Miracle-dz/UniFAR-FTUs huggingface dataset:
Initial Public Debt Offerings

We analyze a sample of firms that choose to tap the public debt markets before the public equity markets. These “debt first” firms are typically significantly larger and less likely to have information asymmetry problems than traditional “equity-first” firms in the same industry and year. Their debt issues are more expensive and face more restrictive covenants than debt issues by publicly listed firms that tap the debt market for the first time or publicly listed firms that have public debt outstanding and issue subsequent additional public debt. However, when the debt-first firms eventually go public, they face lower underpricing than firms without public debt that undertake an initial public offering in the same industry. Our results have significant tactical implications for firms choosing to access the public capital markets for the first time. We show that the reduction in information asymmetry at the time of the initial public debt offering reduces the offer yield at subsequent debt offerings and at the eventual IPO. Finally the proceeds at the eventual IPO are higher, underpricing is lower and fees paid to investment banks are lower suggesting that there are considerable benefits to the firm by choosing to tap the debt market prior to tapping the equity market. Glushkov: Research Director, Wharton Research Data Services (WRDS) (e-mail: glushkov@wharton.upenn.edu); Khorana: (email: ajay khorana1@gmail.com) Rau: University of Cambridge, Judge Business School, Trumpington Street, Cambridge CB2 1AG, UK. (email: r rau@jbs.cam.ac.uk). We would like to thank Tony Saunders for helpful comments. Initial Public Debt Offerings
Fish biodiversity in the shallow waters around the Gökçeada Island , Turkey

The aim of the current study is to determine the fish biodiversity in the shallow waters (0 20 m) of Gökçeada in the North Aegean Sea. The samples were collected monthly between June 2013 June 2014 using by a beach seine (0 2 m) and beam trawl (5 20 m). Field sampling was carried out in two stages. A preliminary sampling survey was carried out in the first phase (March-April 2013). During this period, sampling was conducted in each station around the entire island where sampling gear was feasible to use, and the most productive sampling stations were determined. The second stage was the biodiversity monitoring work. During the study period, 13-monthly sampling surveys were carried out at six seine and dredge stations around the island. During the whole period, a total of 30509 individuals belonging to 80 species were sampled. From the seine samplings (0-2 m), 18702 individuals from 40 species were obtained. The beam trawl samplings (5-10 and 10-20 m) identified 11807 individuals from 66 species. Biodiversity indices were calculated, and species diversities and abundances were determined for the seasons. The most copious seasons in terms of number of species abundance was identified in fall and summer. Fish species diversity and abundance maps were generated for each station. As a result, it was determined that the coastal ecosystems of Gökçeada, northern Aegean Sea, incorporated many important habitats that is rich in biodiversity. In addition, many commercial species that had been over-exploited in the region was determined to use these coastal habitats for feeding, breeding, sheltering, and growing.
Italy on the spotlight: Expo Milan 2015 and Italian Journal of Food Science

The year 2015 will certainly be remembered as the Year of the Universal Exposition (EXPO) hosted in Milan, Italy, focusing on a hot theme in the current scenario: “Feeding the Planet, Energy for Life”. This event has drawn a wide international attention towards Italy as a country with peculiar and valuable food traditions, thus strengthening its reputation as “gastronomic capital of the world” rich in protected designation of origin products (PDOs) and characterised by a longstanding food culture.
Working Paper 2003-5 Technology and Empowerment in Insurance Companies

Both empowerment and the use of emergent technologies are ways to cope with increasing competition and customer demands in service industries. The relationship between empowerment, technology and behaviour at the service encounter is, however, sparsely documented. This article offers comparative empirical analysis of the relationships between job enrichment and perceived performance based on survey and interview data from the Danish insurance industry. The results indicate that empowerment initiatives in insurance companies, unlike in banks, are only weakly associated with perceived price competitiveness and profit orientation. Nonetheless, service quality was significantly associated with empowerment, training, guidelines, and information systems support. Technology in the form of information systems support was found to be especially associated with service quality and the price competitiveness of front-line employees. Furthermore, the study indicated that professionals are less sensitive to empowerment initiatives than are clerks.
Diversity of response and effect traits provides complementary information about avian community dynamics linked to ecological function

This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. Functional Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society 1School of Biological Sciences, University of Reading, Reading, UK 2British Trust for Ornithology, Thetford, UK 3Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland 4Department of Life Sciences, Imperial College London, Berkshire, UK
Credit frictions and co-movement of durable and non-durable goods in a small open economy

