Academic literature on the topic 'Raisin – Analyse informatique'

ObjectiveTo analyze the modulation of the phenotype in manifesting carriers of recessive X-linked myotubular myopathy (XLMTM), searching for possible genetic modifiers.MethodsTwelve Brazilian families with XLMTM were molecularly and clinically evaluated. In 2 families, 4 of 6 and 2 of 5 manifesting female carriers were identified. These females were studied for X chromosome inactivation. In addition, whole-exome sequencing was performed, looking for possible modifier variants. We also determined the penetrance rate among carriers of the mutations responsible for the condition.ResultsMutations in the MTM1 gene were identified in all index patients from the 12 families, being 4 of them novel. In the heterozygotes, X chromosome inactivation was random in 3 of 4 informative manifesting carriers. The disease penetrance rate was estimated to be 30%, compatible with incomplete penetrance. Exome comparative analyses identified variants within a segment of 4.2 Mb on chromosome 19, containing the killer cell immunoglobulin-like receptor cluster of genes that were present in all nonmanifesting carriers and absent in all manifesting carriers. We hypothesized that these killer cell immunoglobulin-like receptor variants may modulate the phenotype, acting as a protective factor in the nonmanifesting carriers.ConclusionsAffected XLMTM female carriers have been described with a surprisingly high frequency for a recessive X-linked disease, raising the question about the pattern of inheritance or the role of modifier factors acting on the disease phenotype. We demonstrated the possible existence of genetic mechanisms and variants accountable for the clinical manifestation in these women, which can become future targets for therapies.

Formulation of problem. The article is focused on the analysis of trends of development of credit unions and the basis for scientific and practical recommendations regarding increasing the financial potential of credit unions in system of development of small forms of agrarian business. The aim of research is the development of theoretical aspects and practical recommendations regarding increasing the financial potential of credit unions in system of development of small forms of governance in agrarian area. The object of the research is the financial potential of credit unions. Methods, used in research: generalization, comparison, logical and informative, scientific knowledge, induction, analysis. The hypothesis of the research: analytical evaluation of development trends of credit unions for identification of the feasibility of fund-raising for small forms agrarian business. The statement of basic materials. The dynamics of quantity of credit unions, the number of persons included by them, the amount of capital, loan and deposit portfolio, risks of activity is analysed as a whole and in the frames of all -Ukrainian association. The critical estimation of le gal status and prudential regulation is provided, their influence on the disclosure of financial potential of credit unions and their advantages for small forms of agrarian business as representation in regions with developed agricultural production, territorial accessibility, the opportunity of to give modest amouts of credit sums for a long term for household plots and farms is determined. The originality and practical significance of the research is the development of recommendations regarding support for small forms of governance in agrarian area by credit unions. Conclusions and perspectives of further researches. Credit unions (CU) have significant competitive advantages over banks at the level of consumer loans and credit for rural commodity producers. Therefore, free fund-raising of credit unions will play an important role in the development of small forms of governance in agrarian area.

One of the key tools that are traditionally used in solving media strategizing problems is advertising. The impacts of advertising on the processes taking place in the economy are significant and remarkably diverse, thus raising a big question to the media strategists to systematize and classify both the types of such impacts and the economic theories that study it. This work is devoted to the study of this issue: the most significant approaches to a comprehensive study of advertising at various planning periods (from instant to long-term strategic) are presented. We analyze the informative and persuasive functions of advertisement, compare the influence of its visual and textual forms and discuss key points of cognitive and behavior approaches to understand how advertisement affects the consumers’ demand. We describe basic models of economic equilibrium, which take the advertisement influence on different market structures into account, as well as two-sided models of media markets. It is shown that the less developed field of the economics of advertising is behavior and market influence analysis of the firms whose specialization is creating and distributing media content and advertisement. Due to this, we introduce the way to construct a new class of market models involving three types of economic agents — consumers, media firms and economic goods producers.

This review presents the current evidence about the use of markers of bone metabolism in the prediction of fracture healing, differences in concentrations of blood markers of bone metabolism in patients with normal and delayed consolidation of bone fragments. We analyze the relationship between the fracture site, time-stage features of its healing and urinary macromolecules, reflecting bone metabolism. Increase in bone turnover, which is observed after the fracture, is characterized by activation markers of bone resorption, with a subsequent increase in the concentration of blood markers of bone formation. However, there is a marked variability in data concerning the levels of bone markers in plasma at different stages of fracture healing. We show that in patients with delayed fracture healing there is a significant delay in raising osteocalcin levels. Prognostic features for determining fracture nonunion include low concentrations of N-terminal propeptide of procollagen type I. Determination of markers of bone metabolism in blood can serve as informative criterion for the course of reparative osteogenesis, but one must consider the nature of traumatic injury, time passed from injury, especially the state of bone tissue at the time of injury, age of the patient to identify the early stages of consolidation disturbances.

AbstractContemporary agricultural engineering searches for “safe” methods of raising crop yields, using a combination of knowledge from a number of sciences. Thus, computer modelling of plant growth and development fits this range, because it has become an area of interdisciplinary research. Presentation of knowledge in the form of mathematical computer models is one of paradigms of agricultural production systems based on the scientific and practical knowledge and information. In the scientific activity concerning agricultural engineering research tasks related to mathematical modelling of agrobiological processes have been carried out for many years. Additionally, the use of modern forecasting techniques in agriculture may bring real financial advantages with regard to the fact that based on crop yield prediction estimation of their cultivation profitability is possible. Dynamic and continuous progress of computer and informative technologies creates new opportunities showing thus growth directions of agricultural engineering. Taking this into consideration, it should be emphasised that mathematical modelling constitutes a support for decision processes which take place in agricultural production. This article discusses mathematical models, where the analysed system is described with the use of mathematical formulas. The objective of the paper was to present the current state of knowledge on mathematical methods in describing and predicting seeds germination. Possibilities of their use and new challenges which occur in the description of seeds germination were presented.

Many studies have revealed that unconscious and intensive use of pesticides causes significant environmental and health problems. In this sense, it is important to investigate the awareness level of pesticide use by producers. The basic material of the study consists of the data obtained from the survey carried out with the farmers producing fruit and vegetables in 10 specified villages in the central county of Tokat province. 110 questionnaires were applied in respect of the production rates of the villages. the data belong to 2017 between October and December. The data obtained from the survey revealed that 97% of the fruit and vegetable producers in Tokat use pesticides but 50% of them have no information about the contents of the pesticides they use. It is observed that they depend on their own experiences (50%) and the recommendations of the pesticide dealers (80%). 55% of the producers stated that the pesticide usage expenditures vary between 2 to 5 thousand Turkish Liras. These expenditure rates, which are quite high in terms of total production cost, shows that pesticides are widely used. Producers state that they use not more than gloves and masks while using pesticides as they accept their unconsciousness of the harms of pesticides to the human and environmental health, whereas they have no opinion about the danger of the residual rates of pesticides on food security. However they indicated that they will not be indifferent to possible informative trainings to be held in their villages or area. In this context, it is necessary to educate producers by experts in raising awareness of them and to ensure the continuity of these educations and to analyze the feedback of the educations by making pesticide residue analyzes.

The realization of high quality medical measures for protecting children’s health remains an important issue at the stage of reforming the domestic medicine. The aim of this work was to study and analyze the system of medical aid for children in Ukraine. The research focused on normative-legal acts regulating the organization of medical aid for children. The research methods are informative, retrospective, historical, logical and analytical. The analysis of normative-legal documents regulating the organization of rendering of medical aid for children established their formality and economic groundlessness. According to January 2017, only 35 documents were included into the Registry of medical technological documents in the direction of «Pediatrics». It means that many children’s pathological states are not covered by standardization, what reduces the quality of medical aid. The national programs for the improvement of health status of children remained unrealized due to the lack of funding, ill-coordinated links between program implementers, the lack of effective monitoring of the quality and results of realizing the state programs. The implementation result of IMChI strategy was the reduction of mortality rate in children of different age groups in the pilot regions. In terms of reforming the combined model (model III) is the most effective and acceptable for pediatric care rendering. The population expenses reach nearly half of the total funding of the sector, what demonstrates the inconsistencies between the real state of children’s assurance in the health care system of Ukraine and national normative acts. It was determined the necessity of structural reorganization of the system, the optimization of beds number, the increase of medical care funding from state and local budgets, the raising of resource efficiency of health care system and the continued development and implementation of modern protocols (standards) for the treatment of children pathologies.

Application of Bayesian inference to analyze real economic phenomena is rare in the literature on applied economics. This study contributes in two ways. Firstly, it contributes to methodological advancement in the literature on applied economic modeling by estimating a structural model using the classical econometric framework as well as the Bayesian two-stage econometric framework. The performance of the two approaches is compared due to the small sample size and the best model is selected. Secondly, the study is used to get fresh evidence about the impact of human capital upon economic growth in the form of Bayes mean estimates along with their Highest Posterior Density Intervals (HPDIs) which give certain ranges of estimates within which the parameters are likely to lie. Annual data on the Pakistan economy ranging from 1965 to 2019 is used for the estimation of the model. Classical estimates are obtained using the efficient GMM method. Bayes mean estimates are simulated using a Bayesian two-stage procedure assuming multivariate normal-Wishart informative priors. Results show that the Bayesian econometric framework gives more precise parameters’ estimates as compared to the classical econometric framework, and hence, the Bayesian inference may be preferred over classical inference, especially in the case of a small sample size. The Bayes estimates show that a 1% increase in education capital and health capital causes raising economic growth by 0.0091% and 0.1778%, respectively, with a 0.95 probability that the estimates are likely to lie within the intervals 0.0085%–0.0097% and 0.1606%–0.1952%, respectively. Hence, human capital might be considered a vital factor to achieve economic growth in Pakistan. Moreover, health capital shows strong effects as compared to education capital in the process of economic growth.

Non-muscle-invasive papillary urothelial carcinoma (NMIPUC) of the urinary bladder is the most common type of bladder cancer. Intravesical Bacille Calmette–Guerin (BCG) immunotherapy is applied in patients with a high risk of recurrence and progression of NMIPUC to muscle-invasive disease. However, the tumor relapses in about 30% of patients despite the treatment, raising the need for better risk stratification. We explored the potential of spatial distributions of immune cell subtypes (CD20, CD11c, CD163, ICOS, and CD8) within the tumor microenvironment to predict NMIPUC recurrence following BCG immunotherapy. Based on analyses of digital whole-slide images, we assessed the densities of the immune cells in the epithelial–stromal interface zone compartments and their distribution, represented by an epithelial–stromal interface density ratio (IDR). While the densities of any cell type did not predict recurrence, a higher IDR of CD11c (HR: 0.0012, p-value = 0.0002), CD8 (HR: 0.0379, p-value = 0.005), and ICOS (HR: 0.0768, p-value = 0.0388) was associated with longer recurrence-free survival (RFS) based on the univariate Cox regression. The history of positive repeated TUR (re-TUR) (HR: 4.93, p-value = 0.0001) and T1 tumor stage (HR: 2.04, p-value = 0.0159) were associated with shorter RFS, while G3 tumor grade according to the 1973 WHO classification showed borderline significance (HR: 1.83, p-value = 0.0522). In a multivariate analysis, the two models with a concordance index exceeding 0.7 included the CD11c IDR in combination with either a history of positive re-TUR or tumor stage. We conclude that the CD11c IDR is the most informative predictor of NMIPUC recurrence after BCG immunotherapy. Our findings highlight the importance of assessment of the spatial distribution of immune cells in the tumor microenvironment.

