A New Species of \u3ci\u3ePediobius\u3c/i\u3e (Hymenoptera: Eulophidae) Parasitizing \u3ci\u3eChyliza Apicalis\u3c/i\u3e (Diptera: Psilidae) in Ash Trees Attacked by \u3ci\u3eAgrilus Planipennis\u3c/i\u3e (Coleoptera: Buprestidae)

Pediobius chylizae, spec. nov. (Hymenoptera: Eulophidae), is described as new and illustrated. This parasitoid has been reared from the puparia of Chyliza apicalis Loew (Diptera: Psilidae) collected from under the bark of ash trees (Oleaceae: Fraxinus spp.) dying after attack by the emerald ash borer, Agrilus planipennis Fairmaire (Coleptera: Buprestidae), an invasive beetle from Asia. This species is compared with related species of Pediobius from the Holarctic Region

Current-induced spin torque resonance of magnetic insulators affected by field-like spin-orbit torques and out-of-plane magnetizations

The spin-torque ferromagnetic resonance (ST-FMR) in a bilayer system consisting of a magnetic insulator such as Y3Fe5O12 and a normal metal with spin-orbit interaction such as Pt is addressed theoretically. We model the ST-FMR for all magnetization directions and in the presence of field-like spin-orbit torques based on the drift-diffusion spin model and quantum mechanical boundary conditions. ST-FMR experiments may expose crucial information about the spin-orbit coupling between currents and magnetization in the bilayers.Comment: 4 pages, 2 figure

ATP binding to bovine serum albumin

AbstractSpecific binding or ATP to bovine serum albumin (BSA) is demonstrated employing ATP derivatives spin-labeled at either N6 or C8 of adenine ring or at the ribose moiety. Based on a 1:1 stoichiometry binding constants are in the 50–100 μM range. Binding is largely competitive with ATP or stearic acid. A small fraction of the labeled nucleotides could not be liberated by these ligands. Binding of AMP is in the millimolar range, only

Near-Infrared Counterparts to Chandra X-ray Sources toward the Galactic Center. I. Statistics and a Catalog of Candidates

We present a catalog of 5184 candidate infrared counterparts to X-ray sources detected towards the Galactic center. The X-ray sample contains 9017 point sources detected in this region by the Chandra X-ray Observatory, including data from a recent deep survey of the central 2 x 0.8 deg of the Galactic plane. A total of 6760 of these sources have hard X-ray colors, and the majority of them lie near the Galactic center, while most of the remaining 2257 soft X-ray sources lie in the foreground. We cross-correlated the X-ray source positions with the 2MASS and SIRIUS near-infrared catalogs, which collectively contain stars with a 10-sigma limiting flux of K_s<=15.6 mag. In order to distinguish absorbed infrared sources near the Galactic center from those in the foreground, we defined red and blue sources as those which have H-K_s>=0.9 and <=0.9 mag, respectively. We find that 5.8(1.5)% of the hard X-ray sources have real infrared counterparts, of which 228(99) are red and 166(27) are blue. The red counterparts are probably comprised of WR/O stars, HMXBs, and symbiotics near the Galactic center. We also find that 39.4(1.0)% of the soft X-ray sources have blue infrared counterparts; most of these are probably coronally active dwarfs in the foreground. There is a noteworthy collection of ~20 red counterparts to hard X-ray sources near the Sagittarius-B H II region, which are probably massive binaries that have formed within the last several Myr. For each of the infrared matches to X-ray sources in our catalog we derived the probability that the association is real, based on the results of the cross-correlation analysis. The catalog will serve spectroscopic surveys to identify infrared counterparts to X-ray sources near the Galactic center.Comment: Submitted to ApJ January 16, 2009; accepted July 21, 2009; 30 pages, 6 figure

Analysis of potentially predictive factors of efficacy of adjunct extended-release quetiapine fumarate in patients with major depressive disorder

