Miracle-dz/UniFAR-FTUs huggingface dataset:
A Model for Analyzing Changes in Systems Development Practices

This paper introduces an empirically grounded model for analyzing intended and unintended changes in the prevalence of information systems development practices. In the model, any development practice observable in a development organization can be analyzed according to two dimensions: the intended scope of defined practices versus the actual scope of enacted practices. Furthermore, the model identifies eight types of change paths in systems development practices based on the two dimensions: emergence, entropy, initiation, abandonment, formalization, informalization, implementation, and recalcitrance. The eight types of change paths provide an integrated theoretical model for understanding how systems development practices can change in organizations and projects and among individual developers in a given context. The paper concludes by discussing how the model complements and integrates concepts of the contemporary research on systems development practices and outlines its potential uses for future research.
The Sociocultural Factors of Russian Stagnation and Modernization

This analysis of the third stage of the transformation of Russian society—modernization—looks at sociocultural spheres that are stagnant and act as brakes on modernization, and examines the hierarchy of the basic values of Russia's population. It reveals the systemic gap between the human dimensions of stagnation in Russia and modernization in the developed countries of Europe, and offers a general sociocultural strategy for the modernization of Russia.
(BV,L p )-decomposition, p = 1,2, of functions in metric random walk spaces

Abstract In this paper we study the ( BV , L p ) {(\mathrm{BV},L^{p})} -decomposition, p = 1 , 2 {p=1,2} , of functions in metric random walk spaces, a general workspace that includes weighted graphs and nonlocal models used in image processing. We obtain the Euler-Lagrange equations of the corresponding variational problems and their gradient flows. In the case p = 1 {p=1} we also study the associated geometric problem and the thresholding parameters describing the behavior of its solutions.
Numerical Study on the Effect of Single Shallow Circumferential Groove Casing Treatment on the Flow Field and the Stability of a Transonic Compressor

The present research investigates the effect of the location and the width of single shallow circumferential groove casing treatment on the flow field and the stability improvement of NASA Rotor 37 utilizing the help of computational fluid dynamics. At first, steady state simulation of Rotor37 was presented for smooth casing (without groove). Then, forty five various grooved casing were simulated and compared with the smooth casing. The results indicated that narrow grooves had slight effect on the adiabatic efficiency but as the width of the groove was increased, a decline in efficiency was observed. The investigation on the stall margin revealed that narrow grooves next to the leading edge could improve the stall margin by a reduction in the size of vortex breakdown zone. Medium-width grooves displayed an effective role in delaying the separationproduced by shock wave and boundary layer interactionon the blade suction side near the casing. This type of grooves could improve the stall margin more than narrow grooves when located on the top of separation zone near the blade suction side. Wide grooves had negative effect on the stall margin and caused a significant drop in the efficiency and the total pressure ratio of the compressor.
Lithium intercalation drives mechanical properties deterioration in bulk and single-layered black phosphorus: a first-principles study

It is of critical importance to understand the mechanical properties change of electrode materials during lithium intercalation in the mechanical design of Li-ion batteries (LIBs), for the purpose of the high reliability and safety in their applications. Here, we investigated the mechanical properties of both bulk and single-layered black phosphorus (BP) during the lithium intercalation process by using the first-principles calculations. Our results show that the Young’s modulus of bulk and single-layered phosphorus strongly depends on the lithium intercalation. The mechanical bearing capacities, such as critical strain and stress, are significantly reduced by several times after lithium intercalation in both bulk and single-layered BP, which may reduce the reliability of LIBs. Our findings suggest that this notable mechanical properties deterioration during lithium intercalation should be considered carefully in the mechanical design of LIBs, in order to keep the work reliable and safe in the charge-discharge process.
Virtual Motion Camouflage Based Nonlinear Constrained Optimal Trajectory Design Method

Nonlinear constrained optimal trajectory control is an important and fundamental area of research that continues to advance in numerous fields. Many attempts have been made to present new methods that can solve for optimal trajectories more efficiently or to improve the overall performance of existing techniques. This research presents a recently developed bio-inspired method called the Virtual Motion Camouflage (VMC) method that offers a means of quickly finding, within a defined but varying search space, the optimal trajectory that is equal or close to the optimal solution. The research starts with the polynomial-based VMC method, which works within a search space that is defined by a selected and fixed polynomial type virtual prey motion. Next will be presented a means of improving the solution’s optimality by using a sequential based form of VMC, where the search space is adjusted by adjusting the polynomial prey trajectory after a solution is obtained. After the search space is adjusted, an optimization is performed in the new search space to find a solution closer to the global space optimal solution, and further adjustments are made as desired. Finally, a B-spline augmented VMC method is presented, in which a B-spline curve represents the prey motion and will allow the search space to be optimized together with the solution trajectory. It is shown that (1) the polynomial based VMC method will significantly reduce the overall problem dimension, which in practice will significantly reduce the computational cost associated with solving nonlinear constrained optimal trajectory problems; (2) the sequential VMC method will improve the solution optimality by sequentially refining certain parameters, such as the prey motion; and (3) the B-spline augmented VMC method will improve the solution iv optimality without sacrificing the CPU time much as compared with the polynomial based approach. Several simulation scenarios, including the Breakwell problem, the phantom track problem, the minimum-time mobile robot obstacle avoidance problem, and the Snell’s river problem are simulated to demonstrate the capabilities of the various forms of the VMC algorithm. The capabilities of the B-spline augmented VMC method are also shown in a hardware demonstration using a mobile robot obstacle avoidance testbed.
K2-146: Discovery of Planet c, Precise Masses from Transit Timing, and Observed Precession

K2-146 is a mid-M dwarf (M⋆ = 0.331 ± 0.009M⊙; R⋆ = 0.330 ± 0.010R⊙), observed in Campaigns 5, 16, and 18 of the K2 mission. In Campaign 5 data, a single planet was discovered with an orbital period of 2.6 days and large transit timing variations due to an unknown perturber. Here, we analyze data from Campaigns 16 and 18, detecting the transits of a second planet, c, with an orbital period of 4.0 days, librating in a 3:2 resonance with planet b. Large, anticorrelated timing variations of both planets exist due to their resonant perturbations. The planets have a mutual inclination of 2. °40 ± 0. °25, which torqued planet c more closely into our line of sight. Planet c was grazing in Campaign 5 and thus missed in previous searches; it is fully transiting in Campaigns 16 and 18, and its transit depth is three times larger. We improve the stellar properties using data from Gaia DR2, and use dynamical fits to find that both planets are sub-Neptunes: their masses are 5.77 ± 0.18 and 7.50 ± 0.23M⊕, and their radii are 2.04 ± 0.06 and 2.19 ± 0.07 R⊕, respectively. These mass constraints set the precision record for small exoplanets (a few gas giants have comparable relative precision). These planets lie in the photoevaporation valley when viewed in Radius–Period space, but due to the low-luminosity M-dwarf host star, they lie among the atmosphere-bearing planets when viewed in Radius–Irradiation space. This, along with their densities being 60–80% that of Earth, suggests that they may both have retained a substantial gaseous envelope.
Temperature and fluid velocity on the freeze-out surface from 
π
, 
K
, and 
p
 spectra in 
pp
, 
p
-Pb, and Pb-Pb collisions

We present a new approach to take into account resonance decays in the blast-wave model fits of identified hadron spectra. Thanks to pre-calculated decayed particle spectra, we are able to extract, in a matter of seconds, the multiplicity dependence of the single freeze-out temperature $T_{\rm fo}$, average fluid velocity $\left $, velocity exponent $n$, and the volume $dV/dy$ of an expanding fireball. In contrast to blast-wave fits without resonance feed-down, our approach results in a freeze-out temperature of $T_{\rm fo}\approx 150\,\text{MeV}$, which has only weak dependence on multiplicity and collision system. Finally, we discuss separate chemical and kinetic freeze-outs separated by partial chemical equilibrium.
Applying Formal Modelling to the Specification and Testing of SDN Network Functionality

Software Defined Networks offers a new paradigm to manage networks, one that favors centralised control over the distributed control used in legacy networks. This brings network operators potential efficiencies in capital investment, operating costs and wider choice in network appliance providers. We explore in this research whether these efficiencies apply to all network functionality by applying formal modelling to create a mathematically rigourous model of a service, a firewall, and using that model to derive tests that are ultimately applied to two SDN firewalls and a legacy stateful firewall. In the process we discover the only publicly available examples of SDN firewalls are not equivalent to legacy stateful firewalls and in fact create a security flaw that may be exploited by an attacker.
Are performance appraisal ratings from different rating sources comparable

The purpose of this study was to test whether a multisource performance appraisal instrument exhibited measurement invariance across different groups of raters. Multiple-groups confirmatory factor analysis as well as item response theory (IRT) techniques were used to test for invariance of the rating instrument across self, peer, supervisor, and subordinate raters. The results of the confirmatory factor analysis indicated that the rating instrument was invariant across these rater groups. The IRT analysis yielded some evidence of differential item and test functioning, but it was limited to the effects of just 3 items and was trivial in magnitude. Taken together, the results suggest that the rating instrument could be regarded as invariant across the rater groups, thus supporting the practice of directly comparing their ratings. Implications for research and practice are discussed, as well as for understanding the meaning of between-source rating discrepancies.
Changing Paradigms in Cell Biology: Their Implication and Possible Applications

The evolution of cell biology in the 20th century has evoked some remarkable changes in the existing paradigms. The discovery of alternative splicing, overlapping genes and protein splicing has shifted the one gene-one protein paradigm to several proteins. Proteins are no more the only catalytic macromolecule since the discovery of ribozymes. Genetic material was known to be stable in the genome and not mobile until the discovery of transposons. RNA editing has made possible the identification of certain missing genes and viruses are no longer considered the smallest infections agents after prions were discovered. Though not conclusive, recent findings suggest the possibility of transcription to occur in the nucleus. All these ground breaking discoveries are making substantial breakthrough in biological sciences particularly in understanding some cellular processes, their mechanisms on gene expression and regulation as well as the pathogenesis of certain illnesses. Also, these discoveries have revealed some potential drug targets and presently, some of the implicated biomolecules are being exploited for various pharmaceutical and biomedical applications.
Large-Scale Hierarchical Alignment for Data-driven Text Rewriting

We propose a simple unsupervised method for extracting pseudo-parallel monolingual sentence pairs from comparable corpora representative of two different text styles, such as news articles and scientific papers. Our approach does not require a seed parallel corpus, but instead relies solely on hierarchical search over pre-trained embeddings of documents and sentences. We demonstrate the effectiveness of our method through automatic and extrinsic evaluation on text simplification from the normal to the Simple Wikipedia. We show that pseudo-parallel sentences extracted with our method not only supplement existing parallel data, but can even lead to competitive performance on their own.
Social media as a student response system: new evidence on learning impact

The ubiquitousness of social media renders it a potentially powerful tool in higher education. This study explores the use of Twitter as a tool to enhance active learning and improve feedback during large-sized lectures. Students in a final-year undergraduate accounting course at an Australian university engaged in Twitter-based synchronous activities, including answering in-lecture quizzes and posting questions. This study explores two key questions: (1) ‘what encourages students to actively utilise social media in their learning process? ’ and (2) ‘what pedagogical advantages are offered by social media in enhancing students’ learning experiences? ’ Results of a student survey administered at the end of the course show that (1) students are more likely to participate in in-lecture Twitter activities if they are familiar with the technology, (2) Twitter activities encourage students to participate in active learning, (3) Twitter provides a platform enabling two-way student–instructor communication and (4) students find Twitter activities helpful regardless of whether they attend the lecture in real time or view online lecture recordings. These findings deepen our understanding of the pedagogical benefits of using Twitter as a student response system, which will assist educators to better harness the power of social media in the learning–teaching process. Published: 27 April 2018 Citation: Research in Learning Technology 2018, 26 : 2043 - http://dx.doi. org/10.25304/rlt.v26. 2043
Classifying exoplanet candidates with convolutional neural networks: application to the Next Generation Transit Survey

Vetting of exoplanet candidates in transit surveys is a manual process, which suffers from a large number of false positives and a lack of consistency. Previous work has shown that convolutional neural networks (CNN) provide an efficient solution to these problems. Here, we apply a CNN to classify planet candidates from the Next Generation Transit Survey (NGTS). For training data sets we compare both real data with injected planetary transits and fully simulated data, as well as how their different compositions affect network performance. We show that fewer hand labelled light curves can be utilized, while still achieving competitive results. With our best model, we achieve an area under the curve (AUC) score of $(95.6\pm {0.2}){{\ \rm per\ cent}}$ and an accuracy of $(88.5\pm {0.3}){{\ \rm per\ cent}}$ on our unseen test data, as well as $(76.5\pm {0.4}){{\ \rm per\ cent}}$ and $(74.6\pm {1.1}){{\ \rm per\ cent}}$ in comparison to our existing manual classifications. The neural network recovers 13 out of 14 confirmed planets observed by NGTS, with high probability. We use simulated data to show that the overall network performance is resilient to mislabelling of the training data set, a problem that might arise due to unidentified, low signal-to-noise transits. Using a CNN, the time required for vetting can be reduced by half, while still recovering the vast majority of manually flagged candidates. In addition, we identify many new candidates with high probabilities which were not flagged by human vetters.
Resolution requirements and resolution problems in simulations of radiative feedback in dusty gas

In recent years a number of authors have introduced methods to model the effects of radiation pressure feedback on flows of interstellar and intergalactic gas, and have posited that the forces exerted by stars' radiation output represents an important feedback mechanism capable of halting accretion and thereby regulating star formation. However, numerical simulations have reached widely varying conclusions about the effectiveness of this feedback. In this paper I show that much of the divergence in the literature is a result of failure to obey an important resolution criterion: whether radiation feedback is able to reverse an accretion flow is determined on scales comparable to the dust destruction radius, which is $\lesssim 1000$ AU even for the most luminous stellar sources. Simulations that fail to resolve this scale can produce unphysical results, in many cases leading to a dramatic overestimate of the effectiveness of radiation feedback. Most published simulations of radiation feedback on molecular cloud and galactic scales fail to satisfy this condition. I show how the problem can be circumvented by introducing a new subgrid model that explicitly accounts for momentum balance on unresolved scales, making it possible to simulate dusty accretion flows safely even at low resolution.
Weakly Supervised Recognition of Surgical Gestures

Kinematic trajectories recorded from surgical robots contain information about surgical gestures and potentially encode cues about surgeon’s skill levels. Automatic segmentation of these trajectories into meaningful action units could help to develop new metrics for surgical skill assessment as well as to simplify surgical automation. State-of-the-art methods for action recognition relied on manual labelling of large datasets, which is time consuming and error prone. Unsupervised methods have been developed to overcome these limitations. However, they often rely on tedious parameter tuning and perform less well than supervised approaches, especially on data with high variability such as surgical trajectories. Hence, the potential of weak supervision could be to improve unsupervised learning while avoiding manual annotation of large datasets. In this paper, we used at a minimum one expert demonstration and its ground truth annotations to generate an appropriate initialization for a GMM-based algorithm for gesture recognition. We showed on real surgical demonstrations that the latter significantly outperforms standard task-agnostic initialization methods. We also demonstrated how to improve the recognition accuracy further by redefining the actions and optimising the inputs.
Painting halos from cosmic density fields of dark matter with physically motivated neural networks

We present a novel halo painting network that learns to map approximate 3D dark matter fields to realistic halo distributions. This map is provided via a physically motivated network with which we can learn the non-trivial local relation between dark matter density field and halo distributions without relying on a physical model. Unlike other generative or regressive models, a well motivated prior and simple physical principles allow us to train the mapping network quickly and with relatively little data. In learning to paint halo distributions from computationally cheap, analytical and non-linear density fields, we bypass the need for full particle mesh simulations and halo finding algorithms. Furthermore, by design, our halo painting network needs only local patches of dark matter density to predict the halos, and as such, it can predict the 3D halo distribution for any arbitrary simulation box size. Our neural network can be trained using small simulations and used to predict large halo distributions, as long as the resolutions are equivalent. We evaluate our model's ability to generate 3D halo count distributions which reproduce, to a high degree, summary statistics such as the power spectrum and bispectrum, of the input or reference realizations.
A stochastic process on a network with connections to Laplacian systems of equations

Abstract We study an open discrete-time queueing network. We assume data is generated at nodes of the network as a discrete-time Bernoulli process. All nodes in the network maintain a queue and relay data, which is to be finally collected by a designated sink. We prove that the resulting multidimensional Markov chain representing the queue size of nodes has two behavior regimes depending on the value of the rate of data generation. In particular, we show that there is a nontrivial critical value of the data rate below which the chain is ergodic and converges to a stationary distribution and above which it is non-ergodic, i.e., the queues at the nodes grow in an unbounded manner. We show that the rate of convergence to stationarity is geometric in the subcritical regime.
Factored LT and Factored Raptor Codes for Large-Scale Distributed Matrix Multiplication

We propose two coding schemes for distributed matrix multiplication in the presence of stragglers. These coding schemes are adaptations of Luby Transform (LT) codes and Raptor codes to distributed matrix multiplication and are termed Factored LT (FLT) codes and Factored Raptor (FRT) codes. We show that all nodes in the Tanner graph of a randomly sampled code have a tree-like neighborhood with high probability. This ensures that the density evolution analysis gives a reasonable estimate of the average recovery threshold of FLT codes. The recovery threshold of the proposed FLT codes is asymptotically optimal when the output degree distribution is Soliton. Empirically, we show that FRT codes have an excellent recovery threshold while the number of worker nodes is moderately large. In addition, using Azuma–Hoeffding inequality, we derive concentration results to show that the recovery threshold of a randomly chosen FLT code is close to the ensemble average. FLT and FRT codes have better recovery thresholds when compared to Product codes and they are expected to have better numerical stability when compared to Polynomial codes, while they can also be decoded with a low-complexity decoding algorithm. Finally, the proposed codes are better matched to the practically important case of sparse matrix-matrix multiplication as compared to many previous schemes.