Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning to Generate and Edit Hairstyles

Modeling hairstyles for classification, synthesis and image editing has many practical applications. However, existing hairstyle datasets, such as the Beauty e-Expert dataset, are too small for developing and evaluating computer vision models, especially the recent deep generative models such as generative adversarial network (GAN). In this paper, we contribute a new large-scale hairstyle dataset called Hairstyle30k, which is composed of 30k images containing 64 different types of hairstyles. To enable automated generating and modifying hairstyles in images, we also propose a novel GAN model termed Hairstyle GAN (H-GAN) which can be learned efficiently. Extensive experiments on the new dataset as well as existing benchmark datasets demonstrate the effectiveness of proposed H-GAN model
Spectral detection of micro‐metastases in lymph node histo‐pathology

The first detection of breast cancer micrometastases in lymph nodes by infrared spectral imaging and methods of multivariate analysis is reported. Micrometastases are indicators of early spread of cancer from the organ originally affected by disease, and their detection is of prime importance for the staging and treatment of cancer. Infrared spectral imaging, at a spatial resolution of ca. 10–12 μm, can detect small metastases down to the level of a few cancerous cells. The results presented here add to a rapidly growing database of infrared spectral imaging results for cancer diagnostics. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Metatranscriptome Analysis for Insight into Whole-Ecosystem Gene Expression during Spontaneous Wheat and Spelt Sourdough Fermentations

ABSTRACT Lactic acid bacteria (LAB) are of industrial importance in the production of fermented foods, including sourdough-derived products. Despite their limited metabolic capacity, LAB contribute considerably to important characteristics of fermented foods, such as extended shelf-life, microbial safety, improved texture, and enhanced organoleptic properties. Triggered by the considerable amount of LAB genomic information that became available during the last decade, transcriptome and, by extension, metatranscriptome studies have become one of the most appropriate research approaches to study whole-ecosystem gene expression in more detail. In this study, microarray analyses were performed using RNA sampled during four 10-day spontaneous sourdough fermentations carried out in the laboratory with an in-house-developed LAB functional gene microarray. For data analysis, a new algorithm was developed to calculate a net expression profile for each of the represented genes, allowing use of the microarray analysis beyond the species level. In addition, metabolite target analyses were performed on the sourdough samples to relate gene expression with metabolite production. The results revealed the activation of different key metabolic pathways, the ability to use carbohydrates other than glucose (e.g., starch and maltose), and the conversion of amino acids as a contribution to redox equilibrium and flavor compound generation in LAB during sourdough fermentation.
On interactive knowledge with bounded communication

The effect of upper bounds on message delivery times in a computer network upon the dynamics of knowledge gain is investigated. Recent work has identified centipedes and brooms—causal structures that combine message chains with time bound information—as necessary conditions for knowledge gain and common knowledge gain, respectively. This paper shows that, under the full-information protocol, these structures are both necessary and sufficient for such epistemic gain. We then apply this analysis to gain insights into the relation between “everyone knows” and common knowledge. We prove a tight threshold on the depth k, beyond which Ek G (everyone in G knows nested to depth k) collapses into CG (common knowledge), when this knowledge concerns the occurrence of a spontaneous event. The threshold depends on the size of the group G of agents, as well as the time that has elapsed since the event of interest occurred. The existence of such a threshold is not guaranteed for all protocols, which is demonstrated here by presenting a counterexample in which no such threshold exists.
Forced vibration analysis of cracked functionally graded microbeams

Forced vibration analysis of a cracked functionally graded microbeam is investigated by using modified couple stress theory with damping effect. Mechanical properties of the functionally graded beam change vary along the thickness direction. The crack is modelled with a rotational spring. The Kelvin-Voigt model is considered in the damping effect. In solution of the dynamic problem, finite element method is used within Timoshenko beam theory in the time domain. Influences of the geometry and material parameters on forced vibration responses of cracked functionally graded microbeams are presented.
Parallel 3-D MOSFET simulation

Describes a parallel solver for the nonlinear Poisson-Boltzmann equation modeling the distribution of an electrostatic potential in a MOSFET in three dimensions. The nonlinear system is solved with Newton's method. The linearized mathematical model is solved by the conjugate gradients method preconditioned by a parallel version of incomplete Cholesky factorization. This technique is easy to implement and reasonably scalable. With this method, one can solve the nonlinear Poisson-Boltzmann equation on a grid of size 160/sup 3/ in approximately 15 minutes on 16 processors of a KSR1 multiprocessor. This time reflects a superlinear speedup of 19 for 16 processors. The greatest barrier to scalability appears to be related to having processor subdivision boundaries cutting across areas where the grid is refined most and the solution is highly variable. <<ETX>>
Strength and Axial Behavior of Cellular Lightweight Concrete-Filled Steel Rectangular Tube Columns under Axial Compression

