Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Cloud Formation behind Shock Waves

Motivated by our previous paper, in which we argued for the formation of molecular clouds from large-scale flows in the diffuse Galactic interstellar medium, we examine the formation of molecular gas behind shocks in atomic gas using a one-dimensional chemical/dynamical model. In our analysis we place particular emphasis on constraints placed on the dynamical evolution by the chemistry. The most important result of this study is to stress the importance of shielding the molecular gas from the destructive effects of UV radiation. For shock ram pressures comparable to or exceeding typical local interstellar medium pressures, self-shielding controls the formation time of molecular hydrogen, but CO formation requires shielding of the interstellar radiation field by dust grains. We find that for typical parameters the molecular hydrogen fractional abundance can become significant well before CO forms. The timescale for (CO) molecular cloud formation is not set by the H2 formation rate on grains, but rather by the timescale for accumulating a sufficient column density or extinction, AV ≳ 0.7. The local ratio of atomic to molecular gas (4 : 1), coupled with short estimates for the lifetimes of molecular clouds (3-5 Myr), suggests that the timescales for accumulating molecular clouds from atomic material typically must be no longer than about 12-20 Myr. Based on the shielding requirement, this implies that the typical product of preshock density and velocity must be nv ≳ 20 cm-3 km s-1. In turn, depending on the shock velocity, this implies shock ram pressures that are a few times the typical estimated local turbulent gas pressure and comparable to the total pressures (gas plus magnetic plus cosmic rays). Coupled with the rapid formation of CO once shielding is sufficient, flow-driven formation of molecular clouds in the local interstellar medium can occur sufficiently rapidly to account for observations. We also provide detailed predictions of atomic and molecular emission and absorption that track the formation of a molecular cloud from a purely atomic medium, with a view toward helping to verify cloud formation by shock waves. However, our predictions suggest that the detection of the pre-CO stages will be challenging. Finally, we provide an analytic solution for time-dependent H2 formation that may be of use in numerical hydrodynamic calculations.
X-Ray and Radio Emission from Ultraviolet-selected Star-forming Galaxies at Redshifts 1.5 ≲ z ≲ 3.0 in the GOODS-North Field

We have examined the stacked radio and X-ray emission from UV-selected galaxies spectroscopically confirmed to lie in the redshift range 1.5 ≲ z ≲ 3.0 in the Great Observatories Origins Deep Survey-North field to determine their average extinction and star formation rates (SFRs). The X-ray and radio data are obtained from the Chandra 2 Ms survey and the Very Large Array, respectively. There is a good agreement among the X-ray, radio, and dereddened UV estimates of the average SFR for our sample of z ~ 2 galaxies of ~50 M☉ yr-1, indicating that the locally calibrated SFR relations appear to be statistically valid in the redshift range 1.5 ≲ z ≲ 3.0. We find that UV-estimated SFRs (uncorrected for extinction) underestimate the bolometric SFRs as determined from the 2-10 keV X-ray luminosity by a factor of ~4.5-5.0 for galaxies over a large range in redshift, 1.0 ≲ z ≲ 3.5.
Exploiting contextual spaces for image re-ranking and rank aggregation

The objective of Content-based Image Retrieval (CBIR) systems is to return the most similar images given an image query. In this scenario, accurately ranking collection images is of great relevance. In general, CBIR systems consider only pairwise image analysis, that is, compute similarity measures considering only pair of images, ignoring the rich information encoded in the relations among several images. This paper presents a novel re-ranking approach based on contextual spaces aiming to improve the effectiveness of CBIR tasks, by exploring relations among images. In our approach, information encoded in both distances among images and ranked lists computed by CBIR systems are used for analyzing contextual information. The re-ranking method can also be applied to other tasks, such as: (i) for combining ranked lists obtained by using different image descriptors (rank aggregation); and (ii) for combining post-processing methods. We conducted several experiments involving shape, color, and texture descriptors and comparisons to other post-processing methods. Experimental results demonstrate the effectiveness of our method.
Deep Watershed Transform for Instance Segmentation

Most contemporary approaches to instance segmentation use complex pipelines involving conditional random fields, recurrent neural networks, object proposals, or template matching schemes. In this paper, we present a simple yet powerful end-to-end convolutional neural network to tackle this task. Our approach combines intuitions from the classical watershed transform and modern deep learning to produce an energy map of the image where object instances are unambiguously represented as energy basins. We then perform a cut at a single energy level to directly yield connected components corresponding to object instances. Our model achieves more than double the performance over the state-of-the-art on the challenging Cityscapes Instance Level Segmentation task.
What and When: Parallel and Convergent Processing in Motor Control

