Previously Incacerated Women\u27s Emotional Experince of Giving Birth in a U.S. Prison

Previously Incarcerated Women’s Emotional Experience of Giving Birth in a U.S. Prison by Brigit Ichard-Henderson MA, Walden University, 2018 MA, Texas A&M University-Central Texas, 2014 BS, Excelsior University, 2009 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Human Services Walden University May 2024   Women have been giving birth while incarcerated since the advent of confinement as a punishment for crime. There is a plethora of information on incarceration rates, pathways to incarceration, access to health care and education while incarcerated, and reasons for recidivism among women. However, little is known about women’s experiences of giving birth while incarcerated. This study aimed to explore female inmates’ experiences of the emotions they felt and recalled at the time of arrest and their interactions with other inmates, health care providers, correctional officers, and their outside support group. Qualitative narrative analysis was used to interpret the data from 15 participants who were previously incarcerated women, 18 years of age and older, who had given birth in US prisons. In semistructured interviews conducted via videoconferencing, participants were asked to recall the emotions they felt during their pregnancy, labor, and delivery. Feminist theory and feminist criminology served as the theoretical frameworks for the study. The eight themes and ten subthemes that emerged showcased participants’ memories of felt emotions such as depression and anxiety. Recommendations include further research on the study topic and related topics such as prenatal health care, nutrition, and education for pregnant incarcerated women in the United States. The study’s findings could promote positive social change by informing human services professionals of the need to create a positive, humane, and dignified birth experience for pregnant incarcerated women in the United States

Random media and processes estimation using non-linear filtering techniques: application to ensemble weather forecast and aircraft trajectories

L'erreur de prédiction d'une trajectoire avion peut être expliquée par différents facteurs. Les incertitudes associées à la prévision météorologique sont l'un d'entre-eux. Qui plus est, l'erreur de prévision de vent a un effet non négligeable sur l'erreur de prédiction de la position d'un avion. En regardant le problème sous un autre angle, il s'avère que les avions peuvent être utilisés comme des capteurs locaux pour estimer l'erreur de prévision de vent. Dans ce travail nous décrivons ce problème d'estimation à l'aide de plusieurs processus d'acquisition d'un même champ aléatoire. Quand ce champ est homogène, nous montrons que le problème est équivalent à plusieurs processus aléatoires évoluant dans un même environnement aléatoire pour lequel nous donnons un modèle de Feynman-Kac. Nous en dérivons une approximation particulaire et fournissons pour les estimateurs obtenus des résultats de convergence. Quand le champ n'est pas homogène mais qu'une décomposition en sous-domaine homogène est possible, nous proposons un modèle différent basé sur le couplage de plusieurs processus d'acquisition. Nous en déduisons un modèle de Feynman-Kac et suggérons une approximation particulaire du flot de mesure. Par ailleurs, pour pouvoir traiter un trafic aérien, nous développons un modèle de prédiction de trajectoire avion. Finalement nous démontrons dans le cadre de simulations que nos algorithmes peuvent estimer les erreurs de prévisions de vent en utilisant les observations délivrées par les avions le long de leur trajectoire.Aircraft trajectory prediction error can be explained by different factors. One of them is the weather forecast uncertainties. For example, the wind forecast error has a non negligible impact on the along track accuracy for the predicted aircraft position. From a different perspective, that means that aircrafts can be used as local sensors to estimate the weather forecast error. In this work we describe the estimation problem as several acquisition processes of a same random field. When the field is homogeneous, we prove that they are equivalent to random processes evolving in a random media for which a Feynman-Kac formulation is done. Then we give a particle-based approximation and provide convergence results of the ensuing estimators. When the random field is not homogeneous but can be decomposed in homogeneous sub-domains, a different model is proposed based on the coupling of different acquisition processes. From there, a Feynman-Kac formulation is derived and its particle-based approximation is suggested. Furthermore, we develop an aircraft trajectory prediction model. Finally we demonstrate on a simulation set-up that our algorithms can estimate the wind forecast errors using the aircraft observations delivered along their trajectory

Genetic diversity of the type III effector RipAX2 in the Ralstonia solanacearum species complex and its impact on the deployment of eggplants carrying the EBWR9 resistance locus in the South-West Indian Ocean

