Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic Growth, 2nd Edition

This graduate level text on economic growth surveys neoclassical and more recent growth theories, stressing their empirical implications and the relation of theory to data and evidence. The authors have undertaken a major revision for the long-awaited second edition of this widely used text, the first modern textbook devoted to growth theory. The book has been expanded in many areas and incorporates the latest research. After an introductory discussion of economic growth, the book examines neoclassical growth theories, from Solow-Swan in the 1950s and Cass-Koopmans in the 1960s to more recent refinements; this is followed by a discussion of extensions to the model, with expanded treatment in this edition of heterogenity of households. The book then turns to endogenous growth theory, discussing, among other topics, models of endogenous technological progress (with an expanded discussion in this edition of the role of outside competition in the growth process), technological diffusion, and an endogenous determination of labor supply and population. The authors then explain the essentials of growth accounting and apply this framework to endogenous growth models. The final chapters cover empirical analysis of regions and empirical evidence on economic growth for a broad panel of countries from 1960 to 2000. The updated treatment of cross-country growth regressions for this edition uses the new Summers-Heston data set on world income distribution compiled through 2000.
Mating Competition and Entrepreneurship: Evidence from a Natural Experiment in Taiwan

We use a natural experiment in Taiwan to test whether mating competition is a major motive for entrepreneurship. With the defeat of the Kuomintang Party in China, more than one million soldiers and civilians, mainly young males, retreated to Taiwan in the late 1940s. Initially, the soldiers were not allowed to marry. The ban was relaxed in 1959, however, suddenly flooding the marriage market with a large number of eligible bachelors. Using data from multiple sources, we find that during times of high marriage competition, young men are more likely to become entrepreneurs.
Exogenous Superoxide Dismutase: Action on Liver Oxidative Stress in Animals with Streptozotocin-Induced Diabetes

Aim. To investigate the effects of exogenous antioxidant copper zinc superoxide dismutase (Cu/Zn SOD) on oxidative stress in the experimental model of diabetes mellitus (DM). Methods. Twenty eight male Wistar rats divided in four groups were used: control (CO), controls treated with SOD (CO + SOD), diabetics (DM), and diabetics treated with SOD (DM + SOD). SOD (orgotein, 13 mg/Kg body weight was administered. DM was induced by a single streptozotocin injection (i.p., 70 mg/kg), and 60 days later, we evaluated liver oxidative stress. Results. Liver lipoperoxidation was increased in the DM group and significantly decreased in the DM + SOD group. Nitrite and nitrate measures were reduced in the DM and increased in the DM + SOD group, while iNOS expression in the DM group was 32% greater than in the CO and 53% greater in the DM + SOD group than in the DM group (P < .01). P65 expression was 37% higher in the DM (P < .05), and there was no significant difference between the DM and DM + SOD groups. Conclusion. SOD treatment reduced liver oxidative stress in diabetic animals, even though it did not change NFκB. SOD also increased NO, probably by the increased dismutation of the superoxide radical. The iNOS expression increase, which became even more evident after SOD administration.
Toxicity of TiO2 Nanoparticles to Escherichia coli: Effects of Particle Size, Crystal Phase and Water Chemistry

Controversial and inconsistent results on the eco-toxicity of TiO2 nanoparticles (NPs) are commonly found in recorded studies and more experimental works are therefore warranted to elucidate the nanotoxicity and its underlying precise mechanisms. Toxicities of five types of TiO2 NPs with different particle sizes (10∼50 nm) and crystal phases were investigated using Escherichia coli as a test organism. The effect of water chemistry on the nanotoxicity was also examined. The antibacterial effects of TiO2 NPs as revealed by dose-effect experiments decreased with increasing particle size and rutile content of the TiO2 NPs. More bacteria could survive at higher solution pH (5.0–10.0) and ionic strength (50–200 mg L−1 NaCl) as affected by the anatase TiO2 NPs. The TiO2 NPs with anatase crystal structure and smaller particle size produced higher content of intracellular reactive oxygen species and malondialdehyde, in line with their greater antibacterial effect. Transmission electron microscopic observations showed the concentration buildup of the anatase TiO2 NPs especially those with smaller particle sizes on the cell surfaces, leading to membrane damage and internalization. These research results will shed new light on the understanding of ecological effects of TiO2 NPs.
An AggreGATE Network Abstraction for Mobile Devices

Mobile devices, as a norm, are equipped with multiple network interfaces, viz. cellular, Wi-Fi and bluetooth, with Wi-Max networks on the horizon. These network interfaces have diverse as well as dynamic characteristics in terms of range, bandwidth and power [3]. Our measurement data of connectivity characteristics of WiFi and cellular networks, along with other recently reported research [1, 4] lead us to make the following observations: (1) There is an interesting fraction of times when the throughputs of these interfaces are comparable and aggregating them would achieve a sizeable speed-up as well as significant increase in absolute throughput, (2) Wi-Fi coverage is spotty and applications would benefit from seamless shifting between Wi-Fi and the more ubiquitous cellular connectivity, and (3) EDGE and even 3G speeds are likely to be insufficient for many applications. Regular contact-patterns among devices [3] can be leveraged for collaborative bandwidth aggregation. To this end, we design a system, AggreGATE, that enables mobile devices to seamlessly and simultaneously use their multiple connectivity options. We present some oft-occuring scenarios to motivate the potential benefits of AggreGATE.
What promotional and textual discourses are constructed over the production lifecycle of ‘The L Word’ and how do audiences respond to producer decisions within such discursive constructions?

