scholarly journals STUDY OF CRITICAL POWER INTERRUPTION FOR SELFSTARTING SUCCESS

Author(s):  
Andrey Isaev ◽  
Mihail Polzikov

The work is devoted to modeling electromechanical transients when powered from a local source. The object of the study is TKG-1 «Pervomayskaya CHPP», LLC «Shchekinoazot». The time critical for maintaining the initial mode of power interruption is obtained when the design conditions are varied. The problem of evaluating the success of self-launching is programmatically solved in Matlab.

Author(s):  
George D. Pappas ◽  
Jacqueline Sagen

We have been interested in the use of neural transplants mainly as a local source of neuroactive substances, rather than as a replacement for damaged neural circuities. In particular, we have been exploring the possibilities of reducing pain by transplants of opioid peptide producing cells, and reducing depression by transplants of monoamine-producing cells. For the past several years, work in our laboratory has demonstrated in both acute and chronic pain models that transplantation of adrenal medullary tissue or isolated chromaffin cells into CNS pain modulatory regions can reduce pain sensitivity in rodents. Chromaffin cells were chosen as donor source since they produce high levels of both opioid peptides and catecholamines, substances which independently, and probably synergistically, reduce pain sensitivity when injected locally into the spinal cord. The analgesia produced by these transplants most likely results from the release of both opioid peptides and catecholamines, since it can be blocked or attenuated by opiate or adrenergic antagonists, respectively. Furthermore, CSF levels of met-enkephalin and catecholamines are increased by the transplants.


2019 ◽  
Author(s):  
Michaela Bonfert ◽  
Claire Andonian ◽  
Christoph Bidlingmaier ◽  
Claudia Berlin ◽  
Ingo Borggraefe ◽  
...  

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.


2008 ◽  
Author(s):  
Christopher J. Westren ◽  
Lester Ian Clark ◽  
Azam Zreik ◽  
Ben Ersan ◽  
Chad Jurica

Author(s):  
Alla Varenik ◽  
Alla Varenik ◽  
Sergey Konovalov ◽  
Sergey Konovalov

Atmospheric precipitations can be an important source of nutrients to open and coastal zones of marine ecosystem. Jickells [1] has published that atmospheric depositions can sup-port 5-25% of nitrogen required to primary production. Bulk atmospheric precipitations have been collected in a rural location at the Black Sea Crimean coast – Katsiveli settlement, and an urban location – Sevastopol city. Samples have been analyzed for inorganic fixed nitrogen (IFN) – nitrate, nitrite, and ammonium. Deposi-tions have been calculated at various space and time scales. The monthly volume weighted mean concentration of IFN increases from summer to winter in both locations. A significant local source of IFN has been revealed for the urban location and this source and its spatial influence have been quantified. IFN deposition with atmospheric precipitations is up to 5% of its background content in the upper 10 m layer of water at the north-western shelf of the Black Sea. Considering Redfield C:N ratio (106:16) and the rate of primary production (PP) in coastal areas of the Black Sea of about 100-130 g C m-2 year-1 we have assessed that average atmospheric IFN depositions may intensify primary production by 4.5% for rural locations, but this value is increased many-fold in urban locations due to local IFN sources.


2018 ◽  
pp. 43-51
Author(s):  
Osamu Saito

This personal reflection of more than 40 years' work on the supply of labour in a household context discusses the relationship between social science history (the application to historical phenomena of the tools developed by social scientists) and local population studies. The paper concludes that historians working on local source materials can give something new back to social scientists and social science historians, urging them to remake their tools.


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