Additional Penalty Research Articles

A new framework for the assessment of model probabilities of the different crystal plasticity models for lamellar grains in Titanium alloys

This paper presents a novel framework for assessing the relative accuracy of the different slip transfer criterion in modeling the constitutive response of the lamellar morphology grains in Titanium alloys. The main steps involved in the proposed framework include: (i) rigorous statistical evaluation of the salient morphological characteristics of the lamellar grains using image processing techniques, (ii) modeling the effects of dislocation slip transfer as additive penalties to the critical resolved shear strengths of the different slip systems in each phase, (iii) consideration of multiple geometric slip transfer criteria for the numerical evaluation of the different penalty terms, and (iv) the Bayesian calibration of the material parameters in the constitutive descriptions using spherical nanoindentation experimental data on a polycrystalline Ti-6Al-4V sample. Step (iv) described above involves the construction and refinement of a Gaussian process (GP) surrogate model for the indentation measurements, which is trained on crystal plasticity finite element simulations incorporating the constitutive descriptions selected in Steps (ii) and (iii). The GP surrogates are then combined with Markov Chain Monte Carlo sampling techniques to calibrate the parameters in the various constitutive models studied in this work. Additionally, we have computed the posterior model probabilities for all the constitutive models considered and identified the most plausible slip transfer criterion. This specific constitutive model is then utilized to present a homogenized crystal plasticity model for the lamellar morphology. The proposed framework presents a robust scale-bridging protocol for incorporating the uncertain information obtained from lower scales.

Analisis Normatif Sanksi Bagi Para Pelaku Pencemaran dan Kerusakan Lingkungan Berdasarkan Prespektif Hukum Lingkungan

Seeing so many cases of pollution and environmental damage that are increasingly more and more complex is one of the problems that must be resolved and addressed immediately. Which based on the analysis conducted at the author of this journal reveals that in order to minimize or even prevent cases of pollution and environmental damage, it is necessary to have a legal instrument that specifically regulates all series of regulations related to environmental management. However, the topic of discussion to be discussed in this journal writing is to emphasize law enforcement for perpetrators of pollution and environmental damage by applying legal sanctions. It should also be underlined that the journal writing method this time uses juridical analysis methods or legal literature studies guided by UUPPLH No. 32 of 2009 as the main foundation. From the results of the analysis that has been carried out, it can be concluded that there are actually 3 types of sanctions that can be given to actors who pollute and damage the environment, including administrative sanctions which include: Reprimand, temporary suspension of operating licenses, revocation of business licenses and the like, then civil sanctions which include: Granting fines, the existence of recovery responsibilities and the like, and the last is criminal sanctions, which include imprisonment, criminal fines, additional penalties and so on. Where these sanctions are given based on how much impact the behavior or actions made by the perpetrators of pollution and damage.

InMTSCCA: An Integrated Multi-task Sparse Canonical Correlation Analysis for Multi-omic Brain Imaging Genetics

Identifying genetic risk factors for Alzheimer’s disease (AD) is an important research topic. To date, different endophenotypes, such as imaging-derived endophenotypes and proteomic expression-derived endophenotypes, have shown the great value in uncovering risk genes compared to case–control studies. Biologically, a co-varying pattern of different omics-derived endophenotypes could result from the shared genetic basis. However, existing methods mainly focus on the effect of endophenotypes alone; the effect of cross-endophenotype (CEP) associations remains largely unexploited. In this study, we used both endophenotypes and their CEP associations of multi-omic data to identify genetic risk factors, and proposed two integrated multi-task sparse canonical correlation analysis (inMTSCCA) methods, i.e., pairwise endophenotype correlation-guided MTSCCA (pcMTSCCA) and high-order endophenotype correlation-guided MTSCCA (hocMTSCCA). pcMTSCCA employed pairwise correlations between magnetic resonance imaging (MRI)-derived, plasma-derived, and cerebrospinal fluid (CSF)-derived endophenotypes as an additional penalty. hocMTSCCA used high-order correlations among these multi-omic data for regularization. To figure out genetic risk factors at individual and group levels, as well as altered endophenotypic markers, we introduced sparsity-inducing penalties for both models. We compared pcMTSCCA and hocMTSCCA with three related methods on both simulation and real (consisting of neuroimaging data, proteomic analytes, and genetic data) datasets. The results showed that our methods obtained better or comparable canonical correlation coefficients (CCCs) and better feature subsets than benchmarks. Most importantly, the identified genetic loci and heterogeneous endophenotypic markers showed high relevance. Therefore, jointly using multi-omic endophenotypes and their CEP associations is promising to reveal genetic risk factors. The source code and manual of inMTSCCA are available at https://ngdc.cncb.ac.cn/biocode/tools/BT007330.