Transmission of human cytomegalovirus (CMV), from a pregnant woman to her fetus can cause congenital CMV infection, with life-long problems in some infected children. The presence of CMV in an infected individual’s bodily fluid is known as shedding. An individual can become infected with CMV through contact with another individual who is shedding CMV in their bodily fluid, and the avoidance of contact with infected fluids may reduce the risk of infection. We explored the experiences of pregnant women taking part in a study investigating CMV shedding, to identify the potential facilitators and barriers towards engaging pregnant women with CMV risk-reduction measures. Twenty pregnant women participated in semi-structured, end-of-study, telephone interviews, analysed using thematic analysis. They participated in an observational study investigating CMV shedding in pregnant women previously infected with CMV living with young children. Participating women considered that CMV testing of themselves and their newborns was a benefit of participation, without raising additional concerns. They identified that their participation was contingent on a balance of convenience and inconvenience, and benefits and risks. Participation increased their awareness of their hygiene-based practices, leading to behavioural modifications that put them in contact with urine and saliva of their children without instructions to do so. These behavioural modifications might interfere with household routines. However, they recognised it to be a time-limited risk-reduction measure, and felt empowered by the knowledge they had gained through study participation and the support they had received from their partners. Participating women gained an increased awareness of their behaviour, resulting in behavioural modification without instructions to do this, in line with previous findings that trial participation can impact on participants’ thinking about their behaviour with a possibility to influence change. Maternal research and risk-reduction measures should be centred around being informative, convenient, empowering, and supportive.

De nos jours, les systèmes de vision sont de plus en plus utilisés dans le contexte routier. Ils permettent ainsi d'assurer la sécurité et faciliter la mobilité. Ces systèmes de vision sont généralement affectés par la dégradation des conditions météorologiques en présence de brouillard ou de pluie forte, phénomènes limitant la visibilité et réduisant ainsi la qualité des images. Afin d'optimiser les performances des systèmes de vision, il est nécessaire de disposer d'un système de détection fiable de ces conditions météorologiques défavorables.Il existe des capteurs météorologiques dédiés à la mesure physique, mais ils sont coûteux. Ce problème peut être résolu en utilisant les caméras qui sont déjà installées sur les routes. Ces dernières peuvent remplir simultanément deux fonctions : l'acquisition d'images pour les applications de surveillance et la mesure physique des conditions météorologiques au lieu des capteurs dédiés. Suite au grand succès des réseaux de neurones convolutifs (CNN) dans la classification et la reconnaissance d'images, nous avons utilisé une méthode d'apprentissage profond pour étudier le problème de la classification météorologique. L'objectif de notre étude est de chercher dans un premier temps à mettre au point un classifieur du temps, qui permet de discriminer entre temps « normal », brouillard et pluie. Dans un deuxième temps, une fois la classe connue, nous cherchons à développer un modèle de mesure de la distance de visibilité météorologique du brouillard. Rappelons que l'utilisation des CNN exige l'utilisation de bases de données d'apprentissage et de test. Pour cela, deux bases de données ont été utilisées, "Cerema-AWP database" (https://ceremadlcfmds.wixsite.com/cerema-databases), et la base "Cerema-AWH database", en cours d'acquisition depuis 2017 sur le site de la Fageole sur l'autoroute A75. Chaque image des deux bases est labellisée automatiquement grâce aux données météorologiques relevées sur le site permettant de caractériser diverses gammes de pluie et de brouillard. La base Cerema-AWH, qui a été mise en place dans le cadre de nos travaux, contient cinq sous-bases : conditions normales de jour, brouillard fort, brouillard faible, pluie forte et pluie faible. Les intensités de pluie varient de 0 mm/h à 70 mm/h et les visibilités météorologiques de brouillard varient entre 50m et 1800m. Parmi les réseaux de neurones connus et qui ont montré leur performance dans le domaine de la reconnaissance et la classification, nous pouvons citer LeNet, ResNet-152, Inception-v4 et DenseNet-121. Nous avons appliqué ces réseaux dans notre système de classification des conditions météorologiques dégradées. En premier lieu, une étude justificative de l'usage des réseaux de neurones convolutifs est effectuée. Elle étudie la nature de la donnée d'entrée et les hyperparamètres optimaux qu'il faut utiliser pour aboutir aux meilleurs résultats. Ensuite, une analyse des différentes composantes d'un réseau de neurones est menée en construisant une architecture instrumentale de réseau de neurones. La classification des conditions météorologiques avec les réseaux de neurones profonds a atteint un score de 83% pour une classification de cinq classes et 99% pour une classification de trois classes.Ensuite, une analyse sur les données d'entrée et de sortie a été faite permettant d'étudier l'impact du changement de scènes et celui du nombre de données d'entrée et du nombre de classes météorologiques sur le résultat de classification.Enfin, une méthode de transfert de bases de données a été appliquée. Cette méthode permet d'étudier la portabilité du système de classification des conditions météorologiques d'un site à un autre. Un score de classification de 63% a été obtenu en faisant un transfert entre une base publique et la base Cerema-AWH. (...)
Nowadays, vision systems are becoming more and more used in the road context. They ensure safety and facilitate mobility. These vision systems are generally affected by the degradation of weather conditions, like heavy fog or strong rain, phenomena limiting the visibility and thus reducing the quality of the images. In order to optimize the performance of the vision systems, it is necessary to have a reliable detection system for these adverse weather conditions.There are meteorological sensors dedicated to physical measurement, but they are expensive. Since cameras are already installed on the road, they can simultaneously perform two functions: image acquisition for surveillance applications and physical measurement of weather conditions instead of dedicated sensors. Following the great success of convolutional neural networks (CNN) in classification and image recognition, we used a deep learning method to study the problem of meteorological classification. The objective of our study is to first seek to develop a classifier of time, which discriminates between "normal" conditions, fog and rain. In a second step, once the class is known, we seek to develop a model for measuring meteorological visibility.The use of CNN requires the use of train and test databases. For this, two databases were used, "Cerema-AWP database" (https://ceremadlcfmds.wixsite.com/cerema-databases), and the "Cerema-AWH database", which has been acquired since 2017 on the Fageole site on the highway A75. Each image of the two bases is labeled automatically thanks to meteorological data collected on the site to characterize various levels of precipitation for rain and fog.The Cerema-AWH base, which was set up as part of our work, contains 5 sub-bases: normal day conditions, heavy fog, light fog, heavy rain and light rain. Rainfall intensities range from 0 mm/h to 70mm/h and fog weather visibilities range from 50m to 1800m. Among the known neural networks that have demonstrated their performance in the field of recognition and classification, we can cite LeNet, ResNet-152, Inception-v4 and DenseNet-121. We have applied these networks in our adverse weather classification system. We start by the study of the use of convolutional neural networks. The nature of the input data and the optimal hyper-parameters that must be used to achieve the best results. An analysis of the different components of a neural network is done by constructing an instrumental neural network architecture. The conclusions drawn from this analysis show that we must use deep neural networks. This type of network is able to classify five meteorological classes of Cerema-AWH base with a classification score of 83% and three meteorological classes with a score of 99%Then, an analysis of the input and output data was made to study the impact of scenes change, the input's data and the meteorological classes number on the classification result.Finally, a database transfer method is developed. We study the portability from one site to another of our adverse weather conditions classification system. A classification score of 63% by making a transfer between a public database and Cerema-AWH database is obtained.After the classification, the second step of our study is to measure the meteorological visibility of the fog. For this, we use a neural network that generates continuous values. Two fog variants were tested: light and heavy fog combined and heavy fog (road fog) only. The evaluation of the result is done using a correlation coefficient R² between the real values and the predicted values. We compare this coefficient with the correlation coefficient between the two sensors used to measure the weather visibility on site. Among the results obtained and more specifically for road fog, the correlation coefficient reaches a value of 0.74 which is close to the physical sensors value (0.76)

