Exploration of a free space optical telemetry system for formation flying sounding rocket sub-payloads

The results of an exploration regarding the novel use of free-space optics (FSO) between sounding rockets and their sub-payloads are presented. This includes an evaluation of optoelectronic and optical devices against environmental and system level criteria. A preliminary test using available in-house components and bench-top equipment was also performed to determine potential distances and data rates of FSO in this environment. Using a light emitting diode with an optical power output of approximately six milliwatts, and a photomultiplier tube originally purposed for use on the Compton GRO, a pulse rate of ten kilohertz was transmitted over a distance of four-hundred meters in-atmosphere. Transmission distance was increased to five-hundred meters using an optical bandpass filter, and nine-hundred meters using a baffle. Because of test equipment limitations and the potential for increased optical power transmission, it is expected that greater distances and data rates can be achieved in the final design

Projectile- And Target-charge Dependent Effects In Ionizing Collisions Of H ⁺ And He 2+ With He, Ne And Ar Atoms

The spectra of electrons emitted in collisions between H + and He 2+ projectiles and He, Ne and Ar targets at energies of 50 and 100 keV amu -1 have been studied. The data are in qualitative agreement with results of Irby el al., but are in disagreement with measurements of Bernardi et al. It is shown that the observed electron spectra have a dependence on both target-ion and projectile effective charge that can be understood qualitatively in terms of \u27saddle-point\u27 ionization. Several issues relevant to saddle-point ionization are discussed. © 1990 IOP Publishing Ltd

Actin and Type I Collagen Propeptide Distribution in the Developing Chick Cornea

PURPOSE. To determine the organization of actin filaments and distribution of type I procollagen during the development of the chick corneal stroma. METHODS. Embryonic chicken corneas of ages 6 to 18 days and 18 days posthatch were cryosectioned and fluorescently labeled for filamentous actin with phalloidin and for the N-and C-terminal propeptides of type I procollagen with specific monoclonal antibodies. Tissue sections were examined by fluorescence and confocal microscopy. RESULTS. Prominent actin filament bundles were present at all embryonic stages, arranged in orthogonal arrays. Type I collagen propeptides were also present, with the C-propeptide visible as small foci, often associated with the actin label. The N-propeptide was also detected in the stromal matrix, especially in Bowman's layer. Actin filaments were also prominent in the corneal epithelium, along with collagen propeptide labeling, up to embryonic day14. CONCLUSIONS. Actin filament bundles are abundant in the stroma, presumably in the keratocytes of the developing chick cornea, and are arranged in an orthogonal manner suggesting a possible role in cell and matrix organization in this tissue. Filament bundles appear to be closely associated with the foci of type I procollagen label, suggesting a possible association between the actin cytoskeleton and the trafficking of collagen. The presence of the N-propeptide of type I collagen in the extracellular matrix and the restricted distribution of the Cpropeptide suggest differential processing of these molecules after secretion. The persistence of the N-propeptide implies a role in development, possibly in association with control of collagen fibril diameter and spacing. (Invest Ophthalmol Vis Sci

Actin and Type I Collagen Propeptide Distribution in the Developing Chick Cornea

PURPOSE. To determine the organization of actin filaments and distribution of type I procollagen during the development of the chick corneal stroma. METHODS. Embryonic chicken corneas of ages 6 to 18 days and 18 days posthatch were cryosectioned and fluorescently labeled for filamentous actin with phalloidin and for the N-and C-terminal propeptides of type I procollagen with specific monoclonal antibodies. Tissue sections were examined by fluorescence and confocal microscopy. RESULTS. Prominent actin filament bundles were present at all embryonic stages, arranged in orthogonal arrays. Type I collagen propeptides were also present, with the C-propeptide visible as small foci, often associated with the actin label. The N-propeptide was also detected in the stromal matrix, especially in Bowman's layer. Actin filaments were also prominent in the corneal epithelium, along with collagen propeptide labeling, up to embryonic day14. CONCLUSIONS. Actin filament bundles are abundant in the stroma, presumably in the keratocytes of the developing chick cornea, and are arranged in an orthogonal manner suggesting a possible role in cell and matrix organization in this tissue. Filament bundles appear to be closely associated with the foci of type I procollagen label, suggesting a possible association between the actin cytoskeleton and the trafficking of collagen. The presence of the N-propeptide of type I collagen in the extracellular matrix and the restricted distribution of the Cpropeptide suggest differential processing of these molecules after secretion. The persistence of the N-propeptide implies a role in development, possibly in association with control of collagen fibril diameter and spacing. (Invest Ophthalmol Vis Sci

Promoter methylation of RASSF1A and DAPK and mutations of K-ras, p53, and EGFR in lung tumors from smokers and never-smokers

<p>Abstract</p> <p>Background</p> <p>Epidemiological studies indicate that some characteristics of lung cancer among never-smokers significantly differ from those of smokers. Aberrant promoter methylation and mutations in some oncogenes and tumor suppressor genes are frequent in lung tumors from smokers but rare in those from never-smokers. In this study, we analyzed promoter methylation in the <it>ras-association domain isoform A (RASSF1A) </it>and the <it>death-associated protein kinase (DAPK) </it>genes in lung tumors from patients with primarily non-small cell lung cancer (NSCLC) from the Western Pennsylvania region. We compare the results with the smoking status of the patients and the mutation status of the K-<it>ras</it>, <it>p53</it>, and <it>EGFR </it>genes determined previously on these same lung tumors.</p> <p>Methods</p> <p>Promoter methylation of the <it>RASSF1A </it>and <it>DAPK </it>genes was analyzed by using a modified two-stage methylation-specific PCR. Data on mutations of K-<it>ras</it>, <it>p53</it>, and <it>EGFR </it>were obtained from our previous studies.</p> <p>Results</p> <p>The <it>RASSF1A </it>gene promoter methylation was found in tumors from 46.7% (57/122) of the patients and was not significantly different between smokers and never-smokers, but was associated significantly in multiple variable analysis with tumor histology (p = 0.031) and marginally with tumor stage (p = 0.063). The <it>DAPK </it>gene promoter methylation frequency in these tumors was 32.8% (40/122) and did not differ according to the patients' smoking status, tumor histology, or tumor stage. Multivariate analysis adjusted for age, gender, smoking status, tumor histology and stage showed that the frequency of promoter methylation of the <it>RASSF1A </it>or <it>DAPK </it>genes did not correlate with the frequency of mutations of the K<it>-ras, p53</it>, and <it>EGFR </it>gene.</p> <p>Conclusion</p> <p>Our results showed that <it>RASSF1A </it>and <it>DAPK </it>genes' promoter methylation occurred frequently in lung tumors, although the prevalence of this alteration in these genes was not associated with the smoking status of the patients or the occurrence of mutations in the K-<it>ras</it>, <it>p53 </it>and <it>EGFR </it>genes, suggesting each of these events may represent independent event in non-small lung tumorigenesis.</p

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark