STOP, LOOK, AND LISTEN TO WHAT YOUR DATA IS TELLING YOU!

Join us for a ride on the Data Train where you will STOP, LOOK, and LISTEN to what your data is telling you and use the information to develop a process of continuous improvement in your after-school program to be an effective co-collaborator of closing the achievement gap. This workshop will provide information and strategies to be used in K – 12. Participants will learn the importance of data analysis in afterschool. Participants will learn how to work with regular day school professionals in determining what data sources to use. Participants will be able to analyze sample data and develop an action plan. Participants will develop a process of continuous improvement which utilizes student data

Faculty Recital, Rex Richardson, trumpet

Rex Richardson\u27s Trumpet Spectacular Magdalena Adamek, pianoTuesday, October 1, 2019 at 7pmSonia Vlahcevic Concert HallW.E. Singleton Center for the Performing Arts922 Park AvenueRichmond, Va.WithJeff Hudson, tubaKevin Maloney, trumpetTabatha Easley, fluteTaylor Barnett, trumpetRussell Wilson, pian

Understanding, Managing and Leading Generation X in the Field of Law Enforcement

Discusses the need for supervisors to understand generation X employees in order to successfully supervise them

Partnership Law

This Article describes and analyzes major developments in partnership law that occurred in Texas between December 1 and November 30 of 2022

Assessing the Readability of Medical Documents: A Ranking Approach

BACKGROUND: The use of electronic health record (EHR) systems with patient engagement capabilities, including viewing, downloading, and transmitting health information, has recently grown tremendously. However, using these resources to engage patients in managing their own health remains challenging due to the complex and technical nature of the EHR narratives. OBJECTIVE: Our objective was to develop a machine learning-based system to assess readability levels of complex documents such as EHR notes. METHODS: We collected difficulty ratings of EHR notes and Wikipedia articles using crowdsourcing from 90 readers. We built a supervised model to assess readability based on relative orders of text difficulty using both surface text features and word embeddings. We evaluated system performance using the Kendall coefficient of concordance against human ratings. RESULTS: Our system achieved significantly higher concordance (.734) with human annotators than did a baseline using the Flesch-Kincaid Grade Level, a widely adopted readability formula (.531). The improvement was also consistent across different disease topics. This method\u27s concordance with an individual human user\u27s ratings was also higher than the concordance between different human annotators (.658). CONCLUSIONS: We explored methods to automatically assess the readability levels of clinical narratives. Our ranking-based system using simple textual features and easy-to-learn word embeddings outperformed a widely used readability formula. Our ranking-based method can predict relative difficulties of medical documents. It is not constrained to a predefined set of readability levels, a common design in many machine learning-based systems. Furthermore, the feature set does not rely on complex processing of the documents. One potential application of our readability ranking is personalization, allowing patients to better accommodate their own background knowledge

Absorption and biotransformation of polybrominated diphenyl ethers DE-71 and DE-79 in chicken (\u3ci\u3eGallus gallus\u3c/i\u3e), mallard (\u3ci\u3eAnas platyrhynchos\u3c/i\u3e), American kestrel (\u3ci\u3eFalco sparverius\u3c/i\u3e) and black-crowned night-heron (\u3ci\u3eNycticorax nycticorax\u3c/i\u3e) eggs

We recently reported that air cell administration of penta-brominated diphenyl ether (penta-BDE; DE-71) evokes biochemical and immunologic effects in chicken (Gallus gallus) embryos at very low doses, and impairs pipping (i.e., stage immediately prior to hatching) and hatching success at 1.8 µg g-1 egg (actual dose absorbed) in American kestrels (Falco sparverius). In the present study, absorption of polybrominated diphenyl ether (PBDE) congeners was measured following air cell administration of a penta-BDE mixture (11.1 lg DE-71 g-1 egg) or an octa-brominated diphenyl ether mixture (octa BDE; DE-79; 15.4 lg DE-79 g-1 egg). Uptake of PBDE congeners was measured at 24 h post-injection, midway through incubation, and at pipping in chicken, mallard (Anas platyrhynchos), and American kestrel egg contents, and at the end of incubation in black-crowned night-heron (Nycticorax nycticorax) egg contents. Absorption of penta-BDE and octa-BDE from the air cell into egg contents occurred throughout incubation; at pipping, up to 29.6% of penta-BDE was absorbed, but only 1.40–6.48% of octa-BDE was absorbed. Higher brominated congeners appeared to be absorbed more slowly than lower brominated congeners, and uptake rate was inversely proportional to the log Kow of predominant BDE congeners. Six congeners or co-eluting pairs of congeners were detected in penta-BDE-treated eggs that were not found in the dosing solution suggesting debromination in the developing embryo, extraembryonic membranes, and possibly even in the air cell membrane. This study demonstrates the importance of determining the fraction of xenobiotic absorbed into the egg following air cell administration for estimation of the lowest-observed-effect level

