Do lycra garments improve function and movement in children with cerebral palsy?

The mother of a 5-year-old boy with athetoid cerebral palsy complains of difficulties putting his Lycra suit on each day. She is keen to know if it actually helps improve his function and movement. STRUCTURED CLINICAL QUESTION In children with cerebral palsy (population), do Lycra garments (intervention) improve function and posture (outcome)? SEARCH STRATEGY The search was performed in October 2009

Gender-Inclusive Library Workgroup Report

The Gender-Inclusive Workgroup explored how VCU Libraries can better serve trans and gender-nonconforming users and staff. The group’s recommendations cover library spaces, staff, systems, services, and culture. Key recommendations include highlighting existing all-gender restrooms; building more gender-inclusive restrooms; expanding availability of menstrual products and disposal bins; continuing support for name-of-use changes in library systems; minimizing display of legal name in library systems; offering ongoing staff training in gender-inclusive language and customer service; and encouraging staff to share pronouns. The workgroup also recommends pursuing a culture of shared learning and inclusive thinking, with a reminder that gender identity is one facet of multiple intersecting identities for people in the VCU community

General Philology by Yuri Rozhdestvensky (1996) Moscow, "Novoye Tysjacheletie" - The "New Millennium" Foundation [Ю. В. Рождественский, Общая филология, 1996, Москва, Фонд “Новое тысячелетие”]

The translation represents Part I of the Institute of English Studies Visiting Fellowship Research (2016-17); Part II is an accompanying analytical paper which will be presented at the conference organised on the Work of Yuri Rozhdestvensky and related subject areas, to be held on 21st October 2017: venue: Room 243, Senate House University of London Russell Square, WC1E 7HU Keywords: Yuri Rozhdestvensky; Narratology; Narrative Theory; History of Communications; Pushkin, Poetics TABLE OF CONTENTS Coordinator’s introduction 3 INSTEAD OF A FOREWORD: LANGUAGE WITHIN THE SEMANTIC INFORMATIONAL PROCESS (THE ISSUES OF SPEECH AND ACTION) 5 INTRODUCTION 19 Followed by Introduction sub-section

Studies on Rearing the Opossum (Didelphys Virginiana)

Author Institution: Gainesville, Florid

Combining biochemical network motifs within an ARN-agent control system.

The Artificial Reaction Network (ARN) is an Artificial Chemistry representation inspired by cell signaling networks. The ARN has previously been applied to the simulation of the chemotaxis pathway of Escherichia coli and to the control of limbed robots. In this paper we discuss the design of an ARN control system composed of a combination of network motifs found in actual biochemical networks. Using this control system we create multiple cell-like autonomous agents capable of coordinating all aspects of their behavior, recognizing environmental patterns and communicating with other agent's stigmergically. The agents are applied to simulate two phases of the life cycle of Dictyostelium discoideum: vegetative and aggregation phase including the transition. The results of the simulation show that the ARN is well suited for construction of biochemical regulatory networks. Furthermore, it is a powerful tool for modeling multi agent systems such as a population of amoebae or bacterial colony

Artificial reaction networks.

In this paper we present a novel method of simulating cellular intelligence, the Artificial Reaction Network (ARN). The ARN can be described as a modular S-System, with some properties in common with other Systems Biology and AI techniques, including Random Boolean Networks, Petri Nets, Artificial Biochemical Networks and Artificial Neural Networks. We validate the ARN against standard biological data, and successfully apply it to simulate cellular intelligence associated with the well-characterized cell signaling network of Escherichia coli chemotaxis. Finally, we explore the adaptability of the ARN, as a means to develop novel AI techniques, by successfully applying the simulated E. coli chemotaxis to a general optimization problem

Exploring aspects of cell intelligence with artificial reaction networks.

