The Discriminatory History of Gun Control

Gun control is an issue that has been ingrained in the societal conscious as a measure to reduce gun violence. Many people, however, are unaware of the discriminatory history on which this legislation is based. The earliest instances of gun control in America can be traced to laws instituted by Southern colonies which explicitly banned African Americans from owning firearms. White slave owners feared an armed uprising and sought to keep weapons away from blacks. This trend continued even after the Civil War. Less explicitly racist laws were enacted, but the goal remained the disarmament of African Americans. The North is often considered to have the most stringent gun regulations, but almost no laws regarding firearms existed there until the end of the 18th century. Gun control only began to gain popularity due to the increasing number of immigrants, especially Eastern and Southern Europeans, who were associated with gun crimes. Crime reduction became the stated goal of gun control, despite its discriminatory intentions. For example, New York City instituted a licensing requirement that seemed like a reasonable measure to lower gun crime. One of the primary motives behind this act was to keep firearms out of the hands of immigrants. The police were given the discretion on who they would grant permits to. This allowed them to deny the applications of those they deemed dangerous or undesirable. More modern gun control consequently targets a new group for discrimination. The poor now faces the largest burden from most firearms regulations. Crime reduction and consumer safety are cited as justification for price floors on firearms. These laws, however, simply shift criminal gun demand to other sectors, but they ensure the poor will not be able to defend themselves. Some may contend that gun control is necessary to reduce gun crime and whatever inherent discrimination exists is a sacrifice that must be made in the name of safety. Unfortunately, most gun control does little or nothing to reduce crime and only the prejudice inherent in these regulations remain

Essays on risk management in portfolio optimization and gas supply networks

This work focuses on developing algorithms and methodologies to solve problems dealing with uncertainty in portfolio optimization and industrial gas networks. First, we study the Mean-SemiVariance Project (MSVP) portfolio selection problem, where the objective is to obtain the optimal risk-reward portfolio of non-divisible projects when the risk is measured by the semivariance of the portfolio\u27s Net-Present Value (NPV) and the reward is measured by the portfolio\u27s expected NPV. Similar to the well-known Mean-Variance portfolio selection problem, when integer variables are present (e.g., due to transaction costs, cardinality constraints, or asset illiquidity), the MSVP problem can be solved using Mixed-Integer Quadratic Programming (MIQP) techniques. However, conventional MIQP solvers may be unable to solve large-scale MSVP problem instances in a reasonable amount of time. In this paper, we propose two linear solution schemes to solve the MSVP problem; that is, the proposed schemes avoid the use of MIQP solvers and only require the use of Mixed-Integer Linear Programming (MILP) techniques. In particular, we show that the solution of a class of real-world MSVP problems, in which project returns are positively correlated, can be accurately approximated by solving a single MILP problem. In general, we show that the MSVP problem can be effectively solved by a sequence of MILP problems, which allow us to solve large-scale MSVP problem instances faster than using MIQP solvers. We illustrate our solution schemes by solving a real MSVP problem arising in a Latin American oil and gas company. Also, we solve instances of the MSVP problem that are constructed using data from thePSPLIB library of project scheduling problems. Both approaches are empirically shown to be effective and outperforming the default benchmark MIQP solver to find near-optimal solutions for the selected instances of the MSVP problem.Second, we present an algorithm to compute near-optimal Value-at-Risk (VaR) portfolios. It is known to be difficult to compute optimal VaR portfolios; that is, an optimal risk-reward portfolio allocation using VaR as the risk measure. This is due to VaR being non-convex and of combinatorial nature. In particular, it is well-known that the VaR portfolio problem can be formulated as a mixed-integer linear program (MILP) that is difficult to solve with current MILP solvers for medium to large-scale instances of the problem. The proposed algorithm addresses the shortcomings of the MILP formulation in terms of solution time. To illustrate the efficiency of the presented algorithm, numerical results are presented using historical asset returns from the US financial market. Empirical results suggest that the developed algorithm obtaining a lower bound for VaR outperforms the recently proposed algorithms from the literature. Additionally, we also show that the developed algorithms are able to obtain and guarantee near-optimal solutions for large scale instances of VaR portfolio optimization problem more efficiently than the off the shelf commercial solvers within 1% accuracy.Third, we analyze the impact of the sensor reading errors on parameters that affect the production costs of a leading US industrial gas supply company. For this purpose, a systematic methodology is applied first to determine the relationship between the system output and input parameters, and second to identify the assigned input sensors whose readings need to be improved in a prioritized manner based on the strength of those input-output relationships. The two main criteria used to prioritize these sensors are the decrease in production costs and the decrease in production costs’ volatility obtained when the selected sensor’s precision is improved. To illustrate the effectiveness of the proposed approach, we first apply it to a simplified version of the real supply network model where the results can be readily validated with the simulated data. Then, we apply and test the proposed approach in the real supply network model with historical data. The experiments suggest that we are able to obtain a significant decrease in production costs and in production costs’ volatility by prioritizing the sensors\u27 maintenance subject to a limited budget.Finally, we analyze the performance of portfolio allocation strategies using clustering techniques based on financial asset\u27s correlation matrices. The Markowitz\u27s mean-variance framework uses first and second order sample moment estimators which are highly subject to estimation errors. The estimation error on the moments could be very significant and it may offset the benefits obtained from the diversification of the portfolio. There are a number of methodologies proposed in the literature to reduce the effect of the estimation error on the moment estimators. A group of these are based on the clustering approaches using sample correlation coefficients as the similarity measure. The idea is to obtain a hierarchical structure between the financial assets and then to use this information to filter the underlying true representative economic information between the assets and to reflect it in a modified correlation matrix. The objective of this study is to replicate and verify some of the published work comparing different allocation strategies and also incorporating recently published hierarchical clustering based portfolio selection strategies into out of sample performance evaluation across different datasets. Initial findings suggest that the difference between the performance of the classical strategies and the recently developed clustering based methodologies are not statistically significant from each other when only positive weights are allowed in the portfolios