The following research is concerned with an exploration of the discourses constructed about lesbian culture both within and surrounding the production and lifecycle of The L Word. The originality of the approach to and development of this thesis is anchored in a consideration of the show as a symbolic good (Garnham, 1999) which encapsulates not only the meanings inherent in the television text, as often focused upon in traditional Television Studies perspectives, but also producer focused branding and creative justification through promotional materials, and audiences sense making. This means that the thesis is the result of the intersection of a number of theoretical approaches to the study of television production as industrial practice, television as meaningful text, and also to audiences as readers. This thesis outlines that The L Word’s textual elements, promotional branding, and the audience response to this wide consideration of the television text altered significantly over six seasons. During this time the priorities of the producer altered from a focus on political representation and a communal sense of lesbian identity, to maintaining narratives and that would ensure appeal to a mainstream audience. This change in focus led to the fragmenting of lesbian subjectivities and formed an ideologically hegemonic lesbian culture within the text. This was further asserted through the othering of lesbian characters considered overtly sexualised, alongside identities of gender and sexuality that blurred the queer boundaries. The developing decoding and reactions of the lesbian audience further support the development of these hierarchies of discourse. Within this thesis it is also argued that the pleasures of the lesbian audience became problematic and their readings had to become increasingly negotiated for them to find enjoyment in the narratives and outcomes of The L Word.
Variation in Effects of Conophthorin on Catches of Ambrosia Beetles (Coleoptera: Curculionidae: Scolytinae) in Ethanol-Baited Traps in the United States

ABSTRACT In 2013, we examined the effects of conophthorin on flight responses of ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) to multiple-funnel traps baited with ethanol in Georgia, Michigan, New Hampshire, and Oregon. Adventive species (=exotic, nonnative, immigrant, introduced) accounted for 91.4% of total catches of ambrosia beetles. Conophthorin increased catches of Xyleborinus saxesenii (Ratzeburg) in Georgia, New Hampshire, and Oregon. Catches of Cyclorhipidion pelliculosum (Eichhoff) were increased by conophthorin in New Hampshire but not in Michigan. In Oregon, conophthorin decreased catches of Xylosandrus germanus (Blandford) to ethanol-baited traps but not in Michigan and New Hampshire. In Georgia, conophthorin increased catches of Gnathotrichus materiarius (Fitch), Xyleborus spp. , and Xylosandrus crassiusculus (Motschulsky) but decreased catches of Cnestus mutilatus (Blandford), Dryoxylon onoharaensum (Murayama), and Cyclorhipidion bodoanum (Reitter). Conophthorin had no effect on catches of Ambrosiophilus atratus (Eichhoff), Anisandrus dispar (F.), Anisandrus sayi (Hopkins), Gnathotrichus sulcatus (Leconte), Monarthrum fasciatum (Say), Monarthrurm mali (Fitch), and Xylosandrus compactus (Eichhoff). Attraction of the bark beetle, Hypothenemus rotundicollis (Eichhoff), was interrupted by conophthorin in Georgia. Our results suggest that adding conophthorin lures to traps baited with ethanol may have utility in detection programs in North America and overseas. However, traps baited with ethanol alone should also be used due to interruption in attraction for some species of ambrosia beetles.
Differential determinants of men's and women's everyday physical activity in later life.

OBJECTIVES The present study of a representative sample of older adults quantified everyday physical activity (EPA) by having participants wear actigraphs. Our objectives were to examine whether poor health may partly explain why older adults become less physically active with advancing age and whether gender might moderate the extent to which health status predicts EPA. METHODS We performed multiple regression analyses on a sample of older, community-dwelling adults (aged 80-98 years, N = 198; women = 63.1%). RESULTS The results imply that age-related declines in EPA may be partially accounted for by health (in men) and by living arrangements (in women). DISCUSSION We consider reasons why poorer health might erode EPA for men (but not women) and why living alone might erode EPA for women (but not men).
Eigenvalues perturbation of integral operator for kernel selection

