The potential influence of extralegal characteristics on the outcome of post-Furman capital cases (1972) has been a focus of criminal justice researchers and legal scholars. Much of this literature has assessed the impact of victim and defendant race on the likelihood of receiving the death penalty while a relatively underdeveloped body of research focuses on how victim sex may affect capital sentencing decisions. The present study uses focal concerns theory and the chivalry hypothesis to test the potential mediating effect of theoretical variables on the relationship between victim sex and juror capital sentence decision-making. In addition, it uses victim sex specific logistic regression models to examine if different theoretical and/or control variables are important predictors of receiving the death penalty for male victim cases versus female victim cases. Findings demonstrate that victim rape mediates the relationship between victim sex and juror death penalty decision-making. In addition, findings reveal that sex specific models better explain juror decision making than the full model including victims of both sexes and that different extralegal and legal characteristics predict juror decision to choose the death penalty in cases with male victims versus female victims. Theoretical and legal implications as well as directions for future research are discussed.

Several justifications exist for the death penalty, yet it is only recently that the concept of “closure” has come to serve as a rationale for American capital punishment. This contemporary justification promises murder victims’ families that the execution of their loved one’s murderer should provide them with “closure”—a contested word that typically denotes an end to the pain associated with their loved one’s murder. How and when this new narrative came about has garnered little scholarly attention, particularly as murder victims’ families begin to challenge closure as relevant to their healing. The goals of the current study seek to: 1) elucidate how closure entered the American death penalty debate; 2) illustrate the myriad meanings assigned to closure, identifying how various stakeholders have trafficked in the term’s use; 3) examine how closure has been used politically to legitimize death penalty practices and the state’s right to take life; and 4) critically analyze claims that closure has “symbolically transformed” the American death penalty today. The study employs discursive textual analysis of nearly 2500 American newspaper stories from 1989 to 2008, legislative hearings, legal case histories, academic and popular sources, and archival materials from American death penalty and victims’ rights groups during this twenty year period. The findings illustrate that closure entered death penalty discourse in the late 1980s, and reached a tipping point in news coverage in 2001 with Timothy McVeigh’s execution. While the term was used in nearly every way imaginable, the findings illustrate it was most prominently used in supporting secondary victims’ “right to view” the executions of their loved ones’ murderers and in justifying Timothy McVeigh’s execution for his role in the Oklahoma City Bombing. I argue that the media’s sensational portrayals of such historical moments allowed them to serve as “galvanizing events” ushering in closure as a powerful symbol in justifying the state’s right to take life and the view that executions are a form of “therapeutic justice.” Despite closure being used to support certain death penalty practices, the analyses presented here provide little support for the notion that closure has “symbolically transformed” American capital punishment today as has been suggested by some scholars. Closure is a small blip in print news coverage and does not resonate strongly with Americans’ support for capital punishment in national opinion polls. The study concludes with a critical examination of the role of closure as a contemporary, and empirically unchallenged, justification for the death penalty—one that serves as an empty promise for murder victims’ loved ones. / text

