How and when do markets tip? Lessons from the Battle of the Bund

In a famous episode of financial history which lasted over eight years, the market for the future on the Bund moved entirely from LIFFE, a London-based derivatives exchange, to DTB, a Frankfurt-based exchange. This paper studies the determinants of the observed dynamics, using a novel panel dataset that contains individual trading firms' membership status at each exchange together with other firms characteristics, and pricing, marketing and product portfolio strategies by each exchange. Our data allows us to distinguish between different explanations for the observed phenomenon. Our results indicate that the main driver was a "market coverage" effect: thanks to the combination its electronic market structure and EU-wide access deregulation, DTB increased the relevant size of the market for exchange members and disproportionately attracted those firms who originally did not exist or used to submit their orders through a broker. Differential liquidity and product portfolio strategies by the exchanges played a secondary role. JEL Classification: G21, G28, L13, L43adoption cost, Bund, electronic trading, Exchange competition, network effect, open outcry, tipping

Reallocating innovative resources around growth bottlenecks

Economy-wide increasing returns to scale embodied in a general purpose technology (GPT) and its applications are often a key source of long-run growth. Yet the successful exploitation of increasing returns calls for coordination on a particular technological direction, reducing flexibility and choice ex post and potentially creating a growth bottleneck. When the bottleneck is controlled by a single firm, the resulting entry barriers reduce the ability of demanders to choose superior, alternative technologies. We examine how such a growth bottleneck can eventually be overcome under certain key conditions. Demand must be fundamentally diverse so that the original GPT does not serve all demanders. Firms barred from entry into the primary GPT market can then reallocate innovative resources to create new markets to meet the unserved demand. The demand in these new markets must be valuable enough (even if not as valuable as in the primary GPT market) to generate a positive-feedback cycle that results in considerable technical advance in the alternative GPT. This ultimately can lead to indirect entry by the alternative GPT into the original GPT market if and when it becomes strong enough to compete with the original GPT. This sequence of (i) increasing returns to scale around a GPT, (ii) reallocation of innovative resources around growth bottlenecks, and (iii) indirect entry has growth implications. A large contribution to growth follows the exploitation of increasing returns to scale in the original GPT. Much later, another large contribution to growth follows when demand is finally met by an alternative, competitive GPT. Between these two periods falls a period of lesser contributions to growth due to the dominant firm bottleneck. The market-based resolution of the bottleneck is not merely a theoretical possibility. We illustrate the role of this sequence in the two most important technologies for automating white-collar work of the past 50 years

Topological Phononic Crystals with One-Way Elastic Edge Waves

We report a new type of phononic crystals with topologically nontrivial band gaps for both longitudinal and transverse polarizations, resulting in protected one-way elastic edge waves. In our design, gyroscopic inertial effects are used to break the time-reversal symmetry and realize the phononic analogue of the electronic quantum (anomalous) Hall effect. We investigate the response of both hexagonal and square gyroscopic lattices and observe bulk Chern numbers of 1 and 2, indicating that these structures support single and multimode edge elastic waves immune to backscattering. These robust one-way phononic waveguides could potentially lead to the design of a novel class of surface wave devices that are widely used in electronics, telecommunication, and acoustic imaging.National Science Foundation (U.S.) (Grant CMMI-1120724)National Science Foundation (U.S.) (Grant CMMI-1149456)National Institutes of Health (U.S.) (Grant DMR-1420570)United States. Army Research Office (Grant W911NF-13-D-0001)National Science Foundation (U.S.) (Grant DMR-1419807

Analyzing the Learning Modes of Learners using Time-Management Modules in Self-Paced Learning

Enhancing the effectiveness of e-learning is animportant topic today. Many factors influence the effectiveness oflearning, among which time management has the most directimpact on self-paced learning. This study developed a calendartime-management module to record the learning process in anself-paced learning environment. After analyzing the learningmodes, we extracted learners that displayed intensive learningtowards the end of a course period. We implemented two types oftime management modules on the extracted subjects: acountdown timer and a course schedule module, and thenanalyzed the influence of the time modules on the learners inself-paced learning. The objective was to promote diligence byhelping learners to begin learning earlier in the course period.Our results demonstrate that the incorporation of the countdowntimer and course schedule time-management modules altered thedistribution of study times and prompted all of the learners tocomplete the reading of course materials. The countdown timermodule presented a stronger correlation with the tendencies oftime management and the use of the time modules. This indicatesthat learners who are sensitive to changing numbers are morelikely to follow a set course. Overall, the time modules differed inthe degree of impact according to the characteristics of learners;however, the use of time modules was proven to enhance theeffectiveness of studying

