Miracle-dz/UniFAR-FTUs huggingface dataset:
Lowly Polarized Light from a Highly Magnetized Jet of GRB 190114C

We report multicolor optical imaging and polarimetry observations of the afterglow of the first TeV-detected gamma-ray burst (GRB), GRB 190114C, using the RINGO3 and MASTER II polarimeters. Observations begin 31 s after the onset of the GRB and continue until ∼7000 s postburst. The light curves reveal a chromatic break at ∼400–500 s, with initial temporal decay α = 1.669 ± 0.013 flattening to α ∼ 1 postbreak, which we model as a combination of reverse and forward shock components with magnetization parameter RB ∼ 70. The observed polarization degree decreases from 7.7% ± 1.1% to 2%–4% 52–109 s postburst and remains steady at this level for the subsequent ∼2000 s at a constant position angle. Broadband spectral energy distribution modeling of the afterglow confirms that GRB 190114C is highly obscured (Av,HG = 1.49 ± 0.12 mag; cm−2). We interpret the measured afterglow polarization as intrinsically low and dominated by dust —in contrast to the P > 10% measured previously for other GRB reverse shocks—with a small contribution from polarized prompt photons in the first minute. We test whether first- and higher-order inverse Compton scattering in a magnetized reverse shock can explain the low optical polarization and subteraelectronvolt emission but conclude that neither is explained in the reverse shock inverse Compton model. Instead, the unexpectedly low intrinsic polarization degree in GRB 190114C can be explained if large-scale jet magnetic fields are distorted on timescales prior to reverse shock emission.
Hybrid Composition with IdleBlock: More Efficient Networks for Image Recognition

We propose a new building block, IdleBlock, which naturally prunes connections within the block. To fully utilize the IdleBlock we break the tradition of monotonic design in state-of-the-art networks, and introducing hybrid composition with IdleBlock. We study hybrid composition on MobileNet v3 and EfficientNet-B0, two of the most efficient networks. Without any neural architecture search, the deeper "MobileNet v3" with hybrid composition design surpasses possibly all state-of-the-art image recognition network designed by human experts or neural architecture search algorithms. Similarly, the hybridized EfficientNet-B0 networks are more efficient than previous state-of-the-art networks with similar computation budgets. These results suggest a new simpler and more efficient direction for network design and neural architecture search.
An Inception Inspired Deep Network to Analyse Fundus Images

A fundus image usually contains the optic disc, pathologies and other structures in addition to vessels to be segmented. This study proposes a deep network for vessel segmentation, whose architecture is inspired by inception modules. The network contains three sub-networks, each with a different filter size, which are connected in the last layer of the proposed network. According to experiments conducted in the DRIVE and IOSTAR, the performance of our network is found to be better than or comparable to that of the previous methods. We also observe that the sub-networks pay attention to different parts of an input image when producing an output map in the last layer of the proposed network; though, training of the proposed network is not constrained for this purpose.
Network Flows That Solve Sylvester Matrix Equations

In this article, we study methods to solve a Sylvester equation in the form of <inline-formula><tex-math notation="LaTeX">$\mathbf {A}\mathbf {X}+\mathbf {X}\mathbf {B}=\mathbf {C}$</tex-math></inline-formula> for given matrices <inline-formula><tex-math notation="LaTeX">$\mathbf {A}, \mathbf {B}, \mathbf {C}\in \mathbb {R}^{n\times n}$</tex-math></inline-formula>, inspired by the distributed linear equation flows. The entries of <inline-formula><tex-math notation="LaTeX">$\mathbf {A}, \mathbf {B},$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\mathbf {C}$</tex-math></inline-formula> are separately partitioned into a number of pieces (or sometimes we permit these pieces to overlap), which are allocated to nodes in a network. Nodes hold a dynamic state shared among their neighbors defined from the network structure. Natural partial or full row/column partitions and block partitions of the data <inline-formula><tex-math notation="LaTeX">$\mathbf {A}, \mathbf {B},$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\mathbf {C}$</tex-math></inline-formula> are formulated by use of the vectorized matrix equation. We show that existing network flows for distributed linear algebraic equations can be extended to solve this special form of matrix equations over networks. A “consensus <inline-formula><tex-math notation="LaTeX">$+$</tex-math></inline-formula> projection <inline-formula><tex-math notation="LaTeX">$+$</tex-math></inline-formula> symmetrization” flow is also developed for equations with symmetry constraints on the matrix variables. We prove the convergence of these flows and obtain the fastest convergence rates that these flows can achieve regardless of the choices of node interaction strengths and network structures.
Effects of ocean climate on the length and condition of forage fish in the Gulf of Alaska