Kernel selection is one of the key issues both in recent research and application of kernel methods. This is usually done by minimizing either an estimate of generalization error or some other related performance measure. It is well known that a kernel matrix can be interpreted as an empirical version of a continuous integral operator, and its eigenvalues converge to the eigenvalues of integral operator. In this paper, we introduce new kernel selection criteria based on the eigenvalues perturbation of the integral operator. This perturbation quantifies the difference between the eigenvalues of the kernel matrix and those of the integral operator. We establish the connection between eigenvalues perturbation and generalization error. By minimizing the derived generalization error bounds, we propose the kernel selection criteria. Therefore the kernel chosen by our proposed criteria can guarantee good generalization performance. To compute the values of our criteria, we present a method to obtain the eigenvalues of integral operator via the Fourier transform. Experiments on benchmark datasets demonstrate that our kernel selection criteria are sound and effective.
A Novel Crowding Genetic Algorithm and Its Applications to Manufacturing Robots

A niche genetic algorithm (GA) based on a novel twin-space crowding (TC) approach is proposed for solving multimodal manufacturing optimization problems. The proposed TC method is designed in a parameter-free paradigm. That is, when cooperatively exploring solutions with GAs, it does not require prior knowledge related to the solution space to design additional problem-dependent parameters in the evolutionary process. This feature makes the proposed TC method suitable for assisting GAs in solving real-world engineering optimization problems involving intractable solution landscapes. A set of numerical benchmark functions is used to compare effectiveness and efficiency in the proposed TCGA, in different niche GAs, and in several evolutionary computation methods. The TCGA is then used to solve multimodal joint-space inverse problems in serial-link robots to compare its convergence performance with that of conventional methods that apply the sharing function. Finally, the TCGA is used to solve iterative collision-free design problems for linkage-bar robotic hands to demonstrate its effectiveness for generating diverse solutions during the design process.
Population III.1 stars: formation, feedback and evolution of the IMF

Abstract I discuss current theoretical expectations of how primordial, Pop III.1 stars form. Lack of direct observational constraints makes this a challenging task. In particular predicting the mass of these stars requires solving a series of problems, which all affect, perhaps drastically, the final outcome. While there is general agreement on the initial conditions, H2-cooled gas at the center of dark matter minihalos, the subsequent evolution is more uncertain. In particular, I describe the potential effects of dark matter annihilation heating, fragmentation within the minihalo, magnetic field amplification, and protostellar ionizing feedback. After these considerations, one expects that the first stars are massive ≳100M⊙, with dark matter annihilation heating having the potential to raise this scale by large factors. Higher accretion rates in later-forming minihalos may cause the Pop III.1 initial mass function to evolve to higher masses.
Ozone Impacts of Natural Gas Development in the Haynesville Shale

S U S A N K E M B A L L C O O K , * , † A M N O N B A R I L A N , † J O H N G R A N T , † L Y N S E Y P A R K E R , † J A E G U N J U N G , † W I L S O N S A N T A M A R I A , † J I M M A T H E W S , ‡ A N D G R E G Y A R W O O D † ENVIRON International Corporation, 773 San Marin Drive, Novato, California 94998, United States, and Mathews and Freeland, LLP, 327 Congress Avenue, Suite 300, Austin, Texas 78767, United States
In silico phenotyping via co-training for improved phenotype prediction from genotype

Motivation: Predicting disease phenotypes from genotypes is a key challenge in medical applications in the postgenomic era. Large training datasets of patients that have been both genotyped and phenotyped are the key requisite when aiming for high prediction accuracy. With current genotyping projects producing genetic data for hundreds of thousands of patients, large-scale phenotyping has become the bottleneck in disease phenotype prediction. Results: Here we present an approach for imputing missing disease phenotypes given the genotype of a patient. Our approach is based on co-training, which predicts the phenotype of unlabeled patients based on a second class of information, e.g. clinical health record information. Augmenting training datasets by this type of in silico phenotyping can lead to significant improvements in prediction accuracy. We demonstrate this on a dataset of patients with two diagnostic types of migraine, termed migraine with aura and migraine without aura, from the International Headache Genetics Consortium. Conclusions: Imputing missing disease phenotypes for patients via co-training leads to larger training datasets and improved prediction accuracy in phenotype prediction. Availability and implementation: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/co-training.html Contact: karsten.borgwardt@bsse.ethz.ch or menno.witteveen@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online.
Order-independent constraint-based causal structure learning