In this paper I investigate, numerically, the co-movement puzzle by testing the ability of borrowing and lending constraints to counter the opposite movement of durable and non-durable goods in response to foreign monetary policy and international bond shocks. I do this by simulating a small open economy sticky price model calibrated to the South African economy over the period 1990Q012014Q04. I show that introducing borrowing and lending constraints into a small open economy sticky price model, in the face of foreign monetary policy tightening and an international bond shock, partially solves the co-movement puzzle. This is because the shadow value of durable goods reduces the incentive to accumulate durables for collateral because foreign lenders are less efficient than domestic lenders at recovering loans. In the case of sticky durables and sticky non-durables, the sticky price model mimics a fall in the relative price of durable goods observed in the data. Thus, financial frictions such as borrowing and lending constraints make it possible to reconcile the sticky price model with the data. JEL codes: E44, E52, F41, F42
SAT and LP Collaborative Bounded Timing Analysis of Scenario-Based Specifications

Timing analysis of scenario-based specifications (SBS) such as message sequence charts and UML interaction models plays an essential role in the design phase of real-time system development. However, it is time-consuming and labor-intensive to conduct analysis on the satisfiability of the timing constraints. In this article, we propose a novel SAT and linear programming (LP) collaborative timing analysis approach named TASSAT for SBS. Instead of using depth-first traversal algorithms, TASSAT encodes the structures of the SBS into propositional formulas and use the SAT solver to find candidate paths. The timing analysis of candidate paths is then reduced to LP problems, where irreducible infeasible set of the infeasible path can be used to prune unnecessary search space of the SAT solver. The experimental results show that TASSAT is effective and offers better performance than existing tools in terms of both time consumption and memory footprint.
Best Answerers Prediction With Topic Based GAT In Q&A Sites

Q&A communities are playing an important role in online knowledge sharing, where a large number of users with various knowledge background make tremendous contributions to solving many technical problems based on crowd intelligence. However, as new questions are increasingly posted, it is a non-trivial issue to find a matching answerer for each question. As a result, many questions fail to receive satisfying answers in time. This paper addresses the problem by predicting the best answerer for the new question. Many existing efforts are devoted to predicting the best answerer mainly by calculating the textual similarity between questions and a user’s historical post documents. Some works consider other features, such as the similarity of tags between questions and users, the average quality of a user’s historical answers, and so on. But few works consider interaction within the community. In recent years, works that take account of the interaction between community items (such as GCN and GAT) have made considerable progress in graph mining tasks like item recommendation, node representation, node classification, and link prediction. This kind of graph mining method can easily leverage interactive information in the community and encode it in an easy-to-use way which is very helpful for downstream tasks such as recommendation. However, questions that need to be recommended to answerers are new coming ones and with no interaction with any other node in the community yet. How to make reasonable use of collaborative information to improve recommendation performance is a real challenge. In this paper, we use the interactive information between candidate answerers and combine text information to make our best answerer recommendation. There are two main parts, LDA(Latent Dirichlet Allocation) topic model is used to capture the text information and graph attention networks (GATs) for interaction. We evaluated our approach on a real dataset from Stack Exchange. The result shows that our approach outperforms all the baseline methods.
An Empirical Study of Multi-discussing Pattern in Open-Source Software Development

GitHub enables developers to expediently contribute their comments on multiple issues and switch their discussion between issues, i.e., multi-discussing. Discussing multiple issues simultaneously is able to enhance work efficiency. However, multi-discussing also relies on developers’ rationally allocating their focus, which may result in the different influence on the resolution of issues. Therefore, investigating how multi-discussing affects the issue resolution is a meaningful research question that can help developers understand the benefits and limitations of multi-discussing. Using quantitative and qualitative methods, this paper proposes a groundbreaking study of the impact of multi-discussing on issue resolution in GitHub. First, we collect and analyze data from 624 GitHub projects to explore how multi-discussing affects the overall issue resolution of the project. Further, we investigate how multi-discussing affects the resolution of a single issue. We find that multi-discussing is a common behavior in GitHub. Also, multi-discussing is connected to a shorter average issue resolution latency of the project. However, during a single issue resolution, more multi-discussing behaviors tend to bring longer issue resolution latency. We also conduct the qualitative analysis to explore the developers’ experiences and expectations of multi-discussing.
Accelerating Accuracy Improvement for Floating Point Programs via Memory Based Pruning

Floating point programs are widely used in science and engineering. These programs approximate real arithmetic with floating point arithmetic, which introduces rounding errors and leads to inaccurate results. In life-critical software systems, inaccuracy can lead to catastrophes. To avoid these tragedies, program rewriting techniques have been proposed to automatically improve accuracy for floating point programs. Unfortunately, efficiency can be the bottleneck of such techniques due to the lack of effective pruning strategy. We introduce a heuristic pruning strategy called Memory Based Pruning to accelerate these rewrite-based approaches. The heuristic comes from an observation that floating point programs with similar computation steps usually suffer from similar inaccuracy problems, therefore they can be improved by the same or similar rewriting rules. With Memory Based Pruning, rewriting rules used in accuracy improvement are memorized in a knowledge memory. While improving accuracy for similar programs, these rules can help to guide the search and prune away probably useless rewriting rules. Consequently, a large amount of rule examinations can be avoided and the improving efficiency is significantly promoted. Based on the above approach, we have implemented a tool called HMBP and evaluated it on FPBench. In the evaluation, we compare the efficiency of HMBP and the well-known accuracy-improving tool Herbie. The results show that HMBP is 2.32x faster than Herbie in average. For the best case, the speedup is up to 29.64x.
Analysis of the Relative Stabilities of Ortho, Meta, and Para MClY(XC4H4)(PH3)2 Heterometallabenzenes (M = Rh, Ir; X = N, P; Y = Cl and M = Ru, Os; X = N, P; Y = CO)

Density functional theory calculations of the relative stabilities of the ortho, meta, and para MClY(XC4H4)(PH3)2 heterometallabenzenes (M = Rh, Ir; X = N, P; Y = Cl and M = Ru, Os; X = N, P; Y = CO) have been carried out. The ortho isomer is the most stable for X = P, irrespective of the metal M. For X = N and M = Ir, Rh the meta is the lowest-lying isomer, whereas for M = Ru, Os the ortho and meta isomers are almost degenerate. The electronic structure and chemical bonding have been investigated with energy decomposition analyses of the interaction energy between various fragments, to discuss the origin of the differences observed. The values of the multicenter index of aromaticity and nucleus-independent chemical shifts indicate that the heterometallabenzenes studied should be classified as aromatic or slightly aromatic.
Clinical Exome Sequencing Enables Congenital Sialidosis Type II Diagnosis in Two Siblings Presenting with Unreported Clinical Features from a Rare Homozygous Sequence Variant p.(Tyr370Cys) in NEU1

Sialidosis is a rare autosomal recessive disease that presents with progressive lysosomal storage of sialylated glycopeptides and oligosaccharides caused by homozygous or compound heterozygous sequence variants in the neuraminidase 1 (NEU1) gene. These sequence variants can lead to sialidosis type I and II; the latter is the most severe and presents prenatally or at early age. However, sialidosis diagnosis is challenging, especially in those health systems with limited resources of developing countries. Consequently, it is necessary to dip into high-throughput molecular diagnostic tools to allow for an accurate diagnosis with better cost-effectiveness and turnaround time. We report a 4-member pedigree segregating an ultrarare missense variant, c.1109A>G; p.Tyr370Cys, in NEU1 as detected by whole-exome sequencing. Two short-lived siblings, who presented with previously unreported clinical features from such a homozygous sequence variant, were diagnosed with sialidosis type II. Additionally, we present a novel molecular model exhibiting the consequences of the variant in the sialidase-1 tridimensional structure. This study allowed us to provide a definitive diagnosis for our patients, increase our understanding of this pathogenic variant, and improve genetic counseling.
Reply to Blair

Blair provides a thorough review of data he claims stands in opposition to our narrative concerning the origins of IIa40/Early Blue glass trade beads and their presence in arctic Alaska prior to Columbus’ initial voyage. He employs three lines of evidence: historical and archaeological data, Instrumental Neutron Activation Analysis, and radiocarbon dating. Our reply addresses his application of these data sets, clarifying his use of our data to arrive at his conclusions. While we continue to disagree with Blair, we do wish to acknowledge his time spent on debating the issue thereby furthering all of our understanding on this topic.
High-resolution X-ray flash radiography of Ti characteristic lines with multilayer Kirkpatrick–Baez microscope at the Shenguang-II Update laser facility

Abstract High-resolution X-ray flash radiography of Ti characteristic lines with a multilayer Kirkpatrick–Baez microscope was developed on the Shenguang-II (SG-II) Update laser facility. The microscope uses an optimized multilayer design of Co/C and W/C stacks to obtain a high reflection efficiency of the Ti characteristic lines while meeting the precise alignment requirement at the Cu Kα line. The alignment method based on dual simulated balls was proposed herein, which simultaneously realizes an accurate indication of the center field of view and the backlighter position. The optical design, multilayer coatings, and alignment method of the microscope and the experimental result of Ti flash radiography of the Au-coned CH shell target on the SG-II Update are described.
Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience

Generalizing the operation of robots in dynamical environments regardless of the task complexity is one of the ultimate goals of robotics researchers. Learning from demonstration approaches supported by transfer learning and user feedback offer a remarkable solution to achieve generalization. The main idea behind such approaches is teaching robots new skills with human instructors and training parametric models with data from demonstrations to achieve and update the desired skills under changing conditions. Herein, the applications of skill transfer with reinforcement learning algorithms and the effect of user experience (UX) on learning from demonstration approaches are reviewed. This review outlines the importance of considering and evaluating UX during human–robot interaction and, especially, robot teaching. A detailed view on the relations between robot learning and UX is provided and approaches for future improvements are derived. Finally, adaptive autonomy sharing between the robot and the user during teaching is presented as a promising approach to enhance the interaction by exploiting user feedback. In the long run, interactive and user‐centered human–robot skill transfer is expected to reduce cognitive and physical load of the user. Discussion on future research questions aiming to improve learning process and semiautonomous behavior concludes the review.
Multidimensional Analysis of the Green Growth of the European Union Countries in 2019

Abstract Green growth is a new approach to the economy that assumes the efficient use of raw materials while minimizing the negative impact on the environment. The aim of the study is to assess green growth in the European Union countries in 2019. For this purpose, secondary data was used and a multidimensional analysis of sustainable development was performed. The non-pattern model together with the Hellwig and Ward methods were implemented. This enabled a comparison between countries, and their classification due to a similar level of development. Based on the analysis, a large discrepancy in terms of green growth was observed in the examined countries. It was noted that the disproportion may turn out to be a problem in the implementation of the sustainable development policy. The results also showed that the position of the country is reflected in its geographic location.
Isotropic Reconstruction of Electron Tomograms with Deep Learning

Cryogenic electron tomography (cryoET) allows visualization of cellular structures in situ. However, anisotropic resolution arising from the intrinsic “missing-wedge” problem has presented major challenges in visualization and interpretation of tomograms. Here, we have developed IsoNet, a deep learning-based software package that iteratively reconstructs the missing-wedge information and increases signal-to-noise ratio, using the knowledge learned from raw tomograms. Without the need for sub-tomogram averaging, Isonet generates tomograms with significantly reduced resolution anisotropy. Applications of IsoNet to three representative types of cryoET data demonstrate greatly improved structural interpretability: resolving lattice defects in immature HIV particles, establishing architecture of the paraflagellar rod in Eukaryotic flagella, and identifying heptagon-containing clathrin cages inside a neuronal synapse of cultured cells. Therefore, by overcoming two fundamental limitations of cryoET, IsoNet enables functional interpretation of cellular tomograms without sub-tomogram averaging. Its application to high-resolution cellular tomograms should also help identify differently oriented complexes of the same kind for near-atomic resolution sub-tomogram averaging.
A Sequence-based Antibody Paratope Prediction Model Through Combing Local-Global Information and Partner Features

Antibodies are proteins which play a vital role in the immune system by recognizing and neutralizing antigens. The region on the antibody binding to an antigen, known as paratope, mediates antibody-antigen interaction with high affinity and specificity. And the accurate prediction of those regions from antibody sequence contributes to the design of therapeutic antibodies and remains challenging. However, the experimental methods are time-consuming and expensive. In this article, we propose a sequence-based method for antibody paratope prediction by combing local and global information of antibody sequence and partner features from partner antigen sequence. Convolution Neural Networks(CNNs) and a sliding window approach on antibody sequence are used to extract local information. Attention-based Bidirectional Long Short-Term Memory (Att-BLSTM) on antibody sequence are used to extract global information. Also, the partner antigen is vital for paratope prediction, and we employ Att-BLSTM on the partner antigen sequence as well. The outputs of CNNs and Att-BLSTM networks are combined to predict antibody paratope by fully-connected networks. The experiments show that our proposed method achieves superior performance over the state-of-the-art sequenced-based antibody paratope prediction methods on benchmark datasets.
The ASC Speck and NLRP3 Inflammasome Function Are Spatially and Temporally Distinct

Although considered the ternary inflammasome structure, whether the singular, perinuclear NLRP3:ASC speck is synonymous with the NLRP3 inflammasome is unclear. Herein we report that the NLRP3:ASC speck is not required for nigericin-induced inflammasome activation, but facilitates and maximizes IL-1β processing. Further, the NLRP3 agonists H2O2 and MSU elicited IL-1β maturation without inducing specks. Notably, caspase-1 activity is spatially distinct from the speck, occurring at multiple cytoplasmic sites. Additionally, caspase-1 activity negatively regulates speck frequency and speck size while speck numbers and IL-1β processing are negatively correlated, cyclical, and can be uncoupled by NLRP3 mutations or inhibiting microtubule polymerization. Finally, when specks are present, caspase-1 is likely activated after leaving the speck structure. Thus, the speck is not the NLRP3 inflammasome itself, but is instead a dynamic structure which may amplify the NLRP3 response to weak stimuli by facilitating the formation and release of small NLRP3:ASC complexes which in turn activate caspase-1.