Forage fish quantity and quality have important effects on the ecology and vital rates of marine top predators, including seabirds (Suryan et al., 2002), marine mammals (Trites & Donnelly, 2003), and large predatory fish (Rose & O'Driscoll, 2002). In particular, the “junk food” hypothesis describes ways in which lower food qual‐ ity may negatively affect marine predator population parameters (Alverson, 1992; Rosen & Trites, 2000; reviewed by Osterblom, Olsson, Blenckner, & Furness, 2008). While it has been well estab‐ lished that prey quality is important to aspects of predator success, drivers of variation in quality remain poorly understood. Only a few studies have been conducted over a long enough period of time to examine interannual or lower‐frequency variation in prey quality (Carscadden, Montevecchi, Davoren, & Nakashima, 2002; Wanless, Harris, Newell, Speakman, & Daunt, 2018; Wanless, Harris, Redman, & Speakman, 2005). Developing a robust understanding of variation in prey size and energetic value is becoming more important with Received: 28 January 2019 | Revised: 9 May 2019 | Accepted: 16 May 2019 DOI: 10.1111/fog.12443
A Recommendation System for Personalized Reviews in Apache Spark

Personalized recommendation systems play an increasingly growing role in customer’s decision making process. The various e-commerce sites differ in their objectives, functions and characteristics but their common primary goal is to efficiently identify user decisions. The most frequent approach is the selection of the reviews with the highest percentage of helpfulness’ votes by users who have read the reviews. Thus, they end up with a selection derived from a limited scope of criteria. In this work, we focus on retrieving a subset of reviews, using personalized criteria. In order to determine which set of reviews may correspond to individual users’ preferences, we focus on the importance of product aspects for each user. Our system is built on Apache Spark enabling the processing of reviews, we evaluate it with a dataset from Amazon and the results are indexed in the distributed search engine, Elasticsearch.
A General Framework for Input Data Usage Static Analysis

Context. Nowadays, thanks to advances in machine learning and the availability of vast amounts of data, computer software plays an increasingly important role in assisting or even fully automating tasks in our daily lives. As a consequence, however, we become increasingly vulnerable to programming errors. In particular, programming errors that do not cause failures can have serious consequences since code that produces an erroneous but plausible result gives no indication that something went wrong. In 2012, flawed code caused losses of billions of dollars for JP Morgan Chase & Co. [4]. In medical applications, programming errors are deadly [2]. It is thus paramount to develop methods and tools that can keep up with these developments and ensure that data science software behaves correctly and reliably.
Sunburn management on ‘Honeycrisp’ in the Hudson Valley in 2016

Gemma Reig1, Dan Donahue2, Peter Jentsch3 1School of Integrative Plant Science, Department of Horticulture Section, Hudson Valley Research Laboratory, Cornell University, Highland, New York 12528 2Eastern New York Commercial Horticulture Program, Cornell Cooperative Extension, Hudson Valley Research Laboratory, Highland, New York 12528 3Department of Entomology, Cornell University, Hudson Valley Research Laboratory, Highland, New York 12528
UCSMNLP: Statistical Machine Translation for WAT 2019