Designed for secondary school and college student research, this book is a readable analysis and ready-reference guide to the war. An introductory essay presents a lucid overview of the main features of the conflict, incorporating the most recent scholarship. Five essays analyze crucial aspects of the war, from the battlefield to the homefront, and a concluding essay assesses the consequences of the war from a contemporary perspective. Ready-reference features include: a chronology of events; lengthy biographical profiles of twenty-one major figures, stressing their role in the war's origins, conduct, or outcome; the text of fifteen key primary documents such as diaries, memoirs, and newspaper editorials; a glossary of selected terms; and an extensively annotated bibliography of recommended further reading and major documentary and feature films made about the war. The essays are designed to be readable and informative, capturing the tragic character of the war as well as presenting an analysis of its main features. Topics covered include the American role in the war, the collapse of the political systems in Russia and Austria-Hungary, the success of Allied military leaders in meeting the threat of German submarine warfare, and life on the homefront in the United States, Britain, France, and Germany. A concluding essay views the war as a shaping force for the entire twentieth century and its impact on the present day. The book presents the day-to-day course of events as it involved individuals by offering excerpts from diaries and memoirs, while decision-making at the highest level appears in selections from leaders' speeches and memoranda. Shifts in public opinion in the United States are illustrated by excerpts from newspaper editorials. A selection of maps completes the text. By raising issues for discussion about The War to End All Wars and providing reference features, this work is a one-stop resource for students, teachers, and library media specialists.

The book includes a collection of articles resulting from research carried out by teachers of the Department of Humanities and whose thematic center is the relationship between people and happiness. Each chapter provides answers from a specific disciplinary field, through a qualitative methodology, the anthropological and ethical problem of achievement of happiness or personal human fulfillment. From education and ethics, the transition from some informative humanities to other performative ones is proposed, which integrate moral formation and values that advocate empathy and solidarity as a human path to happiness. From the anthropological keys of Leonardo Polo, the person can give meaning to their presence in the world, beyond the satisfaction of happiness itself, since human beings has a personal sense capable of manifesting themselves in the hopeful task. Likewise, from the personalistic anthropology, happiness is studied as a life project, moving from the conflict towards spirituality and proposing chose political educational transformations. In the field of historical sciences, the use of the concepts of person and happiness in the Magisterium of John xxiii underlines the perspectives suggested by the Pope and collected by successive pontiffs. From the law, the relationship is analyzed between justice and happiness, applied to the so-called “right to die with dignity”; and from the bioethics, reflections on procreation and happiness are raised based on the current debate on surrogacy.