The Ralstonia solanacearum species complex is responsible for the bacterial wilt disease on many food crops with high economic and food potential. This disease represents one of the major constraints to the sustainable production of Solanaceae crops, with heavy socio-economic consequences for small farmers in the South-West Indian Ocean islands (Comoros, Madagascar, Mauritius, Mayotte, Reunion, Rodrigues and Seychelles). The measures commonly used to limit losses are the implementation of regulations on the circulation of plant material, crop rotation and use of healthy seeds. These prophylactic methods are not totally effective and the use of resistant varieties remains the most promising strategies to control this disease. We evaluated the effectiveness of bacterial wilt resistance of the eggplant AG91-25 carrying the EBWR9 locus (Salgon et al., 2017). This resistance is conferred by the recognition of the type III effector RipAX2 (Morel et al., 2018). A study of RipAX2 diversity was performed by in silico analysis based on 550 genomes assemblies from public databases and by targeted gene sequencing of a collection of 807 global strains. We identified different alleles of RipAX2 and selected a subset of strains representative of this diversity that were inoculated on AG91-25 and MM738 used as a susceptible control. Strains displaying minor polymorphisms of RipAX2 (e.g. amino acid substitutions) were controlled by AG91-25 while those with major variations (e.g. insertion sequence event, frameshift, premature stop codon) were virulent and triggered bacterial wilt symptoms. The phenotyping of these strains complemented with the reference sequence of RipAX2 confirmed the involvement of this effector in the interaction with AG91-25. Finally, we performed a geographical mapping of the virulence profiles of all the strains analyzed in this study, to define a rational deployment plan of the EBWR9 resistance limiting the risks of resistance breakdown in the agroecosystems of the different South-West Indian Ocean islands

Reliability of single-lead electrocardiogram interpretation to detect atrial fibrillation: insights from the SAFER feasibility study

Aims: Single-lead electrocardiograms (ECGs) can be recorded using widely available devices such as smartwatches and handheld ECG recorders. Such devices have been approved for atrial fibrillation (AF) detection. However, little evidence exists on the reliability of single-lead ECG interpretation. We aimed to assess the level of agreement on detection of AF by independent cardiologists interpreting single-lead ECGs and to identify factors influencing agreement. Methods and results: In a population-based AF screening study, adults aged ≥65 years old recorded four single-lead ECGs per day for 1–4 weeks using a handheld ECG recorder. Electrocardiograms showing signs of possible AF were identified by a nurse, aided by an automated algorithm. These were reviewed by two independent cardiologists who assigned participant- and ECG-level diagnoses. Inter-rater reliability of AF diagnosis was calculated using linear weighted Cohen’s kappa (κw). Out of 2141 participants and 162 515 ECGs, only 1843 ECGs from 185 participants were reviewed by both cardiologists. Agreement was moderate: κw = 0.48 (95% confidence interval, 0.37–0.58) at participant level and κw = 0.58 (0.53–0.62) at ECG level. At participant level, agreement was associated with the number of adequate-quality ECGs recorded, with higher agreement in participants who recorded at least 67 adequate-quality ECGs. At ECG level, agreement was associated with ECG quality and whether ECGs exhibited algorithm-identified possible AF. Conclusion: Inter-rater reliability of AF diagnosis from single-lead ECGs was found to be moderate in older adults. Strategies to improve reliability might include participant and cardiologist training and designing AF detection programmes to obtain sufficient ECGs for reliable diagnoses

Prévalence contrastée des souches de l'agent causal du flétrissement bactérien (le complexe d'espèces Ralstonia solanacearum) dans les îles du sud-ouest de l'océan Indien

Le complexe d'espèces Ralstonia solanacearum est l'agent responsable du flétrissement bactérien chez les plantes. Il peut être classifié en trois espèces, quatre phylotypes et une soixante-dizaine de variants phylogénétiques nommés sequevars. Dans le sud-ouest de l'océan Indien, il présente une répartition hétérogène. Le sequevar 31 prédomine partout sauf à Madagascar, à Maurice et à Rodrigues. Les tests de mise en compétition in vitro de ce sequevar prédominant avec le sequevar 18 prédominant à Madagascar montre qu'il est plus compétitif. Dans l'objectif de comprendre pourquoi le sequevar 31 n'arrive pas à prédominer à Madagascar, des analyses de génomiques comparatives ont été réalisées. Un effecteur bactérien, différenciant ces deux sequevars, a été mis en évidence. Des études démontrant l'avirulence de cet effecteur face à un gène de résistance présent chez une accession d'aubergine nous a permis d'établir une carte de prédiction, montrant de nouveau la présence de ce contraste entre Madagascar et les autres îles du sud-ouest de l'océan Indien

HAEMATOLOGICAL PARAMETERS IN H UMAN I MMUNODEFICIENCY V IRUS POSITIVE INDIVIDUALS ON DIFFERENT HAART REGIMEN .