Broken bond models, magic-sized clusters, and nucleation theory in nanoparticle synthesis.

Magic clusters are metastable faceted nanoparticles that are thought to be important and, sometimes, observable intermediates in the nucleation of certain faceted crystallites. This work develops a broken bond model for spheres with a face-centered-cubic packing that form tetrahedral magic clusters. With just one bond strength parameter, statistical thermodynamics yield a chemical potential driving force, an interfacial free energy, and free energy vs magic cluster size. These properties exactly correspond to those from a previous model by Mule et al. [J. Am. Chem. Soc. 143, 2037 (2021)]. Interestingly, a Tolman length emerges (for both models) when the interfacial area, density, and volume are treated consistently. To describe the kinetic barriers between magic cluster sizes, Mule et al. invoked an energy parameter to penalize the two-dimensional nucleation and growth of new layers in each facet of the tetrahedra. According to the broken bond model, barriers between magic clusters are insignificant without the additional edge energy penalty. We estimate the overall nucleation rate without predicting the rates of formation for intermediate magic clusters by using the Becker-Döring equations. Our results provide a blueprint for constructing free energy models and rate theories for nucleation via magic clusters starting from only atomic-scale interactions and geometric considerations.

Maximum softly-penalized likelihood for mixed effects logistic regression

Maximum likelihood estimation in logistic regression with mixed effects is known to often result in estimates on the boundary of the parameter space. Such estimates, which include infinite values for fixed effects and singular or infinite variance components, can cause havoc to numerical estimation procedures and inference. We introduce an appropriately scaled additive penalty to the log-likelihood function, or an approximation thereof, which penalizes the fixed effects by the Jeffreys’ invariant prior for the model with no random effects and the variance components by a composition of negative Huber loss functions. The resulting maximum penalized likelihood estimates are shown to lie in the interior of the parameter space. Appropriate scaling of the penalty guarantees that the penalization is soft enough to preserve the optimal asymptotic properties expected by the maximum likelihood estimator, namely consistency, asymptotic normality, and Cramér-Rao efficiency. Our choice of penalties and scaling factor preserves equivariance of the fixed effects estimates under linear transformation of the model parameters, such as contrasts. Maximum softly-penalized likelihood is compared to competing approaches on two real-data examples, and through comprehensive simulation studies that illustrate its superior finite sample performance.

Efficient computation of extended surface sources

Source extension is a reformulation of inverse problems in wave propagation, that at least in some cases leads to computationally tractable iterative solution methods. The core subproblem in all source extension methods is the solution of a linear inverse problem for a source (right hand side in a system of wave equations) through minimization of data error in the least squares sense with soft imposition of physical constraints on the source via an additive quadratic penalty. For an acoustic formulation for sources supported on a surface, with a soft contraint enforcing concentration at a point, a variant of the time reversal method from photoacoustic tomography provides an approximate solution. This approximate inverse can be used to precondition Krylov space iteration for rapid convergence to the solution of the core subproblem in this setting. Numerical examples illustrate the effectiveness of this preconditioner.

Optimal Beacon Deployment for Positioning in Cluttered Indoor Environments

Accurate indoor positioning is vital for many indoor autonomous systems. This article focuses on the influence of beacon placement on overall positioning quality in cluttered indoor environments. We first propose a metric based on the Fisher information matrix (FIM) to evaluate the performance of the positioning service provided by a specific beacon layout. After analyzing the characteristics of the FIM, we introduce an additional penalty term in the performance metric to handle singular cases. We then investigate the optimal beacon placement with respect to overall positioning quality. We derive the gradient of the optimization objective and propose an efficient optimization method called the quotient-space gradient-based particle swarm optimization (QGPSO), which combines the quotient-space PSO with the gradient ascent method, enabling the particle swarm to obtain more accurate optimization results locally while retaining the original global exploration capability. Numerical results validate our analysis and the superiority of the proposed optimization method over other baselines.

