Criminal Law - Disclosure of Identity of Eyewitness Informer

The Supreme Court of Pennsylvania has held that the governmental privilege\u27 to refrain from disclosing the identity of an informer does not limit the duty of the prosecution to make available the name and whereabouts of all material eyewitnesses to the defense. Commonwealth v. Carter, 427 Pa. 53, 233 A.2d 284 (1967)

On the semiclassical treatment of Hawking radiation

In the context of the semiclassical treatment of Hawking radiation we prove the universality of the reduced canonical momentum for the system of a massive shell self gravitating in a spherical gravitational field within the Painlev\'e family of gauges. We show that one can construct modes which are regular on the horizon both by considering as hamiltonian the exterior boundary term and by using as hamiltonian the interior boundary term. The late time expansion is given in both approaches and their time Fourier expansion computed to reproduce the self reaction correction to the Hawking spectrum.Comment: 18 pages, LaTeX, Corrected typo

The Case for Biological Quantum Computer Elements

An extension to vonNeumann's analysis of quantum theory suggests self-measurement is a fundamental process of Nature. By mapping the quantum computer to the brain architecture we will argue that the cognitive experience results from a measurement of a quantum memory maintained by biological entities. The insight provided by this mapping suggests quantum effects are not restricted to small atomic and nuclear phenomena but are an integral part of our own cognitive experience and further that the architecture of a quantum computer system parallels that of a conscious brain. We will then review the suggestions for biological quantum elements in basic neural structures and address the de-coherence objection by arguing for a self-measurement event model of Nature. We will argue that to first order approximation the universe is composed of isolated self-measurement events which guaranties coherence. Controlled de-coherence is treated as the input/output interactions between quantum elements of a quantum computer and the quantum memory maintained by biological entities cognizant of the quantum calculation results. Lastly we will present stem-cell based neuron experiments conducted by one of us with the aim of demonstrating the occurrence of quantum effects in living neural networks and discuss future research projects intended to reach this objective

The search for biological quantum computer elements

The difficulties encountered in explaining the capacities of the human brain to generate conscious experiences with a neuron switching model has lead researchers to speculate that quantum phenomena may be involved in the human thinking process. This speculation goes beyond acknowledgement of the quantum mechanical basis for bio-molecular chemistry but suggests the architecture of brain functioning parallels the architecture of quantum computers. In this model classically observed neural components act like transmitting and receiving channels to quantum elements analogous to the state-preparation and measurement components in quantum computer architectures. Theories proposed by Penrose and Hameroff suggest such quantum element fields may be supplied by the microtubule structure encountered in neurons, while the DNA field has also been proposed as a candidate for quantum computation. Objections to the quantum brain model rests primarily on the de-coherence expected in the warm-soup environment which simply compounds the isolation difficulties encountered in conventional approaches to quantum computer element construction

Ferric Gluconate Yields Cost-Savings in Hemodialysis Patients with High Ferritin and Low TSAT: Results from the DRIVE Studies

Purpose: One third of hemodialysis patients have high serum ferritin levels and low transferrin saturation (TSAT). The purpose of this analysis was to determine the cost effectiveness of administering 1g of sodium ferric gluconate complex (SFGC: also referred to as ferric gluconate) to patients with serum ferritin \u3e500ng/mL and TSAT ≤25% based on the Dialysis Patients Response to IV Iron with Elevated Ferritin (DRIVE) study and its 6-week observational extension (DRIVE-II). In these studies, IV iron administration resulted in reduced epoetin requirements. Methods: Decision analysis was performed using a time horizon of 12 weeks, consistent with the combined duration of DRIVE and DRIVE II. Treatment effectiveness was based on mean increase in hemoglobin (Hb) for each group (SFGC plus epoetin or epoetin alone) in the intention to treat populations. Costs included drugs (SFGC and epoetin) and hospitalizations due to serious adverse events (SAEs) reported. The primary cost effectiveness measure was cost per g/dL of Hb increase at 12 weeks. Costs were computed from a Medicare perspective using projected 2007 reimbursements. Sensitivity analyses were performed to test the impact of using the safety population, median epoetin and SFGC doses, actual 2005 Medicare reimbursements, median increases in Hb, and SAE rate changes. The model was constructed using TreeAge Pro software. Results: Total cost per patient receiving SFGC plus epoetin was $3675 per g/dL Hb increase, while the total cost per patient receiving epoetin alone was$5065 per g/dL Hb increase. Net savings for SFGC plus epoetin was $1390 per g/dL Hb increase over the 12 week period Sensitivity analyses affirmed the robustness of the model. Conclusion: Administering 1g of SFGC plus epoetin in patients with high ferritin and low TSAT as defined in the DRIVE studies resulted in significant cost-savings compared to epoetin alone

