Controlling for transactions bias in regional house price indices

Transactions bias arises when properties that trade are not a random sample of the total housing stock. Price indices are susceptible because they are typically based on transactions data. Existing approaches to this problem rely on Heckman-type correction methods, where a probit regression is used to capture the differences between properties that sell and those that do not sell in a given period. However, this approach can only be applied where there is reliable data on the whole housing stock. In many countries—the UK included—no such data exist and there is little prospect of correcting for transactions bias in any of the regularly updated mainstream house price indices. Thispaper suggests a possible alternative approach, using information at postcode sector level and Fractional Probit Regression to correct for transactions bias in hedonic price indices based on one and a half million house sales from 1996 to 2004, distributed across 1200 postcode sectors in the South East of England

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance biological efficiency : To evaluate soybean germplasm and cultivars for stress tolerance toward : Moisture Stress

Seventeen soybean genotypes were screened in a laboratory and growth-chamber experiment for water-stress tolerance characteristics. Three osmotic concentrations (0, -0.3 and -0.5 MPa) were used in an 8-day germination test conducted in the laboratory at Alabama A&M University. The Promptness Index (PI) and Germination Stress Index (GSI) were calculated (Bouslama and Schapaugh, 1984)

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance and biological efficiency toward : Moisture Stress

Three soybean cultivars, \u27Lee-74\u27, \u27Wright\u27, and \u27RA 401\u27, were subjected to 100% (control), 75%, and 50% of field capacity during vegetative (Vl), flowering (R2), and pod-filling (R4) stages in greenhouse and field studies. Stress applied at R2 significantly reduced the yield in the green-house, while in the field, the maximum reduction was observed when the plants were subjected to stress at R4. Stress during Vl reduced the yield components less than stress applied during R2 or R4 stages in both studies

Sample size for collecting germplasms - a polyploid model with mixed mating system

The present paper discusses a general expression for determining the minimum sample size (plants) for a given number of seeds or vice versa for capturing multiple allelic diversity. The model considers sampling from a large 2 k-ploid population under a broad range of mating systems. Numerous expressions/results developed for germplasm collection/regeneration for diploid populations by earlier workers can be directly deduced from our general expression by assigning appropriate values of the corresponding parameters. A seed factor which influences the plant sample size has also been isolated to aid the collectors in selecting the appropriate combination of number of plants and seeds per plant. When genotypic multiplicity of seeds is taken into consideration, a sample size of even less than 172 plants can conserve diversity of 20 alleles from 50,000 polymorphic loci with a very large probability of conservation (0.9999) in most of the cases

Outer membrane protein folding from an energy landscape perspective

The cell envelope is essential for the survival of Gram-negative bacteria. This specialised membrane is densely packed with outer membrane proteins (OMPs), which perform a variety of functions. How OMPs fold into this crowded environment remains an open question. Here, we review current knowledge about OFMP folding mechanisms in vitro and discuss how the need to fold to a stable native state has shaped their folding energy landscapes. We also highlight the role of chaperones and the β-barrel assembly machinery (BAM) in assisting OMP folding in vivo and discuss proposed mechanisms by which this fascinating machinery may catalyse OMP folding

Health state utilities associated with attributes of treatments for hepatitis C

BACKGROUND: Cost-utility analyses are frequently conducted to compare treatments for hepatitis C, which are often associated with complex regimens and serious adverse events. Thus, the purpose of this study was to estimate the utility associated with treatment administration and adverse events of hepatitis C treatments. DESIGN: Health states were drafted based on literature review and clinician interviews. General population participants in the UK valued the health states in time trade-off (TTO) interviews with 10- and 1-year time horizons. The 14 health states described hepatitis C with variations in treatment regimen and adverse events. RESULTS: A total of 182 participants completed interviews (50 % female; mean age = 39.3 years). Utilities for health states describing treatment regimens without injections ranged from 0.80 (1 tablet) to 0.79 (7 tablets). Utilities for health states describing oral plus injectable regimens were 0.77 (7 tablets), 0.75 (12 tablets), and 0.71 (18 tablets). Addition of a weekly injection had a disutility of −0.02. A requirement to take medication with fatty food had a disutility of −0.04. Adverse events were associated with substantial disutilities: mild anemia, −0.12; severe anemia, −0.32; flu-like symptoms, −0.21; mild rash, −0.13; severe rash, −0.48; depression, −0.47. One-year TTO scores were similar to these 10-year values. CONCLUSIONS: Adverse events and greater treatment regimen complexity were associated with lower utility scores, suggesting a perceived decrease in quality of life beyond the impact of hepatitis C. The resulting utilities may be used in models estimating and comparing the value of treatments for hepatitis C. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10198-014-0649-6) contains supplementary material, which is available to authorized users