Schedule-based transit assignment models have been studied extensively from 2000, considering more time-dependent transit passenger behavior associated with the transit schedule. Currently, transit schedule information is more easily accessed using new telecommunications systems, such as mobile devices and the internet. One critical example of information sharing is Google's General Transit Feed Specification (GTFS). The information of the schedule per se, however, is not enough to explain the transit passenger's behavior, especially in a congested transit system. Regarding the congestion issues on a transit system, numerous researches have studied a transit schedule network (Nguyen et al., 2001; Nuzzolo et al., 2001; Poon et al., 2004; Hamdouch and Lawphonpanich, 2008, 2010).Along the stream toward understanding transit passenger behavior in the capacitated transit schedule network, we propose solution models for solving the deterministic and stochastic user equilibrium (SUE) problems on a capacitated transit schedule network. Nguyen et al. (2001) introduced how the capacitated user equilibrium (UE) on a transit schedule network is different from the auto user equilibrium. For the foundation of the study, we utilize the link-based and time-expanded (LBTE) transit schedule network introduced by Noh et al. (2012a) which effectively captures turning movements like transfers easily as well as maintaining the efficient size of a schedule-based network. In the LBTE transit network, time points are assigned to each link connecting two stops by each run (or route). Utilizing the "link-based" structure, a link-based shortest path (LBSP) and hyperpath search (LBHP) models (Noh et al., 2012a) are introduced. Especially, the hyperpath employs a log-sum weighting function for incorporating multiple schedule alternatives at each stop node considering passenger's stochastic behavior. One distinctive transit passenger behavior over a congested transit system is a first-in-first-out (FIFO) priority on boarding. A passenger already on board has the higher priority than passengers who are about to boarding, and the passengers arriving earlier at a stop will have higher priority than the passengers arriving later at the stop. To consider the capacitated UE considering the relation between the FIFO boarding priority and vehicle capacity constraint, we apply a "soft-capacity" cost (Nguyen et al., 2001). This soft capacity cost function allows some violation of the predefined vehicle capacity, but the violation will be penalized and affect the cost of the path in the next iteration. The penalty of the soft capacity cost function allows not to assigning passengers on the alternatives having the lower priority of boarding, which finally leads to the solution of the capacitated transit deterministic user equilibrium (DUE) or SUE problems. For the main transit assignment models, we proposed path- and hyperpath-based methods and a self-adaptive method considering deterministic and stochastic passenger behaviors. First, we developed the hyperpath-based assignment method by Noh et al. (2012b). For the FIFO transit passenger behavior, typically accompanying asymmetric (non-separable) cost relation, we also introduce a diagonalization technique (Sheffi, 1985) with the method of successive average (MSA) assignment technique. As expecting a better performance, second, we introduced the path-based assignment models using gradient projection. For the FIFO passenger behavior on boarding, we considered the same diagonalization approach used in the hyperpath-based assignment model and a full-Hessian scaling matrix in the gradient projection. By utilizing a full path set for each O-D pair, a better performance is guaranteed with the path-based model but the diagonalization technique may result in longer iterations. For improving the diagonalization steps, third, we explored several other possible methods. Above all, we proposed the better initial solution (BIS) model which assigns the initial flows on the priority path over congested links and also maintains feasible flows below the capacity constraint. On the other hand, we also added two additional assignment models to improve the diagonalization technique. One utilizes a full Hessian scaling matrix in the proposed path-based assignment model instead of diagonalization and the other is the self-adaptive gradient projection (SAGP) model introduced by Chen et al. (2012) which does not require a scaling matrix by optimizing the step-size in the path-based projection model. For improving the SAGP model, we modified the SAGP model. First, we applied the SAGP at a disaggregate level for each O-D pair as expecting a compact set of path alternatives limited by each O-D pair, called disaggregate self-adaptive gradient projection (DSAGP). Second, we applied a type of diagonalization technique in the SAGP model by maintaining the residual capacities for the estimated flows in the next iteration. Beyond just a single model development, the proposed transit assignment models not only showed various possibilities of the transit assignment, but also showed which model is more efficient and practical in terms of a real application. A computational model structure using the proposed models was mainly designed for an effective model development by sharing numerous components as well as maintaining the efficient data structure. The nine combination models based on the proposed three main models (hyperpath- and path-based and DSAGP assignment models) and the efficient BIS technique for solving the problems were tested and analyzed on a sample network and a partial Sacramento regional transit network.

To cope with dynamics and uncertainties, a novel penalty function-based hybrid, multi-agent shop floor control system is proposed in this dissertation. The key characteristic of the proposed system is the capability of adaptively distributing decision-making power across different levels of control agents in response to different levels of disturbance. The subordinate agent executes tasks based on the schedule from the supervisory level agent in the absence of disturbance. Otherwise, it optimizes the original schedule before execution by revising it with regard to supervisory level performance (via penalty function) and disturbance. Penalty function, mathematical programming formulations, and quantitative metrics are presented to indicate the disturbance levels and levels of autonomy. These formulations are applied to diverse performance measurements such as completion time related metrics, makespan, and number of late jobs. The proposed control system is illustrated, tested with various job shop problems, and benchmarked against other shop floor control systems. In today's manufacturing system, man still plays an important role together with the control system Therefore, better coordination of humans and control systems is an inevitable topic. A novel BDI agent-based software model is proposed in this work to replace the partial decision-making function of a human. This proposed model is capable of 1) generating plans in real-time to adapt the system to a changing environment, 2) supporting not only reactive, but also proactive decision-making, 3) maintaining situational awareness in human language-like logic to facilitate real human decision-making, and 4) changing the commitment strategy adaptive to historical performance. The general purposes human operator model is then customized and integrated with an automated shop floor control system to serve as the error detection and recovery system. This model has been implemented in JACK software; however, JACK does not support real-time generation of a plan. Therefore, the planner sub-module has been developed in Java and then integrated with the JACK. To facilitate integration of an agent, real-human, and the environment, a distributed computing platform based on DOD High Level Architecture has been used. The effectiveness of the proposed model is then tested in several scenarios in a simulated automated manufacturing environment.