Identification of predictors of treatment response in patients with major depressive disorder (MDD) may facilitate improved disease management. Data were pooled from two 6-week, double-blind, placebo-controlled studies of extended-release quetiapine (quetiapine XR; 150 or 300 mg/day) as adjunct to ongoing antidepressant therapy. Effects of psychiatric history and baseline demographic and disease characteristics on efficacy outcomes (Week 6 Montgomery Åsberg Depression Rating Scale [MADRS] total score reduction) were evaluated in population subgroups (quetiapine XR both doses pooled, n = 616; placebo, n = 303). Baseline Clinical Global Impressions-Severity (CGI-S) score and previous depressive episodes on Week 6 MADRS total score change, and baseline MADRS individual item scores on Week 6 change in CGI-Improvement score, were also evaluated. No major differences between responders and non-responders to quetiapine XR were observed for patient characteristics or demographic and disease characteristics. No suggestion of a predictive association was found between baseline CGI-S score, number of depressive episodes, and baseline MADRS item scores and efficacy outcomes. These analyses showed no major differences between responders and non-responders, and no predictive association between the parameters assessed and efficacy outcomes for adjunct quetiapine XR in patients with MDD and an inadequate response to prior antidepressant therapy

Meet the players: local translation at the synapse

It is widely believed that activity-dependent synaptic plasticity is the basis for learning and memory. Both processes are dependent on new protein synthesis at the synapse. Here, we describe a mechanism how dendritic mRNAs are transported and subsequently translated at activated synapses. Furthermore, we present the players involved in the regulation of local dendritic translation upon neuronal stimulation and their molecular interplay that maintain local proteome homeostasis. Any dysregulation causes several types of neurological disorders including muscular atrophies, cancers, neuropathies, neurodegenerative, and cognitive disorders

The AGN Population in X-ray Selected Galaxy Groups at 0.5<z<1.10.5 < z < 1.1

We use Chandra data to study the incidence and properties of Active Galactic Nuclei (AGN) in 16 intermediate redshift ($0.5 < z < 1.1$) X-ray-selected galaxy groups in the Chandra Deep Field-South. We measure an AGN fraction of $f(L_{X,H} > 10^{42}; M_R<-20) = 8.0_{-2.3}^{+3.0}\%$ at $\bar{z} \sim 0.74$, approximately a factor of two higher than the AGN fraction found for rich clusters at comparable redshift. This extends the trend found at low redshift for groups to have higher AGN fractions than clusters. Our estimate of the AGN fraction is also more than a factor of 3 higher than that of low redshift X-ray-selected groups. Using optical spectra from various surveys, we also constrain the properties of emission-line selected AGN in these groups. Contrary to the large population of X-ray AGN ($N(L_{X,H} > 10^{41}$ erg/s) = 25), we find only 4 emission-line AGN, 3 of which are also X-ray bright. Furthermore, most of the X-ray AGN in our groups are optically-dull (i.e. lack strong emission-lines) similar to those found in low redshift X-ray groups and clusters of galaxies. This contrasts with the AGN population found in low redshift optically-selected groups which are dominated by emission-line AGN. The differences between the optically and X-ray-selected AGN populations in groups are consistent with a scenario where most AGN in the densest environments are currently in a low accretion state.Comment: 8 pages, 4 figures, accepted for publication in Ap

The end is the beginning is the end: the closed-loop learning analytics framework

This article provides a comprehensive review of current practices and methodologies within the field of learning analytics, structured around a dedicated closed-loop framework. This framework effectively integrates various aspects of learning analytics into a cohesive framework, emphasizing the interplay between data collection, processing and analysis, as well as adaptivity and personalization, all connected by the learners involved and underpinned by educational and psychological theory. In reviewing each step of the closed loop, the article delves into the advancements in data collection, exploring how technological progress has expanded data collection methods, particularly focusing on the potential of multimodal data acquisition and how theory can inform this step. The processing and analysis step is thoroughly reviewed, highlighting a range of methods including machine learning and AI, and discussing the critical balance between prediction accuracy and interpretability. The adaptivity and personalization step examines the current state of research, underscoring significant gaps and the necessity for theory-informed, personalized learning interventions. Overall, the article underscores the importance of interdisciplinarity in learning analytics, advocating for the integration of insights from various fields to address challenges such as ethical data usage and the creation of quality learning experiences. This framework and review aim to guide future research and practice in learning analytics, promoting the development of effective, learner-centric educational environments driven by balancing data-driven insights and theoretical understanding