This paper presents the experimental results on the strength and axial behavior of rectangular steel tube columns filled with cellular lightweight concrete (CLC) under axial compression. A total of 24 specimens, including 6 reinforced cellular lightweight concrete (RCLC) columns and 18 cellular lightweight concrete-filled steel tube (CLCFT) columns are investigated. The nominal dimension of the rectangular columns are 150×75 mm in cross-section and 750 mm in height. The parameter used in all tests are the ultimate compressive strengths of the CLC, which are 15 MPa, 20 MPa and 25 MPa, and the wall thicknesses of steel tubes, which are 3.0 mm, 4.5 mm and 6.0 mm. All specimens are prepared and loaded concentrically in axial compression to failure. The results of these tests demonstrated that the CLCFT columns have a linear behavior up to the approximately 80-90% of their maximum compressive load. Then, the behavior of the columns is nonlinear. The nonlinear behaviors are due to the crushing of the concrete core and local wall buckling of the steel hollow tube. In addition, it is found that the CLCFT columns have high axial deformability at the failure when compared to the reference RCLC columns. Finally, by comparing the maximum compressive load of the test results with those obtained from the ACI composite design equation, the comparison results show that calculation formula in ACI code can be applied to compute the axial capacity of CLCFT columns under axial compression.
Online Topic-aware Influence Maximization Queries

Influence maximization is the key algorithmic problem behind viral marketing: it requires to identify a set of influential users in a social network, who, when convinced to adopt a product, shall influence other users in the network, leading to a large number of adoptions. Although real world users evidently have di↵erent degrees of interest and authoritativeness on di↵erent topics, the bulk of the literature on influence maximization is topic-blind, in the sense that it treats all items as they were the same. In this paper we study Topic-aware Influence Maximization (TIM) queries: given a directed social graph, where the arcs are associated with a topic-dependent user-to-user social influence strength, and given a budget k, the problem requires to find a set of k users (named seed set) that we shall target in a viral marketing campaign for a given new item (described as a distribution over topics) in order to maximize its adoption. Our goal is to answer such queries in milliseconds, thus enabling online social influence analytics, what-if simulation, and marketing decision making. The main challenge here is the enormous number of potential queries: any possible distribution over the topic space (i.e., any possible item) induces a di↵erent probabilistic graph, and thus a di↵erent instance of the standard influence maximization problem, for which eciency and scalability are still unsolved problems. Given these computational challenges, we propose to build an index over pre-computed solutions for a limited number of possible queries. Our proposal, INFLEX, employs a treebased index for similarity search with Bregman divergences, to eciently retrieve a good-enough set of neighbor points for the query item. Then it performs rank aggregation on their seed sets to produce the final answer to the query. Experimental results on real data show that INFLEX can provide in few milliseconds a solution very similar (Kendall⌧ distance < 0.1) to the one produced by the best known o✏ine computation (which usually takes several days).
Hepatitis B surface antigen serum levels help to distinguish active from inactive hepatitis B virus genotype D carriers.

BACKGROUND & AIMS The accurate identification of inactive (serum HBV-DNA persistently <or=2000 IU/mL) hepatitis B virus (HBV) carriers (IC) is difficult because of wide and frequent HBV-DNA fluctuations. We studied whether hepatitis B surface antigen (HBsAg) serum levels (HBsAgsl) quantification may contribute to diagnosis of HBV phases in untreated hepatitis B e antigen-negative genotype D asymptomatic carriers. METHODS HBsAgsl were measured at baseline and end of follow-up and correlated with virologic and biochemical profiles of 209 consecutive carriers followed-up prospectively (median, 29; range, 12-110 months). HBV phases were defined after 1-year monthly monitoring of HBV-DNA and transaminases. RESULTS HBsAgsl were significantly lower in 56 inactive carriers (IC) than 153 active carriers (AC): median, 62.12 (range, 0.1-4068) vs median, 3029 (range, 0.5-82,480) IU/mL; P<. 001. Among AC, HBsAgsl were lower in 31 AC whose viremia remained persistently <20,000 IU/mL (AC1) than in 122 AC with fluctuations>or=20,000 IU/mL (AC2): 883 (0.5-7838) vs 4233 (164-82,480) IU/mL, P=. 002. HBV infection was less productive in IC and AC1 than AC2 (log10 HBV-DNA/HBsAgsl ratios 0.25 and 0.49 vs 2.06, respectively, P<.001) and in chronic hepatitis than cirrhosis (1.97 vs 2.34, respectively; P=.023). The combined single point quantification of HBsAg (<1000 IU/mL) and HBV-DNA (<or=2000 IU/mL) identified IC with 94.3% diagnostic accuracy, 91.1% sensitivity, 95.4% specificity, 87.9% positive predictive value, 96.7% negative predictive value. During follow-up, HBsAgsl were stable in AC but declined in IC (yearly median decline, -0.0120 vs -0.0768 log10 IU/mL, respectively, P<.001), 10 of whom cleared HBsAg. CONCLUSIONS HBsAgsl vary during chronic hepatitis B e antigen-negative genotype D infection and are significantly lower in IC. Single-point combined HBsAg and HBV-DNA quantification provides the most accurate identification of IC, comparable with that of long-term tight monitoring.
Inhibitive action of hydroquinone-Zn 2 + system in controlling the corrosion of carbon steel in well water