Multi-Year On-Farm Trial Data on the Performance of Long- and Short-Duration Wheat Varieties against Sowing Dates in the Eastern Indo-Gangetic Plain of India

Sub-optimal wheat productivity in the eastern Indo-Gangetic plain of India can largely be attributed to delayed sowing and the use of short duration varieties. The second week of November is the ideal time for sowing wheat in eastern India, though farmers generally plant later. Late-sowing farmers tend to prefer short-duration varieties, leading to additional yield penalty. To validate the effect of timely sowing and the comparative performance of long- and short-duration varieties, multi-location on-farm trials were conducted continuously over five years starting from 2016–2017. Ten districts were selected to ensure that all the agro-climatic zones of the region were covered. There were five treatments of sowing windows: (T1) 1 to 10 November, (T2) 11–20 November, (T3) 21 to 30 November, (T4) 1–15 December, and (T5) 16–31 December. Varietal performance was compared in T3, T4, and T5, as short-duration varieties are normally sown after 20 November. There is asymmetry in the distribution of samples within treatments and over the years due to the allocation of fields by farmers. Altogether, the trial was conducted at 3735 sites and captured 61 variables, including yield and yield attributing traits. Findings suggested that grain yields of long-duration wheat varieties are better even under late sown scenarios.

Hemolysis prediction in bio-microfluidic applications using resolved CFD-DEM simulations

Background and ObjectiveHemolysis, namely hemoglobin leakage from red blood cells (RBCs), is one of the major sources of incorrect results in clinical tests, especially when passive microfluidics is involved. This is due to small characteristic dimensions which could cause strong RBCs deformation. Prediction of hemolysis is essential in the design and optimization of lab-on-a-chip devices for cell sorting and plasma separation. The aim of this work is to provide a numerical simulation tool this purpose applicable to real-scale bio-microfluidic devices with affordable computational cost. MethodsBlood is modelled as a suspension of biological cells, mainly RBCs, in liquid plasma assumed as a Newtonian, incompressible carrier fluid. Therefore, the physics of cells and carrier fluid is coupled by means of an immersed boundary concept known as resolved CFD-DEM. In this approach, the Navier-Stokes equations are numerically solved through a finite volume method with an additional penalty term to account for the presence of RBCs. RBCs’ positions and velocities are updated by solving Newton and Euler equations for conservation of linear and angular momentum. To model the RBCs deformation, a reduced-order model is employed, where each RBC is represented by a clump of overlapping rigid spheres connected by fictional numerical bonds, whose properties are tuned to reproduce the ones of RBCs viscoelastic membrane. This coupled approach allows access to cell-level information and facilitates the usage of strain-based hemolysis models. ResultsDifferent micro-channel geometries and blood hematocrits are simulated, to explore the influence of these factors on RBCs damage. Statistical analysis is performed to extract relevant biophysical quantities from numerical simulations such as hemolysis index distribution at the channel exit. Finally, the effect of carrier fluid viscosity is studied in relation to cell-cell interactions. ConclusionsSimulation results show that hemolysis occurrence is almost independent of the hematocrit values in the microchannel, implying the possibility to speed up calculation using low hematocrit values. Nevertheless, using whole blood viscosity for the carrier fluid overestimates the value of the hemolysis index by almost one order of magnitude.

Time-inconsistent view on a dividend problem with penalty

We consider the dividend maximization problem including a ruin penalty in a diffusion environment. The additional penalty term is motivated by a constraint on dividend strategies. Intentionally, we use different discount rates for the dividends and the penalty, which causes time-inconsistency. This allows to study different types of constraints. For the diffusion approximation of the classical surplus process we derive an explicit equilibrium dividend strategy and the associated value function. Inspired by duality arguments, we can identify a particular equilibrium strategy such that for a given initial surplus the imposed constraint is fulfilled. Furthermore, we illustrate our findings with a numerical example.