Widespread irreproducibility of biomedical research has raised concerns. Journal editors and grant administrators are calling for greater safeguards. The causes go far beyond fraud, lack of transparency, and poor statistical analyses, as commonly thought. The root cause may stem from the same epistemic issues that confront medical reasoning, the necessary use of logical fallacies. However, the use of these fallacies increases the risk of uncertainty and subsequent irreproducibility. Furthermore, many procedures in data analysis actually result in an irretrievable loss of information by the Second Law of Thermodynamics as Applied to Information, thereby increasing the risk for irreproducibility. The second law holds that any irreversible process, such as operating only from the central tendency, as in the mean of a sample, results in a loss of information about the actual sample. The loss of that information makes the study less informative about the management of the individual patient.

Over the years, public policies aimed at Autism Spectrum Disorder (ASD) have evolved in Brazil. Despite this, we still face challenges, such as expanding access to specialized services and raising societal awareness of ASD. It is important that the diagnosis is made early by a multidisciplinary team, so that appropriate treatment can be started as early as possible. Treatment involves several interventions and should be personalized. In addition, it is essential that public policies ensure access to quality diagnosis and treatment for all. The purpose of this chapter is to analyze the Ministry of Health guidelines for the treatment of Autism Spectrum Disorder and to discuss possible long-term consequences. Challenges related to the diagnosis and treatment of autism in the context of the Unified Health System are also addressed. This is a narrative literature review, which aims to understand the development of Autism Spectrum Disorder (ASD), its Lines of Care and Public Policies in Brazil, through the analysis of the scientific production available in the databases Scientific Electronic Library Online (Scielo), National Library of Medicine (PubMed), books and other informative media. Autism Spectrum Disorder (ASD) in Brazil still faces challenges, such as a lack of trained professionals and unequal resources. To ensure adequate and quality care, it is necessary to invest in training and training of professionals, awareness of families and joint work between government, civil society and families, making it possible to build a more inclusive and welcoming society for people with ASD.

This chapter studies the arrival of the Human Rights Council. The idea of a Human Rights Council was raised in 1976, as the Great Enterprise entered a new phase. The documentation in 1976 on this issue is comprehensive, consisting of no less than five informative reports. In addition, the Commission on Human Rights had before it the analysis of the observations received from some Member States. They included an analysis of the deliberations at the Assembly that had taken place in November of 1975, which covered a range of topics, including ‘the possibility of transforming the Trusteeship Council into a Human Rights Council’. In 2005, the Secretary-General announced his plans to propose the establishment of a Human Rights Council to the Commission. A few months later, the World Summit decided on the establishment of a Human Rights Council. The Human Rights Council inaugurated its work with the adoption of two international human rights instruments, which had reached completion in the Commission on Human Rights: the International Convention for the Protection of All Persons from Enforced Disappearance and the United Nations Declaration on the Rights of Indigenous Peoples. It also extended the mandate of the Working Group formed under the Commission to elaborate an optional protocol to the International Covenant on Economic, Social and Cultural Rights and of the Commission’s Working Group on the Right to Development.

Advances in human enhancement technologies raise the prospect that people's identities may be altered so radically by enhancement that they will be essentially a different person after enhancement. To illustrate, some scholars of enhancement claim that individuals are unlikely to “survive” enhancement, in the sense that they continue to exist as one and the same person. Yet, others claim that enhancement is dehumanizing. Common to these claims is the assumption that enhancement affects a discontinuity between an individual's pre- and post-enhancement selves. Although extant analyses of the relationship between enhancement and identity have yielded many useful insights into the possible effects of human enhancement technologies on identity, progress in our understanding is marred by conceptual imprecision, the use of excessively thin conceptions of identity, and the conflation of distinct senses of identity. With respect to the latter, the conflation of numerical and narrative identity is particularly problematic. However, although these senses of identity are distinct, the fact that they are conflated is nevertheless informative about how people untutored in the metaphysics of identity—that is, the vast majority of people—reason about the effects of enhancement on identity. In this chapter, the authors draw on psychological research into self-continuity and dehumanization, respectively, to offer insights into why numerical and narrative identity are conflated, and they argue that future analyses of the relationship between enhancement and identity must be more deeply grounded in psychological and neuroscientific research than has been evidenced to date.

Abstract In the present chapter, we broaden our perspective m order to address the macro-political context of European police cooperation. Our aim is to examine the nature of the relationship between, on the one hand, new transnational and supranational initiatives in the police sector, and on the other, macro-political trends towards integration within the EU and the more general reconfiguration of international relations. The analysis of the relationship between political integration and law enforcement co-operation within the EU contributes to a wider theoretical debate. It raises the general question of the relationship between the forms of policing and the forms of political life. To what extent, and in what manner, are policing arrangements within any society informed by, and informative of the broader institutions, practices and ideas in terms of which that society constitutes itself as a political entity? When social scientists and social theorists conduct this inquiry, they usually do so in either historical or counter-factual terms. They may engage in retrospective analysis of the manner in which the unfolding forms of political life within different societies have become interwoven with the development of a policing function (Robinson and Skaglion 1987). Alternatively, they may proceed by means of hypothetical discussion, attempting to gain insight into the broader significance of policing institutions by asking what difference it would make to the wider polity if such institutions had not evolved in their present form (Bittner 1971; Cohen 1985; Klockars 1985). Both methods have their short comings.