Successful motor behavior requires making appropriate response (response selection) at the right time (timing adjustment). Earlier psychological studies have suggested that the response selection and timing adjustment processes are performed serially in separate stages. We tested this hypothesis using functional magnetic resonance imaging. The subjects performed a choice reaction time task in four conditions: two (on-line response selection required or not) by two (on-line timing adjustment required or not). We found that the neural correlates for the two processes were indeed separate: the anterior medial premotor cortex (presupplementary motor area) was selectively active in response selection, whereas the cerebellar posterior lobe was selectively active in timing adjustment. However, the functional separation was only partial in that the lateral premotor cortex and the intraparietal sulcus were active equally for response selection and timing adjustment. The lateral premotor cortex was most active when both processes were required, suggesting that it integrates the information on response selection and the information on timing adjustment; alternatively, it might contribute to the allocation of attentional resources during dual information processing. The intraparietal sulcus was equally active when either response selection or timing adjustment was required, suggesting that it modifies, rather than integrates, these processes. Furthermore, our results suggest that these activations related to response selection and timing adjustment were distinct from sensory or motor processes.
Discrete sliding mode control of systems with unmatched uncertainty using multirate output feedback

Systems with uncertainties and disturbances are common in practice. In some cases, these disturbances are unmatched. Moreover, in most cases the entire state information is also not available for control purpose. This note proposes a control algorithm for achieving quasi-sliding mode in discrete-time linear time-invariant (LTI) systems with bounded unmatched uncertainties. A multirate output feedback based strategy is used for this purpose. The proposed algorithm is illustrated through an example.
The Performance Effects of Individual and Group Incentives: A Case Study

We study a warehouse that changes its incentive plan from a group plan to an individual plan. We focus on the impact that the change had on productivity, allocation of time to different tasks, and helping across departments. Utilizing time series methods we find that average productivity increased about 15 % but that individuals reacted heterogeneously to the change. The change also affected the organization of helping across departments and the allocation of time to various tasks. In addition to the econometrics analysis we provide a description of the process of changing the incentive plan and discuss the cost effectiveness of the change of the plan.
Distilling Knowledge from Ensembles of Neural Networks for Speech Recognition

Speech recognition systems that combine multiple types of acoustic models have been shown to outperform single-model systems. However, such systems can be complex to implement and too resource-intensive to use in production. This paper describes how to use knowledge distillation to combine acoustic models in a way that has the best of many worlds: It improves recognition accuracy signiﬁcantly, can be implemented with standard training tools, and requires no additional complexity during recognition. First, we identify a simple but particularly strong type of ensemble: a late combination of recurrent neural networks with different architectures and training objectives. To harness such an ensemble, we use a variant of standard cross-entropy training to distill it into a single model and then discriminatively ﬁne-tune the result. An evaluation on 2,000-hour large vocabulary tasks in 5 languages shows that the distilled models provide up to 8.9% relative WER improvement over conventionally-trained baselines with an identical number of parameters.
An Integrated Macroeconomic Model for Assessing Urban Sustainability

A macrolevel approach for integrating regional economic models with urban metabolism models is developed. Challenges with consistency and aggregation persist in the integration of urban models between socioeconomic and environmental systems, and between the micro and macro scale. Using an econometric model as a foundation offers a flexible structure, with low data requirements, that might potentially be integrated with microlevel process models. Such an econometric model is developed and verified for the economy of the Toronto region. The economic model is integrated with a greenhouse gas emission model that simulates emissions from the residential, transportation, and solid waste sectors. Emissions are simulated to 2010 for optimistic and pessimistic exogenous economic climates. In the absence of technological change, emissions will increase in the order of 30%, largely as a result of population growth (22%–23%), which is relatively insensitive to economic growth. The potential to decrease emissions through changing land-use development and increased recycling of solid waste is examined.
Downside Consumption Risk and Expected Returns

The expected utility model captures the attitude toward risk exclusively through the marginal utility. Recognizing this limitation several models explicitly account for aversion to downside risk. This paper presents non-experimental evidence that this feature is empirically relevant in asset pricing.I use rank-dependent expected utility to model aversion to downside risk and derive Euler equations for consumption and asset returns. The resulting model nests the standard CCAPM and allows estimation of preferences parameters by GMM and the tests of significance of the downside risk aversion. I estimate the model using Fama and French 25 portfolios and find that it performs considerably better than the standard CCAPM. The parameter estimates imply that the left tail outcomes are over-weighted while the right tail outcomes are under-weighted. Asset prices reflect a sizable premium for downside risk and the corresponding parameter is strongly significant. The downside risk premium exhibits significant variation across the test portfolios and contributes to value and size premia.
Chateter-associated Urinary Tract Infections in Adults