Curve Data Classification via Functional Principal Component Analysis

[[abstract]]We propose a best predicted curve classification (BPCC) criterion for classifying the curve data. The data are viewed as realizations of a mixture of stochastic processes and each subprocess corresponds to a known class. Under the assumption that all the groups have different mean functions and eigenspaces, an observed curve is classified into the best predicted class by minimizing the distance between the observed and predicted curves via subspace projection among all classes based on the functional principal component analysis (FPCA) model. The BPCC approach accounts for both the means and the modes of variation differentials among classes while other classical functional classification methods consider the differences in mean functions only. Practical performance of the proposed method is demonstrated through simulation studies and a real data example of matrix assisted laser desorption (MALDI) mass spectrometry (MS) data. The proposed method is also compared with other multivariate and functional classification approaches. Overall, the BPCC method outperforms the others when the mean functions and the eigenspaces among classes are significantly distinct. For classifying the MALDI MS data, we found that functional classification methods perform better than multivariate data approaches, and the dimension reduction via FPCA is advantageous to improving the accuracy of classification.[[journaltype]]國內[[ispeerreviewed]]Y[[booktype]]紙本[[booktype]]電子版[[countrycodes]]TW

Roles of Mafb and c-Maf in MGE-derived cortical interneuron development and maturation

An imbalance of excitation and inhibition in key neural circuits is hypothesized to underlie some epileptic disorders and neuropsychiatric diseases, such as schizophrenia and autism spectrum disorder (ASD) (Lim et al., 2018a; Rubenstein and Merzenich, 2003; Sohal and Rubenstein, 2019; Yizhar et al., 2011) . Inhibition in the cortex is primarily generated by cortical interneurons (CINs). CINs are produced by the medial and caudal ganglionic eminences (MGE and CGE). 70% of CINs are MGE-derived and primarily express Parvalbumin (PV+) or Somatostastin (SST+). CINs become postmitotic in the MGE, then tangentially migrate to the cortex, where they mature and integrate into local cortical circuits (Lim et al., 2018a). Great gaps remain in our understanding of the cellular and molecular mechanisms regulating CIN generation, migration and maturation. My thesis work is to focus on elucidating the function of Mafb and c-Maf in MGE-lineage CIN development and maturation. Using conditional Maf knockout animal models together with immunohistochemistry, in vitro primary neuronal culture, in vivo MGE transplantation assay, electrophysiology and single-cell RNA-sequencing techniques, we profiled the expression pattern of Mafb and c-Maf (Chapter 2), and identified that Mafb and c-Maf function together prenatally in the MGE to control SST+ CIN neurogenesis (Chapter 3), while postnatally they function antagonistically in the CINs to control CIN synaptogenesis, morphogenesis and firing properties (Chapter 4). On-going pursuit is to try to figure out the molecular mechanism that is downstream of Mafb and c-Maf to lead to the phenotypes we have observed in the conditional mutants (Chapter 6)