Analisis Yuridis Pencabutan Hak-Hak Politik Pelaku Tindak Pidana Korupsi (Studi Putusan Mahkamah Agung RI Nomor 113 K/PID.SUS/2020)

Eradicating the crime of corruption must apply strict sanctions in order to provide a deterrent effect for corruptors, as well as being expected to reduce anyone from committing corruption. One of the latest breakthroughs is to apply additional criminal sanctions for revocation of certain rights. The formulation of the problem in this thesis is how the legal arrangements for the revocation of political rights against perpetrators of criminal acts of corruption, how criminal responsibility for perpetrators of criminal acts of corruption, how the legal considerations of judges on the revocation of political rights against perpetrators of criminal acts of corruption. The research method used is descriptive analysis that leads to normative juridical legal research, namely research conducted by referring to legal norms, namely researching library materials or secondary materials. Secondary data by processing data from primary legal materials, secondary legal materials and tertiary legal materials. The legal regulation on the revocation of political rights in the form of the right to be elected in public office is the implementation of the application of criminal sanctions that are extraordinary enforcement as regulated in Article 17 of the Law of the Republic of Indonesia Number 31 of 1999 in conjunction with the Law of the Republic of Indonesia Number 20 of 2001 concerning Eradication Corruption crimes may be subject to additional penalties as referred to in Article 18 paragraph (1) letter d and Article 10 letter b number 1 of the Criminal Code concerning additional penalties. The results of the study indicate that the judge's legal considerations for the revocation of political rights against perpetrators of criminal acts of corruption are criminal acts committed cannot be a good example. At the end of its decision, the Panel of Judges imposed an additional penalty on the Defendant in the form of revocation of the right to be elected in public office for 3 (three) years after the Defendant had finished serving his main sentence.

Jointly Learning Non-Cartesian k-Space Trajectories and Reconstruction Networks for 2D and 3D MR Imaging through Projection.

Compressed sensing in magnetic resonance imaging essentially involves the optimization of (1) the sampling pattern in k-space under MR hardware constraints and (2) image reconstruction from undersampled k-space data. Recently, deep learning methods have allowed the community to address both problems simultaneously, especially in the non-Cartesian acquisition setting. This work aims to contribute to this field by tackling some major concerns in existing approaches. Particularly, current state-of-the-art learning methods seek hardware compliant k-space sampling trajectories by enforcing the hardware constraints through additional penalty terms in the training loss. Through ablation studies, we rather show the benefit of using a projection step to enforce these constraints and demonstrate that the resulting k-space trajectories are more flexible under a projection-based scheme, which results in superior performance in reconstructed image quality. In 2D studies, our novel method trajectories present an improved image reconstruction quality at a 20-fold acceleration factor on the fastMRI data set with SSIM scores of nearly 0.92-0.95 in our retrospective studies as compared to the corresponding Cartesian reference and also see a 3-4 dB gain in PSNR as compared to earlier state-of-the-art methods. Finally, we extend the algorithm to 3D and by comparing optimization as learning-based projection schemes, we show that data-driven joint learning-based method trajectories outperform model-based methods such as SPARKLING through a 2 dB gain in PSNR and 0.02 gain in SSIM.

R410A and R32 condensation heat transfer and flow patterns inside horizontal micro-fin and 3-D enhanced tubes

Micro-fin tube, 3-D enhanced tube and smooth tube with an inner diameter of 9.52 mm were used as test tubes to study the condensation heat transfer performance with R410A and R32 as the working fluids at different mass flow rates (150–400 kg/m2s) and vapor qualities (0.2–0.8). For R410A and R32, the heat transfer coefficient of the micro-fin tube is 2.0–2.2 times and 1.5–2.0 times that of the smooth tube, and the heat transfer coefficient of the 3-D enhanced tube is 1.4–1.5 times and 1.5–1.6 times that of the smooth tube, respectively. The micro-fin tube is effective in thinning the condensate thickness and reducing the thermal resistance. The 3-D enhanced tube promotes the generation of turbulence and droplet entrainment, which improves heat transfer of enhanced tubes. The heat transfer coefficient of R32 is greater than that of R410A due to its higher thermal conductivity, latent heat and specific heat capacity. The frictional pressure drop increases monotonically with the mass flow rate. Considering the increment in surface area and the additional pressure drop penalty, the performance evaluation factor of the enhanced tubes ranges from 0.9 to 1.4. The study presents flow pattern maps for smooth and enhanced tubes. Enhanced tubes promote the appearance of intermittent and annular flow.

