Robert Wood Johnson v. Secretary HHS

United States District Court for the District of New Jerse

Reproduction and Gender Self-Determination: Fertile Grounds for Trans Legal Advocacy

Current medical constructions of trans identities reflect heterosexist understandings of gender expression—understandings that deny access to gender-affirming healthcare to those who fail to perform normative binary genders. As medical providers establish norms for how to “properly” be trans, the state codifies these norms, basing trans existence on rigidly defined and harshly enforced understandings of binary gender. When this construction of transness is codified on an institutional level, such as with gender reclassification rules for government identification, it forces trans people to conform their bodies to cisgender norms, and dangerously disrupts trans people’s bodily autonomy and diminishes their control over their reproductive choices. This Article contends that the gender conformity that the state requires of trans people parallels the violence that the state has inflicted on low-income non-trans women of color. As welfare policies have sought to constrain indigent Black women’s reproductive and sexual autonomy, courts use legal gender determination to force trans people to conform to heterosexist sexual and family structures—a project that works to constrain their reproductive freedoms. This Article connects the decades-long struggle of non-trans women of color for reproductive justice with that of trans people’s right to self-identify without medical intervention. In doing so, this Article calls for legal trans advocates to coalition build with existing reproductive justice movements to nurture a trans jurisprudence that rejects heterosexist notions of trans identity and instead embraces the multiplicity of trans embodiment and queer family structures that we, as trans people, can create

Map of Land Cover Agreement: Ensambling Existing Datasets for Large-Scale Training Data Provision

Land cover information plays a critical role in supporting sustainable development and informed decision-making. Recent advancements in satellite data accessibility, computing power, and satellite technologies have boosted large-extent high-resolution land cover mapping. However, retrieving a sufficient amount of reliable training data for the production of such land cover maps is typically a demanding task, especially using modern deep learning classification techniques that require larger training sample sizes compared to traditional machine learning methods. In view of the above, this study developed a new benchmark dataset called the Map of Land Cover Agreement (MOLCA). MOLCA was created by integrating multiple existing high-resolution land cover datasets through a consensus-based approach. Covering Sub-Saharan Africa, the Amazon, and Siberia, this dataset encompasses approximately 117 billion 10m pixels across three macro-regions. The MOLCA legend aligns with most of the global high-resolution datasets and consists of nine distinct land cover classes. Noteworthy advantages of MOLCA include a higher number of pixels as well as coverage for typically underrepresented regions in terms of training data availability. With an estimated overall accuracy of 96%, MOLCA holds great potential as a valuable resource for the production of future high-resolution land cover maps

Large carnivore expansion in Europe is associated with human population density and land cover changes

Aim: The recent recovery of large carnivores in Europe has been explained as resulting from a decrease in human persecution driven by widespread rural land abandonment, paralleled by forest cover increase and the consequent increase in availability of shelter and prey. We investigated whether land cover and human population density changes are related to the relative probability of occurrence of three European large carnivores: the grey wolf (Canis lupus), the Eurasian lynx (Lynx lynx) and the brown bear (Ursus arctos). Location: Europe, west of 64° longitude. Methods: We fitted multi-temporal species distribution models using >50,000 occurrence points with time series of land cover, landscape configuration, protected areas, hunting regulations and human population density covering a 24-year period (1992–2015). Within the temporal window considered, we then predicted changes in habitat suitability for large carnivores throughout Europe. Results: Between 1992 and 2015, the habitat suitability for the three species increased in Eastern Europe, the Balkans, North-West Iberian Peninsula and Northern Scandinavia, but showed mixed trends in Western and Southern Europe. These trends were primarily associated with increases in forest cover and decreases in human population density, and, additionally, with decreases in the cover of mosaics of cropland and natural vegetation. Main conclusions: Recent land cover and human population changes appear to have altered the habitat suitability pattern for large carnivores in Europe, whereas protection level did not play a role. While projected changes largely match the observed recovery of large carnivore populations, we found mismatches with the recent expansion of wolves in Central and Southern Europe, where factors not included in our models may have played a dominant role. This suggests that large carnivores’ co-existence with humans in European landscapes is not limited by habitat availability, but other factors such as favourable human tolerance and policy

Large carnivore expansion in Europe is associated with human population density and land cover changes