Introduction: Hospital-acquired Urinary tract infections make 35% of all the hospital-acquired infections, and about 80% of them are related to the catheterization of the urinary bladder Purpose: To determine clinical characteristics and dominant etiologic factors of Urinary Tract Infections associated with urinary catheter (C-UTIs). Methods: Determined clinical characteristics of C-UTIs were prospectively analyzed on 38 hospitalized patients in the Clinic for Infectious Diseases at the University Clinical Centre Tuzla, from January 1st 2011 to December 31st 2011. The control group constituted of 200 patients with community-acquired Urinary Tract Infections (Co-UTIs) hospitalized in the same period. Results: It was registered on 22 (57.89%) of symptomatic infections, 14 (36.84%) asymptomatic bacteriuria and 2 (5.26%) other C-UTIs. Dominant etiologic factors were: E. coli, caused 14 (36.84%), Extended-Spectrum Beta-lactamase producing (ESBL) Klebsiella pneumoniae 7 (18.42%), Enterococcus faecium and Candida spp. 3 (7.89%) of C-UTIs. E. coli was significantly most common etiologic factor of C-UTIs in younger women (p=0.04). E. coli from C-UTIS showed significantly higher resistance to antimicrobial drugs. Inadequate antimicrobial therapy was significantly more common prescribed to patients from C-UTIs. Lethal outcome was significantly most common associated with certain clinical and laboratory findings. Conclusion: Initial antimicrobial therapy of those serious infections should be based on data from those research.
THE ROLE OF EXCITATORY NEUROTRANSMITTER GLUTAMATE IN BRAIN PHYSIOLOGY AND PATHOLOGY

Glutamate is the principal excitatory amino acid neurotransmitter abundantly present in the brain of mammals, as well as in dietary protein, released by an estimated 40% of all synapses and its interaction and participation with specific membrane receptors in plastic changes in the efficacy of synaptic transmission are responsible for many neurological functions, including cognition, memory, behavior, movement, sensation and in the formation of neural network during development. Our knowledge of the glutamatergic synapse has advanced enormously in the last 10 years, primarily through application of molecular biological techniques to the study of glutamate receptors (GluRs) and transporters. In addition, excitatory neurotransmitters are important in influencing the developmental plasticity of synaptic connections in the nervous system. However, in a variety of pathologic conditions, including stroke and various neurodegenerative disorders, excessive activation of GluRs (Ionotropic and metabotropic) may mediate neuronal injury of death. There is an increased release of glutamate after cerebral ischemia or hypoxia which could cause over stimulation of its receptors leading to an increase in the intracellular Ca 2+ concentration (i[Ca2+]). Sustained elevation in i[Ca2+] is assumed to set various pathological processes into motion which could degenerate neurons by activating proteases, lipases, endonucleases and nitric oxide synthases and by promoting the formation of free oxygen radicals. Drugs capable of inhibiting the increase in i[Ca2+] such as calcium antagonists, N-methyl-D-aspartate (NMDA) and α-amino-2-hydroxy-4-methyl-3-isoxazolepropionate (AMPA) antagonists protect neurons against
Transcriptome Changes Affecting Hedgehog and Cytokine Signalling in the Umbilical Cord: Implications for Disease Risk

Background Babies born at lower gestational ages or smaller birthweights have a greater risk of poorer health in later life. Both the causes of these sub-optimal birth outcomes and the mechanism by which the effects are transmitted over decades are the subject of extensive study. We investigated whether a transcriptomic signature of either birthweight or gestational age could be detected in umbilical cord RNA. Methods The gene expression patterns of 32 umbilical cords from Singaporean babies of Chinese ethnicity across a range of birthweights (1698–4151 g) and gestational ages (35–41 weeks) were determined. We confirmed the differential expression pattern by gestational age for 12 genes in a series of 127 umbilical cords of Chinese, Malay and Indian ethnicity. Results We found that the transcriptome is substantially influenced by gestational age; but less so by birthweight. We show that some of the expression changes dependent on gestational age are enriched in signal transduction pathways, such as Hedgehog and in genes with roles in cytokine signalling and angiogenesis. We show that some of the gene expression changes we report are reflected in the epigenome. Conclusions We studied the umbilical cord which is peripheral to disease susceptible tissues. The results suggest that soma-wide transcriptome changes, preserved at the epigenetic level, may be a mechanism whereby birth outcomes are linked to the risk of adult metabolic and arthritic disease and suggest that greater attention be given to the association between premature birth and later disease risk.
Bridging remote sensing analysts and decision makers : the support of aggregate - mosaic theory to monitor tropical deforestation

