The impact of individual retirement accounts on savings

Bills to expand individual retirement accounts have been introduced in both houses of Congress this year. While proponents argue that these accounts can help reverse the nation's declining saving rate, recent economic research suggests that the effect of the accounts on savings is in fact quite small.Individual retirement accounts ; Saving and investment

Classification of Student Developed Annual Goals

Objective: This study categorizes goals (personal vs professional and long vs short-term) of student pharmacists. An increase in the proportion of long-term, professional goals is expected as students advance through the program. Methods: Annual student goals were classified into categories (personal vs professional and long vs short term). Definitions were developed and a beta-test was conducted to confirm interpretations were consistent between raters. Multiple one-tail Z-tests with Bonferroni correction were used to compare the proportion of personal/professional and short-term/long-term goals for P1 students to the proportion of each of the classes of P2-P5 for the years of 2018 and 2019, respectively. Results: Comparison of goals indicated the proportion of personal goals for P1 students was significantly higher than the proportion of personal goals in all other years of the program for 2018 and 2019 with limited exceptions. The proportion of short-term goals for P1 students was higher than the proportion of short-term goals for most other years of the program. Conclusion: As students progress through the program, self-identified goals become more professional and long-term. Recognition of this difference could aid the College in providing differentiated support for student achievement of their goals

Processing SPARQL queries with regular expressions in RDF databases

Background: As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results: In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions: Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.X113sciescopu

Cultures and Works of Tay People Through Vocative Words

Culture has a close relationship with many fields, including Linguistics. Language is a special product of culture. It is a means of communication and a tool for thinking. Language is a means to reflect, maintain and develop culture. Any meaningful sign of a language contains a cultural element. Vocative words are one of those cases. The article explores the vocative words system in the language of the Tay people in Tuyen Quang Province, Vietnam and concludes that culture is not only a factor that generates language, but also an environment for language to exist and develop. develop. Through the system of vocative words in the Tay language, it shows the cultural characteristics of respect affection of the Tay people

On the Algorithmic Stability and Generalization of Adaptive Optimization Methods

Despite their popularity in deep learning and machine learning in general, the theoretical properties of adaptive optimizers such as Adagrad, RMSProp, Adam or AdamW are not yet fully understood. In this paper, we develop a novel framework to study the stability and generalization of these optimization methods. Based on this framework, we show provable guarantees about such properties that depend heavily on a single parameter $\beta_2$. Our empirical experiments support our claims and provide practical insights into the stability and generalization properties of adaptive optimization methods.Comment: 21 pages including appendi

EFFECTIVENESS OF POWERPOINT PRESENTATION ON VOCABULARY RETENTION OF EFL FIRST-YEAR STUDENTS’ READING COMPREHENSION

Vocabulary learning plays an important role in language learning. To many language learners, lack of vocabulary is one of the biggest obstacles that prevent them from mastering the language. Moreover, there have been a lot of studies conducted to find out the way to help language learners acquire and retain learned vocabulary. Among them, PowerPoint is suggested by many researchers as one good way to help learners learn vocabulary retention through reading comprehension. The purpose of this study was to investigate the effect of PowerPoint on vocabulary retention in reading comprehension of EFL (English as a Foreign Language) first-year students at Long An University of Economics and Industry (DLA), Long An Province, Vietnam. Besides, this study investigates learners’ attitudes towards the use of PowerPoint in learning vocabulary. The participants were 60 non-English major students at DLA. Two instruments were (1) the tests on English vocabulary, (2) the questionnaire on the participants’ attitudes towards the use of PowerPoint in teaching and learning vocabulary, were investigated. The results demonstrated a significant difference in learners’ vocabulary retention: the participants in the experimental group remembered vocabulary longer than those in the control group. The study showed that the learners had positive attitudes towards the use of PPT (PowerPoint Presentation) in learning vocabulary retention.  Article visualizations

Convolutional Neural Networks for Image-based Corn Kernel Detection and Counting

Precise in-season corn grain yield estimates enable farmers to make real-time accurate harvest and grain marketing decisions minimizing possible losses of profitability. A well developed corn ear can have up to 800 kernels, but manually counting the kernels on an ear of corn is labor-intensive, time consuming and prone to human error. From an algorithmic perspective, the detection of the kernels from a single corn ear image is challenging due to the large number of kernels at different angles and very small distance among the kernels. In this paper, we propose a kernel detection and counting method based on a sliding window approach. The proposed method detect and counts all corn kernels in a single corn ear image taken in uncontrolled lighting conditions. The sliding window approach uses a convolutional neural network (CNN) for kernel detection. Then, a non-maximum suppression (NMS) is applied to remove overlapping detections. Finally, windows that are classified as kernel are passed to another CNN regression model for finding the (x,y) coordinates of the center of kernel image patches. Our experiments indicate that the proposed method can successfully detect the corn kernels with a low detection error and is also able to detect kernels on a batch of corn ears positioned at different angles.Comment: 14 pages, 9 figure

Thermal stability of a nanocrystalline HfNbTiZr multi-principal element alloy processed by high-pressure torsion

The microstructural stability of a nanocrystalline HfNbTiZr multi-principal element alloy was studied by annealing the material in a differential scanning calorimeter (DSC). The as-received sample was obtained by severe plastic deformation using the high-pressure torsion (HPT) technique. Samples were annealed to the characteristic temperatures of the DSC thermogram, namely up to 740, 890 and 1000 K, and the microstructure of the heat treated specimens was analyzed. It was found that the heating up to 740 K yielded a decomposition of the initial body-centered cubic (bcc) phase into two bcc phases with a lower and a higher lattice constant. During annealing up to 890 K, a Zr/Hf-rich hexagonal-close packed (hcp) phase started to nucleate. Heating the sample up to 1000 K resulted in the formation of a nanocrystalline Zr/Hf-rich bcc phase beside the Zr/Hf-rich hcp and the Nb-rich bcc phases. Beside the phase transformation a recovery of the severely deformed defect structure and a grain coarsening were also observed which was accompanied by a reduction of the hardness above 740 K

DeepCorn: A Semi-Supervised Deep Learning Method for High-Throughput Image-Based Corn Kernel Counting and Yield Estimation

The success of modern farming and plant breeding relies on accurate and efficient collection of data. For a commercial organization that manages large amounts of crops, collecting accurate and consistent data is a bottleneck. Due to limited time and labor, accurately phenotyping crops to record color, head count, height, weight, etc. is severely limited. However, this information, combined with other genetic and environmental factors, is vital for developing new superior crop species that help feed the world's growing population. Recent advances in machine learning, in particular deep learning, have shown promise in mitigating this bottleneck. In this paper, we propose a novel deep learning method for counting on-ear corn kernels in-field to aid in the gathering of real-time data and, ultimately, to improve decision making to maximize yield. We name this approach DeepCorn, and show that this framework is robust under various conditions. DeepCorn estimates the density of corn kernels in an image of corn ears and predicts the number of kernels based on the estimated density map. DeepCorn uses a truncated VGG-16 as a backbone for feature extraction and merges feature maps from multiple scales of the network to make it robust against image scale variations. We also adopt a semi-supervised learning approach to further improve the performance of our proposed method. Our proposed method achieves the MAE and RMSE of 41.36 and 60.27 in the corn kernel counting task, respectively. Our experimental results demonstrate the superiority and effectiveness of our proposed method compared to other state-of-the-art methods.Comment: 27 pages, 7 figure