Influence of Market Value-To- Book Value (MV/BV) and Return on Equity (ROE) Ratios on Investment Decisions of Common Stockholders in Quoted Manufacturing Companies in North-West Nigeria

This research work aimed at determining the influence of Market Value-to-Book-Value (MV/BV) and Return on Equity (ROE) ratios on investment decisions of common stockholders in quoted manufacturing companies in North-West Nigeria. Two research questions and two null hypotheses were raised for the study. Descriptive survey design was adopted for the study.  The population for the study consisted of 230,898 respondents, made up of 230,638 common stockholders registered with 33 accredited stockbrokerage firms in North-West Nigeria and 260 accountants from 84 quoted manufacturing companies as at 31st December 2017. The proportionate stratified and purposive sampling techniques were employed to select a sample size of 465 respondents made up of 95 accountants in manufacturing companies and 370 common stockholders registered with accredited stockbrokerage firms in manufacturing companies in North-West Nigeria.  The data collected were analyzed using mean to answer the two research questions while t-test analysis was employed in testing the two null hypotheses at 0.05 level of significance.  The findings obtained include: market-to-book value ratio is used as a measure of deviations between book and market values of shares and stockholders do not extensively analyse this ratio and Return on Equity ratio is used by stockholders to compare dividend at the end of the financial year for consistency and with returns from other companies in the same industry to a moderate extent.  It was, therefore, recommended that Common stockholders should always analyse the firms’ Market Value-to-Book-Value (MV/BV) and Return on Equity ratios at the end of every financial year to understand it to a great extent as MV/BV enables them to know the market value of their shares, determine their stock’s performance, while ROE ratio reveals the earning power of a company on stockholders’ book value investment and how much returns the stockholders have been receiving for better investment decisions. Keywords: Market value to book value, return on equity, ratios, common stockholders, investment decisions DOI: 10.7176/RJFA/10-6-05 Publication date:March 31st 201

Untersuchungen zur Belagsbildung und Charakterisierung der Ascheablagerungen in steinkohlegefeuerten Kraftwerken

