Why and how developers fork what from whom in GitHub

Forking is the creation of a new software repository by copying another repository. Though forking is controversial in traditional open source software (OSS) community, it is encouraged and is a built-in feature in GitHub. Developers freely fork repositories, use codes as their own and make changes. A deep understanding of repository forking can provide important insights for OSS community and GitHub. In this paper, we explore why and how developers fork what from whom in GitHub. We collect a dataset containing 236,344 developers and 1,841,324 forks. We make surveys, and analyze programming languages and owners of forked repositories. Our main observations are: (1) Developers fork repositories to submit pull requests, fix bugs, add new features and keep copies etc. Developers find repositories to fork from various sources: search engines, external sites (e.g., Twitter, Reddit), social relationships, etc. More than 42 % of developers that we have surveyed agree that an automated recommendation tool is useful to help them pick repositories to fork, while more than 44.4 % of developers do not value a recommendation tool. Developers care about repository owners when they fork repositories. (2) A repository written in a developer’s preferred programming language is more likely to be forked. (3) Developers mostly fork repositories from creators. In comparison with unattractive repository owners, attractive repository owners have higher percentage of organizations, more followers and earlier registration in GitHub. Our results show that forking is mainly used for making contributions of original repositories, and it is beneficial for OSS community. Moreover, our results show the value of recommendation and provide important insights for GitHub to recommend repositories.     

Polymorphic protein expression (profile) in numigall

Ten protein and enzyme polymorphic systems, viz. haemoglobin, albumin, transferrin, adenosine deaminase, adenylate kinase phosphoglucomutase, esterase-D, glyoxalase, alkaline phosphatase and amylase were studied in numigall (guinea fowl x chicken hybrids) to assess structural gene expression and regulatory gene divergence between the parental species. The investigation revealed presence of both the maternal and paternal electrophoretic components in case of adenosine deaminase, alkaline phosphatase, amylase, albumin and transferrin although no clear differences could be identified for haemoglobin and glyoxalase. Esterase-D and adenylate kinase phenotypes showed a dominance of the chicken type.     

Magnesium potassium phosphate ceramic for Tc immobilization

Technetium-99, present in the US Department of Energy’s (DOE) high-level waste (HLW) as a by-product of fission reactions, poses a serious environmental threat because it has a long half-life, is highly mobile in its soluble Tc⁷⁺ oxidation state and is volatile at high temperatures. Magnesium potassium phosphate (MKP) ceramics have been developed to treat ⁹⁹Tc that has been partitioned and eluted from simulated high-level tank wastes by means of sorption processes. Waste forms were fabricated by adding MKP binder and a reducing agent (SnCl₂) to the ⁹⁹Tc-containing aqueous waste. In addition, waste forms were fabricated by first precipitating ⁹⁹Tc from the waste and subsequently solidifying it in MKP. ⁹⁹Tc loadings in the waste forms were as high as 900 ppm by weight. Waste form performance was established through various strength, leaching, and durability tests. Long-term leaching studies, as per the ANS 16.1 procedure, showed leachability indices between 11 and 14 for ⁹⁹Tc under ambient conditions. The normalized leach rate for ⁹⁹Tc, according to the product consistency test, was as low as 1.1 × 10⁻³ g/m² d. The waste forms exhibited a compressive strength of ≈30 MPa and were durable in an aqueous environment. Containment of ⁹⁹Tc in MKP ceramics is believed to be due to a combination of appropriate reducing environment (determined from Eh-pH measurements) and microencapsulation in a dense matrix.     

Incremental maintenance of aggregate and outerjoin expressions

Views stored in a data warehouse need to be kept current. As recomputing the views is very expensive, incremental maintenance algorithms are required. Over recent years, several incremental maintenance algorithms have been proposed. None of the proposed algorithms handle the general case of relational expressions involving aggregate and outerjoin operators efficiently.     

On the expansion of a penny-shaped crack by a rigid circular disc inclusion

This paper examines the problem of the symmetric indentation of a penny-shaped crack by a smoothly embedded rigid circular thin disc inclusion. The analysis of the problem yields a system of triple integral equations which are solved in an approximate manner. An expression for the stress intensity factor at the boundary of the penny-shaped crack is evaluated in the form of a series which involves the ratio of the radius of the rigid circular inclusion to the radius of the penny-shaped crack.

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Résumé Dans le mémoire, on examine le problème du marquage symétrique d'une fissure en angle noyée par une inclusion mince et lisse, en forme de disque circulaire rigide. L'analyse du problème conduit à un système d'équations intégrales triples, que l'on résoud par approximations. On obtient une expression du facteur d'intensité de contrainte aux frontières de la fissure sous la forme d'une série comportant le rapport du rayon de l'inclusion rigide circulaire au rayon de la fissure.

     

Dynamic-CoMPI: dynamic optimization techniques for MPI parallel applications

This work presents an optimization of MPI communications, called Dynamic-CoMPI, which uses two techniques in order to reduce the impact of communications and non-contiguous I/O requests in parallel applications. These techniques are independent of the application and complementaries to each other. The first technique is an optimization of the Two-Phase collective I/O technique from ROMIO, called Locality aware strategy for Two-Phase I/O (LA-Two-Phase I/O). In order to increase the locality of the file accesses, LA-Two-Phase I/O employs the Linear Assignment Problem (LAP) for finding an optimal I/O data communication schedule. The main purpose of this technique is the reduction of the number of communications involved in the I/O collective operation. The second technique, called Adaptive-CoMPI, is based on run-time compression of MPI messages exchanged by applications. Both techniques can be applied on every application, because both of them are transparent for the users. Dynamic-CoMPI has been validated by using several MPI benchmarks and real HPC applications. The results show that, for many of the considered scenarios, important reductions in the execution time are achieved by reducing the size and the number of the messages. Additional benefits of our approach are the reduction of the total communication time and the network contention, thus enhancing, not only performance, but also scalability.     

Learning Noise-Assisted Robust Image Features for Fine-Grained Image Retrieval

Fine-grained image search is one of the most challenging tasks in computer vision that aims to retrieve similar images at the fine-grained level for a given query image. The key objective is to learn discriminative fine-grained features by training deep models such that similar images are clustered, and dissimilar images are separated in the low embedding space. Previous works primarily focused on defining local structure loss functions like triplet loss, pairwise loss, etc. However, training via these approaches takes a long training time, and they have poor accuracy. Additionally, representations learned through it tend to tighten up in the embedded space and lose generalizability to unseen classes. This paper proposes a noise-assisted representation learning method for fine-grained image retrieval to mitigate these issues. In the proposed work, class manifold learning is performed in which positive pairs are created with noise insertion operation instead of tightening class clusters. And other instances are treated as negatives within the same cluster. Then a loss function is defined to penalize when the distance between instances of the same class becomes too small relative to the noise pair in that class in embedded space. The proposed approach is validated on CARS-196 and CUB-200 datasets and achieved better retrieval results (85.38% recall@1 for CARS-196% and 70.13% recall@1 for CUB-200) compared to other existing methods.     

Optimal coverage of an infrastructure network using sensors with distance-decaying sensing quality

Motivated by recent applications of wireless sensor networks in monitoring infrastructure networks, we address the problem of optimal coverage of infrastructure networks using sensors whose sensing performance decays with distance. We show that this problem can be formulated as a continuous p-median problem on networks. The literature has addressed the discrete p-median problem   on networks and in continuum domains, and the continuous p$p$-median problem in continuum domains extensively. However, in-depth analysis of the continuous p$p$-median problem on networks has been lacking. With the sensing performance model that decays with distance, each sensor covers a region equivalent to its Voronoi partition on the network in terms of the shortest path distance metric. Using Voronoi partitions, we define a directional partial derivative of the coverage metric with respect to a sensor’s location. We then propose a gradient descent algorithm to obtain a locally optimal solution with guaranteed convergence. The quality of an optimal solution depends on the choice of the initial configuration of sensors. We obtain an initial configuration using two approaches: by solving the discrete p$p$-median problem on a lumped   network and by random sampling. We consider two methods of random sampling: uniform sampling and D²$D^2$-sampling. The first approach with the initial solution of the discrete p$p$-median problem leads to the best coverage performance for large networks, but at the cost of high running time. We also observe that the gradient descent on the initial solution with the D²$D^2$-sampling method yields a solution that is within at most 7% of the previous solution and with much shorter running time.