SEXUAL-VIOLENCE OFFENSES IN INDONESIA: ANALYSIS OF THE CRIMINAL POLICY IN THE LAW NUMBER 12 OF 2022

In 2022, Indonesia enacted the Law on Sexual Violence Offenses. The Law criminalizes ten acts of sexual violence and categorizes them as criminal offenses. The Law aims to prevent criminal offenses of sexual violence through deterrence, coordination, and monitoring by central and regional law enforcement agencies. The Law adopts both sanctions and treatment in the matter of criminal sanctions. The Law distinguishes types of punishment based on principal and additional penalties, including against corporations. Based on the severity of the penalty, the Law includes indefinite and definite sentences. However, the Law remains weak on restitution that should be action sanctions rather than criminal sanctions and lack of corporate criminal liability regulation. The severity of the penalty that was adopted by the Law should be in the form of indefinite sentences to provide the maximum deterrent effect. In addition, there is a lack of synchronization between the Law and other laws, including the Laws on Human Trafficking, Pornography, and the Elimination of Domestic Violence.

Direct Numerical Solution of the LQR with Input Derivative Regularization Problem

This paper develops a new method for computing the state feedback gain of a Linear Quadratic Regulator (LQR) with input derivative weighting that circumvents solving the Riccati equation. The additional penalty on the derivatives of the input introduces intuitively tunable weights and enables smoother control characteristics without the need of model extension. This is motivated by position controlled mechanical systems. The physical limitations of these systems are usually their velocity and acceleration rather than the position itself. The presented algorithm is based on a discretization approach to the calculus of variations and translating the original problem into a least-squares with equality constraints problem. The control performance is analyzed using a laboratory setup of an underactuated crane-like system.

Word Segmentation on Discovered Phone Units With Dynamic Programming and Self-Supervised Scoring

Recent work on unsupervised speech segmentation has used self-supervised models with phone and word segmentation modules that are trained jointly. This paper instead revisits an older approach to word segmentation: bottom-up phone-like unit discovery is performed first, and symbolic word segmentation is then performed on top of the discovered units (without influencing the lower level). To do this, I propose a new unit discovery model, a new symbolic word segmentation model, and then chain the two models to segment speech. Both models use dynamic programming to minimize segment costs from a self-supervised network with an additional duration penalty that encourages longer units. Concretely, for acoustic unit discovery, duration-penalized dynamic programming (DPDP) is used with a contrastive predictive coding model as the scoring network. For word segmentation, DPDP is applied with an autoencoding recurrent neural as the scoring network. The two models are chained in order to segment speech. This approach gives comparable word segmentation results to state-of-the-art joint self-supervised segmentation models on an English benchmark. On French, Mandarin, German and Wolof data, it outperforms previous systems on the ZeroSpeech benchmarks. Analysis shows that the chained DPDP system segments shorter filler words well, but longer words might require some external top-down signal.

Trend filtering for functional data

Despite increasing accessibility to function data, effective methods for flexibly estimating underlying functional trend are still scarce. We thereby develop a functional version of trend filtering for estimating trend of functional data indexed by time or on general graph by extending the conventional trend filtering, a powerful nonparametric trend estimation technique for scalar data. We formulate the new trend filtering by introducing penalty terms based on ‐norm of the differences of adjacent trend functions. We develop an efficient iteration algorithm for optimizing the objective function obtained by orthonormal basis expansion. Furthermore, we introduce additional penalty terms to eliminate redundant basis functions, which leads to automatic adaptation of the number of basis functions. The tuning parameter in the proposed method is selected via cross validation. We demonstrate the proposed method is locally adaptive and can identify change points through simulation studies and applications to real‐world datasets.