Morphology and mechanical properties of electrospun polymeric fibers and their nonwoven fabrics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2011.Cataloged from student submitted PDF version of thesis.Includes bibliographical references.Electrospinning is a straight forward method to produce fibers with diameter on the order of a few tens of nanometers to the size approaching commercial fibers (on the order of 10 prm or larger). Recently, the length scale effect on physical properties has attracted great attention because of the potential to produce new materials with unique behavior. In general, the behavior of commercial fibers can be investigated by traditional experiments, and that of nanofibers can be studied by molecular dynamics simulation or Monte Carlo technique. However, the transition of their properties from the bulk to the nanoscale materials is not well understood. Electrospinning provides us a bridge to understand the properties of fibers transiting from the behavior of the bulk material to that of the nanofibers. Among these areas, I am interested in the possible remarkable changes in mechanical properties that may occur in electrospun fibers due to the size effect, where the comprehensive understanding is still lacking. My research objectives are to understand mechanical properties of electrospun polymeric fibers as a function of their size, structure and morphology. The first part of my research is to study internal structures and external topographies of electrospun fibers, and to understand their effect on mechanical properties. Amorphous polystyrene (PS) and semicrystalline polyacrylonitrile (PAN) were dissolved in a high boiling point solvent, dimethylformamide (DMF), for electrospinning. When electrospun in a high-humidity environment, the interior of these fibers was found to be highly porous rather than consolidated, despite the smooth and nonporous appearance of the fiber surfaces. The formation of interior porosity is attributed to the miscibility of water, a nonsolvent for the polymers in solution, with DMF. The resulting morphology is a consequence of the relatively rapid diffusion of water into the jet, leading to a liquid-liquid phase separation that precedes solidification due to evaporation of DMF from the jet. When electrospun in a low humidity environment, the fibers exhibit a wrinkled morphology that can be explained by a buckling instability. Understanding which structures and morphology form under a given set of conditions is achieved through the comparison of three characteristic times: the drying time, the buckling time and the phase separation time. The structures and morphology have important consequences for the properties of the fibers such as their mechanical strength and stiffness.(cont.) Secondly, we studied the size effects of single electrospun fibers on their stiffness and strength. The Young's modulus and yield strength of individual electrospun fibers of amorphous poly(trimethyl hexamethylene terephthalamide) (PA 6(3)T) have been obtained in uniaxial extension. The Young's modulus is found to exhibit values in excess of the isotropic bulk value, and to increase with decreasing fiber diameter for fibers with diameter less than roughly 500 nm. The yield stress is also found to increase with decreasing fiber diameter. These trends are shown to correlate with increasing molecular level orientation within the fibers with decreasing fiber diameter. Using Ward's aggregate model, the correlation between molecular orientation and fiber modulus can be explained, and reasonable determinations of the elastic constants of the molecular unit are obtained. Finally, we identified a relation of stiffness between single electrospun fibers and their nonwoven fabrics. This is of interest because adequate mechanical integrity of nonwoven fabrics is generally a prerequisite for their practical usage. The Young's modulus of electrospun PA 6(3)T nonwoven fabrics were investigated as a function of the diameter of fibers that constitute the fabric. Two quantitative microstructure-based models that relate the Young's modulus of these fabrics to that of the fibers are considered, one assuming straight fibers and the other allowing for sinuous fibers. This study is particularly important for meshes comprising fibers because of our recent discovery of an enhanced size effect on their Young's modulus as well as the tendency towards a curved fiber topology between fiber junctions. The governing factors that affect the mechanical properties of nonwoven mats are the fiber network, fiber curvature, intrinsic fiber properties, and fiber-fiber junctions. Especially for small fibers, both the intrinsic fiber properties and fiber curvature dominate the mechanical behavior of their nonwoven fabrics. This thesis helps us to understand the mechanism behind the enhanced mechanical behavior of small fibers, and to identify determining parameters that can be used to tailor their mechanical performance.by Chia-Ling Pai.Ph.D

Evidence-Based Tuberculosis Diagnosis

Madhukar Pai and colleagues discuss how systematic reviews on tuberculosis diagnostics can influence research, policy, and clinical practice

On the importance of fiber curvature to the elastic moduli of electrospun nonwoven fiber meshes

Adequate mechanical integrity of nonwoven fabrics is generally a prerequisite for their practical usage. Nonwoven fiber mats of poly(trimethyl hexamethylene terephthalamide) (PA 6(3)T) with average fiber diameters from 0.1 to 3.6 microns were electrospun from solutions in dimethylformamide and formic acid and their in-plane mechanical response characterized. Two quantitative microstructure-based models that relate the Young’s moduli of these fabrics to those of the fibers are considered, one assuming straight fibers and the other allowing for curved fibers. It is found that the model allowing for curved fibers provides a quantitative relationship between the Young’s moduli of the mats and those of the fibers themselves. The governing factors that affect the mechanical properties of nonwoven mats are the porosity of the mats, the intrinsic fiber modulus, and the average fiber diameter, curvature (or “curl”) and distance between fiber-to-fiber junctions. Especially for submicron diameter fibers, both the intrinsic fiber properties and fiber curvature make important contributions to the mechanical behavior of their nonwoven fabrics.Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies (Contract ARO W911NF-07-D-0004