Aim: The recent recovery of large carnivores in Europe has been explained as resulting from a decrease in human persecution driven by widespread rural land abandonment, paralleled by forest cover increase and the consequent increase in availability of shelter and prey. We investigated whether land cover and human population density changes are related to the relative probability of occurrence of three European large carnivores: the grey wolf (Canis lupus), the Eurasian lynx (Lynx lynx) and the brown bear (Ursus arctos).Location: Europe, west of 64 degrees longitude.Methods: We fitted multi-temporal species distribution models using >50,000 occurrence points with time series of land cover, landscape configuration, protected areas, hunting regulations and human population density covering a 24-year period (1992-2015). Within the temporal window considered, we then predicted changes in habitat suitability for large carnivores throughout Europe.Results: Between 1992 and 2015, the habitat suitability for the three species increased in Eastern Europe, the Balkans, North-West Iberian Peninsula and Northern Scandinavia, but showed mixed trends in Western and Southern Europe. These trends were primarily associated with increases in forest cover and decreases in human population density, and, additionally, with decreases in the cover of mosaics of cropland and natural vegetation.Main conclusions: Recent land cover and human population changes appear to have altered the habitat suitability pattern for large carnivores in Europe, whereas protection level did not play a role. While projected changes largely match the observed recovery of large carnivore populations, we found mismatches with the recent expansion of wolves in Central and Southern Europe, where factors not included in our models may have played a dominant role. This suggests that large carnivores' co-existence with humans in European landscapes is not limited by habitat availability, but other factors such as favourable human tolerance and policy

The correlates and predictive validity of HIV risk groups among drug users in a community-based sample: Methodological findings from a multi-site cluster analysis

Outreach and intervention with out-of-treatment drug users in their natural communities has been a major part of our national HIV-prevention strategy for over a decade. Intervention design and evaluation is complicated because this population has heterogeneous patterns of HIV risk behaviors. The objectives of this paper are to: (a) empirically identify the major HIV risk groups; (b) examine how these risk groups are related to demographics, interactions with others, risk behaviors, and community (site); and (c) evaluate the predictive validity of these risk groups in terms of future risk behaviors. Exploratory cluster analysis of a sample of 4445 out-of-treatment drug users from the national data set identified eight main risk subgroups that could explain over 99% of the variance in the 20 baseline indices of HIV risk. We labeled these risk groups: Primary Crack Users (29.2%), Cocaine and Sexual Risk (12.8%), High Poly Risk Type 2 (0.3%), Poly Drug and Sex Risk (10.9%), Primary Needle Users (24.1%), High Poly Risk Type 1 (1.4%), High Frequency Needle Users (19.8%), and High Risk Needle Users (1.6%). Risk group membership was highly related to HIV characteristics (testing, sero-status), demographics (gender, race, age, education), status (marital, housing, employment, and criminal justice), prior target populations (needle users, crack users, pattern of sexual partners), and geography (site). Risk group membership explained 63% of the joint distribution of the original 20 HIV risk behaviors 6 months later (ranging from 0.03 to 37.2% of the variance individual indices). These analyses were replicated with both another 25% sample from the national data set and an independent sample collected from a new site. These findings suggest HIV interventions could probably be more effective if they targeted specific subgroups and that evaluations would be more sensitive if they consider community and sub-populations when evaluating these interventions

Campus News November 3, 1995

https://digitalcommons.lasalle.edu/campus_news/2166/thumbnail.jp

The possibilities to Support ZB GIS database update using object-based image analysis in ecognition developer software

The process of updating a spatial database is a necessary part of database management in order to keep the stored information of an acceptable quality. The first step of database update requires change detection. Many methods have been suggested to detect changes, mostly pixel-based. Recently, with the spread of very high resolution images and object-based image analysis, object-based methods were developed, too. This article presents object-based change detection method for update of the vector database ZB GIS, that is a geometric base of the Slovak National infrastructure of spatial information, using orthophoto of the area of interest. The method stages include the following: segmentation of orthophoto using the geometry of database objects and further according to spectral and spatial information, classification according to ZB GISR, defining reclassification rules between two classes. The proposed method was tested in two localities – Malženice (agricultural landscape) and Chopok-Jasna (mountainous landscape) reaching the overall accuracy of classification 87.12% and 84.55%, respectively. The main limitation of the method is that it can be applied only for polygonal objects