A comparative study of Twitter utilization in disaster management between public and private organizations

Twitter has become a commonly used platform by both public and private organizations to assist with the dissemination of information related to disaster management. This research makes use of a mixed‐method approach in determining the extent and manner in which Twitter is used to disseminate disaster management information by both public and private organizations. This research found that public organizations are bound by strict regulations resulting in a lower volume and smaller variety of disaster‐related information being disseminated. The nature of an organization and the processes of decision making therein are suggested to influence the ability of an organization to successfully use Twitter as an effective tool for disaster management. Organizations in Thailand currently underutilize Twitter for disaster management, as neither public nor private organizations use Twitter as a multidirectional communication disaster management tool.     

Deep learning for sex determination: Analyzing over 200,000 panoramic radiographs

The objective of this study is to assess the performance of an innovative AI-powered tool for sex determination using panoramic radiographs (PR) and to explore factors affecting the performance of the convolutional neural network (CNN). The study involved 207,946 panoramic dental X-rays and their corresponding reports from 15 clinical centers in São Paulo, Brazil. The PRs were acquired with four different devices, and 58% of the patients were female. Data preprocessing included anonymizing the exams, extracting pertinent information from the reports, such as sex, age, type of dentition, and number of missing teeth, and organizing the data into a PostgreSQL database. Two neural network architectures, a standard CNN and a ResNet, were utilized for sex classification, with both undergoing hyperparameter tuning and cross-validation to ensure optimal performance. The CNN model achieved 95.02% accuracy in sex estimation, with image resolution being a significant influencing factor. The ResNet model attained over 86% accuracy in subjects older than 6 years and over 96% in those over 16 years. The algorithm performed better on female images, and the area under the curve (AUC) exceeded 96% for most age groups, except the youngest. Accuracy values were also assessed for different dentition types (deciduous, mixed, and permanent) and missing teeth. This study demonstrates the effectiveness of an AI-driven tool for sex determination using PR and emphasizes the role of image resolution, age, and sex in determining the algorithm's performance.     

The Impact of Voter Evaluations of Leaders’ Traits on Voting Behaviour: Evidence from Seven European Countries

This article aims to examine how the evaluation of party leaders’ traits influences voting behaviour. The work incorporates data from election studies across seven countries with different social contexts (Portugal, Spain, Ireland, Germany, United Kingdom, Italy and Hungary). Characteristics of leaders were placed into two groups: competence and warmth, in accordance with the stereotype content model and relevant studies on evaluations of leaders’ traits. Since different personality traits were evaluated within each country, the analysis was based on the two aforementioned dimensions and the political ideology of the leader. Multiple sequential binary logistic regression models were performed to analyse the predictive power of competence and warmth on voting behaviour, controlling for socio-demographic and political ideology variables of voters. Results reinforce the personalisation of politics theory, showing the relevance of leaders’ warm personality traits. As for the competence dimension, it was proven to be decisive only with regard to left-wing party leaders.     

Time-resolved hair analysis of MDMA enantiomers by GC/MS-NCI

The aim of the study was to determine the enantioselective disposition of 3,4-methylenedioxymethamphetamine (MDMA) and other amphetamine-type stimulants (ATS) in segmented hair specimens of self-declared ecstasy abusers, who took part in a double-blind placebo-controlled six-way crossover study during approximately 7 weeks, during which they received a 75 and a 100 mg dose of racemic MDMA twice. Hair specimens were washed and cut into pieces of 2 cm length. After digestion and solid phase extraction, the enantiomers were derivatized with a chiral agent (2S,4R)-N-heptafluorobutyryl-4-heptafluorobutoyloxy-prolyl chloride, developed at the authors laboratory and quantified by gas chromatography coupled to mass spectrometry operating in the negative chemical ionization mode. Most of the hair specimens that were tested positive for MDMA showed a predominance of the (R)-enantiomer. The R/S ratios of MDMA varied between 1.02 and 2.75 and total concentrations ranged from 0.1 to 20.1 ng/mg. The enantiomers of its metabolite 3,4-methylenedioxyamphetamine (MDA) were also quantified in most hair segments. The R/S ratios of MDA varied between 0.60 and 1.60, while the concentrations of the enantiomers ranged from 10 to 160 pg/mg hair. When segmental analysis was performed on single hair specimens, no inversion of the R versus S ratios of MDMA and MDA was observed. The predominance of (R)-MDMA in hair was in accordance with those already published for other matrices. Furthermore, both enantiomers of amphetamine (AM) were also detected in hair segments of four volunteers and the R/S ratios ranged from 1.00 to 1.47.     

Y-chromosomal STR haplotypes in a population from the Amazon region, Brazil

Haplotype and allele frequencies of the nine Y-STR (DYS19, DYS389 I, DYS389 II, DYS390, DYS391, DYS392, DYS393, DYS385 I/II) were determined in a population sample of 200 unrelated males from Belém, Brazil. The most common haplotypes are shared by 1.5% of the sample, while 186 haplotypes are unique. The haplotype diversity is 0.9995+/-0.0006. The data obtained were compared to those of other Brazilian populations. AMOVA indicates that 99.91% of all the haplotypical variation is found within geopolitical regions and only 0.09% is found among regions.     

Implementing Performance Budgeting at the State Level: Lessons Learned from New Jersey

This article considers barriers and strategies for implementing performance budgeting in real-time application by a state-level government. The lessons learned from the State of New Jersey’s implementation of the Governor’s Performance Budgeting Initiative offer guidelines for public and nonprofit sector organizations attempting similar efforts. Data was gathered through a series of focus groups with key executive-level administrators. Observations and recommendations for enhancing and reenergizing current performance budgeting strategies for a state or agency are suggested.     

Optimal patrol routes: interdicting and pursuing rhino poachers

Interdiction patrolling (also known as hot spots policing) is a proactive police operation that depends on good planning. And the pursuit of fleeing suspects is a challenging operation that all police forces engage in on a regular basis. We give software tools that improve the effectiveness of both. We demonstrate the effectiveness of our tools by applying them to the case of rhino poaching in wildlife reserves. An interdiction patrol pre-emptively seeks out poaching parties within a reserve. Upon picking up the trail of a poaching party, a pursuit team needs a pursuit strategy that optimizes their chances of an interception. Our interdiction patrol route tool identifies optimal interdiction patrol routes to walk. This tool is based on a Stackelberg game and represents different types of poachers and their utilities. These utilities are updated (learned) each time new information on poaching party routes is added to the database. Our second tool provides a real-time sequence of team member moves that maximizes the team’s chances of apprehending a pursued party. We show that our tools perform well when applied to simulated and real data.     

The prevention of international economic crime: Make it unprofitable for criminals and cohorts

Economic greed and the possibility of large profits are very powerful incentives for many criminals. This is especially true in the areas of international money laundering and drug related crimes. There are always criminals who are interested in certain activities as long as the financial rewards of these crimes are larger than the possible risks involved. The efforts and tactics which have been used so far to combat international economic crimes were not successful at all and we need to consider new options, even if some of these options seem controversial at first. Doing nothing would have catastrophic consequences for the economic well‐being of our society. Concerted and deliberate action plans are needed to prevent and to discourage criminals, and their facilitators and cohorts, from these types of illegal activities. Governments and citizens need to agree on methods to eliminate the profit motive of these economic crimes. Only after that will we have a chance to prevent the unfair enrichment of small numbers of criminal elements in our society, at the cost of law abiding citizens.