EVOKE: A Value-Driven Concept Selection Method for Early System Design

The development of new technologically advanced products requires the contribution from a range of skills and disciplines, which are often difficult to find within a single company or organization. Requirements establishment practices in Systems Engineering (SE), while ensuring coordination of activities and tasks across the supply network, fall short when it comes to facilitate knowledge sharing and negotiation during early system design. Empirical observations show that when system-level requirements are not available or not mature enough, engineers dealing with the development of long lead-time sub-systems tend to target local optima, rather than opening up the design space. This phenomenon causes design teams to generate solutions that do not embody the best possible configuration for the overall system. The aim of this paper is to show how methodologies for value-driven design may address this issue, facilitating early stage design iterations and the resolution of early stage design trade-offs. The paper describes how such methodologies may help gathering and dispatching relevant knowledge about the ‘design intent’ of a system to the cross-functional engineering teams, so to facilitate a more concurrent process for requirement elicitation in SE. The paper also describes EVOKE (Early Value Oriented design exploration with KnowledgE maturity), a concept selection method that allows benchmarking design options at sub-system level on the base of value-related information communicated by the system integrators. The use of EVOKE is exemplified in an industrial case study related to the design of an aero-engine component. EVOKE’s ability to raise awareness on the value contribution of early stage design concepts in the SE process has been further verified with industrial practitioners in ad-hoc design episodes.     

Technoscientific approaches to deep time

In this paper, I argue that in order to understand the process behind the knowledge production in the historical sciences, we should change our theoretical focus slightly to consider the historical sciences as technoscientific disciplines. If we investigate the intertwinement of technology and theory, we can provide new insights into historical scientific knowledge production, preconditions, and aims. I will provide evidence for my claim by showing the central features of paleontological and paleobiological data practices of the nineteenth and twentieth centuries. In order to work with something that is imperfect and incomplete (the fossil record), paleontologists used different technological devices. These devices process, extract, correct, simulate, and eventually present paleontological explananda. Therefore, the appearance of anatomical features of non-manipulable fossilized organisms, phenomena such as mass-extinctions, or the life-like display of extinct specimens in a museum's hall, depend both on the correct use of technological devices and on the interplay between these devices and theories. Consequently, in order to capture its underlying epistemology, historical sciences should be analyzed and investigated against other technoscientific disciplines such as chemistry, synthetic biology, and nanotechnology, and not necessarily only against classical experimental sciences. This approach will help us understand how historical scientists can obtain their epistemic access to deep time.     

Overreaction in Survey Exchange Rate Forecasts

We use survey data on five bilateral exchange rates to provide empirical evidence of the fact that professional forecasters of foreign exchange rates behave irrationally, in the specific sense that they respond inaccurately to available information in the market when forming their predictions. In particular, we find systematic biases in the forecasts resulting in the overreaction of analysts to past information contained in the exchange rate dynamics: forecasters change their prediction more than it would be rational on the basis of past realized changes. In addition, forecasters are heterogeneous in their irrationality: low performers in previous periods show a more pronounced overreaction effect. This can be read as an indication of perpetration of past errors and continued inability to learn from the past. In the second part of the paper, we exploit the novel structure of our dataset, which consists of survey data extracted from the Bloomberg platform and readily available to anyone. This feature allows us to consider their own and others' past forecasts as part of the information set that analysts use in making their predictions. By using past forecasts as proxies for relevant macroeconomic variables, we find evidence that analysts fail to correctly process not only the information contained in the spot rate past dynamics but also the information in this broader set. We see this as confirmation of the existence of inefficiency and heterogeneity between low and high performers also when full information is available. Copyright © 2014 John Wiley & Sons, Ltd.     

Control of cerebral size and thickness

The mammalian neocortex is a sheet of cells covering the cerebrum that provides the structural basis for the perception of sensory inputs, motor output responses, cognitive function, and mental capacity of primates. Recent discoveries promote the concept that increased cortical surface size and thickness in phylogenetically advanced species is a result of an increased generation of neurons, a process that underlies higher cognitive and intellectual performance in higher primates and humans. Here, we review some of the advances in the field, focusing on the diversity of neocortical progenitors in different species and the cellular mechanisms of neurogenesis. We discuss recent views on intrinsic and extrinsic molecular determinants, including the role of epigenetic chromatin modifiers and microRNA, in the control of neuronal output in developing cortex and in the establishment of normal cortical architecture.     

Ultrastructural localization of 5-methylcytosine on DNA and RNA

DNA methylation is the major epigenetic modification and it is involved in the negative regulation of gene expression. Its alteration can lead to neoplastic transformation. Several biomolecular approaches are nowadays used to study this modification on DNA, but also on RNA molecules, which are known to play a role in different biological processes. RNA methylation is one of the most common RNA modifications and 5-methylcytosine presence has recently been suggested in mRNA. However, an analysis of nucleic acid methylation at electron microscope is still lacking. Therefore, we visualized DNA methylation status and RNA methylation sites in the interphase nucleus of HeLa cells and rat hepatocytes by ultrastructural immunocytochemistry and cytochemical staining. This approach represents an efficient alternative to study nucleic acid methylation. In particular, this ultrastructural method makes the visualization of this epigenetic modification on a single RNA molecule possible, thus overcoming the technical limitations for a (pre-)mRNA methylation analysis.     