Katalikų bažnyčios ir Lietuvos Respublikos institucijoms intensyviai bendradarbiaujant, aktualiu tampa teisinių sistemų derinimas. Tam pagrindą suteikia Šventojo sosto ir Lietuvos Respublikos sutartis, apibrėžianti teisinius bendradarbiavimo pagrindus. O taip pat Bažnyčios kanonų kodekse įtvirtinta nuostata, kad civiliniai įstatymai minimi Bažnyčios teisėje galioja su tomis pačiomis pasekmėmis ir kanonų teisėje tiek, kiek jie nėra priešingi dieviškajai teisei, ir jei kanonų teisė nenustato kitaip. Ypač svarbiu teisinių sistemų suderinamumą laikytume baudžiamosios teisės sferoje. Atsižvelgiant į pastarąsias aktualijas darbo pagrindiniu tikslu tapo Lietuvos Respublikos Baudžiamojo kodekso ir Katalik����� bažnyčios kanonų teisės apibrėžiamų bausmių bei numatomų jų taikymo praktikų palyginimas. / Active collaboration between institutions of Catholic Church and Republic of Lithuania implies importance of coordination between those legislation systems. The foundation for such cooperation ensures the Treaty between the Holy Seat and Republic of Lithuania, which determines the juridical aspect of the collaboration. Also Canon Law of the Church contains the provision that Civil Law, which is mentioned in Canon Law, obtains the same consequences when Civil Law makes no objection to Canon Law. It is especially important to expose the compatibility in field of Criminal Law. Considering the late events the main objective of the work is the comparison of penalties and applications of Penal Code of the Lithuanian Republic and the penalties of the Code of Canon Law. To reach the goal of the work it was juxtaposed the concepts of “penalty” and “offense”. Also it was examined and compared the variety of sanctions in civil and ecclesiastical law. It was established principal similarities and differences between civil and canon law definitions and penalty applications for some particular crimes.

Šiame darbe analizuojamas netesybų (baudos, delspinigių) ir palūkanų santykis civilinėje teisėje. Ši analizė paremta dviejų civilinės teisės institutų tarpusavio palyginimu. Nors teismų praktikos analizuojama tema yra pakankamai daug, tačiau teisės doktrinoje trūksta apibendrinimų, kurie formuotų aiškią ribą tarp netesybų (baudos, delspinigių) ir palūkanų. Todėl darbe gausu nuorodų į teismų praktiką. Siekiant aiškaus konteksto, darbas pradedamas nuo netesybų (baudos, delspinigių) ir palūkanų sampratų apsibrėžimo, kadangi pastaroji samprata nėra pateikta civilinės teisės norminiuose aktuose ir kelia daug klausimų bei neaiškumų tiek teisės doktrinoje, tiek teismų jurisprudencijoje. Taip pat šiame darbe gilinamasi į netesybų (baudos, delspinigių) ir palūkanų teisinio reguliavimo ypatumus Lietuvos Respublikoje, t. y., reikalavimus objektams, jų paskirtį civilinėje teisėje, skaičiavimo tvarką, ieškinio senaties taikymo probleminius aspektus, dydžio nustatymo bei mažinimo problematiką. Išanalizavus teisės doktriną ir teismų praktiką, išaiškėja netesybų (baudos, delspinigių) ir palūkanų atribojimo klausimai. / This study concentrates on analysis of relation between penalty (fine, forfeit) and interest in civil law. An analysis is based on a comparison between two civil law institutes. Although the practice of courts related to the problem under the analysis is abundant enough, but the legal doctrine lacks generalizations forming a clear concept between penalty (fine, forfeit) and interest. For this reason, the study includes abundant references to case law. In order to clarify the context the study starts from definitions of the penalty (fine, forfeit) and the interest, as well as it raises many questions and ambiguities in legal doctrine and jurisprudence of the courts. This study also focuses on penalties (fines, forfeits) and regulatory features of interest in Lithuania, etc. ie, the requirements of objects, their purpose in civil law, the calculation procedure for the application of limitation problematic aspects of sizing and reducing problems. Such review of a legal doctrine and case law, resolve the issues of delimitation of penalty (fine, forfeit) and interest.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

