The Charitable Immunity Doctrine in Pennsylvania: Death Knell

In the face of an overwhelming trend to eliminate the charitable immunity doctrine, the Pennsylvania Supreme Court has consistently refused to abolish the doctrine it created back in 1888. The purpose of this paper is to forecast the future of the charitable immunity doctrine in Pennsylvania by analyzing cases in other areas where the policy arguments advanced were much the same as those raised for the doctrine of charitable immunity. Professor William L. Prosser notes that courts are in full retreat on the charitable immunity doctrine, and predicts its possible extinction within two decades. The doctrine as established in this state and in this country was based upon judicial error because reliance was placed upon overruled authority in England. The charitable immunity doctrine has nevertheless remained law in Pennsylvania until the present time. The Pennsylvania Supreme Court last faced the doctrine in 1961 in Michael v. Hahnemann Medical College and Hospital. At that time the court held, If the doctrine of charitable immunity is . . . no longer suited to the times and should be dispensed with, the proper way to accomplish that end is prospectively by legislation and not retroactively by judicial ukase. ... it is the legislature that can completely declare and promulgate public policy and not the courts. It is to be hoped... the attempts to eliminate the doctrine of charitable immunity .... will assume a state of quiescence so far as further insistent court action is concerned. Perhaps that is too much to hope for. In order to fortify the crumbling walls of the charitable immunity doctrine, which sister states are deserting, the Pennsylvania Supreme Court laid its second emphasis upon stare decisis. Citing McDowell v. Oyer, the Court held that stare decisis is absolutely necessary to any system of jurisprudence, It is this law which we are bound to execute, and not any \u27higher law\u27, manufactured for each special occasion out of our own private feelings and opinions. If it be wrong, the government has a department whose duty it is to amend it, and the responsibility is not in any wise thrown upon the judiciary

Conflict of Laws

Torts should be governed by the local law of the state which has the most significant relationship with the occurrence and the parties. Griffith v. United Airlines, 416 Pa. 1, 203 A.2d 796 (1964)

Technology-Enabled, Evidence-Driven, and Patient-Centered: The Way Forward for Regulating Software as a Medical Device

Artificial intelligence (AI) is a broad discipline that aims to understand and design systems that display properties of intelligence. Machine learning (ML) is a subset of AI that describes how algorithms and models can assist computer systems in progressively improving their performance. In health care, an increasingly common application of AI/ML is software as a medical device (SaMD), which has the intention to diagnose, treat, cure, mitigate, or prevent disease. AI/ML includes either “locked” or “continuous learning” algorithms. Locked algorithms consistently provide the same output for a particular input. Conversely, continuous learning algorithms, in their infancy in terms of SaMD, modify in real-time based on incoming real-world data, without controlled software version releases. This continuous learning has the potential to better handle local population characteristics, but with the risk of reinforcing existing structural biases. Continuous learning algorithms pose the greatest regulatory complexity, requiring seemingly continuous oversight in the form of special controls to ensure ongoing safety and effectiveness. We describe the challenges of continuous learning algorithms, then highlight the new evidence standards and frameworks under development, and discuss the need for stakeholder engagement. The paper concludes with 2 key steps that regulators need to address in order to optimize and realize the benefits of SaMD: first, international standards and guiding principles addressing the uniqueness of SaMD with a continuous learning algorithm are required and second, throughout the product life cycle and appropriate to the SaMD risk classification, there needs to be continuous communication between regulators, developers, and SaMD end users to ensure vigilance and an accurate understanding of the technology

The PiSpec: A Low-Cost, 3D-Printed Spectrometer for Measuring Volcanic SO2 Emission Rates

Spectroscopy has been used to quantify volcanic gas emission rates, most commonly SO2, for a number of decades. Typically, commercial spectrometers costing 1000s USD are employed for this purpose. The PiSpec is a new, custom-designed, 3D-printed spectrometer based on smartphone sensor technology. This unit has ≈1 nm spectral resolution and a spectral range in the ultraviolet of ≈280–340 nm, and is specifically configured for the remote sensing of SO2 using Differential Optical Absorption Spectroscopy (DOAS). Here we report on the first field deployment of the PiSpec on a volcano, to demonstrate the proof of concept of the device’s functionality in this application area. The study was performed on Masaya Volcano, Nicaragua, which is one of the largest emitters of SO2 on the planet, during a period of elevated activity where a lava lake was present in the crater. Both scans and traverses were performed, with resulting emission rates ranging from 3.2 to 45.6 kg s−1 across two measurement days; these values are commensurate with those reported elsewhere in the literature during this activity phase (Aiuppa et al., 2018; Stix et al., 2018). Furthermore, we tested the PiSpec’s thermal stability, finding a wavelength shift of 0.046 nm/∘C between 2.5 and 45∘C, which is very similar to that of some commercial spectrometers. Given the low build cost of these units (≈500 USD for a one-off build, with prospects for further price reduction with volume manufacture), we suggest these units hold considerable potential for volcano monitoring operations in resource limited environments