The unconventional secretion of stress-inducible protein 1 by a heterogeneous population of extracellular vesicles

The co-chaperone stress-inducible protein 1 (STI1) is released by astrocytes, and has important neurotrophic properties upon binding to prion protein (PrP^C). However, STI1 lacks a signal peptide and pharmacological approaches pointed that it does not follow a classical secretion mechanism. Ultracentrifugation, size exclusion chromatography, electron microscopy, vesicle labeling, and particle tracking analysis were used to identify three major types of extracellular vesicles (EVs) released from astrocytes with sizes ranging from 20–50, 100–200, and 300–400 nm. These EVs carry STI1 and present many exosomal markers, even though only a subpopulation had the typical exosomal morphology. The only protein, from those evaluated here, present exclusively in vesicles that have exosomal morphology was PrP^C. STI1 partially co-localized with Rab5 and Rab7 in endosomal compartments, and a dominant-negative for vacuolar protein sorting 4A (VPS4A), required for formation of multivesicular bodies (MVBs), impaired EV and STI1 release. Flow cytometry and PK digestion demonstrated that STI1 localized to the outer leaflet of EVs, and its association with EVs greatly increased STI1 activity upon PrP^C-dependent neuronal signaling. These results indicate that astrocytes secrete a diverse population of EVs derived from MVBs that contain STI1 and suggest that the interaction between EVs and neuronal surface components enhances STI1–PrP^C signaling.     

Do we need pharmacogenetics to personalize antidepressant therapy?

This review examines the role of drug metabolism and drug target polymorphism in determining the clinical response to antidepressants. Even though antidepressants are the most effective available treatment for depressive disorders, there is still substantial need for improvement due to the slow onset of appreciable clinical improvement and the association with side effects. Moreover, a substantial group of patients receiving antidepressant therapy does not achieve remission or fails to respond entirely. Even if the large variation in antidepressant treatment outcome across individuals remains poorly understood, one possible source of this variation in treatment outcome are genetic differences. The review focuses on a few polymorphisms which have been extensively studied, while reporting a more comprehensive reference to the existing literature in table format. It is relatively easy to predict the effect of polymorphisms in drug metabolizing enzymes, such as cytochromes P450 2D6 (CYP2D6) and cytochrome P450 2C19 (CYP2C19), which may be determined in the clinical context in order to explain or prevent serious adverse effects. The role of target polymorphism, however, is much more difficult to establish and may be more relevant for disease susceptibility and presentation rather than for response to therapy.     

Hormonal control of Sertoli cell metabolism regulates spermatogenesis

Hormonal regulation is essential to spermatogenesis. Sertoli cells (SCs) have functions that reach far beyond the physical support of germ cells, as they are responsible for creating the adequate ionic and metabolic environment for germ cell development. Thus, much attention has been given to the metabolic functioning of SCs. During spermatogenesis, germ cells are provided with suitable metabolic substrates, in a set of events mediated by SCs. Multiple signaling cascades regulate SC function and several of these signaling pathways are hormone-dependent and cell-specific. Within the seminiferous tubules, only SCs possess receptors for some hormones rendering them major targets for the hormonal signaling that regulates spermatogenesis. Although the mechanisms by which SCs fulfill their own and germ cells metabolic needs are mostly studied in vitro, SC metabolism is unquestionably a regulation point for germ cell development and the hormonal control of these processes is required for a normal spermatogenesis.     

CDMA系统及其降噪的实验方法：系统设计到硬件测试所通过的超大规模集成电路

本书介绍了意大利比萨大学一个团队的开发项目——CDMA移动终端接受器．以及从中获取的经验，为通信理论到VLSI实现建立了一座桥梁，呈现了从最初系统设计到最终硬件测试所需要的电信和电子相关知识，主要目的是为通信电路的设计提供理论和实践上的支持。书中介绍的知识和技术可以运用到更一般的无线调制解调器的构架设计和实现。     

Model uncertainty,thick modelling and the predictability of stock returns

Recent financial research has provided evidence on the predictability of asset returns. In this paper we consider the results contained in Pesaran and Timmerman (1995), which provided evidence on predictability of excess returns in the US stock market over the sample 1959–1992. We show that the extension of the sample to the nineties weakens considerably the statistical and economic significance of the predictability of stock returns based on earlier data. We propose an extension of their framework, based on the explicit consideration of model uncertainty under rich parameterizations for the predictive models. We propose a novel methodology to deal with model uncertainty based on ‘thick’ modelling, i.e. on considering a multiplicity of predictive models rather than a single predictive model. We show that portfolio allocations based on a thick modelling strategy systematically outperform thin modelling. Copyright © 2005 John Wiley & Sons, Ltd.