A Special Class of Almost Disjoint Families

The collection of branches (maximal linearly ordered sets of nodes) of the tree ${}^{<\omega}\omega$ (ordered by inclusion) forms an almost disjoint family (of sets of nodes). This family is not maximal -- for example, any level of the tree is almost disjoint from all of the branches. How many sets must be added to the family of branches to make it maximal? This question leads to a series of definitions and results: a set of nodes is {\it off-branch} if it is almost disjoint from every branch in the tree; an {\it off-branch family} is an almost disjoint family of off-branch sets; {\frak o}=\min\{|{\Cal O}|: {\Cal O} is a maximal off-branch family$\}$. Results concerning $\frak o$ include: (in ZFC) ${\frak a}\leq{\frak o}$, and (consistent with ZFC) $\frak o$ is not equal to any of the standard small cardinal invariants $\frak b$, $\frak a$, $\frak d$, or ${\frak c}=2^\omega$. Most of these consistency results use standard forcing notions -- for example, $Con({\frak b}={\frak a}<{\frak o}={\frak d}={\frak c})$ comes from starting with a model of $ZFC+CH$ and adding $\omega_2$-many Cohen reals. Many interesting open questions remain, though -- for example, $Con({\frak o}<{\frak d})$

Muscle Unloading Induced Sex Specific Neurophysiological and Myofiber Profile Adaptations

Muscle unloading affects a muscle’s ability to produce a contractile force and it affects the muscle’s endurance. The objective of this project was to investigate the differences between males and females and their neurophysiological adaptations to hindlimb suspension, an effective model of muscle unloading. Thirty nine young adult Wistar rats were divided into the following four groups: 1) male control, 2) female control, 3) male unloading, 4) female unloading. The unloading groups were subjected to a hindlimb suspension model. Soleus muscles were surgically removed to quantify neuromuscular function, and fluorescent fiber type staining was performed to quantify the cross-sectional area and fiber type composition. By using different stimulation protocols, muscle contraction was induced either directly or indirectly (via motor nerve terminals) and muscular force was quantified by a force transducer. Flourescent staining was used to image type I and type II fibers. The results showed that over a 5 minute stimulation protocol, muscle fatigue was greater during indirect stimulation than direct stimulation, indicating that the motor neuron fatigues at a faster rate than the muscle fibers it innervates. Hindlimb suspension affected the females more than the males whether the muscle was stimulated directly or by the nerve. Unloading significantly increased the neuromuscular block over the five minute fatigue train only in the females. There was significant atrophy in the unloaded groups, but no sex-specific significant differences and no fiber type transitions. In summary, the muscle fatigue is likely due to fatigue in the neuron’s ability to stimulate the muscle, and females are more affected by the hindlimb suspension than males. There was also unloading induced atrophy but it was not sex specific

Accelerated panel methods using the fast multipole method

Panel methods are commonly used in computational fluid dynamics for the solution of potential flow problems. The methods are a numerical technique based on the surface distribution of singularity elements. The solution is the process of finding the strength of the singularity elements distributed over the body's surface. This process involves the solution of the matrix problem Pq = p' for a set of unknowns q. The Fast Multipole Method is used to directly compute q without using matrix solvers. The algorithm works in O(N) time for N points, a great improvement over standard matrix solvers. In panel methods, the surface of a body is divided into a series of quadrilateral panels. The methods involve the computation of the influence of all other panels on each individual panel. The influence is based on the surface distribution, though this can be approximated by the area for distant panels. An alternative approximation, though with arbitrary accuracy, is to develop a multipole expansion about the center of the panel to describe the effect of a given panel on distant points in space. The expansion is based on the moments of the panel, thus allow the use of various surface distributions without changing the basic algorithm, just the computation of the various moments. The expansions are then manipulated in a tree walk to develop Taylor series expansions about a point in space which describe the effect of all distant panels on any point within a volume of convergence. The effect of near panels then needs to be computed directly, but the effect of all distant panels can be computed by simply evaluating the resulting expansion. The Fast Multipole Method has been applied to panel methods for the solution of source and doublet distributions. A major feature of the algorithm is that the algorithm does not change to derive the potential and velocity for sources and doublets. The same expansions can be used for both sources and doublets. Since the velocity is related to the potential, and the doublet potential is related to the z-component of the source velocity, all values can be derived from the same expansion by taking a series of partial derivatives. This requires more expansion terms to be kept since terms are lost in the process of taking partial derivatives. Thus to maintain accuracy for the doublet computation, more terms are required than if just evaluating for sources. The resulting Fast Multipole code should then parallelize better than classical panel methods due to the locality of data dependencies found in the Fast Multipole Method. Theoretically the parallelized code should execute in O(log N) time with O(N) processors, though this is not practical. Ongoing work includes implementing the parallel accelerated panel method, including methods to improve the load balancing of the problem by taking advantage of the known geometry of panels, and to encorporate sensitivity analysis into the algorithm

Gender-Specific Neuromuscular Adaptations to Unloading in Isolated Rat Soleus Muscles