Highly active antiretroviral viral therapy (HAART), a combination of three antiretrovirals from at least two drug classes for optimization of hindrance to HIV replication has g reatly increased life expectance. There however, exist numerous of these combinations and thus the questions of which is the best HAART combination with respect to the individual’s haematological status. To investigate this, blood samples were collected fr om 231 retropositive subjects on six different HAART combinations at least six months after HAART commencement, assayed for CD4 and some haematological parameters using cyflow and sysmex(KX - 21) autoanalysier. Baseline data was accessed from the LAMIS data base. The difference between baseline and values after HAART was taken and statistically compared. HAART evaluated includes, Combivir(NVP), Combivir(EFV), Truvada(NVP), Truvada(EFV), Lanten(NVP) and Lanten(EFV). The difference in the parameters assayed a re: CD4(cellmm - 3 ): 154, 205, 172, 206, 262, and 230(P=0.478). Haemoglobin(gdl - 1): - 0.78, - 0.73, 2.35, 1.48, 1.11 and 1.27(P=0.010). PCV(%): - 2.34, - 2.19, 7.65, 7.02, 3.36 and 3.12(P=0.0001). WBC(10 3 μl - 1 ): - 1.19, - 1.02, - 0.37, 0.06, 1.14 and - 0.63(P=0.001) . Neutrophil(%): - 1.51, - 1.83, 3.87, 2.07, 2.71, 2.71 and 1.97(P=0.868). Lymphocyte(%): - 4.26, - 2.87, - 1.45, - 0.19, 2.36 and 3.40(P=0.790). Eosinophil(%): - 0.41, 0.14, - 2.65, 0.14, - 0.46 and 0.12(P=0.094). Platelet(10 3 μl - 1 ): - 49, - 39, - 53, - 53, - 47 and - 35 (P=0.931). The Zidovudine based combinations showed anaemic tendencies; Nevirapen based combinations showed Eosinopenic tendencies. All HAART used induced good immunologic responses along with thrombocytopenic tendencies. The data generated was however ins ufficient to discriminate one combination as being better than the other, rather it was observed that the haematological profile of clients must be well considered when selecting HAAR

Estimation jointe de milieu et processus aléatoire par des techniques de filtrage non-linéaire : application aux prévisons météorologiques d'ensemble et trajectoires avions

L'erreur de prédiction d'une trajectoire avion peut être expliquée par différents facteurs. Les incertitudes associées à la prévision météorologique sont l'un d'entre-eux. Qui plus est, l'erreur de prévision de vent a un effet non négligeable sur l'erreur de prédiction de la position d'un avion. En regardant le problème sous un autre angle, il s'avère que les avions peuvent être utilisés comme des capteurs locaux pour estimer l'erreur de prévision de vent. Dans ce travail nous décrivons ce problème d'estimation à l'aide de plusieurs processus d'acquisition d'un même champ aléatoire. Quand ce champ est homogène, nous montrons que le problème est équivalent à plusieurs processus aléatoires évoluant dans un même environnement aléatoire pour lequel nous donnons un modèle de Feynman-Kac. Nous en dérivons une approximation particulaire et fournissons pour les estimateurs obtenus des résultats de convergence. Quand le champ n'est pas homogène mais qu'une décomposition en sous-domaine homogène est possible, nous proposons un modèle différent basé sur le couplage de plusieurs processus d'acquisition. Nous en déduisons un modèle de Feynman-Kac et suggérons une approximation particulaire du flot de mesure. Par ailleurs, pour pouvoir traiter un trafic aérien, nous développons un modèle de prédiction de trajectoire avion. Finalement nous démontrons dans le cadre de simulations que nos algorithmes peuvent estimer les erreurs de prévisions de vent en utilisant les observations délivrées par les avions le long de leur trajectoire.Aircraft trajectory prediction error can be explained by different factors. One of them is the weather forecast uncertainties. For example, the wind forecast error has a non negligible impact on the along track accuracy for the predicted aircraft position. From a different perspective, that means that aircrafts can be used as local sensors to estimate the weather forecast error. In this work we describe the estimation problem as several acquisition processes of a same random field. When the field is homogeneous, we prove that they are equivalent to random processes evolving in a random media for which a Feynman-Kac formulation is done. Then we give a particle-based approximation and provide convergence results of the ensuing estimators. When the random field is not homogeneous but can be decomposed in homogeneous sub-domains, a different model is proposed based on the coupling of different acquisition processes. From there, a Feynman-Kac formulation is derived and its particle-based approximation is suggested. Furthermore, we develop an aircraft trajectory prediction model. Finally we demonstrate on a simulation set-up that our algorithms can estimate the wind forecast errors using the aircraft observations delivered along their trajectory