The land cover mosaic (LCM) classification concept, which is based on the aggregate-mosaic theory, improves geo-information on tropical deforestation for decision-makers. Land cover mosaics are spatial units constituting mixtures of different land cover types. They are defined by two parameters, that is the mix of different land cover types and the spatial size of these land cover types. In this paper, a sensitivity analysis was performed to test the impact of the parameter spatial size on LCM classification results using two Landsat TM images of a peatswamp forest in Kalimantan, Indonesia. Five methods were selected to evaluate the LCM-classification results, the standard remote sensing accuracy method KHAT, and four Landscape Pattern Metrics as applied in landscape ecology. Results showed that for spatial sizes up to 150 ha, the total area of forest cover remained constant for both the 1990 image and the more fragmented 1996 image. This finding is very useful for assessing the area of forest cover, which often differ widely between various sources. From a decision-making point of view it is important that maps are produced with identical parameter settings, when comparing temporally different images, because spatial size has effect on the spatial arrangement of forest cover. Combining results of KHAT and Landscape Pattern Metrics thematic classes causing significant differences could be indicated. Finally, based on variations in LCM classifications, it can be concluded that between 1990 and 1996 forest was depleted not due to logging practices, but due to agricultural practices. Such a finding could be very useful to support planning and development strategies, and to improve governmental policies to manage tropical rainforests in a sustainable way. * Corresponding author. Tel: +31-317 474 721; Fax: +31-317 419 000
Not fade away: the HPA axis and depression

Salivary cortisol sampling has confirmed the presence of increased cortisol secretion in depression and has also revealed that some aspects of hypothalamo-pituitary-adrenal (HPA) axis disturbance have trait-like characteristics that may predict the risk of future illness. Persistent hypersecretion of cortisol in individuals vulnerable to depression also has implications for the medical co-morbidities associated with mood disorder. Pharmacological treatments targeted at the HPA axis represent a novel approach to the management of depression and its complications; however, a better understanding of the molecular basis of HPA axis dysfunction in depressed patients will be needed before this promise can be fulfilled.
Three Essays on Idiosyncratic Volatility

This thesis consists of three essays. The first essay (chapter two) examines the relationship between idiosyncratic volatility and future returns in the Canadian market. The negative relationship between realized idiosyncratic volatility (RIvol) and future returns uncovered by Ang et al. (2006) for the US market has been attributed to return reversals. For the Canadian market where return reversals have considerably less importance, we find that RIvol is positively related to future returns, even after controlling for risk loadings, illiquidity and reversals. Unlike the findings of Bali et al. (2011) for the US market, we find for the Canadian market that the relationship between extreme positive returns and future returns is positive and that idiosyncratic volatility is consistently positively related to future returns. The second essay (chapter three) discusses the relationship between closed end fund discounts and the level of uncertainty about its holdings. Our trade-off model states that the intrinsic premium of a closed-end fund (CEF) is equal to the CEF’s price minus both its NAVPS (net asset value per share) and the net present value (NPV) of its future benefits from liquidity, managerial abilities and leverage minus its managerial costs. Any additional premium will persist to the extent that arbitrage between these two price series is both costly and risky. We find that arbitrage incompleteness due to the uncertainties about this NPV and the CEF’s holdings, as captured by idiosyncratic risk and other proxies, explains over two-thirds of the variation in CEF premiums or their changes. As expected, we find that the CEF premium is negatively related to gross leverage, management fees, cash and bond holdings, and positively related to liquidity enhancement, CEF performance and net leverage. These results are consistent with our finding that changes in CEF prices and NAVPS are more integrated than segmented using the Kappa test of Kapadia and Pu (2012). The third essay (chapter four) investigates the information content of idiosyncratic volatility around the public release of M&A rumors. We examine the releases of hand-collected initial rumors about potential M&A for 2250 firms. Unlike previous research, we find that a strategy of investing in firms with rumors of lower (greater) credibility yields negative (positive) changes in idiosyncratic volatilities around the rumor dates and subsequent returns. We argue that this asymmetric effect on idiosyncratic volatilities is linked to asymmetric changes in the heterogeneity of the probabilities of actual M&A when conditioned on rumor credibility. Changes in idiosyncratic volatilities are positively related to the market implicit probabilities of M&A as measured by the ratio of the market values at the M&A announcement and rumor dates.