Bei der Verfeuerung fester Brennstoffe in Kraftwerken kann es durch Ascheablagerungen auf Heizflächen (Membranwände, Überhitzer, Zwischenüberhitzer, etc.) zur Verminderung des Wärmetransports und zu Betriebsstörungen und Schädigungen an Anlagenteilen kommen. Verantwortlich für diese Ablagerungen sind die mineralischen Bestandteile der Kohle, die beim Verbrennungsprozess zu schmelzflüssigen Phasen umgewandelt werden können. In einem Heizkraftwerk (730 MWth) wird für drei Steinkohlen das Verbrennungsverhalten im Hinblick auf Asche- und Belagsbildung sowie Belagscharakterisierung untersucht. Ein Schwerpunkt ist die Untersuchung des Belagaufbaus auf gekühlten und ungekühlten Depositionssonden. Mit der gekühlten Sonde wird die Initialschicht, die sich unmittelbar auf den Kesselrohren bildet, untersucht, während mit der ungekühlten Sonde eine Untersuchung im Hinblick auf die Deckschicht durchgeführt wird. Die Initialschichten zeigen für alle drei untersuchten Steinkohlen eine Anreicherung an Eisen im Vergleich zur Deckschicht und des Flugstaubes. Ursächlich für diese eisenreiche Grundschicht ist nach bisherigen Erkenntnissen das Mineral Pyrit. Neben den experimentellen und analytischen Untersuchungen werden mit der Software FactSage Gleichgewichtsberechnungen unter Berücksichtigung der im Brennstoff enthaltenen Mineralien (Pyrit, Illit, Kaolinit und Quarz) und der Analyse von Aschepartikeln unter oxidierenden und reduzierenden Verbrennungsbedingungen durch-geführt. Der Einfluss der Feuerraumatmosphäre auf das Ascheschmelzverhalten und die daraus hervorgehenden Ablagerungen wird mit diesen Berechnungen beurteilt. Die Ergebnisse zeigen, dass die Ablagerung eines Aschepartikels erheblich durch die Partikelhistorie beeinflusst wird. Abgesehen von der Partikelzusammensetzung haben insbesondere die Temperatur und die jeweilige Atmosphäre, die ein Partikel auf seiner Flugbahn bis zum Auftreffen auf die Heizfläche durchläuft, großen Einfluss auf die Mineralumwandlung und das Anhaften des Partikels

Tick bite cases among hazelnut farm workers in Giresun

Ticks are arthropod vectors of many diseases. The prevalence of Lyme disease transmitted by Ixodes is not known in Turkey. The disease is caused by Borrelia species and can also be seen in domestic animals. The aim of this study is to identify the ticks, which are collected from the agricultural workers who admitted to hospitals during the hazelnut harvest season between August and September 2015, at species and genus level and investigate whether these ticks vector of Borrelia spp. Method: In this study, 152 ticks collected from 134 patients were investigated. Of all samples including larvae and nymphs, 95.24% were collected in September. All patients who admitted with complaints of tick bites were agricultural workers collecting nuts in the gardens at sea level. The ticks were identified at species and genus level with stereomicroskop, hemolymph fluid examined directly by dark-field microscope and cultured in the Borellia BarbourStoenner-Kelly (BSK-H) medium. Results: Of all the ticks, 126 (82.9%) were adults, 13 (8.55%) were nymphs and 13 (8.55%) were larvae. Stereoscopic examination of the ticks revealed that 125 (82.2%) of the adults were Ixodes ricinus and 1 (0.65%) was Rhipicephalus sanguineus. All of the 13 nymphs (8.55%) and 13 larvae (8.55%) were identified as Ixodes spp.. All forms of development cycle were detected in the samples and the forms were inconsistent with the expected development cycle. Borrelia spp., the agent of Lyme disease, was investigated in the 146 ticks defined as I. ricinus and Ixodes spp. Borrelia spp were detected by dark field microscope in 3 (2.05%) of the 146 Ixodes and Borrelia spp. were identified in 5 (3.4%) of the cultures. Conclusions: These results demonstrate that Lyme disease can be seen in our region and the most probable vector is Ixodes ricinus

Regression games

The solution of a TU cooperative game can be a distribution of the value of the grand coalition, i.e. it can be a distribution of the payo (utility) all the players together achieve. In a regression model, the evaluation of the explanatory variables can be a distribution of the overall t, i.e. the t of the model every regressor variable is involved. Furthermore, we can take regression models as TU cooperative games where the explanatory (regressor) variables are the players. In this paper we introduce the class of regression games, characterize it and apply the Shapley value to evaluating the explanatory variables in regression models. In order to support our approach we consider Young (1985)'s axiomatization of the Shapley value, and conclude that the Shapley value is a reasonable tool to evaluate the explanatory variables of regression models

