As the number falls,alternatives to the Hagberg–Perten falling number method: A review

This review examines the application, limitations, and potential alternatives to the Hagberg–Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.     

Histone Methylation Marks on Circulating Nucleosomes as Novel Blood-Based Biomarker in Colorectal Cancer

Circulating nucleic acids (CNAs) are under investigation as a liquid biopsy in cancer as potential non-invasive biomarkers, as stable structure in circulation nucleosomes could be valuable sources for detection of cancer-specific alterations in histone modifications. Our interest is in histone methylation marks with a focus on colorectal cancer, one of the leading cancers respective the incidence and mortality. Our previous work included the analysis of trimethylations of lysine 9 on histone 3 (H3K9me3) and of lysine 20 on histone 4 (H4K20me3) by chromatin immuno- precipitation-related PCR in circulating nucleosomes. Here we asked whether global immunologic measurement of histone marks in circulation could be a suitable approach to show their potential as biomarkers. In addition to H3K9me3 and H4K20me3 we also measured H3K27me3 in plasma samples from CRC patients (n = 63) and cancer free individuals (n = 40) by ELISA-based methylation assays. Our results show that of three marks, the amounts of H3K27me3 (p = 0.04) and H4K20me3 (p < 0.001) were significantly lower in CRC patients than in healthy controls. For H3K9me3 similar amounts were measured in both groups. Areas under the curve (AUC) in receiver operating characteristic (ROC) curves indicating the power of CRC detection were 0.620 for H3K27me3, 0.715 for H4K20me3 and 0.769 for the combination of both markers. In conclusion, findings of this preliminary study reveal the potential of blood-based detection of CRC by quantification of histone methylation marks and the additive effect of the marker combination.     

Understanding value creation in closed loop supply chains – Past findings and future directions

The topic of value creation through the recovery of returned products in closed loop supply chains is scattered across various bodies of literature. We undertake a systematic literature review of 144 articles in relevant green, reverse and closed loop supply chain literature to synchronize existing knowledge on value creation. Value manifestations of four types of value, namely economic, environmental, information and customer value, are identified. Value adding concepts from the forward- and reverse supply chain may leverage the process of value creation. They are classified into six subclasses, namely partnerships and collaboration, product design characteristics, service concepts, IT solutions, supply chain processes and organizational characteristics. We present a conceptual framework on a strategic level. In this way companies can create competitive advantages by closing the loop. The results of the literature analysis suggest avenues for future research on the operational and strategic level.     

Small-scale CDM projects in a competitive electricity industry: How good is a simplified baseline methodology?

Setting baseline emissions is one of the principal tasks involved in awarding credits for greenhouse gas emission (GHG) mitigation projects under the Clean Development Mechanism (CDM). An emission baseline has to be project-specific in order to be accurate. However, project-specific baseline calculations are subject to high transaction costs, which disadvantage small-scale projects. For this reason, the CDM-Executive Board (CDM-EB) has approved simplified baseline methodologies for selected small-scale CDM project categories. While the simplified methods help reduce the transaction cost, they may also result in inaccuracies in the estimation of emission reductions from CDM projects. The purpose of this paper is to present a rigorous economic scheduling method for calculating the GHG emission reduction in a hypothetical competitive electricity industry due to the operation of a renewable energy-based power plant under CDM and compare the GHG emission reduction derived from the rigorous method with that obtained from the use of a simplified (i.e., standardized) method approved by the CDM-EB. A key finding of the paper is that depending upon the level of power demand, prices of electricity and input fuels, the simplified method can lead to either significant overestimation or substantial underestimation of emission reduction due to the operation of renewable energy-based power projects in a competitive electricity industry.     

A Dynamic Dictionary for Priced Information with Application

In this paper we design a dynamic dictionary for the priced information model initiated by Charikar et al. Assume that a set S consisting of n elements is given such that each element has an associated price, a positive real number. The cost of performing an operation on elements of S is a function of their prices. The cost of an algorithm is the sum of the costs of all operations it performs. The objective is to design algorithms which incur low cost. In this model we propose a dynamic dictionary, supporting search, insert and delete, for keys drawn from a linearly ordered set. As an application we show that the dictionary can be used in computing the trapezoidal map of a set of line segments, a fundamental problem in computational geometry.     

Analysis and visualisation with host-based software – The features of STNAnaVist™

This article is based on experiences with data and text mining to gain information for strategic business decisions, using host-based analysis and visualisation (A/V), primarily in the field of patents. The potential advantages of host-based A/V are pointed out and the features of the first such A/V software, STN^®AnaVist™, are described in detail. Areas covered include the user interfaces, initial set of documents for A/V, data mining, text mining, reporting, and suggestions for further development.     

NEURAL NETS SPEED FLOW CALCULATION

Neural Nets Successfully Solve Complex Fluid Flow Problem. Much research is being done in the area of neural networks, and industry is actively seeking successful application to real world problems. We describe here a successful application. We have used neural networks to model complex coolant flow patterns, such as those encountered in design of hypersonic aircraft. Previous calculation methods, while reasonably accurate, are iterative and extremely time consuming. Our new approach uses a hierarchical neural network architecture to model coolant flow distribution in multiple heat exchanger panels. This method is direct, fast, and accurate.     

Targets and methods for the detection of processed animal proteins in animal feedstuffs

Bovine spongiform encephalopathy (BSE), or ‘mad cow disease’, is one of several transmissable spongiform encephalopathies (TSEs) known to affect certain mammals and is spread through the ingestion of infected animal tissue. It is believed that the inadvertent contamination of meat and bone meal (MBM) with infected animal tissue and the subsequent use of this material as a feed supplement contributed to the spread of the disease in cattle. As a result, the use of processed animal proteins (PAPs) in animal feeds is regulated in many parts of the world. Although feed testing is the only definitive means to certify compliance, regulatory compliance often relies solely on paper certification. Recently, rapid methods have become available that can be used by regulators to determine compliance during routine inspections. We describe a rapid, immunochromatographic strip test that can detect 0.1% MBM in animal feed. The test takes 15 min to perform and large numbers of samples can be screened for PAPs simultaneously.     

人类HLA-DRB1基因型与民族和人群的神经网络无监督模式分类

HLA-DRB1等位基因主要参与人类的抗原免疫功能,对其进行比较研究,有助于追溯人类的进化迁移史,开发类群特异性药物.本研究以Matlab为平台,用自组织竞争网络(Self-Organizing Competitive Neural Network),对世界54个民族和人群、14个HLA-DRB1等位基因,进行了无监督模式分类.结果表明,各民族之间存在差异性,同民族的各人群之间有相似性.西伯利亚各人群,澳洲各土著人群,黑人各人群,南美印第安各人群,犹太族各人群,日本各人群,及欧美白人各人群有相对独立性:南美印第安人与西伯利亚人有高度相似性;中国民族在南方人群和北方人群间存在较大差异;中国汉族中,广东汉族地位特殊,与少数民族如拉祜族、瑶族关系密切.     

信息化时代企业情报工作与时俱进

针对信息化时代企业情报工作面临的新课题，结合本企业情况，从成为企业技术创新的加油站、成为职工素质提高的资源库、成为企业获取和分析竞争环境的侦察兵、成为企业信息安全的保护伞等方面论述了企业情报工作与时俱进等理念和方法。