The inhibition efficiencies of inhibitor systems constituting various combinations of hydroquinone and zinc ions in controlling corrosion of carbon steel immersed in well water have been evaluated by weight loss method. 100 ppm of zinc has 50% inhibition efficiency (Immersion period =7 days). When 150 ppm of hydroquinone is added, the IE increases to 97%. The nature of the protective film formed on the metal surface has been analyzed by FTIR spectra, SEM and AFM analysis. The protective film is found to consist of Fe hydroquinone complex.
Effect of Mild and Moderate Liver Disease on the Pharmacokinetics of Isavuconazole after Intravenous and Oral Administration of a Single Dose of the Prodrug BAL8557

ABSTRACT Isavuconazole is a promising new antifungal drug with favorable pharmacokinetic properties and excellent activity against a number of fungi. It is administered as a water-soluble prodrug (BAL8557) that is cleaved by plasma esterases to isavuconazole, which is eliminated primarily by hepatic metabolism. The objective of this investigation was to assess the effect of alcohol-related liver disease on the pharmacokinetics of isavuconazole. Subjects were 16 healthy individuals, 16 with mild liver impairment, and 16 with moderate liver impairment who were randomized to receive a single oral or intravenous dose of BAL8557 equivalent to 100 mg isavuconazole. Blood samples were collected for 21 days following drug administration, and plasma concentrations of isavuconazole, BAL8557, and the cleavage product BAL8728 were measured using high-pressure liquid chromatography coupled with tandem mass spectrometry. Following intravenous administration, the half-life of isavuconazole increased from 123 h for healthy volunteers to 224 h and 302 h for subjects with mild and moderate liver impairment, respectively. The systemic clearance of isavuconazole following intravenous administration decreased from 2.73 liters/h for healthy subjects to 1.43 liters/h for subjects with moderate liver impairment (47.6% decrease [P < 0.05]). A similar decrease (23.5%) was observed after oral administration. These results suggest that a dose adjustment may be needed when isavuconazole is used to treat fungal infections in patients with liver disease.
Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free

Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.
EXTRACTING TRANSLITERATION PAIRS FROM COMPARABLE CORPORA

Transliterating words and names from one language to another is a frequent and highly productive phenomenon. For example, English word cacheis transliterated in Japanese asキャッシュ “kyasshu ”. In many cases, recent transliterations are not recorded in machine readable dictionaries so it is impossible to rely on dictionary lookup to find transliteration equivalents. In this paper we describe a method for extracting transliteration pairs from comparable corpora. Proposed method exploits the structure of comparable corpora to extract a large subset of similarly distributed English words for each Japanese transliteration and then relies on phonetic similarity (i.e. back-transliteration) to find the best match in this subset. Back-transliteration also produces a similarity score which can be used to order extracted pairs.
The evolution of faint AGN between z ' 1 and z ' 5 from the COMBO-17 survey

We present a determination of the optical/UV AGN luminosity function and its evolution, based on a large sample of faint (R< 24) QSOs identified in the COMBO-17 survey. Using multi-band photometry in 17 filters within 350 nm < obs < 930 nm, we could simultaneously determine photometric redshifts with an accuracy of z < 0:03 and obtain spectral energy distributions. The redshift range covered by the sample is 1:2 < z < 4:8, which implies that even at z' 3, the sample reaches below luminosities corresponding to MB= 23, conventionally employed to distinguish between Seyfert galaxies and quasars. We clearly detect a broad plateau-like maximum of quasar activity around z ' 2 and map out the smooth turnover between z' 1a ndz' 4. The shape of the LF is characterised by some mild curvature, but no sharp "break" is present within the range of luminosities covered. Using only the COMBO-17 data, the evolving LF can be adequately described by either a pure density evolution (PDE) or a pure luminosity evolution (PLE) model. However, the absence of a strong L-like feature in the shape of the LF inhibits a robust distinction between these modes. We present a robust estimate for the integrated UV luminosity generation by AGN as a function of redshift. We find that the LF continues to rise even at the lowest luminosities probed by our survey, but that the slope is suciently shallow that the contribution of low-luminosity AGN to the UV luminosity density is negligible. Although our sample reaches much fainter flux levels than previous data sets, our results on space densities and LF slopes are completely consistent with extrapolations from recent major surveys such as SDSS and 2QZ.
The emergence of macrocyclic lactone resistance in the canine heartworm, Dirofilaria immitis.