Every day, we are confronted with alarming news of serious injuries and fatalities resulting from car accidents. In the past decade, these incidents have been on the rise, posing a significant concern for individuals and societies worldwide. The impact of these accidents is particularly devastating when innocent lives, including children, are affected by the long-lasting consequences. While driver behavior remains a major contributing factor to road accidents, there are also other indirect reasons such as infrastructure issues and weather conditions. Addressing this global problem is of utmost importance to safeguard lives and create a safer driving environment for everyone. Sunkpho and Wipulanusat (2020) utilized Business Intelligence (BI) methods, specifically data visualization and analytics, to analyze accident data and provincial data obtained from the Talend Data Integration tool, loaded into a MySQL database, and visualized using Tableau. Their aim was to provide insights into highway accidents and advise the Thai government on adopting this system for formulating strategy options and contingency plans to improve the accident situation. Nour et al. (2020) employ advanced data analytics methods, specifically predictive modeling techniques, to predict injury severity levels and evaluate their performance using publicly available road accident data from the UK Department of Transport spanning 2005 to 2019. Golhar and Kshirsagar M (2021) propose and implement various strategies using the Map-Reduce framework, combining video surveillance and big data analytics, to address the issues of increasing on-road traffic, road congestion, rule violations, and road accidents, aiming to improve road traffic management and make urban population life more comfortable. Yuksel and Atmaca S. (2021) use accelerometer and gyroscope sensor data and applied various machine learning algorithms, including C4.5 Decision Tree, Random Forest, Artificial Neural Network, Support-Vector Machine, K-Nearest Neighbor, Naive Bayes, and K-Star algorithms, to model and evaluate risky driving behaviors, ultimately developing a highly accurate and cost-effective system capable of recording and identifying risky driving behaviors, with potential applications in usage-based insurance policies to incentivize safe driving practices. Mesquitela et al. (2022) use a data fusion process, incorporating information from various sources such as road accidents, weather conditions, local authority reports, traffic, and fire brigade, to analyze and identify geo-referenced accident hotspots in urban areas using ArcGIS Pro and Kernel Density and Hot Spot Analysis tools, aiming to evaluate the factors influencing accident severity and provide knowledge for local municipalities to improve their infrastructure and quality of life, with the results validated by an expert committee, and the approach being applicable to other cities with similar data availability. Based on our Scopus search on "road accidents" and "analytics," no existing references were found directly aligned with our research idea. This highlights the originality of our paper, which aims to raise awareness about road accidents as a significant global issue and provide a comprehensive understanding of their key contributing factors through the analysis of road accident data from six representative countries across different continents including the UK, USA, Chile, Australia, Japan/UAE, and South Africa/Egypt. Our research sheds light on critical aspects of these incidents, explores trends, identifies influential factors, determines countries with low accident rates and casualties, and evaluates the potential impact of data analysis techniques on enhancing road safety. We will use datasets from the selected representative countries, focusing on road accidents that occurred between 2021 and 2022. By employing various analytical methods, we will explore the data from different angles, including descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, and cognitive analytics. Each method will contribute valuable insights to our analysis and understanding of the problem. We will employ Power BI for descriptive and diagnostic analytics, Python for predictive analytics using multilinear regression, Power BI for visualizing regression results, MaxDea Lite and Microsoft Excel for prescriptive analytics such as Data Envelopment Analysis (DEA) and Linear Programming, and also simulations to aid decision-making. Through our analysis, we will address key questions related to road accidents and their impact. For instance, we will determine whether the number of road accidents decreased or increased from 2021 to 2022 and identify the major contributing factors. Furthermore, we will assess the countries with the lowest accident rates and casualties based on ratios per million inhabitants for both years. By leveraging visualization techniques in Power BI, we will present the findings in an accessible and informative manner, enabling stakeholders to grasp the insights easily. The visualization and analysis will provide a deeper understanding of the trends, underlying factors, and the potential of data analysis techniques, such as DEA and Linear Programming, in addressing road safety. The importance of this research lies in its potential to generate significant impact. By shedding light on road accidents as a pressing global issue, the findings will raise awareness among individuals worldwide. Understanding the data from the six representative countries will enable comparisons, identification of best practices, and the formulation of informed strategies to reduce accidents and casualties. The results will benefit researchers, policymakers, and organizations involved in road safety initiatives. The insights gained will help shape evidence-based decisions, implement targeted interventions, and promote safer driving practices to prevent tragic outcomes caused by road accidents.

