Synthesis and Characterization of Nanostructured WC-Co/Al Powder Prepared by Mechanical Alloying

Nanostructured WC-Co/Al powder was synthesized from WC-12Co powder and pure Al powder by mechanical alloying (MA). The morphology and microstructural evolution of WC-Co/Al powder were investigated by a series of characterization methods. The results showed that the β-Co phase in the initial WC-12Co powder was replaced by the AlxCo phases (such as Al9Co2 and Al13Co4). As the ball milling time increased, the average grain size of WC in the WC-Co/Al powder decreased firstly and then remained at a constant value of around 40 nm. The deposition behavior of powders sprayed by high velocity oxygen fuel (HVOF) spraying was investigated. During spraying, the WC-Co/Al powder had a better flattening than the WC-12Co powder without ball milling, which is beneficial to fabricate compact coatings with lower porosity

Learning Personalized Story Evaluation

While large language models (LLMs) have shown impressive results for more objective tasks such as QA and retrieval, it remains nontrivial to evaluate their performance on open-ended text generation for reasons including (1) data contamination; (2) multi-dimensional evaluation criteria; and (3) subjectiveness stemming from reviewers' personal preferences. To address such issues, we propose to model personalization in an uncontaminated open-ended generation assessment. We create two new datasets Per-MPST and Per-DOC for personalized story evaluation, by re-purposing existing datasets with proper anonymization and new personalized labels. We further develop a personalized story evaluation model PERSE to infer reviewer preferences and provide a personalized evaluation. Specifically, given a few exemplary reviews from a particular reviewer, PERSE predicts either a detailed review or fine-grained comparison in several aspects (such as interestingness and surprise) for that reviewer on a new text input. Experimental results show that PERSE outperforms GPT-4 by 15.8% on Kendall correlation of story ratings, and by 13.7% on pairwise preference prediction accuracy. Both datasets and code will be released.Comment: 19 page

End-to-end Story Plot Generator

Story plots, while short, carry most of the essential information of a full story that may contain tens of thousands of words. We study the problem of automatic generation of story plots, which includes story premise, character descriptions, plot outlines, etc. To generate a single engaging plot, existing plot generators (e.g., DOC (Yang et al., 2022a)) require hundreds to thousands of calls to LLMs (e.g., OpenAI API) in the planning stage of the story plot, which is costly and takes at least several minutes. Moreover, the hard-wired nature of the method makes the pipeline non-differentiable, blocking fast specialization and personalization of the plot generator. In this paper, we propose three models, $\texttt{OpenPlot}$, $\texttt{E2EPlot}$ and $\texttt{RLPlot}$, to address these challenges. $\texttt{OpenPlot}$ replaces expensive OpenAI API calls with LLaMA2 (Touvron et al., 2023) calls via careful prompt designs, which leads to inexpensive generation of high-quality training datasets of story plots. We then train an end-to-end story plot generator, $\texttt{E2EPlot}$, by supervised fine-tuning (SFT) using approximately 13000 story plots generated by $\texttt{OpenPlot}$. $\texttt{E2EPlot}$ generates story plots of comparable quality to $\texttt{OpenPlot}$, and is > 10$\times$ faster (1k tokens in only 30 seconds on average). Finally, we obtain $\texttt{RLPlot}$ that is further fine-tuned with RLHF on several different reward models for different aspects of story quality, which yields 60.0$\%$ winning rate against $\texttt{E2EPlot}$ along the aspect of suspense and surprise.Comment: 17 page

Ultra-low threshold gallium nitride photonic crystal nanobeam laser

We report exceptionally low thresholds (9.1 μJ/cm2) for room temperature lasing at ∼450 nm in optically pumped Gallium Nitride (GaN) nanobeam cavity structures. The nanobeam cavity geometry provides high theoretical Q (>100 000) with small modal volume, leading to a high spontaneous emission factor, β = 0.94. The active layer materials are Indium Gallium Nitride (InGaN) fragmented quantum wells (fQWs), a critical factor in achieving the low thresholds, which are an order-of-magnitude lower than obtainable with continuous QW active layers. We suggest that the extra confinement of photo-generated carriers for fQWs (compared to QWs) is responsible for the excellent performance.This work was enabled by facilities available at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN), which was supported by the National Science Foundation under NSF Award No. ECS- 0335765. This work was also supported in part by the NSF Materials World Network (Award No. 1008480), the Engineering and Physical Sciences Research Council (Award No. EP/H047816/1), and the Royal Academy of Engineering.This is the author accepted manuscript. The final version is available from AIP at http://scitation.aip.org/content/aip/journal/apl/106/23/10.1063/1.4922211

Evaluation of myocardial work in patients with hypertrophic cardiomyopathy and hypertensive left ventricular hypertrophy based on non-invasive pressure-strain loops

BackgroundThe capacity to distinguish hypertrophic cardiomyopathy (HCM) from hypertensive left ventricular hypertrophy (H-LVH) based on morphological features obtained by conventional echocardiography is limited. We investigated the global myocardial work of the left ventricle in two types of hypertrophies using the non-invasive myocardial work index (NMWI).MethodsConventional echocardiography was performed on 107 subjects with preserved left ventricular ejection fraction (LVEF ≥ 50%), who comprised patients with HCM (n = 40), H-LVH (n = 35), and healthy people with normal blood pressure and left ventricular structure (n = 32). Except for the conventional echocardiographic parameters, the left ventricular myocardial work parameters based on pressure-strain loops, including global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE), were evaluated in three groups. Multivariate discriminant analysis and receiver operating characteristic (ROC) curve were used to evaluate the incremental value of NMWI for distinguishing HCM from H-LVH.ResultsCompared to the control group, GWI and GCW were significantly lower in HCM patients (P < 0.05), whereas GWI was significantly higher in H-LVH patients. GWW was higher and GWE was significantly decreased in both HCM and H-LVH patients than in the control group (P < 0.05). Multivariate discriminant analysis and ROC curve revealed that the inter-ventricular septum thickness (IVST)/left ventricular posterior wall thickness (LVPWT) and GCW were each able to distinguish HCM from H-LVH. The combination of IVST/LVPWT and GCW discriminated HCM and H-LVH with a higher predictive accuracy of 94.7%.ConclusionNMWI may provide additional information in evaluating the myocardial function in patients with HCM and H-LVH. Myocardial work combined with conventional echocardiography could improve the clinical diagnostic accuracy of distinguishing HCM and H-LVH

Способы перевода аббревиатур и сокращений в области компьютерных технологий (на примере русского и немецкого языков)

Выпускная квалификационная работа 75 с., 2 главы, 42 источника. Предмет исследования: способы перевода аббревиатур и сокращений в области компьютерных технологий с немецкого языка на русский язык. Объектом исследования: аббревиатуры и сокращения, относящиеся к области компьютерных технологий. Цель работы: выявить эффективные способы перевода аббревиатур и сокращений в области компьютерных технологий с немецкого языка на русский. Результаты исследования: были сформулированы особенности перевода аббревиатур и сокращений в области компьютерных технологий Степень внедрения/апробация работы: Было опубликовано две статьи Область применения: лингвистика, языкознание, переводоведение.Graduation thesis: 75 pg., 2 chapters, 42 resources. Subject of research: translation methods of acronyms and reductions in the field of computer technology from German into Russian. Object of research: Acronyms and reductions in the field of computer technology. Purpose of research: : to identify the translation methods of acronyms and reductions in the field of computer technology from German into Russian. Results of research: The features of the translation of acronyms and reductions in the area of computer technology has been revealed. Degree of implementation /work approbation: two articles were published. Field of application: Linguistic, theory of translatio