SUMMARY Prevention of heartworm disease caused by Dirofilaria immitis in domestic dogs and cats relies on a single drug class, the macrocyclic lactones (MLs). Recently, it has been demonstrated that ML-resistant D. immitis are circulating in the Mississippi Delta region of the USA, but the prevalence and impact of these resistant parasites remains unknown. We review published studies that demonstrated resistance in D.immitis, along with our current understanding of its mechanisms. Efforts to develop in vitro tests for resistance have not yet yielded a suitable assay, so testing infected animals for microfilariae that persist in the face of ML treatment may be the best current option. Since the vast majority of D. immitis populations continue to be drug-sensitive, protected dogs are likely to be infected with only a few parasites and experience relatively mild disease. In cats, infection with small numbers of worms can cause severe disease and so the clinical consequences of drug resistance may be more severe. Since melarsomine dihydrochloride, the drug used to remove adult worms, is not an ML, the ML-resistance should have no impact on our ability to treat diseased animals. A large refugium of heartworms that are not exposed to drugs exists in unprotected dogs and in wild canids, which may limit the development and spread of resistance alleles.
ANNE: Improving Source Code Search using Entity Retrieval Approach

Code search with natural language terms performs poorly because programming concepts do not always lexically match their syntactic forms. For example, in Java, the programming concept "array" does not match with its syntactic representation of "[ ]". Code search engines can assist developers more effectively over natural language queries if such mappings existed for a variety of programming languages. In this work, we present a programming language agnostic technique to discover such mappings between syntactic forms and natural language terms representing programming concepts. We use the questions and answers in Stack Overflow to create this mapping. We implement our approach in a tool called ANNE. To evaluate its effectiveness, we conduct a user study in an academic setting in which teaching assistants use ANNE to search for code snippets in student submissions. With the use of ANNE, we find that the participants are 29% quicker with no significant drop in correctness and completeness.
Suicide and Lyme and associated diseases

Purpose The aim of this paper is to investigate the association between suicide and Lyme and associated diseases (LAD). No journal article has previously performed a comprehensive assessment of this subject. Introduction Multiple case reports and other references demonstrate a causal association between suicidal risk and LAD. Suicide risk is greater in outdoor workers and veterans, both with greater LAD exposure. Multiple studies demonstrate many infections and the associated proinflammatory cytokines, inflammatory-mediated metabolic changes, and quinolinic acid and glutamate changes alter neural circuits which increase suicidality. A similar pathophysiology occurs in LAD. Method A retrospective chart review and epidemiological calculations were performed. Results LAD contributed to suicidality, and sometimes homicidality, in individuals who were not suicidal before infection. A higher level of risk to self and others is associated with multiple symptoms developing after acquiring LAD, in particular, explosive anger, intrusive images, sudden mood swings, paranoia, dissociative episodes, hallucinations, disinhibition, panic disorder, rapid cycling bipolar, depersonalization, social anxiety disorder, substance abuse, hypervigilance, generalized anxiety disorder, genital–urinary symptoms, chronic pain, anhedonia, depression, low frustration tolerance, and posttraumatic stress disorder. Negative attitudes about LAD from family, friends, doctors, and the health care system may also contribute to suicide risk. By indirect calculations, it is estimated there are possibly over 1,200 LAD suicides in the US per year. Conclusion Suicidality seen in LAD contributes to causing a significant number of previously unexplained suicides and is associated with immune-mediated and metabolic changes resulting in psychiatric and other symptoms which are possibly intensified by negative attitudes about LAD from others. Some LAD suicides are associated with being overwhelmed by multiple debilitating symptoms, and others are impulsive, bizarre, and unpredictable. Greater understanding and a direct method of acquiring LAD suicide statistics is needed. It is suggested that medical examiners, the Centers for Disease Control and Prevention, and other epidemiological organizations proactively evaluate the association between LAD and suicide.
Self-Selection Models in Corporate Finance

Corporate finance decisions are not made at random, but are usually deliberate decisions by firms or their managers to self-select into their preferred choices. This chapter reviews econometric models of self-selection. The review is organized into two parts. The first part reviews econometric models of self-selection, focusing on the key assumptions of different models and the types of applications they may be best suited for. Part two reviews empirical applications of selection models in the areas of corporate investment, financing, and financial intermediation. We find that self-selection is a rapidly growing area in corporate finance, partly reflecting its recognition as a pervasive feature of corporate finance decisions, but more importantly, the increasing recognition of selection models as unique tools for understanding, modeling, and testing the role of private information in corporate finance.