Aim/Purpose: This paper provides the results of the preliminary analysis of the findings of an ongoing study that seeks to examine the social media use, cultural and political awareness, civic engagement, issue prioritization, and social activism of Gen Z students enrolled at four different institutional types located in the Mid-Atlantic region of the United States. The aim of this study is to look at the group as a whole as well as compare findings across populations. The institutional types under consideration include a mid-sized majority serving or otherwise referred to as a traditionally white institution (TWI) located in a small coastal city on the Atlantic Ocean, a small Historically Black University (HBCU) located in a rural area, a large community college located in a county that is a mixture of rural and suburban and which sits on the border of Maryland and Pennsylvania, and graduating high school students enrolled in career and technical education (CTE) programs in a large urban area. This exploration is purposed to examine the behaviors and expectations of Gen Z students within a representative American region during a time of tremendous turmoil and civil unrest in the United States. Background: Over 74 million strong, Gen Z makes up almost one-quarter of the U.S. population. They already outnumber any current living generation and are the first true digital natives. Born after 1996 and through 2012, they are known for their short attention spans and heightened ability to multi-task. Raised in the age of the smart phone, they have been tethered to digital devices from a young age with most having the preponderance of their childhood milestones commemorated online. Often called Zoomers, they are more racially and ethnically diverse than any previous generation and are on track to be the most well-educated generation in history. Gen Zers in the United States have been found in the research to be progressive and pro-government and viewing increasing racial and ethnic diversity as positive change. Finally, they are less likely to hold xenophobic beliefs such as the notion of American exceptionalism and superiority that have been popular with by prior generations. The United States has been in a period of social and civil unrest in recent years with concerns over systematic racism, rampant inequalities, political polarization, xenophobia, police violence, sexual assault and harassment, and the growing epidemic of gun violence. Anxieties stirred by the COVID-19 pandemic further compounded these issues resulting in a powder keg explosion occurring throughout the summer of 2020 and leading well into 2021. As a result, the United States has deteriorated significantly in the Civil Unrest Index falling from 91st to 34th. The vitriol, polarization, protests, murders, and shootings have all occurred during Gen Z’s formative years, and the limited research available indicates that it has shaped their values and political views. Methodology: The Mid-Atlantic region is a portion of the United States that exists as the overlap between the northeastern and southeastern portions of the country. It includes the nation’s capital, as well as large urban centers, small cities, suburbs, and rural enclaves. It is one of the most socially, economically, racially, and culturally diverse parts of the United States and is often referred to as the “typically American region.” An electronic survey was administered to students from 2019 through 2021 attending a high school dual enrollment program, a minority serving institution, a majority serving institution, and a community college all located within the larger mid-Atlantic region. The survey included a combination of multiple response, Likert scaled, dichotomous, open ended, and ordinal questions. It was developed in the Survey Monkey system and reviewed by several content and methodological experts in order to examine bias, vagueness, or potential semantic problems. Finally, the survey was pilot tested prior to implementation in order to explore the efficacy of the research methodology. It was then modified accordingly prior to widespread distribution to potential participants. The surveys were administered to students enrolled in classes taught by the authors all of whom are educators. Participation was voluntary, optional, and anonymous. Over 800 individuals completed the survey with just over 700 usable results, after partial completes and the responses of individuals outside of the 18-24 age range were removed. Findings: Participants in this study overwhelmingly were users of social media. In descending order, YouTube, Instagram, Snapchat, Twitter, Facebook, Pinterest, WhatsApp, LinkedIn and Tik Tok were the most popular social media services reported as being used. When volume of use was considered, Instagram, Snapchat, YouTube and Twitter were the most cited with most participants reporting using Instagram and Snapchat multiple times a day. When asked to select which social media service they would use if forced to choose just one, the number one choice was YouTube followed by Instagram and Snapchat. Additionally, more than half of participants responded that they have uploaded a video to a video sharing site such as YouTube or Tik Tok. When asked about their familiarity with different technologies, participants overwhelmingly responded that they are “very familiar” with smart phones, searching the Web, social media, and email. About half the respondents said that they were “very familiar” with common computer applications such as the Microsoft Office Suite or Google Suite with another third saying that they were “somewhat familiar.” When asked about Learning Management Systems (LMS) like Blackboard, Course Compass, Canvas, Edmodo, Moodle, Course Sites, Google Classroom, Mindtap, Schoology, Absorb, D2L, itslearning, Otus, PowerSchool, or WizIQ, only 43% said they were “very familiar” with 31% responding that they were “somewhat familiar.” Finally, about half the students were either “very” or “somewhat” familiar with operating systems such as Windows. A few preferences with respect to technology in the teaching and learning process were explored in the survey. Most students (85%) responded that they want course announcements and reminders sent to their phones, 76% expect their courses to incorporate the use of technology, 71% want their courses to have course websites, and 71% said that they would rather watch a video than read a book chapter. When asked to consider the future, over 81% or respondents reported that technology will play a major role in their future career. Most participants considered themselves “informed” or “well informed” about current events although few considered themselves “very informed” or “well informed” about politics. When asked how they get their news, the most common forum reported for getting news and information about current events and politics was social media with 81% of respondents reporting. Gen Z is known to be an engaged generation and the participants in this study were not an exception. As such, it came as no surprise to discover that, in the past year more than 78% of respondents had educated friends or family about an important social or political issue, about half (48%) had donated to a cause of importance to them, more than a quarter (26%) had participated in a march or rally, and a quarter (26%) had actively boycotted a product or company. Further, about 37% consider themselves to be a social activist with another 41% responding that aren’t sure if they would consider themselves an activist and only 22% saying that they would not consider themselves an activist. When asked what issues were important to them, the most frequently cited were Black Lives Matter (75%), human trafficking (68%), sexual assault/harassment/Me Too (66.49%), gun violence (65.82%), women’s rights (65.15%), climate change (55.4%), immigration reform/deferred action for childhood arrivals (DACA) (48.8%), and LGBTQ+ rights (47.39%). When the schools were compared, there were only minor differences in social media use with the high school students indicating slightly more use of Tik Tok than the other participants. All groups were virtually equal when it came to how informed they perceived themselves about current events and politics. Consensus among groups existed with respect to how they get their news, and the community college and high school students were slightly more likely to have participated in a march, protest, or rally in the last 12 months than the university students. The community college and high school students were also slightly more likely to consider themselves social activists than the participants from either of the universities. When the importance of the issues was considered, significant differences based on institutional type were noted. Black Lives Matter (BLM) was identified as important by the largest portion of students attending the HBCU followed by the community college students and high school students. Less than half of the students attending the TWI considered BLM an important issue. Human trafficking was cited as important by a higher percentage of students attending the HBCU and urban high school than at the suburban and rural community college or the TWI. Sexual assault was considered important by the majority of students at all the schools with the percentage a bit smaller from the majority serving institution. About two thirds of the students at the high school, community college, and HBCU considered gun violence important versus about half the students at the majority serving institution. Women’s rights were reported as being important by more of the high school and HBCU participants than the community college or TWI. Climate change was considered important by about half the students at all schools with a slightly smaller portion reporting out the HBCU. Immigration reform/DACA was reported as important by half the high school, community college, and HBCU participants with only a third of the students from the majority serving institution citing it as an important issue. With respect to LGBTQ rights approximately half of the high school and community college participants cited it as important, 44.53% of the HBCU students, and only about a quarter of the students attending the majority serving institution. Contribution and Conclusion: This paper provides a timely investigation into the mindset of generation Z students living in the United States during a period of heightened civic unrest. This insight is useful to educators who should be informed about the generation of students that is currently populating higher education. The findings of this study are consistent with public opinion polls by Pew Research Center. According to the findings, the Gen Z students participating in this study are heavy users of multiple social media, expect technology to be integrated into teaching and learning, anticipate a future career where technology will play an important role, informed about current and political events, use social media as their main source for getting news and information, and fairly engaged in social activism. When institutional type was compared the students from the university with the more affluent and less diverse population were less likely to find social justice issues important than the other groups. Recommendations for Practitioners: During disruptive and contentious times, it is negligent to think that the abounding issues plaguing society are not important to our students. Gauging the issues of importance and levels of civic engagement provides us crucial information towards understanding the attitudes of students. Further, knowing how our students gain information, their social media usage, as well as how informed they are about current events and political issues can be used to more effectively communicate and educate. Recommendations for Researchers: As social media continues to proliferate daily life and become a vital means of news and information gathering, additional studies such as the one presented here are needed. Additionally, in other countries facing similarly turbulent times, measuring student interest, awareness, and engagement is highly informative. Impact on Society: During a highly contentious period replete with a large volume of civil unrest and compounded by a global pandemic, understanding the behaviors and attitudes of students can help us as higher education faculty be more attuned when it comes to the design and delivery of curriculum. Future Research This presentation presents preliminary findings. Data is still being collected and much more extensive statistical analyses will be performed.