Un "simposio di sapienza e affetto"

Muscle hypertrophy occurs following increased protein synthesis, which requires activation of the ribosomal complex. Additionally, increased translational capacity via elevated ribosomal RNA (rRNA) synthesis has also been implicated in resistance training-induced skeletal muscle hypertrophy. The time course of ribosome biogenesis following resistance exercise (RE) and the impact exerted by differing recovery strategies remains unknown. In the present study, the activation of transcriptional regulators, the expression levels of pre-rRNA, and mature rRNA components were measured through 48 h after a single-bout RE. In addition, the effects of either low-intensity cycling (active recovery, ACT) or a cold-water immersion (CWI) recovery strategy were compared. Nine male subjects performed two bouts of high-load RE randomized to be followed by 10 min of either ACT or CWI. Muscle biopsies were collected before RE and at 2, 24, and 48 h after RE. RE increased the phosphorylation of the p38-MNK1-eIF4E axis, an effect only evident with ACT recovery. Downstream, cyclin D1 protein, total eIF4E, upstream binding factor 1 (UBF1), and c-Myc proteins were all increased only after RE with ACT. This corresponded with elevated abundance of the pre-rRNAs (45S, ITS-28S, ITS-5.8S, and ETS-18S) from 24 h after RE with ACT. In conclusion, coordinated upstream signaling and activation of transcriptional factors stimulated pre-rRNA expression after RE. CWI, as a recovery strategy, markedly blunted these events, suggesting that suppressed ribosome biogenesis may be one factor contributing to the impaired hypertrophic response observed when CWI is used regularly after exercise

The new CFS Divisia monetary aggregates: design, construction, and data sources

The Center for Financial Stability (CFS) has initiated a new Divisia monetary aggregates database, maintained within the CFS program called Advances in Monetary and Financial Measurement (AMFM). The Director of the program is William A. Barnett, who is the originator of Divisia monetary aggregation and more broadly of the associated field of aggregation-theoretic monetary aggregation. The international section of the AMFM web site is a centralized source for Divisia monetary aggregates data and research for over 40 countries throughout the world. The components of the CFS Divisia monetary aggregates for the United States reflect closely those of the current and former simple-sum monetary aggregates provided by the Federal Reserve. The first five levels, M1, M2, M2M, MZM, and ALL, are composed of currency, deposit accounts, and money market accounts. The liquid asset extensions to M3, M4-, and M4 resemble in spirit the now discontinued M3 and L aggregates, including repurchase agreements, large denomination time deposits, commercial paper, and Treasury bills. When the Federal Reserve discontinued publishing M3 and L, the Fed stopped providing the consolidated, seasonally adjusted components. Also the Fed no longer provides the interest rates on the components. With so much of the needed component quantity and interest-rate data no longer available from the Federal Reserve, decisions about data sources needed in construction of the CFS aggregates have been far from easy and sometimes required regression interpolation. This paper documents the decisions of the CFS regarding United States data sources at the present time, with particular emphasis on Divisia M3 and M4

The new CFS Divisia monetary aggregates: design, construction, and data sources

The Center for Financial Stability (CFS) has initiated a new Divisia monetary aggregates database, maintained within the CFS program called Advances in Monetary and Financial Measurement (AMFM). The Director of the program is William A. Barnett, who is the originator of Divisia monetary aggregation and more broadly of the associated field of aggregation-theoretic monetary aggregation. The international section of the AMFM web site is a centralized source for Divisia monetary aggregates data and research for over 40 countries throughout the world. The components of the CFS Divisia monetary aggregates for the United States reflect closely those of the current and former simple-sum monetary aggregates provided by the Federal Reserve. The first five levels, M1, M2, M2M, MZM, and ALL, are composed of currency, deposit accounts, and money market accounts. The liquid asset extensions to M3, M4-, and M4 resemble in spirit the now discontinued M3 and L aggregates, including repurchase agreements, large denomination time deposits, commercial paper, and Treasury bills. When the Federal Reserve discontinued publishing M3 and L, the Fed stopped providing the consolidated, seasonally adjusted components. Also the Fed no longer provides the interest rates on the components. With so much of the needed component quantity and interest-rate data no longer available from the Federal Reserve, decisions about data sources needed in construction of the CFS aggregates have been far from easy and sometimes required regression interpolation. This paper documents the decisions of the CFS regarding United States data sources at the present time, with particular emphasis on Divisia M3 and M4