Halogenation dictates the architecture of amyloid peptide nanostructures

Amyloid peptides yield a plethora of interesting nanostructures though difficult to control. Here we report that depending on the number, position, and nature of the halogen atoms introduced into either one or both phenylalanine benzene rings of the amyloid β peptide-derived core-sequence KLVFF, four different architectures were obtained in a controlled manner. Our findings demonstrate that halogenation may develop as a general strategy to engineer amyloidal peptide self-assembly and obtain new amyloidal nanostructures

A cultured human neural network operates a robotic actuator

The development of bio-electronic prostheses, hybrid human-electronics devices and bionic robots has been the aim of many researchers. Although neurophysiologic processes have been widely investigated and bio-electronics has developed rapidly, the dynamics of a biological neuronal network that receive sensory inputs, store and control information is not yet understood. Toward this end, we have taken an interdisciplinary approach to study the learning and response of biological neural networks to complex stimulation patterns. This paper describes the design, execution, and results of several experiments performed in order to investigate the behavior of complex interconnected structures found in biological neural networks. The experimental design consisted of biological human neurons stimulated by parallel signal patterns intended to simulate complex perceptions. The response patterns were analyzed with an innovative artificial neural network (ANN), called ITSOM (Inductive Tracing Self Organizing Map). This system allowed us to decode the complex neural responses from a mixture of different stimulations and learned memory patterns inherent in the cell colonies. In the experiment described in this work, neurons derived from human neural stem cells were connected to a robotic actuator through the ANN analyzer to demonstrate our ability to produce useful control from simulated perceptions stimulating the cells. Preliminary results showed that in vitro human neuron colonies can learn to reply selectively to different stimulation patterns and that response signals can effectively be decoded to operate a minirobot. Lastly the fascinating performance of the hybrid system is evaluated quantitatively and potential future work is discussed

Workflow Engineering in Materials Design within the BATTERY 2030+Project

In recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by providing insights inaccessible by experiment. However, this often requires multiple simulation tools to meet the modeling goal. As a result, methods and tools are needed to enable extensive-scale simulations with streamlined execution of all tasks within a complex simulation protocol, including the transfer and adaptation of data between calculations. These methods should allow rapid prototyping of new protocols and proper documentation of the process. Here an overview of the benefits and challenges of workflow engineering in virtual material design is presented. Furthermore, a selection of prominent scientific workflow frameworks used for the research in the BATTERY 2030+ project is presented. Their strengths and weaknesses as well as a selection of use cases in which workflow frameworks significantly contributed to the respective studies are discussed

Workflow Engineering in Materials Design within the BATTERY 2030+ Project

In recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by providing insights inaccessible by experiment. However, this often requires multiple simulation tools to meet the modeling goal. As a result, methods and tools are needed to enable extensive-scale simulations with streamlined execution of all tasks within a complex simulation protocol, including the transfer and adaptation of data between calculations. These methods should allow rapid prototyping of new protocols and proper documentation of the process. Here an overview of the benefits and challenges of workflow engineering in virtual material design is presented. Furthermore, a selection of prominent scientific workflow frameworks used for the research in the BATTERY 2030+ project is presented. Their strengths and weaknesses as well as a selection of use cases in which workflow frameworks significantly contributed to the respective studies are discussed