Acute exposure to sublethal doses of neonicotinoid insecticides increases heat tolerance in honey bees

The European honey bee, Apis mellifera L., is the single most valuable managed pollinator in the world. Poor colony health or unusually high colony losses of managed honey bees result from a myriad of stressors, which are more harmful in combination. Climate change is expected to accentuate the effects of these stressors, but the physiological and behavioral responses of honey bees to elevated temperatures while under simultaneous influence of one or more stressors remain largely unknown. Here we test the hypothesis that exposure to acute, sublethal doses of neonicotinoid insecticides reduce thermal tolerance in honey bees. We administered to bees oral doses of imidacloprid and acetamiprid at 1/5, 1/20, and 1/100 of LD50 and measured their heat tolerance 4 h post-feeding, using both dynamic and static protocols. Contrary to our expectations, acute exposure to sublethal doses of both insecticides resulted in higher thermal tolerance and greater survival rates of bees. Bees that ingested the higher doses of insecticides displayed a critical thermal maximum from 2 ˚C to 5 ˚C greater than that of the control group, and 67%–87% reduction in mortality. Our study suggests a resilience of honey bees to high temperatures when other stressors are present, which is consistent with studies in other insects. We discuss the implications of these results and hypothesize that this compensatory effect is likely due to induction of heat shock proteins by the insecticides, which provides temporary protection from elevated temperatures

Cross-National Coverage of Cross-Border Transit Migration: A Community Structure Approach

A community structure analysis (exploring variations in community/national demographics linked to differences in reporting on critical issues) compared cross-national coverage of cross-border transit migration through Mediterranean and Central European countries in leading newspapers, one per country, in 16 countries, analyzing all articles of 250 words or more from 10/01/14 to 11/01/15. The resulting 238 total articles were coded for “prominence” and “direction” (“government responsibility,” “society responsibility” — including foreign aid, or “balanced/neutral” coverage) and combined into composite “media vector” scores for each newspaper (range 0.1132 to -0.2785, a total range of .3917). A majority of 12 of 16 (75%) of media vectors reflected societal responsibility of transit migration, with the minority (4 of 16, or 25%) registering government responsibility. Pearson correlations revealed the strength of three significant national demographic indicators, two of the three associated with coverage emphasizing government responsibility for transit migration. Crop production index (r= .423, p= .051), a measure of agricultural/economic vulnerability, was linked to coverage emphasizing government responsibility for transit migration. In contrast, another vulnerability measure, global peace index, was associated with more media emphasis on societal responsibility for transit migration (r= -.466, r =.050). One measure of privilege, females in the workforce (r= .426, p= .05), was also linked to government responsibility for transit migration. A regression analysis revealed the strength of a nation’s crop production index (21.2% of the variance), females in the workforce (22.2%) and corruption score (9.8%) all connected to coverage emphasizing government responsibility, collectively accounting for 53.1% of the variance. Contrary to conventional assumptions that media typically act as “guard dogs” reinforcing the interests of political and economic elites, systematic research on demographically linked variations in transit migration coverage reveal that media can “mirror” the interests of a society’s most “vulnerable” inhabitants

Assessment of the quality of brain regions and neuroimaging metrics as biomarkers of Alzheimer’s disease

Alzheimer Disease (AD) is characterized by progressive cognitive decline and dementia. Earlier diagnosis and classification of different stages of the disease are currently the main challenges and can be assessed by neuroimaging. With this work we aim to evaluate the quality of brain regions and neuroimaging metrics as biomarkers of AD. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox functionalities were used to study AD by T1weighted, Diffusion Tensor Imaging and 18FAV45 PET, with data obtained from the AD Neuroimaging Initiative database, specifically 12 healthy controls (CTRL) and 33 patients with early mild cognitive impairment (EMCI), late MCI (LMCI) and AD (11 patients/group). The metrics evaluated were gray-matter volume (GMV), cortical thickness (CThk), mean diffusivity (MD), fractional anisotropy (FA), fiber count (FiberConn), node degree (Deg), cluster coefficient (ClusC) and relative standard-uptake-values (rSUV). Receiver Operating Characteristic (ROC) curves were used to evaluate and compare the diagnostic accuracy of the most significant metrics and brain regions and expressed as area under the curve (AUC). Comparisons were performed between groups. The RH-Accumbens/Deg demonstrated the highest AUC when differentiating between CTRLEMCI (82%), whether rSUV presented it in several brain regions when distinguishing CTRL-LMCI (99%). Regarding CTRL-AD, highest AUC were found with LH-STG/FiberConn and RH-FP/FiberConn (~100%). A larger number of neuroimaging metrics related with cortical atrophy with AUC>70% was found in CTRL-AD in both hemispheres, while in earlier stages, cortical metrics showed in more confined areas of the temporal region and mainly in LH, indicating an increasing of the spread of cortical atrophy that is characteristic of disease progression. In CTRL-EMCI several brain regions and neuroimaging metrics presented AUC>70% with a worst result in later stages suggesting these indicators as biomarkers for an earlier stage of MCI, although further research is necessary

