Using <i>Grammarly</i> to Enhance Students’ Academic Writing Skills

The paper aims to present the results of the experiment in applying the online writing assistant Grammarly.com to evaluate ESP students’ essay writing skills. One hundred master students’ papers were processed by the application to identify persisting errors at a master’s level. Quantitative and qualitative methods enabled the researchers to analyze the essays by setting five parameters: audience, formality, domain, tone, and intent. At the other end, the application broke down the outcome by five measurable factors: correctness, clarity, delivery, engagement, and style issues. The representative number of the essays fed into Grammarly.com provided a vivid and reliable picture of which lexis, grammar, structure, or style issues still need addressing. The most common mistakes detected by Grammarly.com were punctuation, wordy sentences, redundancy, and the abundance of personal pronouns in a formal style. They show that the gaps in students’ academic writing need a remedial course. Another objective of the research was to explore the potential of the online writing tool for students’ self-study. Grammarly.com cannot do work for students: it cannot think for them, neither can it write for them, but it can help learners identify the reoccurring writing problems, eliminate them, and monitor the progress. The application could be particularly useful for advanced students. The functionality of the Grammarly premium version allows for a choice of styles, type of addressee, tone of writing, and many other nuances, which could be beneficial not only for studies but in future professional life. Nonetheless, despite Grammarly’s advanced features, it only suggests a better variant, sometimes it errs, and in no way is it a substitute for a teacher

Subunit Mobility and the Chaperone Activity of Recombinant αB-Crystallin

The comparison of the chaperone-like activity of native and covalently cross-linked human αB-crystallins has confirmed the important role of the subunit mobility in the chaperoning mechanism. Our data clearly demonstrate that the chaperone-like activity of α-crystallin is not only a surface phenomenon as was suggested by some researchers

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid over-fitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian matrix factorization algorithm using stochastic gradient MCMC. Our algorithm, based on Distributed Stochastic Gradient Langevin Dynamics, can not only match the prediction accuracy of standard MCMC methods like Gibbs sampling, but at the same time is as fast and simple as stochastic gradient descent. In our experiments, we show that our algorithm can achieve the same level of prediction accuracy as Gibbs sampling an order of magnitude faster. We also show that our method reduces the prediction error as fast as distributed stochastic gradient descent, achieving a 4.1% improvement in RMSE for the Netflix dataset and an 1.8% for the Yahoo music dataset

Perturbed Rotations of a Rigid Body Close to the Lagrange Case under the Action of Unsteady Perturbation Torques

Perturbed rotations of a rigid body close to the Lagrange case under the action of perturbation torques slowly varying in time are investigated. Conditions are presented for the possibility of averaging the equations of motion with respect to the nutation angle and the averaged system of equations of motion is obtained. In the case of the rotational motion of the body in the linear-dissipative medium the numerical integration of the averaged system of equations is conducted

The trehalose coating effect on the internal protein dynamics

15N and 13C NMR experiments were applied to conduct a comparative study of a cold shock protein (Csp) in two states - lyophilized powder and a protein embedded in a glassy trehalose matrix. Both samples were studied at various levels of rehydration. The experiments used (measuring relaxation rates R 1 and R 1ρ, motionally averaged dipolar couplings and solid state exchange method detecting reorientation of the chemical shift anisotropy tensor) allow obtaining abundant information on the protein structural features and internal motions in a range of correlation times from nanoseconds to seconds. The main results are: (a) the trehalose coating makes the protein structure more native in comparison with the dehydrated lyophilized powder, however, trehalose still cannot remove all non-native hydrogen bonds which are present in a dehydrated protein; (b) trehalose has an appreciable effect on the internal dynamics: the motion of the backbone N-H groups in the nanosecond and microsecond time scales becomes slower while the motional amplitude remains constant; (c) upon adding water to the Csp-trehalose mixture, water molecules accumulate around proteins forming a layer between the protein surface and the trehalose matrix. The protein dynamics become faster, however, not as fast as in the fully hydrated state; (d) the hydration response of dynamics of the NH and CH(CH 2) groups in a protein is qualitatively different: upon increasing protein hydration, the correlation times of the N-H motions become shorter and the amplitude remains stable, and for CH(CH 2) groups the motional amplitude increases and the correlation times do not change. This can be explained by a different ability of the NH and CH(CH 2) groups to form hydrogen bonds. © the Owner Societies 2012

Online Convex Optimization Using Predictions

Making use of predictions is a crucial, but under-explored, area of online algorithms. This paper studies a class of online optimization problems where we have external noisy predictions available. We propose a stochastic prediction error model that generalizes prior models in the learning and stochastic control communities, incorporates correlation among prediction errors, and captures the fact that predictions improve as time passes. We prove that achieving sublinear regret and constant competitive ratio for online algorithms requires the use of an unbounded prediction window in adversarial settings, but that under more realistic stochastic prediction error models it is possible to use Averaging Fixed Horizon Control (AFHC) to simultaneously achieve sublinear regret and constant competitive ratio in expectation using only a constant-sized prediction window. Furthermore, we show that the performance of AFHC is tightly concentrated around its mean

Clinical case of de novo anaplastic ganglioglioma and current status of the problem

The authors report a rare case of de novo malignant ganglioglioma (WHO grade III) in a 26-year old female. The patient has complained of periodic feeling fear, anxiety, episodes of impaired consciousness with extremity muscle cramps sometimes followed by urination, as well as flashes before eyes. Computed tomography perfusion and magnetic resonance spectroscopy were carried out for differential diagnosis between different types of tumors. Stereotactic biopsy was performed for histological examination. High surgical risk became a contraindication to gross total resection of the tumor. The patient has received radiation therapy (Trilogy linear accelerator) in a total dose of 60 Gy. The tumor shrank significantly. In 7 months, monitoring MRT did not detect further growth of the tumor. The authors have analyzed the case and reviewed the existing literature data regarding gangliogliomas. Taking into account low prevalence of these tumors (0.4-1% of all brain tumors), especially of their malignant forms (3-10% of gangliogliomas), lack of sufficient data regarding prognostic factors, life expectancy, time of recurrence, lack of accurate indications for different methods of treatment (surgery, radiation, chemotherapy), these tumors still need further research that should also involve supplementary neuroimaging techniques and stereotactic biopsy

COMFORTABLE RESOURCE-ENERGY-SAVING SYSTEMS OF HEATING AND VENTILATION IN RESIDENTIAL BUILDINGS

Рассмотрены системы поквартирного отопления и вентиляции жилых зданий с целью обеспечения комфортного микроклимата в помещениях квартиры во все периоды года и даны рекомендации по выбору энергоэффективного ресурсо-энергосберегающего и экономически выгодного варианта компоновки этих инженерных систем, что способствует охране окружающей среды в результате уменьшения выбросов тёплого воздуха в атмосферу системами вытяжной вентиляции.=The issue of the systems of apartment heating and ventilation of residential buildings are considered in order to ensure a comfortable microclimate in the premises of the apartment during all seasons, given recommendations on the choice of an energy-efficient, resource-energy-saving and cost-effective option for the layout of these engineering systems, which contributes to environmental protection by reducing warm air emissions into the atmosphere by exhaust ventilation systems

Motor step size and ATP coupling efficiency of the dsDNA translocase EcoR124I

The Type I restriction-modification enzyme EcoR124I is an archetypical helicase-based dsDNA translocase that moves unidirectionally along the 3′–5′ strand of intact duplex DNA. Using a combination of ensemble and single-molecule measurements, we provide estimates of two physicochemical constants that are fundamental to a full description of motor protein activity—the ATP coupling efficiency (the number of ATP consumed per base pair) and the step size (the number of base pairs transported per motor step). Our data indicate that EcoR124I makes small steps along the DNA of 1 bp in length with 1 ATP consumed per step, but with some uncoupling of the ATPase and translocase cycles occurring so that the average number of ATP consumed per base pair slightly exceeds unity. Our observations form a framework for understanding energy coupling in a great many other motors that translocate along dsDNA rather than ssDNA