Determination of Parasitic Contamination in Vegetables Collected from Local Markets in İzmir Province, Türkiye

Objective:Fresh vegetables are an important part of a healthy and nutrient-rich diet but the consumption of raw vegetables without proper washing is the main way for transmission of parasites. This study was aimed at determining the rate of parasitic contamination in prewashed fresh vegetables sold at randomly selected 10 retail markets which is the last step to reach the consumer in İzmir, Türkiye.Methods:A total of 80 samples selected from eight types of vegetables including tomato, spinach, lettuce, rocket, mint, parsley, dill, and cucumber were examined for parasitic agents microscopically by sedimentation method after washing samples with normal saline. Statistical analysis was performed using SPSS software version 20.0.Results:Protozoan cysts, helminth eggs, and larvae were detected in 21 (26.2%) of 80 samples from eight different vegetable species. Rhabditidiform larvae 18.7%, Blastocystis spp. 5%, Toxocara spp. 2.5%; Ascaris spp., Fasciola spp., Entamoeba histolytica/ Entamoeba dispar and hooked worms were found in 1.2%. Spinach and mint samples were contaminated with parasites significantly more than other fresh vegetable samples (p<0.008, odds ratio =80.0; p<0.017, odds ratio =46.6 respectively). Cruznema spp., a plant nematode, was found at the highest rate according to the results of culture, polymerase chain reaction and sequencing, respectively.Conclusion:In this study, the parasitic contamination was found in approximately one of the four vegetables sold in randomly selected markets in İzmir. These findings show that vegetables sold in local markets can cause parasitic infections if they are consumed without adequate washing and awareness should be raised on this issue. In addition, it was concluded that morphological examinations should be confirmed by molecular studies and sequencing as much as possible in order to avoid misdiagnosis of rhabditidiform larvae

Clinical Problems in the Hospitalized Parkinson's Disease Patient: Systematic Review

The problems Parkinson's disease (PD) patients encounter when admitted to a hospital, are known to be numerous and serious. These problems have been inventoried through a systematic review of literature on reasons for emergency and hospital admissions in PD patients, problems encountered during hospitalization, and possible solutions for the encountered problems using the Pubmed database. PD patients are hospitalized in frequencies ranging from 7 to 28% per year. PD/parkinsonism patients are approximately one and a half times more frequently and generally 2 to 14 days longer hospitalized than non-PD patients. Acute events occurring during hospitalization were mainly urinary infection, confusion, and pressure ulcers. Medication errors were also frequent adverse events. During and after surgery PD patients had an increased incidence of infections, confusion, falls, and decubitus, and 31% of patients was dissatisfied in the way their PD was managed. There are only two studies on medication continuation during surgery and one analyzing the effect of an early postoperative neurologic consultation, and numerous case reports, and opinionated views and reviews including other substitutes for dopaminergic medication intraoperatively. In conclusion, most studies were retrospective on small numbers of patients. The major clinical problems are injuries, infections, poor control of PD, and complications of PD treatment. There are many (un-researched) proposals for improvement. A substantial number of PD patients' admissions might be prevented. There should be guidelines concerning the hospitalized PD patients, with accent on early neurological consultation and team work between different specialities, and incorporating nonoral dopaminergic replacement therapy when necessary. © 2011 Movement Disorder Societ

On Strong NP-Completeness of Rational Problems

The computational complexity of the partition, 0-1 subset sum, unbounded subset sum, 0-1 knapsack and unbounded knapsack problems and their multiple variants were studied in numerous papers in the past where all the weights and profits were assumed to be integers. We re-examine here the computational complexity of all these problems in the setting where the weights and profits are allowed to be any rational numbers. We show that all of these problems in this setting become strongly NP-complete and, as a result, no pseudo-polynomial algorithm can exist for solving them unless P=NP. Despite this result we show that they all still admit a fully polynomial-time approximation scheme.Comment: to appear in Proc. of CSR 201