Energy capture optimization of heave oscillating buoy wave energy converter based on model predictive control

The optimal constant damping control based on the peak frequency of irregular wave is commonly adopted to improve the wave energy capture efficiency for the oscillating buoy wave energy converter (WEC) while the influence of the wave frequency change cannot be considered. In this paper, a real-time PTO force control optimization method is proposed based on model predictive control (MPC). Firstly, the dynamic model of the buoy is built based on the Cummins equation. Secondly, the additional penalty terms which may make the optimization problem convex are introduced into the original maximized energy objective, and their effects on the efficiency are investigated. Then, the deterministic sea wave prediction method is used to predict the future wave force aiming to make up the shortage that the classical MPC cannot compensate the external disturbance. Finally, the energy capture performance of MPC for the oscillating buoy WEC was compared with the resistive control. The results show that the MPC method can improve the energy capture by about 40%–60% under the irregular wave conditions.

Tinjauan Yuridis Sanksi Pidana Delik Perbuatan Cabul terhadap Anak dalam Undang-Undang Nomor 35 Tahun 2014 tentang Perlindungan Anak dan Undang-Undang Nomor 12 Tahun 2022 tentang Tindak Pidana Kekerasan Seksual

This study focuses on sexual crimes in the form of obscene acts against children. According to R. Soesilo, obscene acts are all acts that violate decency or decency, or can also constitute a heinous act that is included in the environment of sexual lust. The problem lies in the criminal sanctions regulated between the two regulations. Criminal sanctions regulated in the PA Law and the PKS Law have differences in terms of the length of the sentence, the amount of the fine, and others. Then there will also be a test of the PA Law and the TPKS Law against the theory of the purpose of punishment. The research method used is a normative research method, namely research conducted with reference to the principles, legal concepts, legal norms contained in the legislation. The results of this research are that in terms of the comparison of the length of imprisonment or the number of fines, the PA Law is more effective than the TPKS Law. There are also articles regulated in the PA Law that are not regulated in the TPKS Law, such as Articles 76D and 76E. In the article, it is more specific how to commit obscene acts, namely by means of "threats of violence and violence." Both the PA Law and the TPKS Law adhere to a combined theory. In the PA Law and the TPKS Law, the main punishments regulated are imprisonment, fines and payment of restitution to victims. If it is related to the combined theory, then the PA Law and the TPKS Law have fulfilled the purpose of the combined theory. However, in the TPKS Law, in addition to stipulating the main punishment, it also regulates additional crimes, namely revocation of child custody or revocation of guardianship, announcement of the identity of the perpetrator and/or confiscation of profits and/or assets obtained from criminal acts of sexual violence. With the provision of additional penalties in the TPKS Law, it can be seen that the types of criminal sanctions in the TPKS Law provide more complete understanding of the combined theory. So that it can be concluded that the TPKS Law in terms of types of criminal sanctions is more comprehensive in its arrangement.

SANKSI TERHADAP PERJANJIAN PENETAPAN HARGA (PRICE FIXING) PADA SEKTOR JASA PENGANGKUTAN UDARA (Analisis Putusan KPPU Nomor 15/KPPU-I/2019)

This study discusses the sanctions imposed by the KPPU in the price fixing agreement and how the Commission Council considers the price fixing agreement. This research uses normative legal research, with the research approach used in this study using a statutory approach and a case approach and the data collection method in this research is library research. The results of this study are that the administrative sanctions imposed on the Reported Parties in this decision are only to notify the Business Competition Supervisory Commission in writing before taking any business actor policies that will affect the business competition map. The reported parties should be subject to administrative sanctions in the form of fines. However, due to the ratification of Law Number 11 of 2020 concerning Job Creation, especially Article 48 and also Article 49 concerning additional penalties in this Law, it was removed. Then, according to Article 5 of Government Regulation Number 44 of 2021, especially in paragraph (1) letter c, the Commission Council in deciding this case considered a clear reason, namely the Corona Virus Disease 2019 (COVID-19) Pandemic. So, the Reported Parties in this case were only given administrative sanctions and they were not given. Then, in deciding the case, the Commission Council considered it from the philosophical, sociological and juridical aspects.