Fibroset™ and neuromuscular pain: a multicentric, real world, observational, post-marketing surveillance study in Indian patients suffering from neuromuscular pain

Background: Neuromuscular disease (NMD) is a condition due to abnormality or damage to muscles and nerves causing painful symptoms. Symptomatic management involves use of conventional painkillers, but desirable relief is not achieved due to multimodal pathophysiology of disease. This study evaluated the efficacy and safety of Fibroset™ tablets in subjects with neuromuscular pain. Methods: Subjects with neuromuscular pain, previously unsatisfied with standard therapies, were enrolled. Subjects were advised to take Fibroset™ one tablet BID for 2 weeks with their standard therapy. Efficacy was evaluated on pain, stiffness, swelling, weakness, tenderness, and difficulty in activity of daily living (ADL) as per the visit schedule. Tolerability of therapy was also evaluated. Results: 59 patients were enrolled in study and 46 patients were included in the final analysis. Fibroset™ supplementation significantly reduced all evaluated parameters (p<0.05 vs baseline). The mean pain score from 2.50 to 0.89, while mean stiffness score was reduced to 0.55 from 1.87 at end of study. The mean swelling score was reduced to 0.81 from 2.04, while the mean weakness score was reduced to 0.64 from baseline score of 1.79. The mean tenderness score was reduced from baseline score of 1.90 to 0.65 and the mean ADL score was reduced to 0.63 from baseline score of 2.00. No treatment related side effects were observed. Conclusions: Fibroset™ is a potentially effective and safe therapy for subjects with neuromuscular pain. It can be used to reduce symptoms in patients with unsatisfactory results with conventionally standard care therapy

Optimization and deployment of CNNs at the Edge: The ALOHA experience

Deep learning (DL) algorithms have already proved their effectiveness on a wide variety of application domains, including speech recognition, natural language processing, and image classification. To foster their pervasive adoption in applications where low latency, privacy issues and data bandwidth are paramount, the current trend is to perform inference tasks at the edge. This requires deployment of DL algorithms on low-energy and resource-constrained computing nodes, often heterogenous and parallel, that are usually more complex to program and to manage without adequate support and experience. In this paper, we present ALOHA, an integrated tool flow that tries to facilitate the design of DL applications and their porting on embedded heterogenous architectures. The proposed tool flow aims at automating different design steps and reducing development costs. ALOHA considers hardware-related variables and security, power efficiency, and adaptivity aspects during the whole development process, from pre-training hyperparameter optimization and algorithm configuration to deployment

Reduced graphene oxide for the development of wearable mechanical energy-harvesters: A review

The unique characteristics of graphene have generated a lot of interest in the research community. A concept of utilizing graphene and its derivatives in the development of energy harvesters has just appeared in recent decades. This paper focuses on the application of reduced graphene oxide (rGO), a graphene derivative, in the development of wearable mechanical energy-harvesters to enable self-powered wearable sensing systems. Harvesting of energy has been a state-of-the-art phenomenon due to the ever-increasing requirement of power to run the sensing systems. Flexible systems that used rGO to gather energy with intensities ranging from a few microwatts to a few hundreds of microwatts have been used. Some examples are presented, focusing on the class of piezoelectric and triboelectric-based energy harvesters, with descriptions of their material composition, manufacturing methods, operating principle, and performance. Finally, the challenges and drawbacks of rGO-based energy harvesters are discussed, along with some of the potential solutions