Introduction: The potential of gender to affect unloading-induced neuromuscular adaptations was investigated. Methods: Twenty male and 20 female rats were assigned to control (CTL), or unloaded (UL) conditions. After 2 weeks of unloading, soleus muscles were removed, and neuromuscular function was assessed during a train of alternating indirect (neural) and direct (muscle) stimuli. Results: In rested muscle, strength showed significant (P female) and treatment (CTL \u3e UL). By the end of the testing protocol, when muscles showed fatigue, gender-related and treatment-related differences in strength had disappeared. Neuromuscular transmission efficiency and strength suffered a greater decline during the testing protocol in males than females. Unloaded male muscles displayed greater contractile velocity than female muscles both when rested and fatigued. Conclusions: Gender affected unloading-induced neuromuscular adaptations. The greater strength of rested male muscles was due to greater muscle mass and neuromuscular transmission efficiency

Knowledge Maps for Intelligent Questioning Systems in Engineering Education

The development of a hierarchical knowledge map with an intelligent questioning system to improve the educational process in engineering courses is discussed. Knowledge map represents the architecture of the entire curriculum and each course as an interconnection of modules. The knowledge system provides the necessary framework to allow a questioning system to select appropriate questions. It will also give immediate feedback and assistance to the student for improving the delays with classical assessment

Modeling heterogeneous processor scheduling for real time systems

A new model is presented to describe dataflow algorithms implemented in a multiprocessing system. Called the resource/data flow graph (RDFG), the model explicitly represents cyclo-static processor schedules as circuits of processor arcs which reflect the order that processors execute graph nodes. The model also allows the guarantee of meeting hard real-time deadlines. When unfolded, the model identifies statically the processor schedule. The model therefore is useful for determining the throughput and latency of systems with heterogeneous processors. The applicability of the model is demonstrated using a space surveillance algorithm

An Instrument for Assessing Knowledge Gain in a First Course in Circuit Theory

Although there has been considerable research on the development and use of assessment instruments to measure the effectiveness of various pedagogical approaches to teaching introductory physics classes (Hestenes et al. 1, Hestenes et al 2, Hake 3, Saul et al. 4) and other science courses (for example, see Vosniadou 5), there is relatively little similar work that has been done to develop assessment instruments for the first circuit theory course that is taught in electrical and computer engineering. Given the large numbers of students nationwide who take such a course, the challenge this course presents to beginning engineering students, and the introduction of new approaches to teach this material, an instrument similar to those available for physics is needed to identify student misconceptions at the beginning of the class and to measure the normalized learning gain at the end of the class (Hake 3). These gains and other metrics can then be used to compare the effect of different teaching methods. In addition, this same instrument or portions of it can be offered at later times in the curriculum to measure retention and reinforcement from other courses. This concept-based testing approach is useful to examine the overall effectiveness of the circuit component of a curriculum and could thus be used as part of the continuous self-improvement process required under the ABET 2000 rules

Effects of Exercise Training on Neuromuscular Junction Morphology and Pre- to Post-Synaptic Coupling in Young and Aged Rats

The objective of this study was to determine whether pre- to post-synaptic coupling of the neuromuscular junction (NMJ) could be maintained in the face of significant morphological remodeling brought about by exercise training, and whether aging altered this capacity. Eighteen young adult (8 mo) and eighteen aged (24 mo) Fischer 344 rats were randomly assigned to either endurance trained (treadmill running) or untrained control conditions resulting in four groups (N = 9 / group). After the 10-week intervention rats were euthanized and hindlimb muscles were surgically removed, quickly frozen at approximate resting length and stored at - 85 degrees C. The plantaris and EDL muscles were selected for study as they have different functions (ankle extensor and ankle flexor, respectively) but both are similarly and overwhelmingly comprised of fast-twitch myofibers. NMJs were stained with immunofluorescent procedures and images were collected with confocal microscopy. Each variable of interest was analyzed with a 2-way ANOVA with main effects of age and endurance training; in all cases significance was set at P \u3c = 0.05. Results showed that no main effects of aging were detected in NMJs of either the plantaris or the EDL. Similarly, endurance training failed to alter any synaptic parameters of EDL muscles. The same exercise stimulus in the plantaris however, resulted in significant pre- and post-synaptic remodeling, but without altering pre- to post-synaptic coupling of the NMJs. Myofiber profiles of the same plantaris and EDL muscles were also analyzed. Unlike NMJs, myofibers displayed significant age-related atrophy in both the plantaris and EDL muscles. Overall, these results confirm that despite significant training-induced reconfiguration of NMJs, pre- to post-synaptic coupling remains intact underscoring the importance of maintaining proper apposition of neurotransmitter release and binding sites so that effective nerve to muscle communication is assured. (C) 2015 IBRO. Published by Elsevier Ltd. All rights reserved

Integrations between Autonomous System and Modern Computing Techniques: A Mini-review

The emulation of human behavior for autonomous problem solving has been an interdisciplinary field of research. Generally, classical control systems are used for static environments, where external disturbances and changes in internal parameters can be fully modulated before or neglected during operation. However, classical control systems are inadequate at addressing environmental uncertainty. By contrast, autonomous systems, which were first studied in the field of control systems, can be applied in an unknown environment. This paper summarizes the state of the art autonomous systems by first discussing the definition, modeling, and system structure of autonomous systems and then providing a perspective on how autonomous systems can be integrated with advanced resources (e.g., the Internet of Things, big data, Over-the-Air, and federated learning). Finally, what comes after reaching full autonomy is briefly discussed