The analysis of coal with phenol as a solvent

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Design and evaluation of additively manufactured parts with three dimensional continuous fibre reinforcement.

Additive manufacturing (AM) provides many benefits such as reduced manufacturing lead times, streamlined supply chains, part consolidation, structural optimisation and improved buy-to-fly ratios. Barriers to adoption include high material and processing costs, low build rates, isotropic material properties, and variable processing conditions. Currently AM polymer parts are far less expensive to manufacture than AM metal parts, therefore improving the properties of polymer parts is highly desirable. This paper introduces a design methodology used to integrate continuous reinforcement into AM polymer parts with the aim of improving their mechanical properties. The method is validated with the design and testing of three case studies, a pulley housing, hook and universal joint used to demonstrate the applicability of the method for tensile, bending and torsion loading types respectively. Physical testing showed that it was possible to improve the strength of parts by over 4000%, elongation to failure by over 2000% and stiffness by approximately 200%. In addition a method of integrating condition monitoring capabilities into the parts was demonstrated. An analysis of the specific strength of the parts suggests that the reinforced parts are comparable to aluminium alloys, suggesting that in some cases AM polymer composite parts could supplant more costly metal parts

Description, Reliability and Validation of a Novel Ground-Reaction-Force-Triggered Protocol for Simulation of Tripping Perturbations During Gait

Tripping is a common cause of falls across different age populations particularly in older adults. Concerns regarding the validity of simulated-fall research protocols reside in the current literature. The purpose of this study was to develop a novel treadmill-based tripping protocol that allowed researchers to deliver unanticipated tripping perturbations during walking with a high level of timing precision. The protocol utilized a side-by-side split-belt treadmill instrumented with force platforms. Treadmill belt acceleration profiles (two levels of perturbation severity: small perturbation vs large perturbation) were delivered unilaterally when the tripped leg bore 20% of the body weight during early stance. Peak trunk flexion angle during trip recovery was the primary variable used to represent the fall recovery response and likelihood of falls. Test-retest reliability of the fall responses was examined in a group of 10 young participants; validity was examined through differentiation of the fall responses between young and older adults (age 20.9 vs. 57.1 years, n=10 per group). We found that the perturbations were precisely delivered during the early stance phase (10-45 ms after initial contact). Moreover, this protocol elicited excellent reliability of recovery responses during both perturbation severities (ICC=0.944 and 0.911). Older adults exhibited significantly greater peak trunk flexion angle than young adults (p=0.035), indicating the current protocol was valid in differentiating individuals with different levels of fall risks. This novel protocol addressed some of the issues of previous simulated-fall protocols and may be useful as a tool for future fall research and clinical intervention

Home Area Networks and the Smart Grid

With the wide array of home area network (HAN) options being presented as solutions to smart grid challenges for the home, it is time to compare and contrast their strengths and weaknesses. This white paper examines leading and emerging HAN technologies. The emergence of the smart grid is bringing more networking players into the field. The need for low consistent bandwidth usage differs enough from the traditional information technology world to open the door to new technologies. The predominant players currently consist of a blend of the old and new. Within the wired world Ethernet and HomePlug Green PHY are leading the way with an advantage to HomePlug because it doesn't require installing new wires. In the wireless the realm there are many more competitors but WiFi and ZigBee seem to have the most momentum

AMI Communication Requirements to Implement Demand-Response: Applicability of Hybrid Spread Spectrum Wireless

While holistically defining the smart grid is a challenge, one area of interest is demand-response. In 2009, the Department of Energy announced over $4 billion in grant and project funding for the Smart Grid. A significant amount of this funding was allotted to utilities for cost sharing projects to deploy Smart Grid technologies, many of whom have deployed and are deploying advanced metering infrastructure (AMI). AMI is an enabler to increase the efficiency of utilities and the bulk power grid. The bulk electrical system is unique in that it produces electricity as it is consumed. Most other industries have a delay between generation and consumption. This aspect of the power grid means that there must be enough generation capacity to meet the highest demand whereas other industries could over produce during off-peak times. This requires significant investment in generation capacity to cover the few days a year of peak consumption. Since bulk electrical storage doesn't yet exist at scale another way to curb the need for new peak period generation is through demand-response; that is to incentivize consumers (demand) to curtail (respond) electrical usage during peak periods. Of the various methods proposed for enabling demand-response, this paper will focus on the communication requirements for creating an energy market using transactional controls. More specifically, the paper will focus on the communication requirements needed to send the peak period notices and receive the response back from the consumers

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK

A Stress Induced Source of Phonon Bursts and Quasiparticle Poisoning

The performance of superconducting qubits is degraded by a poorly characterized set of energy sources breaking the Cooper pairs responsible for superconductivity, creating a condition often called "quasiparticle poisoning." Recently, a superconductor with one of the lowest average quasiparticle densities ever measured exhibited quasiparticles primarily produced in bursts which decreased in rate with time after cooldown. Similarly, several cryogenic calorimeters used to search for dark matter have also observed an unknown source of low-energy phonon bursts that decrease in rate with time after cooldown. Here, we show that a silicon crystal glued to its holder exhibits a rate of low-energy phonon events that is more than two orders of magnitude larger than in a functionally identical crystal suspended from its holder in a low-stress state. The excess phonon event rate in the glued crystal decreases with time since cooldown, consistent with a source of phonon bursts which contributes to quasiparticle poisoning in quantum circuits and the low-energy events observed in cryogenic calorimeters. We argue that relaxation of thermally induced stress between the glue and crystal is the source of these events, and conclude that stress relaxation contributes to quasiparticle poisoning in superconducting qubits and the athermal phonon background in a broad class of rare-event searches.Comment: 13 pages, 6 figures. W. A. Page and R. K. Romani contributed equally to this work. Correspondence should be addressed to R. K. Roman

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

Damien Caillaud is with UT Austin and Max Planck Institute for Evolutionary Anthropology; Margaret C. Crofoot is with the Smithsonian Tropical Research Institute, Max Planck Institute for Ornithology, and Princeton University; Samuel V. Scarpino is with UT Austin; Patrick A. Jansen is with the Smithsonian Tropical Research Institute, Wageningen University, and University of Groningen; Carol X. Garzon-Lopez is with University of Groningen; Annemarie J. S. Winkelhagen is with Wageningen University; Stephanie A. Bohlman is with Princeton University; Peter D. Walsh is with VaccinApe.Background -- The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings -- Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance -- We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.The National Center For Ecological Analysis is supported by NSF Grant DEB-0553768, the University of California Santa Barbara and the State of California. The Forest Dynamics Plots were funded by NSF Grants to Stephen Hubbell DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, and by the Center for Tropical Forest Science, the Smithsonian Tropical Forest Research Institute, The John D. and Catherine T. MacArthur Foundation, the Mellon Foundation and the Celera Foundation. DC is supported by NSF grant DEB-0749097 to L.A. Meyers. SS is supported by an NSF Graduate Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis