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Single-ended step-up regulator-chopper power supply /employing conventional chopper circuitry/ combines the advantages of the chopper and switching regulator circuits. Schematic of the power supply incorporating the step-up regulator is shown.
This paper reports and analyzes recent single event effects (SEE) and total ionizing dose (TID) test results for the Analog Devices RH3845 synchronous current mode step-down controller. This device has been tested and evaluated for use in a harsh space radiation environment.
Light, through the mediation of the pigment phytochrome, modulates the gravitropic response of the shoots and roots of many plants. The transduction of both light and gravity stimuli appears to involve Ca(2+)-regulated steps, one or more of which may represent points of intersection between the two transduction chains. To be confident that Ca2+ plays a critical role in stimulus-response coupling for gravitropism, it will be important to identify specific targets of Ca2+ action whose function can be clearly linked to the regulation of growth. Calcium typically exerts its influence on cell metabolism through binding to and activating key regulatory proteins. The three best characterized of these proteins in plants are the calmodulins, calcium-dependent protein kinases, and annexins. In this review we summarize what is known about the structure and function of these proteins and speculate on how their activation by Ca2+ could influence the differential growth response of gravitropism.
Small-signal models are derived for the power stage of the voltage step-up (boost) and the current step-up (buck) converters. The modeling covers operation in both the continuous-mmf mode and the discontinuous-mmf mode. The power stage in the regulated current step-up converter on board the Dynamics Explorer Satellite is used as an example to illustrate the procedures in obtaining the small-signal functions characterizing a regulated converter.
This report presents total ionizing dose evaluation data for the Linear Technology Corporation LTC1877 high efficiency monolithic synchronous step-down regulator. Data sheet parameters were tracked as a function of ionizing dose up to a total of 20 krad(SiO2). Control devices were also used.
Post-translational modifications (PTMs) are biochemical modifications that can significantly alter protein structure, function, stability, localization, and interactions with other molecules, thereby activating or inactivating intracellular processes. A growing body of research has begun to highlight the role of PTMs, including phosphorylation, ubiquitination, acetylation, and redox modifications, during virus-host interactions. Collectively, these PTMs regulate key steps in mounting the host immune response and control critical host pathways required for productive viral replication. This has led to the conception of antiviral therapeutics that focus on controlling host protein PTMs, potentially offering pathogen-agnostic treatment options and revolutionizing our capacity to prevent virus transmission. On the other hand, viruses can hijack the host cellular PTM machinery to modify viral proteins in promoting viral replication and evading immune surveillance. PTM regulation during virus-host interactions is complex and poorly mapped, and the development of effective PTM-targeted antiviral drugs will require a more comprehensive understanding of the cellular pathways essential for virus replication. In this review, we discuss the roles of PTMs in virus infection and how technological advances in mass spectrometry-based proteomics can capture systems-level PTM changes during viral infection. Additionally, we explore how such knowledge is leveraged to identify PTM-targeted candidates for developing antiviral drugs. Looking ahead, studies focusing on the discovery and functional elucidation of PTMs, either on the host or viral proteins, will not only deepen our understanding of molecular pathology but also pave the way for developing better drugs to fight emerging viruses.
Abstract Adding photovoltaic (PV) systems in distribution networks, while desirable for reducing the carbon footprint, can lead to voltage violations under high solar‐low load conditions. The inability of traditional volt‐VAr control in eliminating all the violations is also well‐known. This article presents a novel coordinated inverter control methodology that leverages system‐wide situational awareness to significantly improve hosting capacity (HC). The methodology employs a real‐time voltage‐reactive power (VQ) sensitivity matrix in an iterative linear optimizer to calculate the minimum reactive power intervention from PV inverters needed for mitigating over‐voltage without resorting to active power curtailing or requiring step voltage regulator setting changes. The algorithm is validated using the EPRI J1 feeder under an extensive set of realistic use cases and is shown to provide 3x improvement in HC under all scenarios.
LLNL led two major Technical Areas (TAs) within the PEDOMETER program: TA3 focused on biocontainment and TA4 focused on developing electrochemical TNT degradation sensors and testbeds. A key takeaway from our work is the importance of chassis host strain choice for kill switch design and actuator choice. Genetic instability of the kill switch circuit is a major barrier toward establishing a kill switch, which is host dependent. Addition of a host down-selection step to regulator and actuator screening stages would be beneficial to hasten kill switch development.
An independent variable different from the time for elliptic orbit integration is used. Such a time transformation provides an analytical step-size regulation along the orbit. An intermediate anomaly (an anomaly intermediate between the eccentric and the true anomaly) is suggested for optimum performances. A particular case of an intermediate anomaly (the elliptic anomaly) is defined, and its relation with the other anomalies is developed.
A closed loop regulated dc-to-dc converter employing an unregulated two winding inductive energy storage converter is provided by using a magnetically coupled multivibrator acting as duty cycle generator to drive the converter. The multivibrator is comprised of two transistor switches and a saturable transformer. The output of the converter is compared with a reference in a comparator which transmits a binary zero until the output exceeds the reference. When the output exceeds the reference, the binary output of the comparator drives transistor switches to turn the multivibrator off. The multivibrator is unbalanced so that a predetermined transistor will always turn on first when the binary feedback signal becomes zero.
A dc-to-dc regulated-converter circuit employing duty-cycle control with variable on and variable off time has been presented. A unique feature of this converter is the method by which the bistable-comparator output controls the duty cycle of the power switching transistor through the action of the encoder. The utilization of minor-loop flux excursions of a saturable-core transformer in the encoder makes it feasible to extend the converter switching frequency considerably higher than would normally be possible. With this converter circuit, high and very-high frequency converter operations were explored.
A combination of methods is proposed of predicting spacecraft trajectories that possibly include multiple maneuvers and/or perturbing accelerations, with greater speed, accuracy, and repeatability than were heretofore achievable. The combination is denoted the WeavEncke method because it is based on unpublished studies by Jonathan Weaver of the orbit-prediction formulation of the noted astronomer Johann Franz Encke. Weaver evaluated a number of alternatives that arise within that formulation, arriving at an orbit-predicting algorithm optimized for complex trajectory operations. In the WeavEncke method, Encke's method of prediction of perturbed orbits is enhanced by application of modern numerical methods. Among these methods are efficient Kepler s-equation time-of-flight solutions and self-starting numerical integration with time as the independent variable. Self-starting numerical integration satisfies the requirements for accuracy, reproducibility, and efficiency (and, hence, speed). Self-starting numerical integration also supports fully analytic regulation of integration step sizes, thereby further increasing speed while maintaining accuracy.
The specific biochemical steps required for glucose-regulated insulin exocytosis from beta-cells are not well defined. Elevation of glucose leads to increases in cytosolic [Ca2+]i and biphasic release of insulin from both a readily releasable and a storage pool of beta-granules. The effect of elevated [Ca2+]i on phosphorylation of isolated beta-granule membrane proteins was evaluated, and the phosphorylation of four proteins was found to be altered by [Ca2+]i. One (a 18/20-kDa doublet) was a Ca2+-dependent increase in phosphorylation, and, surprisingly, three others (138, 42, and 36 kDa) were Ca2+-dependent dephosphorylations. The 138-kDa beta-granule phosphoprotein was found to be kinesin heavy chain (KHC). At low levels of [Ca2+]i KHC was phosphorylated by casein kinase 2, but KHC was rapidly dephosphorylated by protein phosphatase 2B beta (PP2Bbeta) as [Ca2+]i increased. Inhibitors of PP2B specifically reduced the second, microtubule-dependent, phase of insulin secretion, suggesting that dephosphorylation of KHC was required for transport of beta-granules from the storage pool to replenish the readily releasable pool of beta-granules. This is distinct from synaptic vesicle exocytosis, because neurotransmitter release from synaptosomes did not require a Ca2+-dependent KHC dephosphorylation. These results suggest a novel mechanism for regulating KHC function and beta-granule transport in beta-cells that is mediated by casein kinase 2 and PP2B. They also implicate a novel regulatory role for PP2B/calcineurin in the control of insulin secretion downstream of a rise in [Ca2+]i.
In cyanobacteria, the free-living ancestors of chloroplasts, photosynthesis simultaneously sustains growth and generates reactive oxygen species (ROS) that damage proteins, lipids, and DNA when light capture outpaces carbon fixation. Maintaining redox balance, therefore, requires cells to read photosynthetic electron flow as a signal that continuously tunes gene expression and protein activity. This review traces how these redox signals are transduced to transcription machinery through three routes: membrane-localized sensors, cytoplasmic redox sensors downstream of photosystem I, and ROS generated when electron sinks are saturated. Membrane-bound histidine kinases (two-component systems) relay the redox state of the plastoquinone pool to control photosystem remodeling, pigment biosynthesis, and circadian timing. Cytoplasmic one-component regulators, by contrast, sense redox directly through thiol-disulfide switches, glutathionylation, iron-sulfur clusters, and metal-catalyzed oxidation to control photosystem-cofactor, electron-carrier, and transition-metal homeostasis. Because many of these regulators persist in algal and plant chloroplasts, cyanobacteria illuminate principles of redox control across photosynthetic eukaryotes. Post-transcriptional and translational control further shapes redox-dependent gene expression programs through transcript stability, ribosome assembly, and translation initiation, extending redox regulation beyond transcription to every step of protein synthesis and even activity modulation. Finally, we connect redox regulation to photosynthetic physiology, stress resilience, and the rational engineering of cyanobacteria for sustainable bioproduction.
Several important aspects of the Regulator with a Prescribed Degree of Stability (RPDS) methodology and its applications are considered. The solution of the time varying RPDS problem as well as the characterization of RPDS closed loop eigenstructure properties are obtained. Based on the asymptotic behavior of RPDS root loci, a one step algorithm for designing Regulators with Prescribed Damping Ratio (RPDR) is developed. The robustness properties of RPDS are characterized in terms of the properties of the return difference and the inverse return difference matrices for the RPDS state feedback loop. This class of regulators is found to possess excellent multiloop margins with respect to stability and degree of stability properties. The ability of RPDS design to tolerate changing operating conditions and unmodelled dynamics are illustrated with a multiterminal dc/ac power system example. The output feedback realization of RPDS requires the use of Linear Quadratic Gaussian (LQG) methodology.
The central dogma of molecular biology states that information is stored in DNA, transcribed to messenger RNA (mRNA) and then translated into proteins. This picture is significantly augmentated when we consider the action of certain proteins in regulating transcription. These transcription factors provide a feedback pathway by which genes can regulate one another's expression as mRNA and then as protein. To review: DNA, RNA and proteins have different functions. DNA is the molecular storehouse of genetic information. When cells divide, the DNA is replicated, so that each daughter cell maintains the same genetic information as the mother cell. RNA acts as a go-between from DNA to proteins. Only a single copy of DNA is present, but multiple copies of the same piece of RNA may be present, allowing cells to make huge amounts of protein. In eukaryotes (organisms with a nucleus), DNA is found in the nucleus only. RNA is copied in the nucleus then translocates(moves) outside the nucleus, where it is transcribed into proteins. Along the way, the RNA may be spliced, i.e., may have pieces cut out. RNA then attaches to ribosomes and is translated to proteins. Proteins are the machinery of the cell other than DNA and RNA, all the complex molecules of the cell are proteins. Proteins are specialized machines, each of which fulfills its own task, which may be transporting oxygen, catalyzing reactions, or responding to extracellular signals, just to name a few. One of the more interesting functions a protein may have is binding directly or indirectly to DNA to perform transcriptional regulation, thus forming a closed feedback loop of gene regulation. The structure of DNA and the central dogma were understood in the 50s; in the early 80s it became possible to make arbitrary modifications to DNA and use cellular machinery to transcribe and translate the resulting genes; more recently, genomes (i.e., the complete DNA sequence) of many organisms have been sequenced. This large-scale sequencing began with simple organisms, viruses and bacteria, progressed to eukaryotes such as yeast, and more recently (1998) progressed to a multi-cellular animal, the nematode Caenorhabditis elegans. Sequencers have now moved on to the fruit fly Drosophila melanogaster, whose sequence is slated for completion by the end of 1999. The human genome project is expected to determine the complete sequence of all 3 billion bases of human DNA within the next five years. In the wake of genome-scale sequencing, further instrumentation is being developed to assay gene expression and function on a comparably large scale. Much of the work in computational biology focuses on computational tools used in sequencing, finding genes that are related to a particular gene, finding which parts of the DNA code for proteins and which do not, understanding what proteins will be formed from a given length of DNA, predicting how the proteins will fold from a one-dimensional structure into a three dimensional structure, and so on. Much less computational work has been done regarding the function of proteins. One reason for this is that different proteins function very differently, and so work on protein function is very specific to certain classes of proteins. There are, for example, proteins such enzymes that catalyze various intracellular reactions, receptors that respond to extracellular signals and ion channels that regulate the flow of charged particles into and out of the cell. In this chapter, we will consider a particular class of proteins called transcription factors(TFs), which are responsible for regulating when a certain gene is expressed in a certain cell, which cells it is express in, and how much is expressed. Understanding these processes will involve developing a deeper understanding of transcription, translation, and the cellular processes that control those processes. All of these elements fall under the aegis of gene regulation or more narrowly transcriptional regulation. Some of the key questions in gene regulation are: What genes are expressed in a certain cell at a certain time? How does gene expression differ from cell to cell in a multicellular organism? Which proteins act as transcription factors, i.e., are important in regulating gene expression? From questions like these, we hope to understand which genes are important for various macroscopic processes. Nearly all of the cells of a multicellular organism contain the same DNA. Yet this same genetic information yields a large number of different cell types. The fundamental difference between a neuron and a liver cell, for example, is which genes are expressed. Thus understanding gene regulation is an important step in understanding development. Furthermore, understanding the usual genes that are expressed in cells may give important clues about various diseases. Some diseases, such as sickle cell anemia and cystic fibrosis, are caused by defects in single, non-regulatory genes; others, such as certain cancers, are caused when the cellular control circuitry malfunctions - an understanding of these diseases will involve pathways of multiple interacting gene products. There are numerous challenges in the area of understanding and modeling gene regulation. First and foremost, biologists would like to develop a deeper understanding of the processes involved, including which genes and families of genes are important, how they interact, etc. From a computation point of view, there has been embarrassingly little work done. In this chapter there are many areas in which we can phrase meaningful, non-trivial computational questions, but questions that have not been addressed. Some of these are purely computational (what is a good algorithm for dealing with a model of type X) and others are more mathematical (given a system with certain characteristics, what sort of model can one use? How does one find biochemical parameters from system-level behavior using as few experiments as possible?). In addition to biological and algorithmic problems, there is also the ever-present issue of theoretical biology - what general principles can be derived from these systems, what can one do with models other than just simulate time-courses, what can be deduced about a class of systems without knowing all the details? The fundamental challenge to computationalists and theorists is to add value to the biology - to use models, modeling techniques and algorithms to understand the biology in new ways.
The present invention provides methods to modify the genetic regulation of mammalian tissue, bone, cells or any combination thereof by preferential activation, up-regulation and/or down-regulation. The method comprises steps of tuning the predetermined profiles of one or more time-varying stimulation fields by manipulating the B-Field magnitude, rising slew rate, rise time, falling slew rate, fall time, frequency, wavelength, and duty cycle, and exposing mammalian cells or tissues to one or more tuned time-varying stimulation fields with predetermined profiles. Examples of mammalian cells or tissues are chondrocytes, osteoblasts, osteocytes, osteoclasts, nucleus pulposus, associated tissue, or any combination. The resulted modification on gene regulation of these cells, tissues or bones may promote the retention, repair of and reduction of compromised mammalian cartilage, bone, and associated tissue.