setting of numerical parameters. This paper focuses on the sensitivity analysis of key formulations of topology optimization using the implementation of mathematical programming techniques in MATLAB software. For the purposes of the study, sensitivity analysis of a simple spatial task—cantilever bending—is performed. This paper aims to present the formulations of the optimization problem—in this case, minimization of compliance. It should be noted that this paper does not present any new mathematical formulas but rather provides an introduction into the mathematical theory (including filtering methods and calculating large-size problems using the symmetry of matrices) as well as a step-by step guideline for the minimization of compliance within the density-based topology optimization and search for an optimal shape. The results can be used for complex commercial applications produced by traditional manufacturing processes or by additive manufacturing methods.

This is the continuation of a numerical study on vortex shedding from a blunt trailing-edge of a hydrofoil. In our previous work (Lee et al., 2015), numerical schemes for efficient computations were successfully implemented; i.e. multiple domains, the approximation of domain boundary conditions using cubic spline functions, and particle- based domain decomposition for better load balancing. In this study, numerical results through a hybrid particle-mesh method which adopts the Vortex-In-Cell (VIC) method and the Brinkman penalization model are further rigorously validated through comparison to experimental data at the Reynolds number of 2 × 106. The effects of changes in numerical parameters are also explored herein. We find that the present numerical method enables us to reasonably simulate vortex shedding phenomenon, as well as turbulent wakes of a hydrofoil.

This article describes the organization principles for wireless mesh-networks (software-defined net-works of mobile objects). The emphasis is on the questions of getting effective routing algorithms for such networks. The mathematical model of the system is the standard transportation network. The key parameter of the routing system is the node reachability coefficient — the function depending on several basic and additional parameters (“mesh-factors”), which characterize the route between two network nodes. Each pair (arc, node) is juxtaposed to a composite parameter which characterizes the “reacha-bility” of the node by the route which begins with this arc. The best (“shortest”) route between two nodes is the route with the maximum reachability coefficient. The rules of building and refreshing the routing tables by the network nodes are described. With the announcement from the neighbor the node gets the information about the connection energy and reliability, the announcement time of receipt, the absence of transitional nodes and also about the connection capability. On the basis of this informationthe node applies the penalization (decreasing the reachability coefficient) or the reward (increasing the reachability coefficient) to all routes through this neighbor node. The penalization / reward scheme has some separate aspects: 1. Penalization for the actuality of information. 2. Penalization / reward for the reliability of a node. 3. Penalization for the connection energy. 4. Penalization for the present connection capability. The simulator of the wireless mesh-network of mobile objects is written. It is based on the suggested heuristic algorithms. The description and characteristics of the simulator are stated in the article. The peculiarities of its program realization are also examined.

The paper analysis the principle of proportionality, which is widely applied in the EU legal order and is therefore one of the fundamental principles of the system of the European Union. It is one of the legal principles that govern decision-making processes and common strategic objectives, and which are applicable when establishing European Union legislation and transposing it into national law, including in the area of criminal law, although the current analyses do not often focus on discussing this aspect. Due to its complexity and significance for the processes of establishing and applying the law, the principle of proportionality requires detailed and separate discussion, especially in the context of European criminal law.

Using the penalty method, we prove the existence of solutions to nonlinear parabolic unilateral problems with an obstacle depending on time. To find a solution, the original inequality is transformed into an equality by adding a positive function on the right-hand side and a complementary condition. This result can be seen as a generalization of the results by Mokrane in [11] where the obstacle is zero.

Defining the scope of criminal law and legitimated level ofintervention through criminal law over the rights and freedom ofcitizens as the most serious kind of such intervention, is a complicatedand difficult matter. The principle of criminal law as the last and theleast resort as a basic principle of this knowledge, technique andinstrument of social control, as emphasizes upon the destructiveresults of abuse of penal concepts, instruments and institutions, tries todetennine the appropriate level of intervention through criminal lawand provide the possibility of usage for other kinds of social controlinstruments and institutions. This article, as emphasizes upon thenecessity of considering this principle in more details, will discuss theconcepts, basics and implications of this principle for penal policy(criminalization and penalization).

We study the penalized obstacle problem in the unit half ball, i.e. an approximation of the obstacle problem in the unit half ball. The main result states that when the approximation parameter is small enough and when certain level sets are sufficiently close to the hyperplane ${x_1=0}$, then these level sets are uniformly $C^1$ regular graphs. As a by-product, we also recover some regularity of the free boundary for the limiting problem, i.e., for the obstacle problem.

We present existence and stability results for periodic solutions of quasilinear parabolic equation related to Leray-Lions's type operators. To prove existence and localization, we use the penalty method; while for stability we use an approximation scheme.

When the domain of a variational inequality is given as intersection of level sets of functionals, then it is useful to introduce a separation scheme. Starting from this it is possible to carry out, in a uniform way, several topics, as penalization, regularization, gap functions, duality.

Many strategies for asset allocation involve the computation of the expected value and the covariance matrix of the returns of financial instruments. How much of each instrument to own is determined by an attempt to minimize risk — the variance of linear combinations of investments in these financial assets — subject to various constraints such as a given level of return, concentration limits, etc. The covariance matrix contains many parameters to estimate and two main problems arise. First, the data will very likely have outliers that will seriously affect the covariance matrix. Second, with so many parameters to estimate, a large number of return observations are required and the nature of markets may change substantially over such a long period. In this paper we discuss using robust covariance procedures, FAST-MCD, Iterated Bivariate Winsorization and Fast 2-D Winsorization, to address the first problem and penalization methods for the second. When back-tested on market data, these methods are shown to be effective in improving portfolio performance. Robust asset allocation methods have great potential to improve risk-adjusted portfolio returns and therefore deserve further exploration in investment management research.

Pharmacological penalization with atropine has been shown to be equally effective as conventional occlusion therapy in the treatment of amblyopia in children. Reverse amblyopia of the sound eye with atropine penalization has been reported before, but is more common in cases where the effect is augmented with optical penalization and is mostly reversible. We report a case of reverse amblyopia with atropine penalization, in a 4-year-old girl, which was refractory to treatment. This report highlights the need for strict monitoring of the vision in the sound eye and regular follow-up in children undergoing amblyopia treatment.

When the domain of a variational inequality is given as intersection of level sets of functionals, then it is useful to introduce a separation scheme. Starting from this it is possible to carry out, in a uniform way, several topics, as penalization, regularization, gap functions, duality.