The Artificial Reaction Network (ARN) is a Cell Signalling Network inspired connectionist representation belonging to the branch of A-Life known as Artificial Chemistry. Its purpose is to represent chemical circuitry and to explore computational properties responsible for generating emergent high-level behaviour associated with cells. In this paper, the computational mechanisms involved in pattern recognition and spatio-temporal pattern generation are examined in robotic control tasks. The results show that the ARN has application in limbed robotic control and computational functionality in common with Artificial Neural Networks. Like spiking neural models, the ARN can combine pattern recognition and complex temporal control functionality in a single network, however it offers increased flexibility. Furthermore, the results illustrate parallels between emergent neural and cell intelligence

Artificial chemistry approach to exploring search spaces using artificial reaction network agents.

The Artificial Reaction Network (ARN) is a cell signaling network inspired representation belonging to the branch of A-Life known as Artificial Chemistry. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri Nets, Random Boolean Networks and S-Systems. The ARN has been previously applied to control of limbed robots and simulation of biological signaling pathways. In this paper, multiple instances of independent distributed ARN controlled agents function to find the global minima within a set of simulated environments characterized by benchmark problems. The search behavior results from the internal ARN network, but is enhanced by collective activities and stigmergic interaction of the agents. The results show that the agents are able to find best fitness solutions in all problems, and compare well with results of cell inspired optimization algorithms. Such a system may have practical application in distributed or swarm robotics

Low-cost eye phantom for stereophotogrammetry-based optic nerve head topographical 3D imaging

Glaucoma is the second leading cause of blindness globally. Stereophotogrammetry-based optic nerve head topographical imaging systems could potentially allow for objective glaucoma assessment in settings where technologies such as optical coherence tomography and the Heidelberg Retinal Tomograph are prohibitively expensive. In the development of such systems, eye phantoms are invaluable tools for both system calibration and performance evaluation. Eye phantoms developed for this purpose need to replicate the optical configuration of the eye, the related causes of measurement artefacts, and give the possibility to present to the imaging system the targets required for system calibration. The phantoms in the literature that show promise of meeting these requirements rely on custom lenses to be fabricated, making them very costly. Here, we propose a low-cost eye phantom comprising a vacuum formed cornea and commercially available stock bi-convex lens, that is optically similar to a gold-standard reference wide-angle schematic eye model and meets all the compliance and configurability requirements for use with stereo-photogrammetry-based ONH topographical imaging systems. Moreover, its modular design, being fabricated largely from 3D-printed components, lends itself to modification for other applications. The use of the phantom is successfully demonstrated in an ONH imager

Functional outcomes from a head-to-head, randomized, double-blind trial of lisdexamfetamine dimesylate and atomoxetine in children and adolescents with attention-deficit/hyperactivity disorder and an inadequate response to methylphenidate

Attention-deficit/hyperactivity disorder (ADHD) is associated with functional impairments in multiple domains of patients' lives. A secondary objective of this randomized, active-controlled, head-to-head, double-blind, dose-optimized clinical trial was to compare the effects of lisdexamfetamine dimesylate (LDX) and atomoxetine (ATX) on functional impairment in children and adolescents with ADHD. Patients aged 6-17 years with an ADHD Rating Scale IV total score ≥ 28 and an inadequate response to methylphenidate treatment (judged by investigators) were randomized (1:1) to once-daily LDX or ATX for 9 weeks. Parents/guardians completed the Weiss Functional Impairment Rating Scale-Parent Report (WFIRS-P) at baseline and at week 9 or early termination. p values were nominal and not corrected for multiple comparisons. Of 267 randomized patients, 200 completed the study (LDX 99, ATX 101). At baseline, mean WFIRS-P total score in the LDX group was 0.95 [standard deviation (SD) 0.474; 95% confidence interval (CI) 0.87, 1.03] and in the ATX group was 0.91 (0.513; 0.82, 1.00). Scores in all WFIRS-P domains improved from baseline to endpoint in both groups, with least-squares mean changes in total score of -0.35 (95% CI -0.42, -0.29) for LDX and -0.27 (-0.33, -0.20) for ATX. The difference between LDX and ATX was statistically significant (p < 0.05) for the Learning and School (effect size of LDX vs ATX, 0.43) and Social Activities (0.34) domains and for total score (0.27). Both treatments reduced functional impairment in children and adolescents with ADHD; LDX was statistically significantly more effective than ATX in two of six domains and in total score