We consider constraint-based methods for causal structure learning, such as the PC-, FCI-, RFCI- and CCD- algorithms (Spirtes et al., 1993, 2000; Richardson, 1996; Colombo et al., 2012; Claassen et al., 2013). The first step of all these algorithms consists of the adjacency search of the PC-algorithm. The PC-algorithm is known to be order-dependent, in the sense that the output can depend on the order in which the variables are given. This order-dependence is a minor issue in low-dimensional settings. We show, however, that it can be very pronounced in high-dimensional settings, where it can lead to highly variable results. We propose several modifications of the PC-algorithm (and hence also of the other algorithms) that remove part or all of this order-dependence. All proposed modifications are consistent in high-dimensional settings under the same conditions as their original counterparts. We compare the PC-, FCI-, and RFCI-algorithms and their modifications in simulation studies and on a yeast gene expression data set. We show that our modifications yield similar performance in low-dimensional settings and improved performance in high-dimensional settings. All software is implemented in the R-package pcalg.
On Maximizing Resource Utilization for Simultaneous Multi-Threading ( SMT ) Processors by Instruction Recalling ∗

Simultaneous multi-threading (SMT) has been a very popular design in improving resource utilization by sharing key datapath components among multiple independent threads. When critical resources are shared by multiple threads, to effective use of these resources proves to be the most important factor in fully exploiting the system potential. Allowing any of the threads to overwhelm these shared resources not only leads to unfair thread processing but may also result in severely degraded overall performance. How to prevent idling threads from clogging the critical resources in the pipeline becomes a must in sustaining system performance. In this paper, we show that, if one can manage to recall instructions of idling threads from Issue Queue (IQ), a very important shared resource in the SMT pipeline, the system performance is easily enhanced by a significant margin. An even more noteworthy feature about this technique is that the ensuing hardware overhead is very insignificant and its effect in clock timing also is negligible. The feature proposed in this paper can also be easily coupled with other advanced techniques employed in other stages of the SMT pipeline.
Structural bootstrapping at the sensorimotor level for the fast acquisition of action knowledge for cognitive robots

Autonomous robots are faced with the problem of encoding complex actions (e.g. complete manipulations) in a generic and generalizable way. Recently we had introduced the Semantic Event Chains (SECs) as a new representation which can be directly computed from a stream of 3D images and is based on changes in the relationships between objects involved in a manipulation. Here we show that the SEC framework can be extended (called “extended SEC”) with action-related information and used to achieve and encode two important cognitive properties relevant for advanced autonomous robots: The extended SEC enables us to determine whether an action representation (1) needs to be newly created and stored in its entirety in the robot's memory or (2) whether one of the already known and memorized action representations just needs to be refined. In human cognition these two processes (1 and 2) are known as accommodation and assimilation. Thus, here we show that the extended SEC representation can be used to realize these processes originally defined by Piaget for the first time in a robotic application. This is of fundamental importance for any cognitive agent as it allows categorizing observed actions in new versus known ones, storing only the relevant aspects.
p66ShcA modulates oxidative stress and survival of endothelial progenitor cells in response to high glucose.

AIMS A close relationship exists between hyperglycaemia, oxidative stress, and diabetic complications. In fact, high glucose (HG) determines the overproduction of reactive oxygen species (ROS) by the mitochondria. p66ShcA is a gene that regulates the apoptotic responses to oxidative stress. Indeed, p66ShcA knockout (ko) mice display decreased ROS production and increased resistance to ROS-induced cell death in a variety of pathophysiological settings. Reduced endothelial progenitor cell (EPC) number, differentiation, and function are relevant components of the angiogenesis impairment observed in diabetic patients. We examined the role of p66ShcA in the EPC deficit induced by HG. METHODS AND RESULTS Mouse bone marrow-derived c-kit+ cells differentiate in endothelial-like cells when plated on fibronectin (BM-derived EPCs). We found that cell culture in the presence of HG up-regulated p66ShcA protein expression and that HG exposure markedly decreased the number of BM-derived EPCs. Conversely, p66ShcA ko BM-derived EPCs were not sensitive to HG inhibition. Indeed, the resistance of p66ShcA ko BM-derived EPCs to HG was associated with reduced levels of both apoptosis and oxidative stress. To functionally link the HG response to ROS production, p66ShcA ko BM-derived EPCs were reconstituted either with p66ShcA wild-type (wt) or with a p66ShcA allele (p66ShcA qq) that was devoid of its ROS-generating function. We found that only p66ShcA wt and not the qq mutant rescued p66ShcA ko cell sensitivity to HG. One major feature of oxidative stress is its ability to reduce the bio-availability of nitric oxide (NO) that, in turn, plays a crucial role in endothelial differentiation and function. We found that the p66ShcA deletion prevented the HG-induced increase of nitrotyrosine, and that the resistance to HG of p66ShcA ko BM-derived EPCs was prevented by NO synthase inhibition. With a reciprocal approach, the treatment of p66ShcA wt cells with a NO donor prevented the HG-induced deficit. Finally, using a Matrigel plug angiogenesis assay, we demonstrated that p66ShcA ko prevented diabetic impairment of angiogenesis in vivo. CONCLUSION p66ShcA deletion rescues the BM-derived EPCs defect induced by HG, indicating p66ShcA as a potential therapeutic target in diabetic vasculopathy.