The causes and consequences of changes in virulence following pathogen host shifts.

Emerging infectious diseases are often the result of a host shift, where the pathogen originates from a different host species. Virulence--the harm a pathogen does to its host-can be extremely high following a host shift (for example Ebola, HIV, and SARs), while other host shifts may go undetected as they cause few symptoms in the new host. Here we examine how virulence varies across host species by carrying out a large cross infection experiment using 48 species of Drosophilidae and an RNA virus. Host shifts resulted in dramatic variation in virulence, with benign infections in some species and rapid death in others. The change in virulence was highly predictable from the host phylogeny, with hosts clustering together in distinct clades displaying high or low virulence. High levels of virulence are associated with high viral loads, and this may determine the transmission rate of the virus.BL and FMJ are supported by a NERC grant (NE/L004232/1), a European Research Council grant (281668, DrosophilaInfection), a Junior Research Fellowship from Christ’s College, Cambridge (BL) and a Royal Society University Research Fellowship (FMJ). JDH is supported by a Royal Society University Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final published version. It first appeared at http://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1004728

Host shifts result in parallel genetic changes when viruses evolve in closely related species.

Host shifts, where a pathogen invades and establishes in a new host species, are a major source of emerging infectious diseases. They frequently occur between related host species and often rely on the pathogen evolving adaptations that increase their fitness in the novel host species. To investigate genetic changes in novel hosts, we experimentally evolved replicate lineages of an RNA virus (Drosophila C Virus) in 19 different species of Drosophilidae and deep sequenced the viral genomes. We found a strong pattern of parallel evolution, where viral lineages from the same host were genetically more similar to each other than to lineages from other host species. When we compared viruses that had evolved in different host species, we found that parallel genetic changes were more likely to occur if the two host species were closely related. This suggests that when a virus adapts to one host it might also become better adapted to closely related host species. This may explain in part why host shifts tend to occur between related species, and may mean that when a new pathogen appears in a given species, closely related species may become vulnerable to the new disease

Examining the Links between Multi-Frequency Multibeam Backscatter Data and Sediment Grain Size

Publication history: Accepted - 13 April 2021Acoustic methods are routinely used to provide broad scale information on the geographical distribution of benthic marine habitats and sedimentary environments. Although single-frequency multibeam echosounder surveys have dominated seabed characterisation for decades, multifrequency approaches are now gaining favour in order to capture different frequency responses from the same seabed type. The aim of this study is to develop a robust modelling framework for testing the potential application and value of multifrequency (30, 95, and 300 kHz) multibeam backscatter responses to characterize sediments’ grain size in an area with strong geomorphological gradients and benthic ecological variability. We fit a generalized linear model on a multibeam backscatter and its derivatives to examine the explanatory power of single-frequency and multifrequency models with respect to the mean sediment grain size obtained from the grab samples. A strong and statistically significant (p < 0.05) correlation between the mean backscatter and the absolute values of the mean sediment grain size for the data was noted. The root mean squared error (RMSE) values identified the 30 kHz model as the best performing model responsible for explaining the most variation (84.3%) of the mean grain size at a statistically significant output (p < 0.05) with an adjusted r2 = 0.82. Overall, the single low-frequency sources showed a marginal gain on the multifrequency model, with the 30 kHz model driving the significance of this multifrequency model, and the inclusion of the higher frequencies diminished the level of agreement. We recommend further detailed and sufficient ground-truth data to better predict sediment properties and to discriminate benthic habitats to enhance the reliability of multifrequency backscatter data for the monitoring and management of marine protected areas.This research was funded by the Marine Institute under the Marine Research Programme by the Irish Government Cruise CE19007 Backscatter and Biodiversity of Shelf Sea Habitats (BaBioSSH) survey. Staffing was supported through the Marine Protected Area Monitoring and Management (MarPAMM) project, which is supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPM) with matching funding from the Government of Ireland, the Northern Ireland Executive, and the Scottish Government, as well as the PhD studentship through a Vice Chancellor Research Scholarship of Ulster University (U.K.)