My dissertation mainly focuses on the regularization of parameters in the multivariate linear regression under different assumptions on the distribution of the errors. It consists of two topics where we develop iterative procedures to construct sparse estimators for both the regression coefficient and scale matrices simultaneously, and a third topic where we develop a method for testing if the skewness parameter in the skew-normal distribution is parallel to one of the eigenvectors of the scale matrix. In the first project, we propose a robust procedure for constructing a sparse estimator of a multivariate regression coefficient matrix that accounts for the correlations of the response variables. Robustness to outliers is achieved using heavy-tailed t distributions for the multivariate response, and shrinkage is introduced by adding to the negative log-likelihood l1 penalties on the entries of both the regression coefficient matrix and the precision matrix of the responses. Taking advantage of the hierarchical representation of a multivariate t distribution as the scale mixture of normal distributions and the EM algorithm, the optimization problem is solved iteratively where at each EM iteration suitably modified multivariate regression with covariance estimation (MRCE) algorithms proposed by Rothman, Levina and Zhu are used. We propose two new optimization algorithms for the penalized likelihood, called MRCEI and MRCEII, which differ from MRCE in the way that the tuning parameters for the two matrices are selected. Estimating the degrees of freedom when penalizing the entries of the matrices presents new computational challenges. A simulation study and real data analysis demonstrate that the MRCEII, which selects the tuning parameter of the precision matrix of the multiple responses using the Cp criterion, generally does the best among all methods considered in terms of the prediction error, and MRCEI outperforms the MRCE methods when the regression coefficient matrix is less sparse. The second project is motivated by the existence of the skewness in the data for which the symmetric distribution assumption on the errors does not hold. We extend the procedure we have proposed to the case where the errors in the multivariate linear regression follow a multivariate skew-normal or skew-t distribution. Based on the convenient representation of skew-normal and skew-t as well as the EM algorithm, we develop an optimization algorithm, called MRST, to iteratively minimize the negative penalized log-likelihood. We also carry out a simulation study to assess the performance of the method and illustrate its application with one real data example. In the third project, we discuss the asymptotic distributions of the eigenvalues and eigenvectors for the MLE of the scale matrix in a multivariate skew-normal distribution. We propose a statistic for testing whether the skewness vector is proportional to one of the eigenvectors of the scale matrix based on the likelihood ratio. Under the alternative, the likelihood is maximized numerically with two different ways of parametrization for the scale matrix: Modified Cholesky Decomposition (MCD) and Givens Angle. We conduct a simulation study and show that the statistic obtained using Givens Angle parametrization performs well and is more reliable than that obtained using MCD.

Using data from the 2013 American Community Survey, the author examines the wage returns to same-sex parenthood and their role in the sexual orientation wage gap. Specifically, he compares individuals by gender, sexual orientation, and household earner status. The importance of accounting for household specialization among heterosexual men and women is illustrated by the significant differences in returns to parenthood between heterosexuals of the same gender, but different earner statuses. The empirical results show that gay men face a fatherhood penalty for the presence of children between the ages of 5 and 18 irrespective of earner status. Lesbians on the other hand, experience motherhood premiums for the presence of children under the age of 5, but modest motherhood penalties for the presence of children between the ages of 5 and 18. Ultimately, differences in the wage returns to parenthood for gays, lesbians, and their respective heterosexual counterparts play a negligible role in sexual orientation wage differentials.

Coal has been used as a fuel for electricity generation for centuries. Inexpensive electricity from coal has been a key component in building large industrial economies such as USA and China. But in recent decades the negative aspects of coal, mainly carbon dioxide emissions, has changed the view on the fuel. Carbon capture and storage (CCS) is a solution to be able to continue using coal as an energy source, while limiting carbon emissions. One of the drawbacks of CCS is the energy need associated with the capture process, the energy penalty. This study aims to gather and analyze the energy penalties for the most developed types of carbon capture technologies. It also aims to model how the implementation of CCS would affect the future coal consumption. The results show that the range of energy penalties for a given type of technology is wide. Despite obtaining the energy penalty with the same simulation software, the energy penalty for post- combustion with MEA can range between 10.7% and 39.1%. Comparing mean energy penalties show that pre-combustion capture is the most efficient capture method (18.4% ± 4.4%) followed by oxy- fuel (21.6% ± 5.5%) and post-combustion (24.7% ± 7.9%). Further on, CCS implementation scenarios were compared and used as a starting point for coal consumption calculations. Three pathways were constructed in order to investigate how different distributions of technologies would affect the amount of needed coal. The pathways describe a implementation with only the most efficient technology, the least efficient and a middle option. The results suggest that a large scale implementation of CCS on coal power plant will have a significant impact on the global coal consumption. Under certain assumptions it takes up to 35 % more coal to deliver the same amount electricity with CCS in comparison without CCS. It is also found that certain implementation scenarios will struggle to produce the amount of coal that is needed to power the plants. A sensitivity analysis was performed to examine the impact of assumptions made on for instance plant efficiencies. The analysis shows that optimistic assumptions on development in plant efficiency and deploying only the best technology, uses less coal than a development without CCS and with current plant efficiencies.