This paper represents UCSMNLP’s submission to the WAT 2019 Translation Tasks focusing on the Myanmar-English translation. Phrase based statistical machine translation (PBSMT) system is built by using other resources: Name Entity Recognition (NER) corpus and bilingual dictionary which is created by Google Translate (GT). This system is also adopted with listwise reranking process in order to improve the quality of translation and tuning is done by changing initial distortion weight. The experimental results show that PBSMT using other resources with initial distortion weight (0.4) and listwise reranking function outperforms the baseline system.
CERTAINTY IN FUNCTIONAL UNCERTAINTY

This paper offers a non-movement account of Mandarin Chinese Unbounded Dependencies, including topicalization and relativization. The theory of Functional Uncertainty (Zaenen and Kaplan 1989) in Lexical-functional Grammar is adopted. It is shown that various predictions of movements accounts, such as island constraints, re not borne out in Mandarin. In contrast, the seemingly problematic contrasts between Mandarin and languages observing island constraint can be straightforwardly accounted for with our functional uncertainty analysis. We also observe that dependencies involving Mandarin object controllers are not allowed, contrary to the prediction of multiple path resolutions in the theory of functional uncertainty. We argue that this is due to a language specific parameter requiring that a dependency ends in a unique function. Formal revisions of theoretical definitions are proposed to account for this parameter as well to reconcile the potential conflict between the functional uniqueness condition and the theory of functional uncertainty. The study of long-distance dependencies motivates the postulation of COMP-to-COMP movements in classical transformational grammar (TG) and an elaborated typology of empty categories in the Government and Binding (GB) theory. However, it has never been ascertained that the accounts of constructions such as topicalization and relativization depend crucially on the postulation of movements. Even some of the linguists who adopt the transformational theories question the
Quantum beats in the polarization of the spin-dependent photon echo from donor-bound excitons in CdTe/(Cd,Mg)Te quantum wells

We study the quantum beats in the polarization of the photon echo from donor-bound exciton ensembles in semiconductor quantum wells. To induce these quantum beats, a sequence composed of a circularly polarized and a linearly polarized picosecond laser pulse in combination with an external transverse magnetic field is used. This results in an oscillatory behavior of the photon echo amplitude, detected in the $\sigma^+$ and $\sigma^-$ circular polarizations, occurring with opposite phases relative to each other. The beating frequency is the sum of the Larmor frequencies of the resident electron and the heavy hole when the second pulse is polarized along the magnetic field. The beating frequency is, on the other hand, the difference of these Larmor frequencies when the second pulse is polarized orthogonal to the magnetic field. The measurement of both beating frequencies serves as a method to determine precisely the in-plane hole $g$ factor, including its sign. We apply this technique to observe the quantum beats in the polarization of the photon echo from the donor-bound excitons in a 20-nm-thick CdTe/Cd$_{0.76}$Mg$_{0.24}$Te quantum well. From these quantum beats we obtain the in-plane heavy hole $g$ factor $g_h=-0.143\pm0.005$.
Towards Reducing Bias in Gender Classification

Societal bias towards certain communities is a big problem that affects a lot of machine learning systems. This work aims at addressing the racial bias present in many modern gender recognition systems. We learn race invariant representations of human faces with an adversarially trained autoencoder model. We show that such representations help us achieve less biased performance in gender classification. We use variance in classification accuracy across different races as a surrogate for the racial bias of the model and achieve a drop of over 40% in variance with race invariant representations.
The impact of the Working Time Regulations on medical education and training : Literature review. Report for the General Medical Council.

