Collecting Provenance via the Xen Hypervisor

The Provenance Aware Storage Systems project (PASS) currently collects system-level provenance by intercepting system calls in the Linux kernel and storing the provenance in a stackable filesystem. While this approach is reasonably efficient, it suffers from two significant drawbacks: each new revision of the kernel requires reintegration of PASS changes, the stability of which must be continually tested; also, the use of a stackable filesystem makes it difficult to collect provenance on root volumes, especially during early boot. In this paper we describe an approach to collecting system-level provenance from virtual guest machines running under the Xen hypervisor. We make the case that our approach alleviates the aforementioned difficulties and promotes adoption of provenance collection within cloud computing platforms.Engineering and Applied Science

The possible role of symmetric instability in the formation of precipitation bands

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric and Planetary Sciences, 1984.Microfiche copy available in Archives and Science.Bibliography: leaves 65-66.by Marc Allen Seltzer.M.S

Development of a Large Scale, High Speed Wheel Test Facility

Draper Laboratory, with its internal research and development budget, has for the past two years been funding a joint effort with the Massachusetts Institute of Technology (MIT) for the development of a large scale, high speed wheel test facility. This facility was developed to perform experiments and carry out evaluations on levitation and propulsion designs for MagLev systems currently under consideration. The facility was developed to rotate a large (2 meter) wheel which could operate with peripheral speeds of greater than 100 meters/second. The rim of the wheel was constructed of a non-magnetic, non-conductive composite material to avoid the generation of errors from spurious forces. A sensor package containing a multi-axis force and torque sensor mounted to the base of the station, provides a signal of the lift and drag forces on the package being tested. Position tables mounted on the station allow for the introduction of errors in real time. A computer controlled data acquisition system was developed around a Macintosh IIfx to record the test data and control the speed of the wheel. This paper describes the development of this test facility. A detailed description of the major components is presented. Recently completed tests carried out on a novel Electrodynamic (EDS) suspension system, developed by MIT as part of this joint effort are described and presented. Adaptation of this facility for linear motor and other propulsion and levitation testing is described

Towards 3D printed multifunctional immobilization for proton therapy: initial materials characterization

Purpose: 3D printing technology is investigated for the purpose of patient immobilization during proton therapy. It potentially enables a merge of patient immobilization, bolus range shifting, and other functions into one single patient-speci c structure. In this rst step, a set of 3D printed materials is characterized in detail, in terms of structural and radiological properties, elemental composition, directional dependence, and structural changes induced by radiation damage. These data will serve as inputs for the design of 3D printed immobilization structure prototypes. Methods: Using four di erent 3D printing techniques, in total eight materials were subjected to testing. Samples with a nominal dimension of 20×20×80 mm3 were 3D printed. The geometrical printing accuracy of each test sample was measured with a dial gage. To assess the mechanical response of the samples, standardized compression tests were performed to determine the Young’s modulus. To investigate the e ect of radiation on the mechanical response, the mechanical tests were performed both prior and after the administration of clinically relevant dose levels (70 Gy), multiplied with a safety factor of 1.4. Dual energy computed tomography (DECT) methods were used to calculate the relative electron density to water ρe, the e ective atomic number Ze , and the proton stopping power ratio (SPR) to water SPR. In order to validate the DECT based calculation of radiological properties, beam measurements were performed on the 3D printed samples as well. Photon irradiations were performed to measure the photon linear attenuation coe cients, while proton irradiations were performed to measure the proton range shift of the samples. The direc- tional dependence of these properties was investigated by performing the irradiations for di erent orientations of the samples. Results: The printed test objects showed reduced geometric printing accuracy for 2 materials (deviation > 0.25 mm). Compression tests yielded Young’s moduli ranging from 0.6 to 2940 MPa. No deterioration in the mechanical response was observed after exposure of the samples to 100 Gy in a therapeutic MV photon beam. The DECT-based characterization yielded Ze ranging from 5.91 to 10.43. The SPR and ρe both ranged from 0.6 to 1.22. The measured photon attenuation coe cients at clinical energies scaled linearly with ρe. Good agreement was seen between the DECT estimated SPR and the measured range shift, except for the higher Ze . As opposed to the photon attenuation, the proton range shifting appeared to be printing orientation dependent for certain materials. Conclusions: In this study, the rst step toward 3D printed, multifunctional immobilization was performed, by going through a candidate clinical work ow for the rst time: from the material printing to DECT characterization with a veri cation through beam measurements. Besides a proof of concept for beam modi cation, the mechanical response of printed materials was also investigated to assess their capabilities for positioning functionality. For the studied set of printing techniques and materials, a wide variety of mechanical and radiological properties can be selected from for the intended purpose. Moreover the elaborated hybrid DECT methods aid in performing in-house quality assurance of 3D printed components, as these methods enable the estimation of the radiological properties relevant for use in radiation therapy

Role of TNF-alpha during central sensitization in preclinical studies

Tumor necrosis factor-alpha (TNF-α) is a principal mediator in pro-inflammatory processes that involve necrosis, apoptosis and proliferation. Experimental and clinical evidence demonstrate that peripheral nerve injury results in activation and morphological changes of microglial cells in the spinal cord. These adjustments occur in order to initiate an inflammatory cascade in response to the damage. Between the agents involved in this reaction, TNF-α is recognized as a key player in this process as it not only modulates lesion formation, but also because it is suggested to induce nociceptive signals. Nowadays, even though the function of TNF-α in inflammation and pain production seems to be generally accepted, diverse sources of literature point to different pathways and outcomes. In this review, we systematically searched and reviewed original articles from the past 10 years on animal models of peripheral nervous injury describing TNF-α expression in neural tissue and pain behavior

Workshop Report for Cancer Research: Defining the Shades of Gy: Utilizing the Biological Consequences of Radiotherapy in the Development of New Treatment Approaches—Meeting Viewpoint

The ability to physically target radiotherapy using image-guidance is continually improving with photons and particle therapy that include protons and heavier ions such as carbon. The unit of dose deposited is the gray (Gy); however, particle therapies produce different patterns of ionizations, and there is evidence that the biological effects of radiation depend on dose size, schedule, and type of radiation. This National Cancer Institute (NCI)–sponsored workshop addressed the potential of using radiation-induced biological perturbations in addition to physical dose, Gy, as a transformational approach to quantifying radiation

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder