49 research outputs found
Pretrial Detention in Maryland
In September of 2013, the Maryland courts upheld DeWolfe v. Richmond. This ruling warrants impoverished defendants to have state-appointed counsel present at their initial appearance before a District Court commissioner. Since its implementation, funding required to meet the rulingâs stipulations has added to the already high costs of the judicial process.
This paper reviews the history and current state of pretrial release both nationally and locally in Maryland. In addition, it investigates the issues related to pretrial detention and recommends a policy solution to Governor Hogan along with an analysis of the proposal.
Reviews of case studies and data found that Marylandâs current pretrial laws have detrimental financial and social impacts. Many of the issues are related to the stateâs use of money bonds as a condition of pretrial release.
It is recommended Governor Hogan adopt a policy that limits the use of money bonds, repurposes District Court commissioners to conduct data-driven risk assessments to determine defendantsâ release, and establishes a statewide pretrial supervision agency to ensure the publicsâ safety and defendantsâ appearance in court
Rapid diagnostic susceptibility testing of bacteria and fungi from clinical samples using silicon gratings
Bacterial and fungal infections persistently plague society and have amounted to one of the most prevalent issues in healthcare today. Thus, significant research effort is directed towards developing rapid diagnostic techniques for determination of the correct antibiotic (or antifungal) for a patient-tailored therapy. We have developed a rapid phenotypic antimicrobial susceptibility testing (AST) in which photonic 2D silicon microarrays are employed as both the optical transducer element and as a preferable solid-liquid interface for bacterial/fungal colonization. We harness the intrinsic ability of the micro-architectures to relay optical phase-shift reflectometric interference spectroscopic measurements (termed PRISM) and incorporate it into a platform for culture-free, label-free tracking of bacterial/fungal colonization, proliferation, and death. For example, bacteria proliferation within the microtopologies results in an increase in refractive index of the medium, yielding an increase in optical path difference, while cell death or bacteriostatic activity results in decreasing or unchanged values. The optical responses of bacteria, including clinical isolates and samples derived from patients at neighboring hospitals, to various concentrations of relevant antibiotics are tracked in real time, allowing for accurate determination of the minimum inhibitory concentration (MIC) values within 2-3 hours in comparison to assay times of <8 hours (using standard broth microdilution techniques or state-of-the-art clinical automated systems. This has opened the door to the observation of unique bacterial behaviors, as we can evaluate bacterial adhesion, growth, and antibiotic resistance on different micro-architectures, different surface chemistries, and even different strains. Motility, charge, and biofilm abilities have been explored for their effect of bacterial adhesion to the microstructures as we further develop our method of rapid, label-free AST for full clinical application. © 2019 SPIE
Family planning among people living with HIV in post-conflict Northern Uganda: A mixed methods study
<p>Abstract</p> <p>Background</p> <p>Northern Uganda experienced severe civil conflict for over 20 years and is also a region of high HIV prevalence. This study examined knowledge of, access to, and factors associated with use of family planning services among people living with HIV (PLHIV) in this region.</p> <p>Methods</p> <p>Between February and May 2009, a total of 476 HIV clinic attendees from three health facilities in Gulu, Northern Uganda, were interviewed using a structured questionnaire. Semi-structured interviews were conducted with another 26 participants. Factors associated with use of family planning methods were examined using logistic regression methods, while qualitative data was analyzed within a social-ecological framework using thematic analysis.</p> <p>Results</p> <p>There was a high level of knowledge about family planning methods among the PLHIV surveyed (96%). However, there were a significantly higher proportion of males (52%) than females (25%) who reported using contraception. Factors significantly associated with the use of contraception were having ever gone to school [adjusted odds ratio (AOR) = 4.32, 95% confidence interval (CI): 1.33-14.07; p = .015], discussion of family planning with a health worker (AOR = 2.08, 95% CI: 1.01-4.27; p = .046), or with one's spouse (AOR = 5.13, 95% CI: 2.35-11.16; p = .000), not attending the Catholic-run clinic (AOR = 3.67, 95% CI: 1.79-7.54; p = .000), and spouses' non-desire for children (AOR = 2.19, 95% CI: 1.10-4.36; p = .025). Qualitative data revealed six major factors influencing contraception use among PLHIV in Gulu including personal and structural barriers to contraceptive use, perceptions of family planning, decision making, covert use of family planning methods and targeting of women for family planning services.</p> <p>Conclusions</p> <p>Multilevel, context-specific health interventions including an integration of family planning services into HIV clinics could help overcome some of the individual and structural barriers to accessing family planning services among PLHIV in Gulu. The integration also has the potential to reduce HIV incidence in this post-conflict region.</p
TRY plant trait database â enhanced coverage and open access
Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of traitâbased plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
The Future of Cyber Enabled Financial Crime: New Crimes, New Criminals, and Economic Warfare
What will the future of cyber-enabled financial crime, perpetrated by either criminals or nation states, look like 10 years from now? In the coming decade, those who engage in cyber-enabled financial crimes (CEFC) will take advantage of a collection of technologies and adjacent practices -- creating new classes of crimes, conditions, and adversary vectors. There are numerous technologies at the forefront of societal evolution, including cryptocurrency, artificial intelligence, 5G, physical and digital autonomous systems, the Internet of Things (IoT), Smart Cities, biometric identity, space-based systems, and quantum computing. The combination of changes in these technologies and in society are likely to also include an over-reliance on digital devices, digital payments, monopolized smart systems, and broader technology dependencies. In addition, the nature of financial crimes is expected to change in that they will initially target vulnerable communities, consumers, companies, and cyber computer systems. Furthermore, financial crimes will increasingly be used to enable more advanced and egregious economic warfare opportunities for adversarial nations and nation-state proxies
Long-term cumulative incidence of cervical intraepithelial neoplasia grade 3 or worse after abnormal cytology: impact of HIV infection.
To estimate the long term cumulative risk for cervical intraepithelial neoplasia grade 3 or worse after an abnormal cervical Pap test and to assess the effect of HIV infection on that risk. Participants in the Women's Interagency HIV Study were followed semiannually for up to 10 years. Pap tests were categorized according to the 1991 Bethesda system. Colposcopy was prescribed within 6 months of any abnormality. Risk for biopsy-confirmed CIN3 or worse after abnormal cytology and at least 12 months follow-up was assessed using Kaplan-Meier curves and compared using log-rank tests. Risk for CIN2 or worse was also assessed, since CIN2 is the threshold for treatment. After a median of 3 years of observation, 1,947 (85%) women subsequently presented for colposcopy (1,571 [81%] HIV seropositive, 376 [19%] seronegative). CIN2 or worse was found in 329 (21%) of HIV seropositive and 42 (11%) seronegative women. CIN3 or worse was found in 141 (9%) of seropositive and 22 (6%) seronegative women. In multivariable analysis, after controlling for cytology grade HIV seropositive women had an increased risk for CIN2 or worse (H.R. 1.66, 95% C.I 1.15, 2.45) but higher risk for CIN3 or worse did not reach significance (H.R. 1.33, 95% C.I. 0.79, 2.34). HIV seropositive women with abnormal Paps face a marginally increased and long-term risk for cervical disease compared to HIV seronegative women, but most women with ASCUS and LSIL Pap results do not develop CIN2 or worse despite years of observation
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Long-term cumulative incidence of cervical intraepithelial neoplasia grade 3 or worse after abnormal cytology: impact of HIV infection.
To estimate the long term cumulative risk for cervical intraepithelial neoplasia grade 3 or worse after an abnormal cervical Pap test and to assess the effect of HIV infection on that risk. Participants in the Women's Interagency HIV Study were followed semiannually for up to 10 years. Pap tests were categorized according to the 1991 Bethesda system. Colposcopy was prescribed within 6 months of any abnormality. Risk for biopsy-confirmed CIN3 or worse after abnormal cytology and at least 12 months follow-up was assessed using Kaplan-Meier curves and compared using log-rank tests. Risk for CIN2 or worse was also assessed, since CIN2 is the threshold for treatment. After a median of 3 years of observation, 1,947 (85%) women subsequently presented for colposcopy (1,571 [81%] HIV seropositive, 376 [19%] seronegative). CIN2 or worse was found in 329 (21%) of HIV seropositive and 42 (11%) seronegative women. CIN3 or worse was found in 141 (9%) of seropositive and 22 (6%) seronegative women. In multivariable analysis, after controlling for cytology grade HIV seropositive women had an increased risk for CIN2 or worse (H.R. 1.66, 95% C.I 1.15, 2.45) but higher risk for CIN3 or worse did not reach significance (H.R. 1.33, 95% C.I. 0.79, 2.34). HIV seropositive women with abnormal Paps face a marginally increased and long-term risk for cervical disease compared to HIV seronegative women, but most women with ASCUS and LSIL Pap results do not develop CIN2 or worse despite years of observation
Modelling the transmission of healthcare associated infections: a systematic review.
BACKGROUND: Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. METHODS: MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. RESULTS: In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. CONCLUSIONS: Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models