This report presents the findings of primary research that aimed to evaluate the possible effects of the Working Time Regulations (1998; the WTR) on postgraduate medical education and training across the UK. It follows a literature review conducted as part of the same tender, delivered in January 2012. Conclusion The Temple Review urged that medical education and training make ‘every moment count’, meaning that medical education should be embedded in medical practice, and that service delivery should be aware of its educational component. This is not yet the case for many trainees, and there is an increasing separation between work and education that may be adding new stressors to the trainee population. Moves to further implement the recommendations of the Temple Review (a consultant-delivered service, concerted faculty development, and greater integration of education into service) should address some of the concerns arising from this research. If working time is to be considered as a component of educational governance and quality improvement, monitoring processes need to be reviewed, and their acceptance and trust by organisations and trainees ensured, to guarantee that any links between working time and education are reliably identified. The GMC has power as the regulator of medical education, and may be able to redress the balance of education and service through its role in quality assurance. Education and training should be placed at the heart of service delivery. Education is not seen as at the expense of patient care, but as a means of maintaining it.
Yottixel - An Image Search Engine for Large Archives of Histopathology Whole Slide Images

With the emergence of digital pathology, searching for similar images in large archives has gained considerable attention. Image retrieval can provide pathologists with unprecedented access to the evidence embodied in already diagnosed and treated cases from the past. This paper proposes a search engine specialized for digital pathology, called Yottixel, a portmanteau for "one yotta pixel," alluding to the big-data nature of histopathology images. The most impressive characteristic of Yottixel is its ability to represent whole slide images (WSIs) in a compact manner. Yottixel can perform millions of searches in real-time with a high search accuracy and low storage profile. Yottixel uses an intelligent indexing algorithm capable of representing WSIs with a mosaic of patches by converting them into a small number of methodically extracted barcodes, called "Bunch of Barcodes" (BoB), the most prominent performance enabler of Yottixel. The performance of the prototype platform is qualitatively tested using 300 WSIs from the University of Pittsburgh Medical Center (UPMC) and 2,020 WSIs from The Cancer Genome Atlas Program (TCGA) provided by the National Cancer Institute. Both datasets amount to more than 4,000,000 patches of 1000x1000 pixels. We report three sets of experiments that show that Yottixel can accurately retrieve organs and malignancies, and its semantic ordering shows good agreement with the subjective evaluation of human observers.
Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates

Recent years have witnessed the growth of large-scale distributed machine learning algorithms -- specifically designed to accelerate model training by distributing computation across multiple machines. When scaling distributed training in this way, the communication overhead is often the bottleneck. In this paper, we study the local distributed Stochastic Gradient Descent~(SGD) algorithm, which reduces the communication overhead by decreasing the frequency of synchronization. While SGD with adaptive learning rates is a widely adopted strategy for training neural networks, it remains unknown how to implement adaptive learning rates in local SGD. To this end, we propose a novel SGD variant with reduced communication and adaptive learning rates, with provable convergence. Empirical results show that the proposed algorithm has fast convergence and efficiently reduces the communication overhead.
From Iterated Integrals and Chronological Calculus to Hopf and Rota–Baxter Algebras

Gian-Carlo Rota mentioned in one of his last articles the problem of developing a theory around the notion of integration algebras, which should be dual to the one of differential algebras. This idea has been developed historically along three lines: using properties of iterated integrals and generalisations thereof, as in the theory of rough paths; using the algebraic structures underlying chronological calculus such as shuffle and pre-Lie products, as they appear in theoretical physics and control theory; and, more generally, using a particular operator identity which came to be known as Rota-Baxter relation. The recent developments along each of these lines of research and their various application domains are not always known to other communities in mathematics and related fields. The general aim of this survey is therefore to present a modern and unified perspective on these approaches, featuring among others non-commutative Rota-Baxter algebras and related Hopf and Lie algebraic structures such as descent algebras, algebras of simplices as well as shuffle, pre- and post-Lie algebras and their enveloping algebras. Accordingly, two viewpoints are proposed. A geometric one, that can be derived using combinatorial properties of Euclidean simplices and the duality between integrands and integration domains in iterated integrals. An algebraic one, provided by the axiomatisation of integral calculus in terms of Rota-Baxter algebra.
DINKS, DEWKS & Co.