Inflation has decreased since April, and it is projected to continue to reduce significantly throughout 2024 as it converges toward 3%. In September 2023, the headline annual inflation rate was 10.99% and completed six consecutive months of declines. Core inflation, excluding food and regulated items, has experienced three consecutive months of reductions and currently stands at 9.5%. The reduction in inflation has been slower than the projected by the Central Bank and market analysts, primarily due to: More persistent price increases in services and regulated baskets, which are affected by indexation mechanisms of past inflation and minimum wage. Increases in some prices of perishable food items. Going forward, monetary policy actions will continue contributing to inflation reduction in 2024 and its convergence toward the 3% target during 2025. Projections for 2024 consider the impact of the El Niño with moderate effects on food and energy prices, the implementation of healthy taxes, and necessary adjustments in fuel prices. Economic activity and employment continue to grow, with a projected GDP growth of 1.2% for 2023. The economic slowdown this year allows economic activity and consumption and investment expenditures to align with the long-term productive capacity of the economy, contributing to inflation reduction. For the third quarter, available economic indicators suggest an annual GDP growth of 0.4%. Despite the low growth rate, economic activity would maintain the high levels achieved in the first half of the year. Employment continues to grow in most economic sectors, and the unemployment rate remains historically low. The economic slowdown has been milder than the projected by the Central Bank, resulting in an upward revision of the 2023 growth rate from 0.9% to 1.2%. For 2024, the economy is expected to maintain a slow growth pace (0.8%), contributing to the inflation convergence to the target. Private consumption will adjust, while investment levels will remain lower than before the pandemic. In 2025, the economy is expected to return to growth rates close to those sustainable in the long-term. These adjustments in the economy are reflected in a reduction of the current account deficit and less vulnerability to external conditions changes. The policy interest rate remains at 13.25%, currently appropriate level to consolidate inflation reduction toward the 3% target and to foster sustainable economic growth. In the September and October meetings of 2023, the Board of Directors, by majority, decided to keep the interest rate unchanged at 13.25%. The current monetary policy stance is driven by persistent high inflation, forecasts and expectations of inflation exceeding the 3% target, and with levels of economic activity close to its productive capacity. The Bank will continue to monitor the economy and its key risks to make decisions that are in the best interest of the country. Some important risk factors to watch in the coming months include: El Niño phenomenon evolution, which may result in additional impacts on inflation. Wage adjustments that will be determined in the coming months. The persistence of higher price increases, particularly, in the services sub-basket. The behavior of global short and long-term interest rates that may affect the exchange rate. The economic slowdown. Reducing inflation brings multiple benefits to the economy: Reducing inflation toward the target supports the preservation of wage purchasing power. Low and stable inflation prevents regressive income and wealth redistributions. In particular, low-income individuals and the unemployed have fewer mechanisms to shield themselves from the eroding impact of inflation on their income and savings. When inflation is low, it becomes more predictable and facilitates the development and continuity of long-term financing markets (such as TES and mortgages), enabling the financing of government, corporate, and household investment projects. Additionally, when inflation is low, real interest rates are lower, making it more affordable to finance these projects. When inflation is low and stable, price movements of goods and services are more informative about the sectors in which it is most valuable to increase production. This leads to a better sectoral allocation of capital and labor and, therefore, to raising the total productivity of the economy.