Along with new modern family lifestyles, came the given marketing names caricaturing each of these new types of families. Accordingly, couples choosing to be childless have been denoted as DINKS, for "double incomes no kids", and couples with children as DEWKS, for "dually employed with kids". In this paper, we build an endogenous fertility model able to explain the following three stylized facts: first, single women are much more likely to be childless than married women but, when mothers, their fertility is almost as high as marrieds’, second, childlessness exhibits a U-Shaped relationship with education for both single and married women, and third, there is a hump-shaped relationship between marriage rates and education levels. These facts have not been treated in the population economics literature yet.
IWH Discussion Papers

Technological complementarity is argued to be a crucial element for effective Research and Development (R&D) collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis. The results illustrate sectors being complements both from a dyadic and portfolio/ network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.
Population status and genetic analysis of captive red goral (Naemorhedus baileyi) in Shanghai Zoo, China

Abstract. The red goral is an endangered species with a small population and narrow distribution in China. The only captive population (21 individuals) is held in Shanghai Zoo, China. Demographic and genetic analyses were carried out to assess the status of this captive population and put forward conservation and management proposals. Population status was assessed on the basis of studbook records from 1981 to 2016. The population size grew from seven (three males, four females) to 31 (19 males, 12 females) in 2012 (λ = 1.06) and 21 (17 males, four females) in 2016 (λ = 0.91). From 1981 to 2016, a total of 81 births (45 males, 36 females) and 68 deaths (32 males, 32 females, four unknown) occurred. The mean kinship (MK) of the population is 0.2614 and the average inbreeding index is 0.2037. Parturition mainly occurs in May, June and July, and deaths occurred in January, February, July and November. In addition, the genetic diversity of this population was analysed on the basis of nine microsatellite loci. The results revealed that 14 primer-amplified bands were found; nine of them were stable, with four loci highly polymorphic (polymorphic information content, PIC > 0.05), three moderate (0.25 < PIC < 0.5), one low (PIC < 0.25) and one monomorphic (PIC = 0). In total, 34 alleles were detected from eight microsatellite loci, with the number of alleles per locus (A) ranging from 3-6 (x̄ = 4.250), and the effective number of alleles (Ne) from 1.245 to 3.862 (x̄ = 2.529). The observed heterozygosity (H0) varied from 0.143 to 0.857 (x̄ = 0.562), and the expected heterozygosity (He) from 0.201 to 0.755 (x̄ = 0.550). The polymorphism information content (PIC) varied from 0.188 to 0.705 (x̄ = 0.500). The results indicated a moderate level of genetic diversity among the red goral population in Shanghai Zoo.
Hippocampus Radiomic Biomarkers for the Diagnosis of Amnestic Mild Cognitive Impairment: A Machine Learning Method

Background: Recent evidence suggests the presence of hippocampal neuroanatomical abnormalities in subjects of amnestic mild cognitive impairment (aMCI). Our study aimed to identify the radiomic biomarkers of the hippocampus for building the classification models in aMCI diagnosis. Methods: For this target, we recruited 42 subjects with aMCI and 44 normal controls (NC). The right and left hippocampi were segmented for each subject using an efficient learning-based method. Then, the radiomic analysis was applied to calculate and select the radiomic features. Finally, two logistic regression models were built based on the selected features obtained from the right and left hippocampi. Results: There were 385 features derived after calculation, and four features remained after feature selection from each group of data. The area under the receiver operating characteristic (ROC) curve, specificity, sensitivity, positive predictive value, negative predictive value, precision, recall, and F-score of the classification evaluation index of the right hippocampus logistic regression model were 0.76, 0.71, 0.69, 0.69, 0.71, 0.69, 0.69, and 0.69, and those of the left hippocampus model were 0.79, 0.71, 0.54, 0.64, 0.63, 0.64, 0.54, and 0.58, respectively. Conclusion: Results demonstrate the potential hippocampal radiomic biomarkers are valid for the aMCI diagnosis. The MRI-based radiomic analysis, with further improvement and validation, can be used to identify patients with aMCI and guide the individual treatment.